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The issue of avoidance : information avoidance in the context of personal health concerns Addison, Colleen Victoria 2017

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  	 THE	ISSUE	OF	AVOIDANCE:		INFORMATION	AVOIDANCE	IN	THE	CONTEXT	OF	PERSONAL	HEALTH	CONCERNS	by		Colleen	Victoria	Addison	B.A.	(Hons.),	University	of	Alberta,	1997	M.A.,	University	of	New	Brunswick,	2001	M.L.I.S.,	University	of	Western	Ontario,	2007	A	THESIS	SUBMITTED	IN	PARTIAL	FULFILLMENT	OF	THE	REQUIREMENTS	FOR	THE	DEGREE	OF	DOCTOR	OF	PHILOSOPHY	in	The	Faculty	of	Graduate	and	Postdoctoral	Studies	(Library,	Archival	and	Information	Studies)	THE	UNIVERSITY	OF	BRITISH	COLUMBIA		(Vancouver)	August,	2017		©	Colleen	Victoria	Addison		 ii	Abstract	 Information	is	increasingly	available	at	the	touch	of	a	button,	and	yet	limits	are	still	present	in	the	ability	and	willingness	of	individuals	to	access	that	information.		These	limits	can	result	in	information	avoidance,	a	phenomenon	in	which	individuals	prefer	not	to	seek	or	be	exposed	to	information.		Nowhere	is	this	phenomenon	more	evident	and	more	problematic	than	in	health,	where	information	has	been	linked	to	better	health	outcomes,	and	where	the	consumer	health	movement	has	shifted	the	responsibility	of	health	information	seeking	from	healthcare	professionals	to	patients.		This	dissertation	examines	such	health	information	avoidance,	looking	in	particular	at	the	mechanisms	that	constitute	this	phenomenon,	and	the	affective,	personality,	and	information	source	factors	that	influence	it.		Two	studies	were	performed,	the	first	an	online	survey	using	the	crowdsourcing	platform	Mechanical	Turk	for	recruitment,	and	the	second	a	user	study	in	which	participants	interacted	with	health	information	and	were	then	interviewed.		Both	studies	also	employed	scales	such	as	the	Need	for	Cognition	scale,	the	Threatening	Medical	Situations	Inventory	(examining	monitoring	and	blunting	styles),	and	the	Positive	and	Negative	Affect	short	scale.			Results	indicate	that	very	few	people	are	willing	to	report	practising	complete	information	avoidance.		However,	numerous	participants	reported	avoiding	some	information,	often	through	filtering	mechanisms	such	as	self-regulation	and	delegation.		This	evidence	of	partial	avoidance	suggests	that	information	avoidance	can	be	located	on	a	continuum	of	information	seeking	behaviours,	rather	than	existing	as	a	simple	negation	of	information	seeking.		Significant	factors	that	influence	the	practice	of	information	avoidance	were	found	to	include	affect	such	as	fear,	disgust,	and	disinterest,	all	factors	that	can	indicate	a	threat	to	the	participant.		While	the	personality	and	information	source	factors	tested	were	also	influential,	this	work	found	that	for	these	participants,	affective	factors	often	functioned	as	a	primary	influence.		This	work	indicates	that	health	information	avoidance	is	a	situation-dependent	information	behaviour,	rather	than	primarily	a	personality	trait	as	previously	claimed.		As	such,	it	should	be	included	in	models	that	depict	people’s	general	behavioural	patterns	with	regard	to	information,	such	as	Wilson’s	(1999)	General	Model	of	Information	Seeking	and	Johnson’s	(1997)	Comprehensive	Model	of	Information	Seeking.							  	 iii	Lay	Summary		 If	you	have	health	concerns,	you	probably	turn,	like	most	people,	to	Dr.	Google.		But	how	long	do	you	search?		And	what	sites	do	you	look	at?		This	dissertation	examines	the	phenomenon	of	information	avoidance,	in	which	people	avoid	or	filter	out	information	about	their	own	health	concerns,	rather	than	looking	for	it.		I	performed	two	studies,	the	first	an	online	survey,	the	second	a	series	of	in-person	interviews	and	website	browsing	sessions.		Numerous	participants	reported	regulating	how	they	look	for	information,	either	by	limiting	their	information	searches	or	by	letting	others	search	for	them.		Although	some	of	this	behaviour	was	due	to	participants’	personalities	or	issues	with	the	information	at	which	participants	were	looking,	most	participants	cited	emotional	reasons:		they	were	afraid,	not	interested,	or	disgusted.		These	emotions,	fear,	disgust	and	disinterest,	show	that	participants	look	for	information	differently,	based	on	the	situation,	rather	than	primarily	following	patterns	of	behaviour	established	by	habit	or	personality.			 		 iv	Preface		The	MedBrowser	websites	used	in	the	Interview	and	Interaction	study	were	created	by	Dr.	Luanne	Freund	and	myself,	and	included	material	found	by	a	graduate	research	assistant.			I	was	responsible	for	conducting	all	interaction	sessions	and	interviews	in	this	study,	as	well	as	for	the	administration	of	the	scales.		The	Affect	and	Avoidance	study	design	and	questionnaire	was	developed	with	assistance	from	Dr.	Luanne	Freund	and	performed	by	myself.			Ethics	was	obtained	for	this	research,	under	its	former	title	“When	Information	Hurts.”		The	University	of	British	Columbia	Human	Ethics	board	granted	approval	using	the	number	H14-00877.						 		 v		Table	of	Contents		Abstract	.......................................................................................................................................	ii	Lay	Summary	...........................................................................................................................	iii	Preface	........................................................................................................................................	iv	Table	of	Contents	.....................................................................................................................	v	List	of	Tables	.........................................................................................................................	viii	List	of	Figures	...........................................................................................................................	ix	Acknowledgements	.................................................................................................................	x	Dedication	.................................................................................................................................	xi	1	 	Introduction	......................................................................................................................	1	1.	1		 Research	Focus	......................................................................................................................	5	1.2		 Contributions	..........................................................................................................................	6	2	 Literature	Review	.............................................................................................................	8	2.1	 Introduction	..............................................................................................................................	8	2.2		 Theories	and	concepts	of	information	avoidance	......................................................	8	2.2.1		 Monitoring	and	Blunting	..............................................................................................................	9	2.2.2	 Selective	Exposure	.........................................................................................................................	10	2.2.3	 Health	Information	Avoidance	.................................................................................................	12	2.2.3.1	 Uncertainty	Management	....................................................................................................................	13	2.3	 Reasons	for	Information	Avoidance	..............................................................................	15	2.3.1	 Personality	........................................................................................................................................	16	2.3.2	 Affective	State	..................................................................................................................................	18	2.3.3	 Source	Characteristics	.................................................................................................................	19	2.4	 Related	Research	in	Information	Behaviour	..............................................................	22	2.4.1	 Information	Literacy	.....................................................................................................................	22	2.4.2	 Information	Overload	..................................................................................................................	23	2.5	 Research	in	Health	Fields	..................................................................................................	24	2.5.1	 Health	Communication	................................................................................................................	25	2.5.2	 Consumer	Health	............................................................................................................................	26	2.6	 Conclusion	..............................................................................................................................	29	3	 Methods	.............................................................................................................................	30	3.1	 Introduction	...........................................................................................................................	30	3.2	 Research	design	....................................................................................................................	31		 vi	3.3	 Research	Questions	.............................................................................................................	32	3.4	 Study	1:		Affect	and	Avoidance	Study	............................................................................	33	3.4.1	 Procedure	and	Instruments	......................................................................................................	33	3.4.2	 Scenarios	............................................................................................................................................	36	3.4.3	 Participation	and	Recruitment	.................................................................................................	40	3.4.4	 Data	Analysis	....................................................................................................................................	41	3.5	 Study	2:		Interview	and	Interaction	Study	...................................................................	42	3.5.1	 Procedure	and	Instruments	......................................................................................................	43	3.5.2	 Scenarios	............................................................................................................................................	45	3.5.3	 MedBrowser	Portal	.......................................................................................................................	47	3.5.4	 Interview	Questions	......................................................................................................................	50	3.5.5	 Participation	and	Recruitment	.................................................................................................	51	3.5.6	 Data	Analysis	....................................................................................................................................	52	3.6		 Conclusion	.............................................................................................................................	56	4	 Affect	and	Avoidance	Study	........................................................................................	59	4.1	 Participants	............................................................................................................................	59	4.2	 Information	Seeking	and	Avoidance	.............................................................................	60	4.3	 Personal	Characteristics	...................................................................................................	61	4.4	 Situational	Affect	..................................................................................................................	62	4.5	 Qualitative	Data	....................................................................................................................	68	4.6	 Conclusion	..............................................................................................................................	72	5	 Results	from	the	Interview	and	Interaction	Study	.............................................	74	5.1	 Demographic	Data	...............................................................................................................	74	5.2	 Health	Information	Seeking	and	Avoidance	...............................................................	77	5.3	 Need	for	Cognition	(NfC),	Threatening	Medical	Situations	Inventory	(TMSI)	and	Positive	and	Negative	Affect	Schedule	(PANAS)	..........................................................	78	5.3.1		 Need	for	Cognition	(NfC)	...........................................................................................................	79	5.3.2	 Monitoring	and	Blunting	(Threatening	Medical	Situations	Inventory	or	TMSI)	81	5.3.3		 Situational	Affect	...........................................................................................................................	83	5.4	 Themes	Identified	in	the	Interviews	.............................................................................	86	5.5	 Self-regulation	......................................................................................................................	86	5.6	 Delegation	..............................................................................................................................	92	5.6.1		 Delegation	To	and	On	Behalf	of	Family	Members	...........................................................	93	5.6.2	 Delegation	to	Healthcare	Professionals	...............................................................................	95	5.7	 Factors	that	Influenced	Information	Avoidance	.......................................................	98	5.8	 Belief	in	One’s	Health	as	a	Personal	Responsibility	.................................................	98	5.9	 Belief	that	One’s	Health	is	in	the	Hands	of	Healthcare	Professionals	or	Fate	 102	5.10	 Belief	in	Healthcare	Professionals	as	Trustworthy	.............................................	106	5.11	 Belief	in	Healthcare	Professionals	as	Not	Trustworthy	.....................................	110	5.12	 Belief	in	Information	Seeking	as	a	Societal	Responsibility	...............................	114	5.13	 Information	Seeking	as	Not	a	Societal	Responsibility	........................................	117		 vii	5.14	 Profile	of	Information	Avoiders	.................................................................................	118	5.15	 Conclusion	.........................................................................................................................	121	6	 Discussion	......................................................................................................................	123	6.1	 Summary	of	Results	..........................................................................................................	123	6.2	 Information	Avoidance	....................................................................................................	126	6.3	 Mechanisms	of	Health	Information	Avoidance	........................................................	127	6.3.1	 Self-regulation	..............................................................................................................................	128	6.3.2	 Delegation	......................................................................................................................................	128	6.3.3	 Filtering	Mechanisms	................................................................................................................	129	6.4	 Influencing	Factors	Associated	with	Health	Information	Avoidance	...............	130	6.4.1	 Personality	.....................................................................................................................................	131	6.4.2	 Affect	.................................................................................................................................................	132	6.4.3	 Information	Source	....................................................................................................................	134	6.5	 Theoretical	Implications	.................................................................................................	135	6.6	 Implications	for	Practice	.................................................................................................	138	6.7	 Conclusion	............................................................................................................................	140	7	 Conclusion	......................................................................................................................	143	7.1	 Overview	...............................................................................................................................	143	7.2	 Limitations	...........................................................................................................................	144	7.3	 Future	Work	........................................................................................................................	147	7.4	 Summary	...............................................................................................................................	148	Bibliography	.........................................................................................................................	149	Appendices	...........................................................................................................................	168	Appendix	A:		Questionnaire	for	Affect	and	Avoidance	Study*	.......................................	168	Appendix	B:		Questionnaire	for	Interview	and	Interaction	Study*	.............................	175	Appendix	C:		Recruitment	form	for	Interview	and	Interaction	study	.........................	181	Appendix	D:		Consent	form	for	Interview	and	Interaction	study	.................................	182	Appendix	E:		Website	material	included	in	the	MedBrowser	for	the	Interview	and	Interaction	study	..........................................................................................................................	185	Appendix	F:		Interview	and	Interaction	study	interview	questions	............................	190	Appendix	G:		Code	rationale	for	interview	data	in	Interview	and	Interaction	study	.............................................................................................................................................................	192			 		 viii	List	of	Tables		Table	3-1	Conditions	with	descriptions	........................................................................................................	38	Table	3-2	Strong	and	weak	scenarios	............................................................................................................	40	Table	3-3	Scenarios	for	conditions	used	in	the	Interaction	and	Interview	study	.......................	46	Table	4-1	Age,	general	health	perception,	and	current	health	perception	of	participants	in	the	Affect	and	Avoidance	study	...............................................................................................................	60	Table	4-2	Comparison	of	pre-	and	post-scenario	emotional	states	measured	by	the	PANAS	scale	.....................................................................................................................................................................	64	Table	5-1	Age,	general	health	perception,	and	current	health	perception	of	participants	in	the	Interview	and	Interaction	study	.....................................................................................................	75	Table	5-2	Health	of	participants	.......................................................................................................................	76	Table	5-3	Interaction	session	measures	for	the	Interview	and	Interaction	study	.....................	77	Table	5-4	Number	of	items	of	health	information	material	viewed	per	genre	category	per	session	................................................................................................................................................................	78	Table	5-5	Interview	and	Interaction	study	scales	....................................................................................	79	Table	5-6	NfC	scores	compared	with	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed	..	79	Table	5-7	Monitoring	scores	and	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed	.........	82	Table	5-8	Blunting	scores	and	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed	.........	82	Table	5-9	Positive	affect	compared	with	total	time	spent	per	item	of	health	information	material,	total	time	spent,	and	number	of	items	of	health	information	material	viewed	...............................................................................................................................................................................	84	Table	5-10	Negative	affect	compared	with	time	spent	per	item	of	health	information	material,	total	time	spent,	and	number	of	items	of	health	information	material	viewed	...............................................................................................................................................................................	84			 		 ix		List	of	Figures		Figure	3-1	Screen	shot	of	Bell's	palsy	(order	1)	........................................................................................	48	Figure	3-2	Screen	shot	for	Bell's	palsy	(order	2)	......................................................................................	49				 		 x	Acknowledgements	I	would	like	to	thank	my	participants.		I	am	so	thankful	to	all	of	you	for	helping	me	to	understand	your	experiences,	viewpoints,	and	struggles.		I	am	also	very	grateful	for	your	enthusiasm	for	my	project.		You	guys	are	awesome!		Next	I	would	also	like	to	thank	George	and	Anne	Piternick,	whose	much-appreciated	grant	allowed	me	to	pay	my	participants.		Thank	you	as	well	to	my	local	community	centre,	whose	staff	very	kindly	permitted	me	to	use	rooms	at	a	discounted	rental	rate.									I	am	especially	grateful	to	all	of	the	people	over	the	course	of	this	degree,	some	of	whom	I	knew	and	some	who	I	didn’t,	who	all	showed	interest	and	excitement	in	my	topic.		It	was	great	to	know	that	other	people	shared	my	fascination,	and	a	good	deal	of	your	comments	informed	my	reading	and	the	final	project.							This	work	would	not	have	been	possible	without	mentoring	and	support	from	my	chief	advisor,	Dr.	Luanne	Freund.		Thank	you	for	all	your	help,	advice,	and	(much)	patience	J	It	was	super	fun	working	with	you.					Thank	you	as	well	to	members	of	my	thesis	committee,	Drs.	Heather	O’Brien,	Eric	Meyers,	and	Leanne	Currie,	who	provided	me	with	valuable	feedback	and	advice	on	my	work.		Thank	you	especially	to	Heather,	whose	timely	and	extensive	comments	were	much	appreciated.			And	of	course,	thanks	to	my	friends,	family	and	my	beautiful	little	kitty,	for	your	love,	support,	hugs,	great	conversations	(yes	of	course	the	cat	talks	J),	cooking	tips,	tea-and-cookie	afternoons,	dating	advice,	movie	nights,	yoga	classes,	and	some	really	cool	new	facts	from	Blair.		Hey,	are	you	guys	reading	this?		Love	to	all,	and	special	snuggles	to	my	sweet	Summer	J				 		 xi	Dedication										To	little	kitty	because	she	got	better,	To	my	nieces—STAY	HEALTHY!!			And	to	Dad.		Thanks	for	the	money!				 		 1	1	 	 Introduction		The	scope	and	delivery	of	information	in	the	Western	world	is	undergoing	a	dramatic	change.		The	advent	of	online	resources	has	enabled	more	and	better	availability	of	information,	resulting	in	new	expectations	for	those	newly	informed	and	capable	information	consumers	who	access	these	resources.		These	expectations	are	especially	evident	in	health,	where	the	recent	emphasis	on	consumer	health	lauds	the	power	of	newly	available	online	information,	which,	it	is	said,	will	enable	people	facing	health	concerns	to	better	research	options,	make	suitable	decisions,	and	more	capably	take	charge	of	their	lives	(Harris,	Wathen,	&	Wyatt,	2010;	Barbarin,	Klasnja	&	Veinot,	2016).		Advocates	of	consumer	health	often	refer	to	information	searching	as	a	means	of	empowerment,	and	point	to	what	they	see	as	the	promise	of	information	to	grant	information	searchers	a	status	akin	to	experts	(Harris,	Wathen	&	Wyatt,	2010;	Barbarin,	Klasnja	&	Veinot,	2016).		But	this	promise	has	not	been	fully	realized.		Although	many	patients	and	caregivers	are	taking	advantage	of	the	wealth	of	health	information	now	accessible	via	the	Internet,	the	overall	picture	is	more	complex,	with	some	people	unable	or	unwilling	to	access	health	information:		preferring	to	avoid	rather	than	seek	(Lambert,	Loiselle	&	Macdonald,	2009;	Howell	&	Shepperd,	2013,	2016,	2017;	Sweeny	&	Miller,	2012).		The	stress	on	searching	and	searching	benefits	renders	this	avoidance	problematic;	avoiders	can	be	disadvantaged	and,	in	effect,	disempowered	by	behaviour	previously	common	in	health	care	settings,	the	lack	of	searching	out	health	information.				Access	to	quality	information	in	health	has	long	been	associated	with	health	benefits:		better	communication	with	doctors,	the	making	of	better	health	decisions	and	the	taking	of	fewer	health	risks	(see	Johnson,	1997;	Shneyderman,	Rutten,	Arheart,	Byrne,	Kornfeld	&	Schwartz,	2016;	Weinstein,	1980,	1982;	Lu,	Dzwo,	Hou	&	Andrews,	2011	for	examples).		These	clear	advantages	of	information	in	health	are	related	to	the	concept	of	health	literacy,	defined	as	a	level	of	communicative	ability	and	skills	necessary	to	make	informed	decisions	(Ferguson,	2013;	Hernandez	&	Pleasant,	2013),	a	desirable	attribute	under	the	banner	of	consumer	health	(Veinot,	2010).		Here	barriers	to	information	seeking	are	attributed	to	difficulties	with	language	and	lack	of	education	or	searching	ability,	as	well	as	to	disparities	in	financial	resources	(see	Oh	&	Cho,	2015	for	one	example).		However,	research	shows	that	other	forces	may	be	at	work,	as	studies	indicate	an	association	between		 2	stress,	anxiety,	and	information	(Miller,	1980;	Lambert,	Loiselle	&	Macdonald,	2009;	Howell	&	Shepperd,	2013,	2016,	2017;	Sweeny	&	Miller,	2012).		In	some	cases,	this	research	demonstrates,	stressed	people	will	avoid	“threat-relevant”	information	(Miller,	1980,	p.	156),	preferring	to	remain	ignorant	rather	than	to	learn	(Miller,	1980;	Howell	&	Shepperd,	2013,	2016,	2017;	Sweeny	&	Miller,	2012).		This	phenomenon,	referred	to	as	“information	avoidance”	(Sweeny,	Miller,	Melnyk	&	Shepperd,	2010,	p.	23)	is	little	understood	but	is	clearly	linked	to	times	of	crisis	such	as	when	individuals	face	health	concerns	and	to	the	negative	emotions	such	as	fear	and	anxiety	generated	by	those	concerns	(Miller,	1980;	Howell,	Ratliff	&	Shepperd,	2016;	Sweeny	&	Miller,	2012).			Many	health	initiatives	designed	to	maintain	good	health	and	assist	in	disease	management	rely	on	information	searching	(Wyatt,	Harris	&	Wathen,	2010;	see	Canada	Health	Infoway	for	one	example).		Some	resources	are	designed	specifically	to	assist	those	who	have	language	or	technology	difficulties	that	prevent	the	access	of	information,	although	more	initiatives	are	required	in	this	area	as	well	(Bjarnadottir,	Millery,	Fleck	&	Bakken,	2016).		In	contrast,	those	patients	and	caregivers	who	may	not	wish	to	search	usually	go	unacknowledged	(Dwyer,	Shepperd	&	Stock,	2015;	Howell	&	Shepperd,	2017).				Thus,	while	access	to	health	information	is	linked	to	better	choices	and	more	effective	health	decisions,	it	is	clear	that	at	certain	times,	some	people	do	avoid	information,	behaviour	often	ignored	by	health	information	providers	(Case	&	Johnson,	2012).		An	important	research	goal	is	to	learn	more	about	this	behaviour,	to	discover	how,	when	and	why	information	avoidance	occurs.				Although	the	phrase	“information	avoidance”	suggests	the	opposite	of	information	searching,	the	phenomenon	is	more	complex.		The	mechanisms	by	which	people	avoid	information	are	little	understood	(Case,	2012;	Howell	&	Shepperd,	2016;	Case	&	Johnson,	2012;	Case,	Andrews,	Johnson	&	Allard,	2005).		Some	studies	of	information	avoidance	have	examined	doctor-patient	communications,	looking	at	whether	or	not	patients	demanded	information	of	health	professionals	(see	Miller,	1980,	1987,	1995,	2014	for	examples).		These	studies	defined	avoidance	as	simply	not	seeking,	i.e.,	not	asking	information	of	the	health	provider	(Miller,	1980,	1987,	1995,	2014).		However,	work	in	the	past	decade,	which	takes	into	account	the	ready	availability	of	health	information	on	the	Internet,	has		 3	suggested	a	more	nuanced	definition	of	information	avoidance.		Examples	of	more	finely	distinguished	avoidance	behaviours	are	found	in	some	recent	studies	(Barbour,	Rintamaki,	Ramsey	&	Brashers,	2012;	Lambert,	Loiselle	&	Macdonald,	2009;	Eheman,	Berkowitz,	Lee,	Mohile,	Purnell,	Rodriguez,	Roscoe,	Johnson,	Kirshner	&	Morrow,	2009;	Howell	&	Shepperd,	2016).		Barbour	and	colleagues	(2012)	report	that	strategies	for	avoiding	information	can	include	removing	or	ignoring	stimuli	(i.e.,	avoiding	knowledgeable	people)	and	controlling	conversations	(i.e.,	changing	the	subject),	while	Lambert,	Loiselle	and	Macdonald	(2009)	suggests	that	avoidance	behaviours	can	include	a	preference	for	one	source	over	another	(i.e.,	speaking	to	healthcare	professionals	only	and	not	with	friends	or	family;	see	also	Sweeny	et	al.,	2010).		Lambert,	Loiselle	and	Macdonald	(2009)	also	describe	information	avoidance	as	following	on	previous	seeking	behaviours;	after	looking	for	information,	patients	may	stop	searching	and	just	“go	with	the	flow”	(p.	32;	see	also	Eheman	et	al.,	2009;	Savolainen,	2012).							Another,	related,	question	is	the	issue	of	why	people	avoid	information.		Explanations	have	ranged	from	suggestions	first	that	avoidance	is	a	personality	trait	or	a	function	of	personality	traits	(Miller,	1980;	Bandura,	1977)	and	second,	that	there	are	links	between	information	avoidance	and	a	person’s	affective	state	(Sweeny	&	Miller,	2012;	Melnyk	&	Shepperd,	2012;	Howell	&	Shepperd,	2016).		A	third,	less	explored	factor	is	found	in	the	characteristics	of	information	sources,	which	can	be	said	to	influence	people’s	information	seeking,	including	decisions	to	use	or	ignore	information	(Nahl,	2005;	Mentis,	2007;	Mentis	&	Rosson,	2009;	James	&	Nahl,	2014).				The	notion	of	information	avoidance	as	a	personality	trait	is	well	established.		Miller	(1980),	in	her	seminal	explanation	of	information	avoidance,	divided	people	into	two	groups:		monitors,	who	search	for	information	in	times	of	stress;	and	blunters,	who	do	not	(see	also	Baker,	1996,	1997).		Although	research	has	linked	this	behaviour	most	thoroughly	to	health	problems	(Howell	&	Shepperd,	2016;	Williams-Piehota	et	al,	2009),	Miller’s	(1980,	1995)	research,	and	the	scale	she	later	developed	(Miller,	1987),	points	to	a	tendency	of	some	people	to	avoid	information	that	persists	across	a	range	of	situations,	from	a	dangerous	plane	ride	to	a	potential	job	loss.		Similarly,	researchers	have	also	examined	other	personality	traits	that	might	stimulate	the	avoidance	of	information	in	a	range	of	situations.		Folkman	and	Lazarus’s	(1984)	stress	and	coping	theory	posits	two	personality-	 4	linked	categories,	problem-focused	copers	and	emotion-focused	copers,	depending	on	which	aspect	of	the	situation	people	pay	attention	to	while	under	stress:		problems	(i.e.,	people	may	cope	by	searching	for	solutions)	or	emotions	(i.e.,	people	may	cope	by	attempting	to	relax	and	not	think	about	the	stress-inducing	problem).		This	theory	has	been	linked	to	information	seeking	and	avoidance	(Lambert	&	Loiselle,	2007;	Howell	&	Shepperd,	2016),	with	problem-focused	copers	tending	to	seek	information	while	emotion-focused	copers	tending	to	avoid	it.					A	more	situational	approach	to	information	avoidance	considers	it	to	be	a	function	of	the	negative	affect	people	in	situations	of	crisis	experience	(Dawson,	Savitsky	&	Dunning,	2006;	Howell	&	Shepperd,	2013;	Sweeny	&	Miller,	2012).		Negative	affect	in	general	is	associated	with	hindrances	in	information	seeking	(Wilson,	1999;	Nahl,	2005).		Fear	and	anxiety,	emotions	that	have	been	shown	to	result	from	health	problems	have	also	been	closely	linked	with	people’s	refusal	to	search	for	information	(Howell	&	Shepperd,	2013;	Sweeny	&	Miller,	2012;	Savolainen,	2014).		Health	research	shows	that	problems	that	are	extremely	serious	and	more	likely	to	produce	negative	affect,	as	in	the	diagnosis	of	a	fatal	disease,	and	those	in	which	the	outcome	will	remain	unaffected	by	people’s	behaviour,	as	in	an	untreatable	disease,	are	the	most	likely	to	produce	information	avoidance	(Melnyk	&	Shepperd,	2012;	Lambert,	Loiselle	&	Macdonald,	2009;	Case	&	Johnson,	2012;	Johnson,	2014;	Dawson,	Savitsky	&	Dunning,	2006).			Similarly,	Uncertainty	Management	Theory	(Babrow,	1992;	Brashers,	Neidig,	Haas,	Dobbs,	Cardillo	&	Russell,	2001;	Neuberger	&	Silk,	2016),	a	theory	that	has	been	linked	to	health	suggests	that	people	might	control	(i.e.,	either	increase	or	decrease)	their	information	seeking	in	order	to	manage	their	uncertainty	about	possible	outcomes.						Another	factor	is	found	in	the	characteristics	of	the	information	sources.		Research	exists	that	details	people’s	preferences	for	certain	information	sources	over	others;	for	example,	a	common	information	science	principle	that	people	prefer	interpersonal	information	sources	over	other	types	is	detailed	by,	among	others,	Wathen	and	Harris	(2007).		This	preference	may	be	reordered	in	times	of	stress	or	crisis,	particularly	in	health,	where	people	may	seek	information	from	traditionally	authoritative	sources	such	as	healthcare	professionals	(Case	&	Johnson,	2012;	Lambert,	Loiselle	&	Macdonald,	2009;	Wathen	&	Harris,	2007;	Toms,	O’Brien,	Kopak	&	Freund,	2005).		Other	research	suggests		 5	links	between	health	information	seeking	and	common	characteristics	of	information	sources	such	as	ease	of	use	(Weng,	Weng,	Kuo,	Yang	&	Lo,	2013;	Lialiou	&	Mantas,	2015;	Lazar	&	Briggs,	2015);	presence	or	absence	of	medical	jargon	(Baker,	1996;	York,	Brannon	&	Miller,	2012;	Williams-Piehota,	Latimer,	Katulak,	Cox,	Silvera,	Mowad	&	Salovey,	2009),	and	presence	or	absence	of	personal	narratives	(Crutzen,	Cyr,	Larios,	Ruiter	&	de	Vries,	2013).		However,	the	range	and	relative	importance	of	such	features	are	still	open	questions.			1.	1		 Research	Focus		 This	dissertation	explores	the	phenomenon	of	information	avoidance,	its	process,	and	the	effect	of	three	factors,	personality	traits,	affective	state,	and	information	source	characteristics.		The	project	focuses	on	the	subject	of	health,	as	this	is	an	arena	in	which	information	plays	a	critical	role,	and	as	avoidance	has	been	documented	as	a	response	to	information	by	people	who	are	experiencing	health	concerns	(Howell	&	Shepperd,	2013,	2016,	2017).		As	this	project	is	in	the	information	behaviour	domain,	information	behaviour	is	defined	very	broadly	and	includes	a	wide	range	of	information	related	activities	such	as	gaining	information	from	interpersonal	sources,	including	family,	friends	and	professionals;	active	seeking	of	information	through	the	use	of	the	Internet	or	other	electronic	and	print	resources;	and	passive	or	incidental	acquisition	of	information	through	exposure	to	the	news	or	other	media.		In	some	health	domains,	stronger	distinctions	are	sometimes	made	between	information-related	activities	such	as	shared	decision-making,	diagnosis	and	screening	leading	to	divisions	between	healthcare	avoidance	(Lund-Nielsen,	Midtgaard,	Rørth,	Gottrup	&	Adamsen,	2011,	p.	277)	and	information	avoidance	(see	also	Persoskie,	Ferrer	&	Klein,	2014).		However,	this	project	takes	a	broader	approach	consistent	with	the	information	behaviour	domain.		The	following	research	questions	guide	this	work:			1. What	factors	contribute	to	information	avoidance?	More	specifically,	to	what	extent	do	personality	traits,	situational	affect,	and	the	nature	of	available	information	sources	influence	information	avoidance?		 Previous	research	has	suggested	that	these	three	factors	influence	information	avoidance,	but	little	research	has	compared	the	three	or	looked	more	closely	at	how	the		 6	influence	of	these	factors	may	function.		Personality	is	here	defined	in	accordance	with	Phares	(1991)	as	“a	pattern	of	characteristic	thoughts,	feelings,	and	attitudes	that	distinguishes	one	person	from	another	and	that	persists	over	time	and	situations	(p.	4).		Affect	is	here	defined	as	the	broad	range	of	people’s	emotional	and	mood	based	experience	(Nash,	2010).		An	information	source	is	defined	as	an	object	that	is	commonly	supposed	to	contain	information,	such	as	a	book	or	an	Internet	website	(Johnson,	1997).					2. What	are	the	mechanisms	of	information	avoidance?				 Information	avoidance	includes	various	patterns	of	behaviour	(i.e.,	controlling	conversations,	ignoring	certain	sources)	and	multiple	levels	(i.e.,	from	total	avoidance	to	the	preferences	for	some	sources	over	others	or	under	certain	conditions).		I	examine	these	more	closely	to	ascertain	the	ways	in	which	people	may	avoid	information.				1.2		 Contributions		This	research	contributes	to	the	disciplines	of	information	science	and	health	communication	by	extending	our	understanding	of	the	nature	and	processes	of	information	avoidance,	and	by	potentially	informing	practices	within	professional	realms	such	as	nursing	and	librarianship.		Information	avoidance	is	infrequently	studied,	and	caregivers	and	information	providers	can	benefit	from	understanding	when	and	how	people	are	likely	to	avoid	information.		This	project	also	adds	to	the	growing	body	of	research	in	information	science	on	affect,	which	Nahl	(2007)	cites	as	an	important	field	of	study,	one	that	rectifies	previous	views	of	the	user	as	a	simple	sender-receiver	of	messages	and	more	fully	examines	people’s	motivations	and	disincentives	for	searching.		I	explore	the	hindering	effects	of	negative	affect,	which,	although	touched	upon	by	several	researchers	(Nahl,	2005;	Mentis,	2007;	James	&	Nahl,	2014	for	examples)	have	not	as	yet	been	examined	in	depth.				This	work	also	benefits	the	health	community,	in	areas	such	as	health	communication.		While	some	researchers	in	this	field	have	looked	at	this	topic,	questions	do	remain.		A	concentration	on	information	source	characteristics,	perhaps	understandably,	has	not	entered	into	the	realm	of	health	research	on	information	avoidance	(see	Melnyk	&	Shepperd,	2012;	Dawson,	Savitsky	&	Dunning,	2006	for	examples).		While	researchers	have		 7	examined	the	effect	of	information	source	characteristics	on	selection,	few	have	looked	at	the	effects	of	such	characteristics	on	avoidance	under	stressful	conditions,	an	important	consideration	in	the	health	domain.		In	practical	terms,	the	results	provide	guidance	on	the	presentation	and	dissemination	of	consumer	health	information,	especially	information	regarding	life-threatening	illnesses.				 	This	dissertation	will	detail	the	studies	that	constitute	the	research	as	well	as	discussing	implications	of	the	results.		I	will	begin	with	a	review	examining	the	literature	that	guided	the	research	(Chapter	2).		Next,	I	will	continue	with	a	methods	chapter	(Chapter	3)	outlining	the	two	studies	that	make	up	the	research,	following	with	two	chapters	(Chapters	4	and	5)	that	explain	the	results	of	each	study.		In	the	next	chapter	(Chapter	6),	I	will	discuss	the	results,	looking	at	the	theoretical	and	practical	implications	of	the	research	before	concluding	the	dissertation	in	a	final	chapter	(Chapter	7).					 		 		 8		2	 Literature	Review		2.1	 Introduction		“We	can	seek	knowledge	in	order	to	reduce	anxiety...we	can	also	avoid	knowing	in	order	to	reduce	anxiety.”		So	said	Maslow	(1963,	p.	114),	and	yet	fifty	years	later,	information	avoidance,	conceptualized	by	Sweeny,	Melnyk,	Miller	&	Shepperd	(2010)	as	“any	behaviour	intended	to	prevent	or	delay	the	acquisition	of	available	but	potentially	unwanted	information’’	(p.	341)	remains	largely	unclear.		The	situation	is	particularly	problematic	in	health,	as	the	avoidance	of	information	by	patients	and	caregivers	can	lead	to	delayed	treatments,	a	lack	of	knowledge	of	the	effects	of	health	conditions,	and	poor	decision-making.		Explorations	of	this	topic	have	been	relatively	rare,	in	part	because	information	avoidance	has	been	viewed	as	a	negative	and	abnormal	behaviour	that	counters	the	dominant	narratives	of	healthcare	and	information	studies	in	which	information	seeking	is	viewed	as	a	positive	and	normative	behaviour.		This	subject	is	currently	of	concern,	but	many	questions	still	remain:		among	these	are	uncertainties	regarding	the	personality	traits	and	affect	of	avoiders	and	seekers,	and	the	sources	they	choose	or	do	not	choose.		This	review	of	the	literature	explores	the	research	on	information	avoidance,	information	behaviour	and	health	information	seeking	in	order	to	identify	some	of	the	open	questions	that	remain.			2.2		 Theories	and	concepts	of	information	avoidance		Research	on	information	avoidance	tends	to	focus,	with	some	exceptions,	on	two	theoretical	frameworks,	Miller’s	(1980,	1987,	1995,	2014)	Monitoring	and	Blunting	theory	and	the	concept	of	Selective	Exposure	(Hyman	&	Sheatsley,	1947;	Festinger,	1957,	1961).		Research	also	exists	that	discusses	information	avoidance	particularly	in	the	area	of	health,	sometimes	referencing	Uncertainty	Management	Theory.						 		 9	2.2.1		 Monitoring	and	Blunting		Miller’s	(1980)	seminal	study	looked	at	information	avoidance	among	stressed	patients	preparing	for	a	medical	procedure.		Based	on	previous	research,	Miller	(1980)	proposed	a	division	of	these	patients	into	two	categories,	concluding	that	monitors	are	people	who	under	stress	are	comforted	by	information	and	will	welcome	and	seek	it	out,	while	blunters	are	people	who	under	stress	are	made	more	anxious	by	information	and	will	thus	avoid	it.		Miller’s	(1980,	1987)	categories	differentiate	behaviour	in	situations	of	stress,	hence	their	presence	in	medical	patients	experiencing	extreme	stress.		However,	Miller’s	(1980)	research	posits	that	these	categories	are	present	in	other	stressful	situations	as	well.		Miller	(1980,	1987)	also	developed	and	tested	a	scale,	the	Miller	Behavioural	Style	Scale	(MBSS),	which	gives	people	four	hypothetical	stress-inducing	scenarios,	one	that	pertained	to	health.		The	specific	health	scenario	asks	participants	to	“vividly	imagine	that	you	are	afraid	of	the	dentist	and	have	to	get	some	dental	work	done”	(Miller,	1980,	p.	155).		The	rest	of	the	scenarios	present	other	stressful	situations:		being	held	hostage,	a	plane	crash,	and	job	loss.		Monitoring	or	Blunting	statements	follow:		“I	would	ask	the	dentist	for	an	explanation”	or	“I	would	do	mental	puzzles	in	my	head”	(p.	155).		Respondents	check	those	statements	that	apply.		This	method	of	assessing	personality	tendencies	is	limited	because	to	“vividly	imagine”	(p.	155)	is	not	to	experience,	and	thus	people’s	reactions	to	such	scenarios	might	not	match	their	actual	behaviour	(Lambert	&	Loiselle,	2007;	Evans,	Roberts,	Keeley,	Blossom,	Amaro,	Garcia,	Stough,	Canter,	Robles	&	Reeb,	2014).		However,	this	scale,	as	well	as	later	scales	based	on	the	MBSS	such	as	the	Threatening	Medical	Situations	Inventory	(van	Zuuren,	de	Groot,	Mulder	&	Muris,	1996)	and	Miller’s	(1980,	1987,	1995)	Monitoring	and	Blunting	categories	are	often	used	as	a	way	of	characterizing	and	assessing	information	avoidance	(see	Baker,	1996;	Williams-Piehota	et	al.,	2009;	McCloud,	Jung,	Gray	&	Viswanath,	2013;	Howell	&	Shepperd,	2016;	Miller,	2014).					Other	limitations	of	Miller’s	(1980,	1987,	1995,	2014)	work	is	that	her	categories	do	not	explain	much	about	how	people	avoid	information,	and	that	they	do	not	include	online	sources	such	as	websites	and	social	media.		Some	researchers	have	extended	Miller’s	(1980,	1987)	study.		Two	groups	of	researchers,	Lambert,	Loiselle	and	Macdonald	(2009)	and	Barbour,	Rintamaki,	Ramsey	and	Brashers	(2012),	identify	some	patterns	of	avoidance	behaviour.		Lambert,	Loiselle	and	Macdonald	(2009)	state	that	Miller’s	(1980)	term	Blunting	is	inexact,	proposing	instead	two	further	categories:		information	disinterest		 10	(minimal	information	seeking)	and	avoidance	(guarded	information	seeking),	giving	examples	of	each	(Hertwig	&	Engel,	2016).		However,	their	description	of	avoidance	is	incomplete	and	does	not	explain	why	some	guarders	seek	more	information	than	others.		Barbour	et	al.	(2012),	in	their	attempt	to	clarify	what	they	considered	the	typical	oversimplification	of	research	on	information	avoidance,	conducted	a	qualitative	study	in	which	they	distributed	questionnaires	to	507	students	and	418	community	participants	regarding	their	health	information	behaviour.		They	identified	two	avoidance	strategies,	removing	or	ignoring	stimuli	and	controlling	conversations.		Both	sets	of	researchers	suggest	that	people	avoid	information	in	other	ways;	however,	neither	looks	at	these	multiple	ways	of	avoidance.				2.2.2	 Selective	Exposure		Selective	Exposure,	originally	conceptualized	by	Hyman	&	Sheatsley	(1947)	as	the	purposeful	selection	of	some	stimuli	over	others,	is	often	associated	with	information	avoidance	(Sweeny	et	al.,	2010).		Based	on	work	by	Festinger	(1957,	1961),	Selective	Exposure	is	a	cognitive	process	wherein	people	who	have	pre-existing	ideas	about	a	topic	or	issue	are	thus	motivated	to	seek	out	information	that	agrees	with	their	existing	state	of	knowledge	(see	also	Mills,	1965;	Muramatsu	&	Pratt,	2001;	Westerwick,	Johnson	&	Knobloch-Westerwick,	2013,	2016;	Nielsen	&	Shapiro,	2009).		Sears	and	Freedman	(1967),	building	on	Festinger’s	(1957,	1961)	work,	added	a	caveat	in	their	finding	that	people	may	temper	their	ideas	with	incongruent	facts,	rather	in	the	manner	of	exceptions	proving	rules.		However,	the	majority	of	dissonant	information	is	avoided.						Some	work	on	Selective	Exposure	has	been	done,	resulting	in	the	documentation	of	certain	source	preferences	exhibited	by	non-healthcare	professionals	(Wathen	&	Harris,	2006;	Lustria,	2007;	Case	&	Johnson,	2012;	Johnson,	2014;	Westerwick,	Johnson	&	Knobloch-Westerwick,	2013,	2016).		Johnson	(2014)	cites	the	common	information	science	principle	that	interpersonal	sources	are	more	likely	to	be	consulted	(see	also	Gretzel,	2007;	Chang	&	Caneday,	2011)	but	suggests	that	in	some	health	situations,	these	preferences	may	be	altered	in	favour	of	other,	traditionally	authoritative,	health	sources	such	as	doctors,	nurses,	or	emergency	room	professionals	(see	also	Johnson,	1997;	Case	&	Johnson,	2012;	Savolainen,	2007;	Catellier	&	Yang,	2012;	Veinot,	Kim	&	Meadowbrooke,	2011).		These		 11	source	preferences	may	not	be	complete;	Westerwick,	Johnson	and	Knobloch-Westerwick	(2013,	2016)	found	that	many	people	engage	in	self-regulatory	behaviours	involving	partial	consultation	of	information	sources,	particularly	when	these	sources	might	encourage	or	discourage	health	beliefs	or	actions.					Johnson’s	(1997;	Case	&	Johnson,	2012;	Johnson,	2014)	Comprehensive	Model	of	Information	Seeking	(CMIS)	theorizes	that	some	factors	present	in	health	information	seekers	result	in	different	source	choices.		The	CMIS,	which	was	independently	developed	and	then	empirically	tested	in	various	areas	such	as	health	and	business	organizations	(Case	&	Johnson,	2012),	defines	these	factors	as	demographics,	experience,	beliefs,	and	“salience”	(Johnson,	1997,	p.	71),	a	form	of	personal	relevance	in	which	individuals	perceive	the	applicability	of	information	to	a	faced	problem.		Johnson	(1997)	details	stages	in	which	the	varying	salience	alters	the	choice	of	sources	consulted	by	health	information	seekers:		casual,	in	which	a	generalized	interest	in	health	and	little	salience	is	present;	purposive-placid,	which	involves	slightly	more	salience	and	awareness	of	health,	but	no	specific	concerns;	purposive-clustered,	in	which	people	seek	information	about	a	particular	issue	or	disease	and	thus	more	salience	is	present;	and	directed,	usually	occurring	after	a	disease	diagnosis	and	where	much	salience	is	present.		Johnson’s	(1997)	contention	is	that	sources	consulted	in	the	purposive-clustered	and	directed	stages,	where	people	are	seeking	information	that	personally	concerns	them,	are	generally	those	sources	which	are	considered	more	authoritative	by	the	seeker.		Case	and	Johnson	(2012),	though,	suggest	that	in	some	cases	people	disagree	on	which	other	sources	possess	authority	(see	also	Ward,	Coffey	&	Meyer,	2015).		Catellier	and	Yang	(2012),	for	example,	point	out	that	trust	of	certain	institutions,	government	for	example,	increases	the	likelihood	that	people	will	seek	information	on	material	they	perceive	as	associated	with	those	institutions.					Monitoring	and	Blunting	and	Selective	Exposure	both	propose	some	mechanisms	of	people’s	information	avoidance	such	as	not	asking	questions	of	a	health	professional	and	selecting	one	source	over	another.		However,	this	list	of	patterns	of	behaviour	seems	incomplete,	particularly	with	regards	to	broader	range	of	sources	and	ways	people	interact	with	information.		Monitoring	and	Blunting	and	Selective	Exposure	also	suggest	only	partial	explanations	for	this	behaviour.		Monitoring	and	Blunting	suggests	that	avoidance	is	linked	to	people’s	innate	reactions	to	stress,	leaving	out	situational	factors	such	as	affect.		Selective		 12	Exposure	does	include	affect	but	attributes	information	avoidance	only	to	fear,	omitting	other	forms	of	affect	or	indeed	other	personality	traits	that	may	function	as	influences	on	information	behaviour.		Thus	how	and	why	people	avoid	information	remain	open	questions.						2.2.3	 Health	Information	Avoidance		Information	avoidance	has	been	documented	in	the	field	of	health,	where	people	can	avoid	health	information	pertaining	to	their	illnesses	or	conditions	(Sweeny	et	al.,	2010;	Miller,	1980,	1987,	1995;	Sweeny	&	Miller,	2012;	Case	&	Johnson,	2012;	Lu,	Dzwo,	Hou	&	Andrews,	2011;	Lambert,	Loiselle	&	Macdonald,	2009;	Howell	&	Shepperd,	2013;	2016).		Some	research	links	health	information	in	certain	cases	to	increased	anxiety	and	fear	(Howell,	Shepperd	&	Logan,	2013;	Shepperd,	Emanuel,	Howell	&	Logan,	2015;	Lu,	Andrews	&	Hou,	2009;	Melnyk	&	Shepperd,	2012;	Sweeny	&	Miller,	2012;	Miller,	1980,	1987,	1995).		In	a	focus	group	study,	Howell,	Shepperd	and	Logan	(2013)	studied	participants,	80	black	adults,	as	to	the	barriers	that	prevented	these	people	from	undergoing	screening	for	mouth	and	throat	cancer	(MTC),	a	condition	for	which	they	were	particularly	at	risk.		The	researchers	found	that,	in	cases	where	the	adults	were	more	fearful	about	MTC,	they	were	less	likely	to	be	screened,	calculating	that	the	fear	of	not	knowing	was	preferable	to	the	terror	and	anxiety	that	a	positive	screening	would	bring.			One	consideration	here	is	the	notion	of	health	information	itself,	for	which	definitions	differ.		The	key	theories	described	in	sections	2.2.1	and	2.2.2,	Monitoring	and	Blunting	and	Selective	Exposure,	include	diverse	aspects	of	healthcare	in	the	category	of	“information,”	e.g.,	questions	posed	to	healthcare	professionals	and	to	adjacent	staff	such	as	receptionists	and	facts	on	informational	brochures	(Miller,	1980;	Hyman	&	Sheatsley,	1947;	Sweeny	et	al.,	2010;	Case	&	Johnson,	2012).		This	broad	definition	of	information	is	consistent	with	research	in	the	information	behaviour	field	of	study,	and	conforms	to	approaches	taken	by	many	studying	the	acquisition	and	avoidance	of	health	information	(Howell	&	Shepperd,	2013,	2016;	Wathen	&	Harris,	2007;	Warner	&	Procaccino,	2004).		Howell	and	Shepperd	(2013,	2016)	comment	on	the	avoidance	of	screening	results,	informational	websites,	and	visits	to	healthcare	professionals	as	“health	information	avoidance”	(Howell	&	Shepperd,	2013,	p.	258),	while	Wathen	and	Harris	(2007)	refer	to		 13	websites,	comments	from	healthcare	professionals,	and	phone	calls	from	relatives	as	“health	information”	(p.	639).		Other	researchers	distinguish	between	some	forms	of	information,	e.g.,	Internet	and	social	media	information,	information	from	healthcare	professionals	(Lund-Nielsen	et	al.,	2011;	Persoskie,	Ferrer	&	Klein,	2014).		Other	researchers	consider	that	some	of	the	above	constitute	“information,”	i.e.,	written	information	from	the	Internet,	social	media	platforms,	and	print	resources,	and	other,	often	verbal	information	from	healthcare	professionals	is	part	of	healthcare	(Lund-Nielsen	et	al.,	2011;	Kryworuchko,	Hill,	Murray,	Stacey	&	Fergusson,	2012;	Feenstra,	Boland,	Lawson,	Harrison,	Kryworuchko,	Leblanc	&	Stacey,	2014).		Lund-Nielsen	and	colleagues	note	that	“healthcare	avoidance”	(p.	277),	i.e.,	information	and	potential	treatment	from	healthcare	professionals,	is	poorly	defined	and	may	or	may	not	include	information	sources	recommended	by	healthcare	professionals	such	as	websites.		However,	a	more	inclusive	approach	to	information	can	also	be	limited,	as	it	may	ignore	differences	stemming	from	situation,	e.g.,	a	verbal	diagnosis	from	a	healthcare	professional	employed	in	a	decision-making	scenario	differs	significantly	from	information	provided	by	an	online	website.		Patterns	of	avoidance	may	vary	in	these	different	situations.						2.2.3.1	 Uncertainty	Management		Some	health	research	links	avoidance	and	seeking	of	information	to	the	management	of	uncertainty	(Case	&	Johnson,	2012;	Neuberger	&	Silk,	2016;	Sairanen	&	Savolainen,	2010;	Barbour	et	al.,	2012;	Brashers	et	al.,	2001).		Uncertainty	Management	Theory	suggest	that	people	experience	uncertainty,	defined	in	this	dissertation	as	a	“cognitive	state	causing	affective	symptoms	of	anxiety	and	lack	of	confidence”	(Kuhlthau,	1993,	p.	347),	in	various	manners,	depending	on	cognitive	appraisals	of	the	situation	(Babrow,	1992;	Brashers	et	al.,	2001).		Negative	uncertainty,	for	example,	a	gap	in	knowledge,	is	often	perceived	as	a	stimulus	to	information	seeking	(Kuhlthau,	2004;	Wilson,	1999);	yet	people	can	maintain	uncertainty	in	situations	where	it	is	viewed	as	positive,	for	example,	where	remaining	uncertain	can	engender	hope	when	faced	with	a	disease	with	a	possible	negative	prognosis	(Folkman,	2010;	Shepperd,	Pogge	&	Howell,	2016).		Following	this	logic,	people	may	use	information	to	manipulate	uncertainty,	seeking	information	when	negative	uncertainty	occurs	and	avoiding	information	in	order	to	preserve	positive	uncertainty	(Neuberger	&	Silk,	2016).		In	a	study	by	Sairanen	and	Savolainen	(2010),	for		 14	example,	nine	students	discussed	their	reactions	to	health	information,	citing	instances	where	they	chose	to	preserve	uncertainty	and	avoid	information.		Avoidance	was	common	in	situations	in	which	the	students	felt	that	information	would	cause	them	to	face	such	negative	affect	as	fear,	anxiety	and	depression,	and	at	times	when	the	students	felt	particularly	unable	to	cope	with	such	affect	due	to	other	stressors.					One	instance	of	the	above	stated	preservation	of	positive	uncertainty	has	been	found	in	people’s	efforts	to	maintain	their	optimistic	bias	(Lu,	Andrews	&	Hou,	2009;	Sairanen	&	Savolainen,	2010;	Shepperd,	Pogge,	Howell,	2016).		The	optimistic	bias	theory	suggests	that	people	have	great	confidence	in	their	own	abilities	to	withstand	risks,	as	compared	with	their	peers	(Weinstein	1980,	1982).		In	Weinstein’s	(1982)	study,	100	college	students	rated	their	susceptibility	to	45	health-	and	life-threatening	problems;	Weinstein	(1982)	discovered	that	most	saw	their	chances	of	experiencing	these	problems	as	below	average.		Optimistic	bias	has	been	associated	with	avoiding	information,	in	particular	with	the	avoidance	of	screening	tests	for	various	diseases	(Lu,	Andrews	&	Hou,	2009;	Shepperd,	Klein,	Waters	&	Weinstein,	2013;	Howell,	Shepperd	&	Logan,	2013;	Shepperd,	Emanuel,	Howell	&	Logan,	2015).		In	Lu,	Dzwo,	Hou	&	Andrews’s	(2011)	study,	for	example,	optimistic	bias	was	cited	as	one	reason	that	many	of	the	566	Taiwanese	respondents	surveyed	indicated	that	they	would	not	seek	information	about	potential	restrictions	regarding	arsenic-contaminated	frying	oil,	despite	the	serious	health	risks	inherent	in	such	food	and	the	predominant	use	of	the	oil	in	Taiwanese	cuisine;	i.e.,	these	respondents	were	optimistic	that	their	food	would	not	be	contaminated.		Shepperd	and	colleagues	(Shepperd,	Klein,	Waters	&	Weinstein,	2013;	Shepperd,	Pogge,	Howell,	2016),	though,	point	out	that	while	such	optimistic	biases	are	prevalent,	they	can	vary	in	intensity	and	thus	may	not	always	directly	predict	information	seeking	actions.							Thus	much	information	avoidance	takes	place	in	the	health	domain,	where	the	receipt	of	information	can	be	associated	with	negative	affect	and	where	the	lack	of	information	may	allow	positive	emotions	to	persist.		Two	common	information	avoidance	theories	are	Miller’s	(1980,	1987,	1995,	2014)	Monitoring	and	Blunting	theory	and	the	concept	of	Selective	Exposure	(Hyman	&	Sheatsley,	1947;	Festinger,	1957,	1961).		Monitoring	and	Blunting	explains	that	people	fall	generally	into	two	categories	regarding	their	responses	to	stressful	situations:		monitors	concentrate	on	the	stress-causing	problem,		 15	while	blunters	concentrate	on	the	emotions	resulting	from	that	problem.		These	categories	have	been	criticised	as	they	do	not	explain	how	information	avoidance	takes	place,	and	as	they	omit	ways	that	people	access	or	encounter	information	online.			Selective	Exposure,	originally	defined	by	Hyman	&	Sheatsley	(1947)	as	the	purposeful	selection	of	some	stimuli	over	others,	Selective	Exposure	details	a	cognitive	process	wherein	people	having	pre-existing	ideas	about	a	topic	or	issue	seek	out	information	that	agrees	with	these	ideas.		Selective	Exposure	has	been	influential	in	the	health	domain,	where	the	source	preferences	of	patients	and	caregivers	have	been	documented,	in	particular	by	Johnson	(1997;	Case	&	Johnson,	2012;	Johnson,	2014)	as	explain	in	his	Comprehensive	Model	of	Information	Seeking	(CMIS).		Research	also	exists	that	discusses	information	avoidance	particularly	in	the	area	of	health,	although	this	research,	as	discussed,	can	define	“health	information”	in	dissimilar	ways.		Uncertainty	Management	Theory	explains	that	uncertainty,	here	defined	as	both	affective	and	cognitive,	functions	as	a	stimulus	and	hindrance	to	information	seeking,	with	negative	uncertainty	being	associated	with	information	seeking	and	positive	uncertainty	linked	to	information	avoidance.		The	next	section	(2.3)	discusses	reasons	for	information	avoidance,	thus	detailing	the	literature	regarding	one	of	the	research	questions.		This	section	will	refer	back	to	some	of	these	theories	in	order	to	explain	why	people	avoid.			2.3	 Reasons	for	Information	Avoidance			 A	second	element	of	information	avoidance	that	is	not	well	explained	is	why	people	avoid	information.		Health	information	behaviour	has	to	do	with	complex	factors	including,	among	other	factors,	finances,	time,	information	searching	habits,	perceived	efficacy	of	searching	behaviour,	and	perceived	efficacy	of	healthcare	professionals	recommending	the	behaviour	(Johnson,	2014;	Prochaska	&	DiClimente,	1983;	Kryworuchko	et	al.,	2012;	Nouvet	et	al.,	2016).		This	research	focuses	on	a	subset	of	all	possible	factors:		personality,	affect,	and	information	source.		Other	factors	may	of	course	influence	people’s	health	information	behaviour,	but	they	are	beyond	the	scope	of	this	dissertation.		Miller	(1980,	1987,	1995)	offers	a	personality-linked	explanation;	she	found	that	innate	reactions	to	stress	among	her	participants	led	to	distinct	patterns	of	information	behaviour,	resulting	in	two	categories,	monitors	and	blunters.		Selective	Exposure	suggests	an	affective	state-based	explanation:		some	information	results	in	negative	affect	among	people,	which	leads	them	to	ignore	this	information	as	opposed	to	other,	less	frightening	information.		A	third	explanation	related	to	Selective	Exposure	is	found	in	the	characteristics	of	information		 16	sources,	in	which	some	elements	of	some	information	sources	cause	them	to	be	avoided.		In	this	section,	I	will	review	these	three	factors,	personality,	affect,	and	information	sources,	as	to	how	they	relate	to	information	avoidance.					2.3.1	 Personality		Some	researchers	see	information	avoidance	as	a	behaviour	strongly	influenced	by	personality	(see	Moorman	&	Matulich,	1993;	Dutta-Bergman,	2004,	2006;	Bandura,	1977;	Folkman	&	Lazarus,	1984;	Miller,	1980).		Personality	is	here	defined	in	accordance	with	Phares	(1991)	as	“a	pattern	of	characteristic	thoughts,	feelings,	and	attitudes	that	distinguishes	one	person	from	another	and	that	persists	over	time	and	situation”	(p.	4).		Values	and	preferences	are	also	incorporated	in	this	definition	of	personality,	an	inclusion	that	points	to	one	of	the	key	difficulties	in	defining	personality	(Heinstrom,	2003,	2010).		In	her	work,	Heinstrom	(2003)	notes	that	studies	of	personality	are	often	criticised,	as	it	is	problematic	to	determine	whether	traits	belonging	to	people	persist	over	time	or	are	due	to	a	particular,	and	more	fleeting,	situation.		She	additionally	comments	that	in	some	situations	such	as	extreme	illness,	the	influence	of	personality	can	be	modified	or	even	reversed	as	people	struggle	to	encompass	difficult	circumstances.		This	difficulty	is	made	manifest	in	the	work	of	some	health	researchers,	who	comment	that	preferences	and	values	can	be	changeable	in	situations	such	as	acute	or	end-of-life	care,	and	thus	resultant	decisions	regarding	aspects	of	these	situations	must	be	achieved	by	continuous	consultation	with	patients	(Kryworuchko	et	al.,	2012;	Feenstra	et	al.,	2014;	Nouvet,	Strachan,	Kryworuchko,	Downar	&	You,	2015).		Despite	these	criticisms,	though,	personality	has	been	identified	as	an	influence	on	health	information	seeking	and	avoidance.		Moorman	and	Matulich	(1993),	for	example,	suggest	that	people	have	different	and	consistent	attitudes	about	health;	this	health	motivation,	defined	as	a	“goal-directed	arousal	to	engage	in	preventative	health	behaviours”	(p.	210)	is	considered	personality-based	and	can	result	in	varying	levels	of	health	information	seeking	(Dutta-Bergman,	2004,	2006;	Oduyemi,	Ayegboyin,	&	Salami,	2016).				Similarly,	Bandura’s	(1977)	concept	of	self-efficacy	has	been	related	to	health	information	seeking	and	avoidance	(Nabi	&	Thomas,	2013;	Lee	&	Hawkins,	2016).		In	a	description	of	this	concept,	Bandura	(1977)	comments	that	people	have	different	beliefs	in		 17	their	ability	to	follow	a	model	of	new	behaviour,	and	thus	those	people	with	low	self-efficacy	may	search	for	information	less	than	others	(see	also	Chatman,	1991,	1996,	1999).		Johnson	(1997;	Case	&	Johnson,	2012)	notes,	too,	that	people’s	beliefs	in	the	efficacy	of	good	“health	behaviours”	and	the	efficacy	of	treatment,	can	govern	their	information	seeking	decisions	and	behaviours.		Some	of	these	beliefs	may	reflect	a	desire	to	be	optimistic;	Folkman	(2010)	posits	that	medical	hope	can	be	maintained	by	a	lack	of	information	seeking	and	a	blind	faith	in	personal	strength,	a	higher	power	or	God,	or	the	expertise	of	healthcare	professionals.		Although	Bandura’s	(1977)	original	concept	is	situation-specific,	other	later	researchers	conceptualize	a	similar	“perceived	competence”	(Wallston,	Osborn,	Wagner	&	Hilker,	2010,	p.	110)	that	remains	constant	over	time	(Smith,	Wallston	&	Smith,	1995;	Wallston,	1989).		Bandura’s	(1977)	concept	can	also	be	related	to	another	personality-based	trait,	health	perception.		This	trait	is	a	complex	concept	determining	people’s	personal	views	of	their	own	health	(Powers	&	Oltmanns,	2013;	Lu,	Andrews	&	Hou,	2009;	Lu,	Dzwo,	Hou	&	Andrews,	2011).		Health	perception	can	be	difficult	to	ascertain	as	laypeople	can	define	health	differently	than	do	healthcare	professionals	(Huber,	Knottnerus,	Green,	van	der	Horst,	Jadad,	Kromhout,	Smit	et	al.,	2011).				 Self-efficacy	can	also	be	related	to	other	personality	traits.		Folkman	and	Lazarus	(1984)	identify	different	personality-based	reactions	to	stress,	which	can	also	affect	information	seeking.		Stress	and	coping	theory	defines	stress	as	a	particular	relationship	between	a	person	and	his/her	environment	appraised	by	the	person	as	threatening	or	otherwise	beyond	his/her	ability	to	handle.		People	cope	with	stress	either	by	focusing	on	the	problem	from	which	the	stress	originates	or	by	concentrating	on	the	emotion	generated	by	the	stress-inducing	problem.		Problem-focused	coping	has	been	linked	to	information	seeking,	while	emotion-focused	coping	is	connected	with	avoidance	(Lambert	&	Loiselle,	2007;	Howell	&	Shepperd,	2016;	Williams-Piehota	et	al.,	2009).				Though	these	links	between	personality	and	information	seeking	have	been	questioned	(see	Lambert	&	Loiselle,	2007	for	one	example),	the	link	between	personality	traits	and	information	seeking	has	been	further	developed	in	the	work	of	Heinstrom	(2003,	2010),	who	relates	such	personality	traits	or	“dimensions”	(Heinstrom,	2003,	p.	165)	to	information	styles	such	as	invitational,	exploring,	purposeful,	passive,	and	avoiding,	with	that	last	being	linked	to	such	traits	as	introversion	and	lack	of	conscientiousness	(see	also		 18	Bawden	&	Robinson,	2011).		One	limitation	of	this	work	is	that,	as	stated	earlier,	personality	is	difficult	to	determine,	with	multiple	meanings;	additionally,	tests	to	determine	personality	are	also	controversial	(see	Heinstrom,	2003;	Bawden	&	Robinson,	2011	for	criticisms).		Another	problem	is	that	the	influence	of	personality	on	information	behaviour	is	equally	difficult	to	determine,	due	to	the	effect	of	other	contributing	factors	such	as	situation	and	affective	state	(Ek	&	Heinstrom,	2011;	Heinstrom,	2010;	Heinstrom,	Sormunen,	&	Kaunisto-Laine,	2014).		Nevertheless,	personality	traits	are	often	suggested	as	a	reason	for	information	avoidance	(Miller,	1980,	1987,	1995).				2.3.2	 Affective	State		Affect	itself	is	also	difficult	to	define.		It	is	usually	explained	in	accordance	with	Nash	(2010)	as	broadly	denoting	the	ranges	of	people’s	emotional	and	mood	based	experience,	containing	lists	of	elements	such	as	Nahl’s	(2007)	“emotion,	feeling,	mood,	sentiment,	affection,	disposition,	preference,	interest,	value,	motivation,	intention,	and	goals”	(p.	xviii;	see	also	Kuhlthau,	2004).		However,	some	researchers	consider	affect	to	be	equivalent	to	emotion	(Fulton,	2009);	they	argue	that,	otherwise,	affect	functions	as	a	catch-all,	with	all	human	attributes	that	do	not	correspond	to	cognition	or	behaviour	being	placed	in	the	category	of	affect.				Despite	these	difficulties	defining	affect,	negative	affect	in	particular	has	been	strongly	linked	to	information	avoidance.		Research	shows	that	in	many	cases	where	extreme	negative	affect	is	generated,	when	people	fear,	for	example,	the	diagnosis	of	a	severe	and	untreatable	health	condition	or	the	approach	of	an	unalterable	and	difficult	life	situation,	information	avoidance	is	more	likely	to	take	place	(Melnyk	&	Shepperd,	2012;	Sweeny	&	Miller,	2012;	Howell	&	Shepperd,	2013,	2016,	2017;	Dwyer,	Shepperd	&	Stock,	2015).		In	their	studies	on	avoidance	of	breast	cancer	information	among	undergraduate	women	and	women	over	the	age	of	35,	Melnyk	and	Shepperd	(2012)	found	that	greater	negative	affect,	specifically	fear,	exacerbated	the	likelihood	of	these	women	avoiding	information	detailing	their	lifetime	risk	for	breast	cancer.		Melnyk	and	Shepperd	(2012)	distributed	brochures	that	alternately	depicted	controllable	and	uncontrollable	aspects	of	breast	cancer	and	then	gave	participants	the	opportunity	to	be	tested	for	genes	strongly	linked	to	breast	cancer,	the	BRCA1	and	BRCA2	genes.		The	study	found	that	more	women		 19	who	read	about	uncontrollable	factors	of	breast	cancer	were	fearful	of	the	disease	and	less	likely	to	opt	to	learn	their	risk	than	those	who	read	about	controllable	factors.		Similar	experiments	have	taken	place	manipulating	disease	severity	with	similar	results	(Dawson,	Savitsky	&	Dunning,	2006;	Sweeny	&	Miller,	2012).				2.3.3	 Source	Characteristics		Although	few	conclusions	have	been	reached	about	which	sources	are	chosen	when	people	selectively	expose	themselves	to	information,	some	relevant	research	does	exist	on	source	choice.1		Some	research	has	identified	characteristics	that	affect	people’s	choice	of	sources;	these	include	perspective	(Nielsen	&	Shapiro,	2009;	Neuberger	&	Silk,	2016;	Barbour	et	al.,	2012)	and	presence	or	absence	of	personal	narratives	(Yli-Uotila,	Rantanen	&	Suominen,	2013;	Beck,	Aubuchon,	McKenna,	Ruhl	&	Simmons,	2014;	Crutzen,	Cyr,	Larios,	Ruiter	&	de	Vries,	2013).		Nielsen	and	Shapiro	(2009),	citing	research	on	Selective	Exposure	(see	above),	suggest	that	the	perspective	of	the	source,	whether	convergent	or	divergent	with	people’s	previously	held	beliefs,	may	influence	its	selection	(see	also	Neuberger	&	Silk,	2016);	however,	they	do	not	address	other	factors	such	as	format.		Barbour	and	colleagues	(2012)	in	their	survey	of	students	and	community	members,	found	several	strategies	for	information	avoidance	in	interpersonal	communications,	usually	taking	place	with	friends,	including	purposefully	not	paying	attention	and	changing	the	topic	of	conversation.		However,	these	strategies	were	not	found	to	be	present	in	communications	with	physicians,	with	many	people	choosing	to	simply	avoid	going	to	the	doctor.		Barbour	and	colleagues	(2012)	propose	that	friends	might	be	sought	out	over	physicians,	as	there	is	a	greater	possibility	that	friends’	perspectives	may	be	convergent	with	the	patient’s	own.		Physicians,	whose	perspective	is	more	likely	to	be	divergent,	were	more	often	avoided	(see	also	Lambert,	Loiselle	&	Macdonald,	2009;	Veinot,	Kim	&	Meadowbrooke,	2011).		Shepperd	and	colleagues	(Shepperd,	Emanuel,	Howell	&	Logan,	2015)	add	that	personal	circumstances	may	also	influence	this	behaviour;	these	researchers	found	that	people	who	possessed	coping	resources	were	less	likely	to	avoid	physicians,	even	in	situations	where	a	divergent	perspective	might	be	expected.																																												 																					1	Please	note	that	here,	despite	some	discussion	of	a	distinction	between	information	‘sources’	and	information	‘channels’	(see	Johnson,	1997;	Case	&	Johnson,	2012),	the	term	‘source’	will	be	used	here	to	denote	both	in	accordance	with	other	research	that	does	not	distinguish	between	the	two	(see	for		 20	The	presence	or	absence	of	personal	narratives	may	also	affect	health	information	seeking;	however,	the	extent	of	influence	may	vary	(Yli-Uotila,	Rantanen	&	Suominen,	2013;	Beck	et	al.,	2014;	Crutzen	et	al.,	2013).		Yli-Uotila	and	colleagues	(2013)	used	an	online	questionnaire	with	open-ended	questions	to	examine	the	information	seeking	of	74	Finnish	cancer	patients,	finding	that	these	patients	looked	to	the	Internet	for	the	social	support	unavailable	from	friends	and	family	and	sought	out	people	with	narratives	similar	to	the	patients’	own.		Similarly,	other	studies	claim	that	personal	narratives	are	the	key	element	in	source	selection,	although	the	attention	paid	each	source	is	limited.		In	a	content	analysis	of	celebrity	health	narratives,	Beck	and	colleagues	(2014)	conclude	that	such	narratives	shape	health	policy	by	encouraging	conversations	about	various	health	conditions.		However,	the	effect	of	these	narratives	is	often	short-lived,	waxing	and	waning	as	it	does	with	fame	and	media	attention.		Crutzen	and	colleagues	(2013),	in	a	multi-methods	health	communication	study,	examined	the	effects	of	the	social	presence,	i.e.,	human	images	and	personal	testimonials,	on	Internet	interventions	about	Hepatitis	A,	B,	and	C,	measuring	both	frequency	of	access	and	reading	time.		They	found	that	while	reading	time	between	those	Internet	sites	with	social	presence	and	those	without	did	not	differ,	participants	accessed	the	sites	with	social	presence	more	frequently.				 	Researchers	have	also	found	that	genre	is	a	key	element	in	information	seeking	in	general,	with	specific	genre-related	aspects	of	health	information	material	being	more	or	less	consulted	in	differing	circumstances.		Freund	(2008,	2013)	found	that	users	consider	genre,	defined	as	“typified	communicative	actions	characterized	by	similar	substance	and	form	and	taken	in	response	to	recurrent	situations”	(Yates	&	Orlikowski,	1992,	p.	299),	when	selecting	information	in	response	to	an	information	need	or	task.		Freund	(2013)	further	demonstrated	that	some	genres,	such	as	web	or	homepages	and	news	articles,	are	considered	more	“useful”	(p.	1116)	than	others.		This	preference	may	also	be	felt	in	health	information	seeking;	as	other	researchers	point	out	that	compact	and	easy-to-digest	formats	such	as	those	present	on	health	websites	and	news	articles	are	preferred	by	health	information	seekers	(Weng,	Weng,	Kuo,	Yang	&	Lo,	2013;	Lialiou	&	Mantas,	2015;	Lazar	&	Briggs,	2015).		Similarly,	researchers	posit	that	people	have	inclinations	regarding	the	use	or	non-use	material	they	view	as	containing	medical	jargon,	usually	defined	in	accordance	with	plain	language	guidelines	as	“specialized	terms	used	by	a	group	or	profession”	(Wright,	n.d.)	(Baker,	1996;	York,	Brannon	&	Miller,	2012;	Williams-Piehota,	Latimer,	Katulak,	Cox,		 21	Silvera,	Mowad	&	Salovey,	2009).		Health-related	disabilities	such	as	vision	impairment	may	also	influence	choice	of	genre;	for	example,	some	people	with	vision	impairments	may	prefer	larger	fonts	(Lazar	&	Briggs,	2015;	Blechner,	2015).			 This	review	has	considered	three	possible	explanations	for	information	avoidance.		Personality	traits	may	cause	some	people	to	avoid	information,	as,	for	example,	Miller’s	(1980,	1987,	1995)	reactions	to	stress.		People’s	affective	state	may	also	result	in	information	avoidance,	with	negative	affect	often	documented	as	a	hindering	influence	on	people’s	information	seeking.		Information	source	characteristics,	for	example	divergence	from	people’s	previously	held	beliefs	and	likings	for	certain	genres,	can	also	lead	to	information	avoidance.			 		 		 22	2.4	 Related	Research	in	Information	Behaviour		Information	avoidance	has	been	relatively	infrequently	studied	in	the	information	behaviour	field,	which	tends	to	focus	on	information	seeking.		Commonly	referenced	models,	for	example,	do	not	mention	information	avoidance.		One	reason	for	this	focus	may	be	the	emphasis	placed	by	information	studies	on	the	positive	aspects	of	information.		Information	behaviour,	a	term	introduced	in	1994	by	Wilson	but	based	on	early	communication	research	(see	Wilson,	2010),	is	defined	as	the	identification	of	“aspects	of	information-related	behaviour	that…appear	to	be	identifiable,	observable,	and,	hence,	researchable”	(Wilson,	1994,	p.	16).		A	later,	more	complete	definition	sees	information	behaviour	as	the	study	of	the	“totality	of	human	behaviour	in	relation	to	sources	and	channels	of	information,	including	both	active	and	passive	information	seeking	and	information	use”	(Wilson,	1999,	p.	249;	Fisher,	Erdelez	&	McKechnie,	2005).		Information	seeking,	a	subset	of	information	behaviour,	is	defined	as	the	“purposive	seeking	for	information	as	a	consequence	of	a	need	to	satisfy	some	goal”	(Wilson,	2000,	p.	49)	and	often	functions	as	the	subject	of	information	behaviour	research	(Bawden	&	Robinson,	2009,	2011,	2015;	Case	&	Johnson,	2012).2		Bawden	and	Robinson	(2009,	2011,	2015)	point	to	a	need	for	a	deeper	understanding	of	information	behaviour;	similarly,	Case	and	Johnson	(2012)	specifically	identify	information	avoidance	as	an	area	often	ignored	by	researchers	who	concentrate	on	information	seeking	behaviour.		This	stress	on	information	seeking	may	be	the	reason	for	little	discussion	of	the	mechanisms	of	information	avoidance;	in	Monitoring	and	Blunting,	for	example,	information	avoidance	is	seen	as	a	simple	negation	of	information	searching,	in	this	case	asking	questions	of	healthcare	professionals.			2.4.1	 Information	Literacy		Information	access	tends	to	be	seen	as	positive,	with	the	information	garnered	viewed	as	beneficial	(Bawden	&	Robinson,	2009;	Case,	Andrews,	Johnson	&	Allard,	2005;	Hertwig	&	Engel,	2016);	thus	information	skills	such	as	search	strategies	and	database	training	are	assumed	to	be	advantageous	(Eisenberg,	Low	&	Spitzer,	2008).		Studies	in	the	field	of	information	literacy	are	based	on	the	assumption	that	people	who	do	not	find	and																																									 																					2		One	exception	here	is	the	work	of	McKenzie	(2001,	2003,	2004,	2010),	who	refers	to	information	practices	rather	than	information	behaviour.		Information	practices	encompasses	both	Wilson’s	(2000)	definition	as	well	as	instances	in	which	information	comes	or	is	given	through	the	initiatives	of	other	agents.						 23	use	relevant	and	available	information	are	somehow	lacking	or	deficient	(Gross	&	Latham,	2011,	2013,	2007,	2009;	see	Bawden	&	Robinson,	2009	for	an	opposing	view).		This	assumption	runs	counter	to	the	notion	that	some	people	purposefully	avoid	information.		Information	literacy,	a	term	introduced	by	Zurkowski	(1974),	is	defined	as	a	“set	of	integrated	abilities	encompassing	the	reflective	discovery	of	information,	the	understanding	of	how	information	is	produced	and	valued,	and	the	use	of	information	in	creating	new	knowledge	and	participating	ethically	in	communities	of	learning”	(Association	of	Research	&	College	Libraries,	2016,	2000).		These	information	literacy	skills	are	highly	valued,	linked	as	they	are	to	the	new	information	economy,	and	subsequently	to	economic	success	(Eisenberg,	Lowe	&	Spitzer,	2008;	Nazari	&	Webber,	2012).		This	definition	of	information	literacy	has	been	questioned	in	other	work	(Lloyd,	2005,	2006,	2011,	2012,	2014;	Lloyd	&	Somerville,	2006;	Bawden	&	Robinson,	2009;	Julien	&	Williamson,	2010),	and	recent	changes	to	the	Framework	for	Information	Literacy	for	Higher	Education	(Association	of	Research	Libraries,	2016)	refers	to	foundational	ideas	or	“threshold	concepts”	(Townsend,	Hofer,	Hanick	&	Brunetti,	2015,	p.	23)	such	as	a	comprehension	of	the	value	of	information,	rather	than	skills	such	as	how	to	operate	an	informational	database.		This	new	framework	serves	as	a	way	to	shift	the	discipline’s	attention	away	from	a	checklist	and	towards	underlying	concepts	that	people	need	to	understand	in	order	to	be	information	literate.		However,	one	criticism	raised	is	the	difficulty	this	new	framework	presents	to	teachers	of	information	literacy,	who	may	be	unable	to	translate	these	ideas	into	workable	lessons	(Hosier,	2015).			2.4.2	 Information	Overload		One	exception	to	the	general	perception	of	information	as	positive	within	information	behaviour	is	the	attention	paid	by	some	researchers	to	negative	aspects	of	information.		Researchers	have	noted	the	existence	of	a	broader	range	of	information	behaviours	outside	of	information	seeking.		One	example	is	information	encountering,	in	which	people	“bump	into”	(Erdelez,	1999,	p.	25)	information	rather	than	actively	seeking	it	(see	also	Erdelez,	2004).		However,	these	behaviours	still	indicate	that	reception	or	seeking	of	information	has	positive	results.		Bawden	and	Robinson	(2009),	on	the	other	hand,	identify	difficulties	with	information	that	have	to	do	with	the	amount	of	information	searching	necessary	in	the	information	age,	what	they	call	“information	pathologies”	(p.		 24	180):		information	overload,	information	anxiety,	infobesity.		The	first	of	these,	information	overload,	is	a	term	popularized	by	Toffler	(1970)	who	speculated	that	vast	amounts	of	information	have	the	potential	for	instilling	negative	affect,	what	he	termed	shock,	in	information	seekers	(see	also	Johnson,	2014).		In	Toffler’s	(1970)	view,	limits	on	the	human	ability	to	deal	with	multiple	messages	can	cause	people	to	be	overwhelmed	by	too	much	information	(see	also	Miller,	1956;	Bawden	&	Robinson,	2009;	Johnson,	2014).		These	feelings	of	overload	can	be	exaggerated	in	times	of	crisis;	research	on	stress	states	that	cognitive	activity	in	stressful	times	taxes	cognitive	resources,	leaving	little	for	information	processing	(Johnson,	2014).				The	association	of	information	with	the	production	of	negative	affect	is	present	in	some	studies	of	information	behaviour,	particularly	with	regards	to	health	information	(Lu,	Dzwo,	Hou	&	Andrews,	2011;	Melnyk	&	Shepperd,	2012).		Many	studies	focus	on	the	importance	of	access	to	health	information	(Howell	&	Shepperd,	2013;	see	Dwyer,	Shepperd	&	Stock,	2015	for	one	example).		However,	other	researchers	have	found	that	both	information	searching	and	information	acquisition	can	lead	to	the	production	of	anxiety	and	fear	(Sweeny	&	Miller,	2012;	Toffler,	1970;	Johnson,	2014).				The	majority	of	work	in	information	behaviour	has	thus	focused	on	information	seeking,	with	a	strong	positive	value	assigned	both	to	skills	that	enable	people	to	seek	information	and	to	the	information	itself.		Such	an	emphasis	may	give	rise	a	more	simplistic	view	of	information	avoidance,	as	simply	the	opposite	of	information	seeking;	however,	other	behaviours	have	been	noted	with	regards	to	people’s	interactions	with	information.		A	minority	of	researchers,	though,	have	noted	that	some	information	access	is	associated	with	negative	affect,	particularly	in	the	area	of	health.				2.5	 Research	in	Health	Fields		 Some	research	conducted	in	fields	relating	to	health	has	to	do	with	information	avoidance.		Researcher	in	the	field	of	health	communication	perform	studies	that	examine	how	people	respond	to	heath	messages,	while	consumer	health	studies	consider	the	changing	role	of	patients	and	caregivers	in	a	system	which	increasingly	regards	these		 25	people	as	consumers.		This	last	field	has	received	some	criticism	regarding	the	attitudes	held	by	health	consumer	advocates	concerning	information	seeking,	also	detailed	here.			2.5.1	 Health	Communication		The	field	of	health	communication,	which	measures	the	effects	of	health	interventions	and	communications	from	health	providers	and	organisations	to	patients	and	caregivers,	places	a	strong	emphasis	on	the	positive	nature	of	information	(Nabi	&	Thomas,	2013;	York,	Brannon	&	Miller,	2012;	Williams-Piehota	et	al,	2009).		Much	health	communication	research	has	to	do	with	passive	attention,	which	is	contrasted	with	information	seeking,	the	“purposive	seeking	for	information	as	a	consequence	of	a	need	to	satisfy	some	goal”	(Wilson,	1999,	p.	49;	Howell	&	Shepperd,	2013).		Passive	attention	can	include	such	behaviours	as	watching	a	television	commercial,	viewing	website	pop-up	advertisements,	or	listening	to	someone	speak	(Wilson,	1999;	Lambert	&	Loiselle,	2007).		Thus	health	communication	deals	not	with	people’s	active	information	seeking,	but	with	their	reception	and	use	of	information	provided	by	the	health	care	system.		Here	such	reception	and	use	is	generally	associated	with	positive	benefits;	however,	health	communication	does	emphasize	that	information	must	be	presented	in	certain	ways	in	order	to	increase	these	benefits.		In	Nabi	and	Thomas	(2013),	for	example,	a	health	communication	experimental	study	tested	the	effects	of	television	advertisements	about	healthy	eating	on	snack	choices;	however,	only	advertisements	that	were	aired	during	reality	television	programs	about	weight	loss	led	to	better	snack	choices	among	participants.		Similarly,	York,	Brannon	and	Miller	(2012)	examined	how	website	pop-ups	can	alter	attitudes	about	binge	drinking	among	undergraduates,	finding	that	some	pop-ups	on	websites	for	advertising	commodities	other	than	alcohol	led	to	less	alcohol	consumption,	although	other	pop-ups	located	on	sites	advertising	alcohol	did	not.		One	aspect	of	health	communication	is	the	self-management	of	chronic	diseases,	in	which	patients	may	be	expected	to	adhere	to	complex	management	regimens	requiring	much	attention	to	information	(Barbarin,	Klasnja	&	Veinot,	2016).		In	a	study	of	38	families,	Barbarin,	Klasnja	and	Veinot	(2016)	concluded	that	those	families	who	kept	informal	records	of	their	personal	health	were	able	to	meet	their	information	needs,	including	the	temporal	need	to	reflect	on	the	illness	experience.							 26	Some	health	communication	research	is	problematic	in	that	it	tends	to	conflate	information	reception	with	information	use,	with	such	“use”	variously	defined	(see	Williams-Piehota,	Latimer,	Katulak,	Cox,	Silvera,	Mowad,	&	Salovey,	2009;	York,	Brannon	&	Miller,	2012	for	examples).		Savolainen	(2009)	proposes	two	explanations	for	information	use:		knowledge	creation	and	decision-making	(Savolainen,	2009).		Health	communication	tends	to	lean	towards	the	second	form	of	use,	decision-making,	when	people	may	simply	be	using	the	information	garnered	to	fill	knowledge	gaps.		For	example,	Williams-Piehota	et	al.	(2009)	describe	information	tailoring,	in	which	messages	are	tailored	according	to	characteristics	of	respondents	such	as	their	gender	or	their	willingness	to	receive	information	(see	also	Johnson,	2014).		In	the	view	of	Williams-Piehota	and	colleagues	(2009),	this	tailored	information	will	result	in	changed	behaviour,	as	the	information	will	be	more	likely	to	be	greeted	with	increased	scrutiny.		However,	this	perception	is	not	grounded	in	research	on	how	people	change	their	health	behaviours,	as	seen	in	the	Transtheoretical	Model	of	Health	Behaviour	Change	(Prochaska	&	DiClemente,	1983;	Prochaska,	DiClimente	&	Norcross,	1992).		This	model	lists	five	stages	through	which	people	progress	when	changing	health	behaviour,	precontemplation,	contemplation,	preparation,	action,	and	maintenance.		The	model	posits	that	people	proceed	linearly	through	these	stages,	but	they	can	stop	frequently	along	the	way,	either	temporarily	or	permanently.		These	stages	demonstrate	that	behavioural	change	is	much	more	complex	than	merely	receiving	and	acting	upon	information.					 Thus	health	communication	research	tends	to	emphasize	a	positive	view	of	information,	with	the	receipt	of	relevant	information	assumed	to	lead	to	better	health	behaviours.		One	problematic	aspect	of	health	communication	is	that	a	common	definition	of	“use”	of	information	is	not	currently	received.		However,	the	field	does	stress	that	information	must	be	presented	in	such	a	way	that	people	accept	it.				2.5.2	 Consumer	Health		Despite	evidence	of	information	avoidance	in	health,	many	researchers	have	unaccountably	either	ignored	people’s	avoidance	of	information	or	portrayed	people	who	avoid	information	as	in	some	way	lacking.		Information	access	is	often	seen	as	beneficial,	with	information	seeking	the	dominant—and	correct—approach.		This	view	predominates		 27	in	the	consumer	health	movement	in	which	information	access	is	often	described	as	“empowering”	(Wyatt,	Harris	&	Wathen,	2010,	p.	2).		This	consumer	health	movement	views	health	information	as	a	purchasable	consumer	good	much	like	cars	or	clothing,	to	which	access	is	highly	desirable	(Wyatt,	Harris	&	Wathen,	2010;	see	also	Johnson,	2013).		Access	to	information	can	allow	patients	to	cross	previously	established	boundaries	between	doctors	and	patients,	permitting	patients	to	access	medical	knowledge	(Wilson,	2010;	Aronson,	2013;	Campbell,	Scott,	Skovdal,	Madanhire,	Nyamukapa	&	Gregson,	2015).		Wilcox	(2010)	describes	the	concept	of	what	she	calls	an	“expert	patient”	(p.	41).		Although	she	does	indicate	that	this	expertise	can	mean	the	personal	experience	of	being	a	patient	as	well	as	healthcare	professional	expertise,	Wilcox	(2010)	points	to	the	use	of	the	term	expert	patient	as	a	signifier	that	the	doctor-patient	hierarchy	is,	in	consumer	health,	equalized.				In	this	movement,	new	opportunities	to	search	are	viewed	as	advantageous	(Wyatt,	Harris	&	Wathen,	2010;	Johnson,	2014).		For	some	advocates	of	the	consumer	health	movement,	information	access	can	mean	an	ability	to	engage	with	the	health	care	system,	becoming	an	active	participant	in	this	system	and	in	one’s	own	health	(Wilcox,	2010).		Being	active	is	generally	viewed	as	positive;	Henwood,	Harris	and	Spoel	(2011)	point	to	the	use	of	the	word	“choice,”	stating	that	this	word	is	often	used	in	discourses	of	consumer	health.		These	researchers	comment	that	“choice”	is	often	not	representative	of	how	health	care	is	practiced,	as	budget	considerations	can	restrict	the	number	of	available	treatment	alternatives	in	both	public	and	private	systems.		Nevertheless,	these	researchers	posit	that	the	“logic	of	choice”	(Henwood,	Harris	&	Spoel,	2011,	p.	2027),	with	its	implication	of	personal	freedom	on	the	part	of	the	patient,	dominates	discourses	of	consumer	health	(see	also	Adams,	2010;	MacGregor	&	Wathen,	2014).				This	positive	view	may	be	one	reason	why	patients	with	chronic	conditions	are	being	encouraged	to	practice	self-management,	a	series	of	skills,	attitudes	and	behaviours	that	allow	patients	to	become	more	knowledgeable	about	their	health	and	thus	able	to	“live	well”	(Adams,	Greiner	&	Corrigan,	2004,	p.	57)	with	any	conditions	they	might	have	(see	also	British	Columbia	Ministry	of	Health,	2011).		Researchers,	however,	have	pointed	out	that	the	consumer	health	notion	of	health	information	access	as	empowering	may	not	be	completely	valid	(Wyatt,	Harris	&	Wathen,	2010;	MacGregor	&	Wathen,	2014;	Bakardjieva,	2010;	Veinot,	2010).		Indeed,	“there	is	little	evidence	to	demonstrate	that	improved	access		 28	to	health	information...actually	‘empowers’	patients”	(Wyatt,	Harris	&	Wathen,	2010,	p.	2).		Many	studies,	in	fact,	suggest	the	reverse,	that	information	seeking	disempowers	patients,	becoming	a	form	of	“healthwork”	(Mykhalovskiy	&	McCoy,	2002,	p.	17)	a	term	denoting	the	active	and	purposeful	work	that	people	do	to	manage	their	health.		Researchers	have	posited	that	some	people	can	find	healthwork	onerous	and	time-consuming	(MacGregor	&	Wathen,	2014),	which	can	lead	to	a	preference	for	a	more	traditional	model	of	healthcare	whereby	healthcare	professionals	do	the	healthwork	and	patients	remain	passive	(Lawn,	McMillan	&	Pulverenti,	2011).					Another	difficulty	with	consumer	health	is	the	contrast	presented	by	this	new	role	of	the	patient	as	an	informed	questioning	person	to	the	role	previously	established	by	traditional	health	care	(Aronson,	2013;	Buist,	2011;	Campbell,	Scott,	Skovdal,	Madanhire,	Nyamukapa	&	Gregson,	2015).		Healthcare	professionals	and	researchers	have	noted	the	desire	in	patients	to	be	“good	patients”	(Aronson,	2013,	p.	796);	however,	“good	patient”	is	a	contested	term,	with	studies	showing	that	healthcare	professionals	and	patients	can	view	“good”	in	differing	and	often	contrasting	ways.		Aronson	(2013)	concluded	that	patients	and	caregivers	may	feel	a	strong	impulse	to	be	passive	and	unquestioning	of	medical	authority,	while	Buist	(2011)	noted	that	patients	should	be	exhorted	to	be	active	participants	in	their	health.		Campbell	and	colleagues	(Campbell,	Scott,	Skovdal,	Madanhire,	Nyamukapa	&	Gregson,	2015),	in	their	study	of	patient-and-nurse	interactions	in	a	Zimbabwean	free	clinic	discuss	various	views	of	how	to	be	a	“good	patient”	(p.	404)	and	concluded	that	patients	could	use	different	behaviours	from	presenting	healthcare	professionals	with	easy-to-solve	problems	to	adhering	completely	to	good	health	behaviours	in	order	to	establish	themselves	as	good	patients.			Much	health	research	assumes	that	people	wish	to	know	about	their	health.		In	particular,	the	viewpoint	of	consumer	health	portrayed	health	patients	who	are	empowered	by	such	information	and	more	in	control	of	their	own	health.		However,	complicated	attitudes	surround	patients	and	their	willingness	to	assume	healthwork;	while	consumer	health	assumes	that	all	patients	want	to	know	about	their	health,	the	truth	is	far	more	complex.		These	assumptions	on	the	part	of	consumer	health,	though,	are	one	reason	why	there	is	little	research	on	information	avoidance	scratching	below	the	surface	of	this	phenomenon.			 29	2.6	 Conclusion		Researchers	have	long	acknowledged	that	people	avoid	information,	particularly	in	cases	where	they	are	experiencing	negative	affect	(Sweeny,	Melnyk,	Miller	&	Shepperd,	2010;	Miller,	1980,	1987,	1995;	Howell	&	Shepperd,	2013,	2016,	2017).		However,	information	avoidance	behaviour	has	been	infrequently	studied,	with	limited	research	detailing	how	and	why	people	avoid	information.		Two	concepts	related	to	information	avoidance	are	Miller’s	(1980,	1987,	1995)	Monitoring	and	Blunting	theory	and	Selective	Exposure	(Hyman	&	Sheatsley,	1947;	Festinger,	1957,	1961),	both	of	which	suggest	some	patterns	of	avoidance	behaviour	as	well	as	some	explanations	for	information	avoidance.		Patterns	of	behaviour	suggested	are	not	asking	questions	of	health	professionals	and	choosing	to	consult	one	information	source	over	another,	while	three	possible	explanations	for	this	behaviour	are	personality,	affect,	and	information	source	characteristics.		Part	of	the	reason	for	this	lack	of	detail	may	be	the	value	placed	on	information	seeking	and	on	information	in	general.		Although	some	information	behaviour	researchers	look	at	the	negative	aspects	of	information,	most	do	not,	with	the	skills	needed	to	obtain	information	being	viewed	as	highly	valued.		Even	in	health,	in	which	much	information	avoidance	has	been	documented,	many	researchers	stress	the	positive	aspects	of	the	information,	in	particular	in	consumer	health.		Thus	issues	still	remain,	particularly	around	the	patterns	of	behaviour	that	form	information	avoidance	and	the	explanations	for	this	behaviour.		These	issues	provide	the	basis	for	the	research	undertaken	and	described	in	the	following	chapters,	which	answer	the	following	research	questions:		1.		What	factors	contribute	to	information	avoidance?	More	specifically,	to	what	extent	do	personality	traits,	situational	affect,	and	the	nature	of	available	information	sources	influence	information	avoidance?		2.		What	are	the	mechanisms	of	information	avoidance?				 		 		 		 30	3	 Methods	3.1	 Introduction		Rather	like	Pontius	Pilate,	the	Roman	general	who	announced	to	Jesus	that	there	were	multiple	forms	of	truth,	neopragmatists	such	as	myself	also	believe	that	there	are	truths:		that	much	in	the	world	possesses	a	higher,	unknowable	truth	beyond	the	level	of	linguistic	explanation,	an	Everest-type	goal	to	which	one	should	aspire	(Patton,	2002;	Feilzer,	2010;	Johnson	&	Onwuegbuzie,	2004;	Rorty,	1999).		As	these	researchers-cum-philosophers	suggest,	attempting	to	embody	this	Everest-style	truth	in	research	is	extremely	difficult;	they	advocate	instead	more	“commonsense”	(Johnson	&	Onwuegbuzie,	2004,	p.	20)	approaches	to	find	solutions	to	practical	problems.		Thus	in	lieu	of	finding	this	ultimate,	all-encompassing	truth	about	information	avoidance,	my	aim	in	conducting	this	research	is	to	reach	a	“real	world”	(Creswell	&	Plano	Clark,	2007,	p.	28)	understanding	of	how	and	why	people	avoid	information.				 	Therefore,	I	took	a	mixed	methods	approach	in	examining	people’s	reasons	for	and	process	of	avoiding	health	information	when	faced	with	health	difficulties.		In	choosing	mixed	methods,	I	bore	in	mind	Fidel’s	(2008)	and	Greene’s	(2005)	arguments	that	care	must	be	taken	to	ensure	that	the	methods	are	integrated	together	rather	than	appearing	as	a	precise	delineation	of	research	question	equalling	research	method.		Thus	the	methods	were	an	online	survey	containing	qualitative	and	quantitative	elements	and	using	an	online	labour	market	for	recruitment	and	an	experimental	user	study	which	included	quantitative	scales,	a	timed	session	of	information	seeking	and	qualitative	interviews.		Both	studies	were	used	to	answer	both	research	questions.				 	Data	collection	began	with	the	Affect	and	Avoidance	study	consisting	of	an	online	survey,	conducted	in	January	of	2015.		198	participants	were	surveyed	using	a	questionnaire	exploring	their	general	information	seeking	preferences	as	well	as	their	emotional	responses	to	health	scenarios.		The	survey	was	conducted	via	an	online	labour	market,	Amazon’s	Mechanical	Turk	(2017)	(MTurk).		A	user	study,	the	Interview	and	Interaction	study,	was	then	conducted	in	the	summer	of	2015	in	a	large	Canadian	West	Coast	city,	with	35	members	of	the	general	public.		This	second	study	collected	demographic		 31	and	health-related	information,	and	included	both	a	timed	health	information	interaction	session	and	a	qualitative	interview.				 	The	following	section	will	detail	the	specifics	of	the	methods	used	to	conduct	this	research,	beginning	with	the	research	design	and	followed	by	recruitment	and	participation,	measures,	procedures	and	data	analysis	for	each	study.			3.2	 Research	design		Hailed	as	an	“intellectual	and	practical	synthesis”	(Creswell	&	Plano	Clark,	2007,	p.	129)	of	qualitative	and	quantitative	methods,	mixed	methods	are	selected	when	a	problem	benefits	from	being	viewed	comprehensively	from	multiple	angles.		By	“methods”	I	mean	“methodologies,”	which	includes	issues	and	strategies	involving	data	collection,	research,	and	philosophical	stances	(see	Greene,	2006),	which	Johnson,	Onwuegbuzie	and	Turner	(2007)	state	is	the	usual	interpretation	of	the	word	“methods”	in	mixed	methods	research.			Of	the	research	that	exists	on	information	avoidance,	much	examines	separate	aspects	of	avoidance,	rather	than	the	topic	as	a	whole	(Sweeny,	Melnyk,	Miller	&	Shepperd,	2010;	Hertwig	&	Engel,	2016).		Researchers	most	often	examine	only	one	situation	or	condition;	thus	Miller	(1980)	studied	gynaecological	patients	waiting	for	surgery,	while	Sweeny	and	Miller	(2012)	presented	university	students	with	potential	romantic	entanglements.		By	contrast,	these	studies	asked	people	about	their	health	information	as	it	pertained	to	numerous	conditions,	thus	examining	information	avoidance	as	a	broader	phenomenon	and	at	a	higher	level	of	granularity.					 This	research	project	is	comprised	of	two	studies,	an	online	survey	and	a	mixed	methods	user	study	and	interview.		A	complementary	mixed	methods	approach,	in	which	different	and	overlapping	facets	of	a	topic	are	studied	(Greene,	Caracelli		&	Graham,	1989),	was	chosen	to	look	at	the	influencing	factors	of	why	and	how	people	avoid	information	in	the	area	of	health.		A	sequential	explanatory	strategy	was	used,	with	a	primarily	quantitative	study	(QUAN-qual,	in	the	words	of	Creswell	and	Plano-Clark,	2007)	being	first,	followed	by	a	primarily	qualitative	(QUAL-quan)	study.		Concurrent	methods	were	viewed	as	impractical	as	the	implementation	and	results	of	the	first	study	were	employed	to	aid	in	the	design	of	the	second	study.		For	example,	responses	given	to	an	optional	comment	in	the		 32	first	study	were	employed	to	aid	in	the	creation	of	an	interview	guide	in	the	second	study.		This	design	was	selected	with	the	intent	of	using	the	primarily	quantitative	study	as	an	informative	base	from	which	to	explore	some	aspects	of	this	issue	in	finer	detail.		The	design	also	proved	especially	beneficial	in	this	case	as	unexpected	results	arose	from	the	first	study;	i.e.,	a	very	small	amount	of	participants	admitted	to	avoiding	information,	leading	me	to	consider	aspects	such	as	the	societal	value	of	health	information	seeking	that	might	have	contributed	to	this	finding	(Creswell	&	Plano-Clark,	2007).								 In	research	such	as	this	that	involves	discussion	and	exposure	to	information	regarding	health	concerns	that	may	have	a	strong	emotional	and	personal	impact	on	participants,	ethics	are	of	foremost	importance.		Both	studies	used	scenarios	that	described	health	concerns	in	some	detail,	and	in	the	second	study,	participants	were	also	exposed	to	potentially	distressing	health	information	material	and	were	asked	questions	regarding	their	own	personal	health	concerns.		Ethics	approval	for	these	studies	was	sought	and	granted	through	the	University	of	British	Columbia	Behavioural	Human	Ethics	Board.		Care	was	also	taken	that	participants	should	be	comfortable;	i.e.,	all	questions,	both	written	in	the	online	survey	and	verbal,	were	optional	(see	Appendices	A	and	B	for	questionnaires),	and	a	private	room	was	used	for	in-person	sessions.		Additionally,	procedures	such	as	interviews	about	general	health	information	seeking	and	instruments	such	as	descriptions	of	health	concerns	were	based	on	those	from	previous	studies	in	which	no	ill	effects	were	reported	in	participants	(Miller,	1980;	Melnyk	&	Shepperd,	2012;	McKenzie,	2001;	Lambert,	Loiselle	&	Macdonald,	2009).		(See	Appendices	C	and	D	for	recruitment	and	consent	forms.)				3.3	 Research	Questions		The	studies	were	designed	to	answer	the	following	research	questions:			1.		What	factors	contribute	to	information	avoidance?	More	specifically,	to	what	extent	do	personality	traits,	situational	affect,	and	the	nature	of	available	information	sources	influence	information	avoidance?	2.		What	are	the	mechanisms	of	information	avoidance?				The	individual	studies	are	detailed	in	the	following	sections.			Ethics	approval	was	applied	for	and	granted	for	both	studies	through	the	University	of	British	Columbia	Behavioural	Human	Ethics	Board.			 		 33	3.4	 Study	1:		Affect	and	Avoidance	Study		The	Affect	and	Avoidance	Study,	a	scenario-based	assessment	of	the	role	of	affect	and	other	factors	on	health	information	avoidance,	was	conducted	in	January	and	February	of	2015.		It	consisted	of	an	online	survey	designed	to	measure	respondents’	personality	traits	and	emotional	responses	in	relation	to	self-reported	information	seeking	and	avoidance	questions.		The	study	also	functioned	to	test	the	effect	of	ten	hypothetical	medical	scenarios	varied	by	disease	(comprising	five	diseases)	and	level	of	severity	(comprising	two	levels	of	severity)	on	user	behaviour	and	affect.		(Please	see	Appendix	A	for	the	questionnaire	used	in	this	study.)			3.4.1	 Procedure	and	Instruments		Data	were	collected	using	online	questionnaires	hosted	by	LimeSurvey	(Schmitz,	2015)	software.		Recruiting	was	carried	out	via	crowdsourcing	software,	Amazon’s	Mechanical	Turk	(2017)	(MTurk),	chosen	due	to	its	ability	to	reach	a	large	number	of	participants	quickly	and	the	fact	that	the	survey	was	short	and	well-suited	to	this	micro-task	crowdsourcing	platform	(see	Paolacci	&	Chandler,	2014;	Paolacci,	Chandler,	&	Ipeirotis,	2010;	Rand,	2011).		Participants	began	the	Affect	and	Avoidance	Study	by	logging	on	to	MTurk	(2017).		After	indicating	their	consent	to	participate,	they	followed	a	link	to	LimeSurvey	(Schmitz,	2015),	a	survey	instrument	with	content	stored	in	Canada3,	which	led	to	the	questionnaire.		Separate	questionnaires	were	created	for	each	of	the	ten	scenarios,	and	these	surveys	were	released	sequentially.		The	first	20	participants	responded	to	the	first	scenario,	then	next	20	to	the	next	scenario,	and	so	on	until	all	10	scenarios	were	complete.	Overall,	each	participant	responded	to	a	single	scenario	of	the	ten	scenarios	used.		Upon	completion,	participants	were	given	a	code,	which,	when	entered	into	MTurk	(2017),	signified	completion	of	the	study	and	made	them	eligible	for	compensation.		Participants’	MTurk	(2017)	IDs	were	checked	to	ensure	that	participants	completed	the	survey	only	once	each;	no	duplications	were	found.					 	The	online	questionnaire	(see	Appendix	A)	was	presented	as	a	series	of	web	pages.		All	questions	included	a	non-response	option.					 34	The	first	section	contained	demographic	questions	asking	participants	to	indicate	their	gender,	age,	and	education	level.				Next,	participants	were	asked	how	they	perceived	their	current	level	of	health	on	a	five-point	Likert	scale,	a	question	taken	from	the	RAND-36	Health	Status	(Hays	&	Morales,	2001),	as	health	perception	has	been	linked	to	information	avoidance	(Lu,	Andrews	&	Hou,	2009;	Shepperd,	Klein,	Waters	&	Weinstein,	2013).		Participants	were	also	asked	how	they	perceived	their	health	as	compared	with	one	year	ago,	measured	on	a	second	five-point	Likert	scale.		This	second	question	was	included	as	researchers	point	out	the	difficulty	of	measuring	self-perception	using	a	single	item	(Oh	&	Cho,	2015).		In	addition,	it	was	felt	that	a	question	involving	a	comparison	with	another	time	period	(here	“one	year	ago”)	would	allow	people	to	give	a	more	accurate	description	of	their	health.				Internet	usage	was	measured	using	a	six-point	Likert	scale,	using	a	scale	tested	in	a	previous	study	(Freund	&	Berzowska,	2010).		Participants	were	then	given	the	test	question	asking	them	to	define	disease,	which	was	used	to	assess	the	quality	of	responses	by	measuring	English	language	and	attention	levels.			 	Next,	participants’	Need	for	Cognition	was	measured	using	the	Need	for	Cognition	scale	(NCS).		Originally	developed	in	1982	by	Cacioppo	and	Petty,	the	NCS	scale	was	chosen	as	it	represents	one	personality-based	trait	that	might	influence	health	information	avoidance:		the	Need	for	Cognition,	long	held	to	be	a	trait	that	influences	people’s	overall	desire	to	look	for	information	(Wilson,	1997;	Cacioppo,	Petty,	Feinstein	&	Jarvis,	1996).		The	scale	consists	of	eighteen	statements,	of	which	sample	statements	include	“I	would	prefer	complex	to	simple	problems.”	“The	notion	of	thinking	abstractly	is	appealing	to	me.”	“I	usually	end	up	deliberating	about	issues	even	when	they	do	not	affect	me	personally.”		Participants	rate	the	statements	on	a	five	point	Likert	scale,	ranging	from	extremely	uncharacteristic	to	extremely	uncharacteristic.		Although	some	forms	of	this	scale	contain	a	nine-point	scale,	the	five-point	scale	was	chosen	as	research	shows	participants	have	difficulty	responding	to	scales	with	more	than	seven	options	(see	Peterson,	2000).		The	scale	is	reliable,	with	Cronbach’s	alpha	measurements	reported	as	being	between	0.82	and	0.88	(Salvador,	Arquero	&	Romero-Frias,	2015).				 35	Emotional	state	was	tested	using	the	twenty	point	Positive	and	Negative	Affect	Schedule	short	form	(see	Appendix	B;	PANAS),	developed	in	1988	by	Watson,	Clark	and	Tellegren.		PANAS	is	well	established	as	a	measure	of	emotional	response	and	has	been	much	used	in	research	on	information	seeking	(McCay-Peet,	Laimas	&	Navalpakkum,	2012;	Lopatovska,	2014).		Using	this	scale,	participants	stated	the	extent	to	which	they	felt	a	certain	emotion	as	measured	on	a	five	point	Likert	scale	ranging	from	1	(very	slightly	or	not	at	all)	to	5	(extremely).		Ten	emotions	are	ranked	as	positive	affect	(PA);	10	are	ranked	as	negative	affect	(NA).		In	this	scale,	high	PA	is	signalled	by	such	terms	as	“excited,”	“delighted,”	“active,”	and	“determined,”	while	a	score	of	low	PA	represents	the	opposite:		lethargy	and	depression.		High	NA	is	represented	by	another	broad	range	of	moods,	“nervous,”	for	example,	or	“afraid,”	“guilty,”	or	“hostile,”	while	low	NA	again	points	to	the	opposite	of	these	moods,	calm	and	relaxed	(see	Watson,	Clark,	&	Tellegren,	1988).		Although	PANAS	can	be	used	to	determine	current	and	past	emotional	states,	including	last	week,	last	month,	and	last	year,	the	wording	regarding	the	current	emotional	state	was	used,	i.e.	“This	question	will	ask	you	about	your	current	emotional	state.”		This	scale	is	reliable,	with	Chronbach’s	alpha	measurements	reported	as	ranging	from	.82	to	.86	for	the	positive	factors	and	.84	to	.87	for	the	negative	factors	(Serafini,	Malin-Mayor,	Nich,	Hunkele	&	Carroll,	2016;	Thompson,	2007).				At	this	point,	participants	were	shown	a	scenario,	one	of	ten.		As	noted	above,	scenario	assignment	was	based	on	the	order	of	registration	of	participants	with	only	one	scenario	per	participant.		In	these	scenarios,	participants	were	informed	that	they	had	just	been	diagnosed	with	a	specific	medical	condition.		Participants	were	also	asked	about	their	level	of	knowledge	and	perceptions	of	this	condition.		This	between-subjects	design,	with	each	participant	experiencing	only	one	scenario,	was	chosen	to	maintain	a	level	of	naturalism	(Polit,	2010);	i.e.,	diagnoses	usually	come	singly.							Participants	then	completed	the	PANAS	scale	again	to	measure	their	emotional	response	after	exposure	to	the	scenario.				Next,	participants	were	asked	how	likely	they	would	be	to	look	for	information	about	the	condition	described	in	the	scenario,	as	measured	on	a	six-point	Likert	scale,	and	finally,	were	asked	to	give	an	optional	comment	providing	more	details	about	their	choice.				 36	3.4.2	 Scenarios		With	significant	input	from	my	supervisory	committee,	I	created	ten	hypothetical	disease	scenarios	describing	various	health	conditions	and	asking	participants	to	imagine	that	they	had	just	been	informed	that	they	were	diagnosed	with	this	condition	(Table	3.2).	Hypothetical	scenarios	have	been	much	used	in	other	research	on	information	seeking	and	avoidance	(see	Miller,	1980;	Weinstein,	1982;	Dawson,	Savitsky	&	Dunning,	2006;	Melnyk	&	Shepperd,	2012;	Sweeny	&	Miller,	2012)	and	are	usually	cited	as	stimuli	for	either	information	seeking	or	avoidance.		Scenarios	created	for	this	study	were	based	on	those	used	in	previous	studies	(Dawson,	Savitsky	&	Dunning,	2006;	Melnyk	&	Shepperd,	2012;	Sweeny	&	Miller,	2012;	see	also	Miller,	1980;	van	Zuuren	&	Hanewald,	1993;	van	Zuuren	&	Muris,	1993).		I	emulated	the	style,	wording,	and	format	of	scenarios	found	in	these	studies,	substituting	new	conditions.		All	scenarios	started	with	a	sentence	stating,	“Your	doctor	tells	you	that	you	have…”	and	concluding	with	a	medical	condition.		This	sentence	was	followed	by	a	short	definition	and	some	side	effects	of	the	condition.		Finally,	two	or	three	possible	treatments	were	included.		Although	scenarios	used	in	previous	work	began	with	a	sentence	such	as	“Imagine	you	are	in	your	doctor’s	office,”	this	sentence	was	omitted	as	other	researchers	pointed	out	that	these	studies	unduly	emphasized	the	hypothetical	nature	of	the	scenario	and	resulted	in	participants	feeling	overly	removed	from	the	study	(Evans	et	al.,	2014;	Dawson,	Savitsky	&	Dunning,	2006;	see	also	Miller,	1980;	van	Zuuren	&	Hanewald,	1993;	van	Zuuren	&	Muris,	1993).				The	employment	of	scenarios	has	been	questioned,	as	researchers	point	out	that	these	are	artificial	stimuli	and	thus	responses	are	not	necessarily	reflective	of	people’s	real	behavior	(Lambert	&	Loiselle,	2007).		Researchers	have,	though,	pointed	out	the	many	benefits	of	the	use	of	these	scenarios.		Hypothetical	scenarios	may	allow	for	participants	to	feel	some	psychological	distance	and	thus	remove	observer	effects	such	as	“yea-saying.”		Such	scenarios	have	also	been	seen	as	ways	to	ethically	examine	people	in	problematic	situations	(Sweeny	&	Miller,	2012;	Evans	et	al.,	2014)	and	also	as	a	useful	way	to	demonstrate	how	people	react	to	similar	but	slightly	modified	situations	(Evans	et	al.,	2014;	van	Zuuren,	Groot,	Muris	&	Mulder,	1996;	Dawson,	Savitsky	&	Dunning,	2006;	Melnyk	&	Shepperd,	2012).		The	situations	in	this	study,	for	example,	all	began	with	the	same	phrase	but	included	different	conditions	and	different	side	effects,	a	tactic	similar	to	other	studies		 37	that	used	versions	of	the	same	scenario	to	measure	different	factors	that	might	influence	people’s	information	seeking	(Dawson,	Savitsky	&	Dunning,	2006).				The	Affect	and	Avoidance	Study	employed	a	range	of	conditions	from	potentially	fatal	to	non-life-threatening	and	from	permanent	to	temporary	(see	Table	3.1	for	a	list	of	conditions).		Although	it	is	difficult	to	determine	people’s	impressions	concerning	health	conditions	and	thus	problematic	to	label	any	condition	more	severe	than	another,	van	Zuuren	and	colleagues	(van	Zuuren,	Groot,	Muris	&	Mulder,	1996)	point	out	that	medical	stressors	center	around	two	factors:		the	potential	controllability	of	the	disease	and	the	potential	predictability	of	the	disease.		Thus	acoustic	neuromas,	lupus,	and	meningiomas	were	selected	as	the	courses	of	these	conditions	are	less	likely	to	be	predictable.	For	example,	these	conditions	are	fatal	in	some	cases	but	not	in	others.		Crohn’s	disease	and	Bell’s	palsy,	while	also	unpleasant,	are	much	less	likely	to	be	fatal,	given	that	any	condition	can	be	fatal	in	extreme	circumstances	such	as	advanced	age	or	unusual	complications.		Similarly,	Crohn’s	disease	can	more	easily	be	controlled	with	medication	and	Bell’s	palsy	with	time	(it	is	usually	a	temporary	condition),	while	meningiomas,	lupus,	and	acoustic	neuromas	are	less	easily	controllable.				These	conditions	were	chosen	in	reference	to	other	studies,	which	have	used	similar	distinctions	between	“severe”	and	“less	severe”	descriptions	of	diseases	(Dawson,	Savitsky	&	Dunning,	2006;	Melnyk	&	Shepperd,	2012;	Williams-Piehota,	Latimer,	Katulak,	Cox,	Silvera,	Mowad	&	Salovey,	2009;	Flight,	Wilson,	Zajac,	Hart	&	McGillivray,	2012).		Conditions	chosen	were	relatively	rare,	and	it	was	hoped	that	their	rarity	would	encourage	a	response	uninfluenced	by	experiences	participants	had	with	their	own	or	others’	health.		The	conditions	were	gender-	and	age-neutral	and	thus	able	to	strike	anyone	at	any	time.		Table	3-1	lists	the	conditions	used	with	definitions.				 		 38	Table	3-1		Conditions	used	in	Study	1	with	definitions	Condition	 Definition	Acoustic	neuroma	 A	benign	tumour	located	in	the	ear	canal	Bell’s	palsy	 Idiopathic	facial	paralysis	(usually	temporary)	Crohn’s	disease	 A	digestive	disorder	Lupus	 An	autoimmune	disorder	Meningioma	 A	malignant	or	benign	tumour	located	in	the	meninges	of	the	brain		Table	3-1	Conditions	with	descriptions		 Scenarios	were	also	varied	with	respect	to	the	tone	of	the	description.		For	each	disease,	two	levels	of	description	were	created:	strong	negative	and	weak	negative	(see	Table	3-2	for	the	full	set	of	scenarios).		These	changes	in	wording	were	modelled	on	other	studies	in	which	participants	were	exposed	to	conditions	described	alternately	as	treatable	and	untreatable,	and	severe	and	mild	(Dawson,	Savitsky	&	Dunning,	2006;	Melnyk	&	Shepperd,	2012;	Williams-Piehota	et	al.,	2009;	Flight	et	al.,	2012).		In	the	strong	negative	scenario,	side	effect	severity	was	emphasized	and	more	specific	details	were	provided	(e.g.	the	growth	of	the	tumour	is	described	as	1.5mm/year	in	the	strong	negative	scenario	and	as	‘the	tumour	grows	slowly’	in	the	weak	negative	scenario).		The	number	of	scenario	treatment	options	given	varied	depending	on	the	options	cited	in	the	medical	literature	I	used	to	construct	the	scenarios.		For	example,	the	treatment	for	lupus	was	cited	as	medication,	while	the	treatment	for	meningiomas	was	noted	as	observation,	surgery,	or	radiation.		This	use	of	varying	treatment	options	reduced	some	of	the	control	and	consistency	between	scenarios;	for	example,	decision-making	regarding	surgery	can	be	more	complex	than	decision-making	regarding	medication	(Evans	et	al.,	2014).		However,	this	disparity	in	treatment	options	was	intended	to	reflect	the	nature	of	the	underlying	condition.										 		 39		Table	3-2		Scenarios	used	in	study	1	by	condition	and	scenario	tone	Condition	and	Scenario	tone			Acoustic	neuroma:		strong	negative		Scenario			Your	doctor	tells	you	that	you	have	an	acoustic	neuroma,	a	noncancerous	tumour	located	in	your	ear	and	close	to	your	brain.		It	has	a	number	of	side	effects,	the	most	common	being	hearing	loss	in	the	tumour	ear;	others	include	facial	paralysis,	loss	of	brain	function,	and	even	death.		The	tumour	grows	at	a	rate	of	1.5mm/yr.		Treatment	options	are	observation,	surgical	removal	or	radiation.				Acoustic	neuroma:		weak	negative		 	Your	doctor	tells	you	that	you	have	an	acoustic	neuroma,	a	rare	noncancerous	tumour	located	on	the	hearing	nerve	connecting	your	ear	to	your	brain.		It	has	a	number	of	side	effects,	but	these	are	mild	in	most	cases,	the	most	common	being	loss	of	hearing	in	the	affected	ear.		The	tumour	grows	slowly	and	if	small,	can	be	managed	by	watchful	observation.		If	you	do	need	treatment,	radiation	and	surgery	are	options.						Bell’s	palsy:		strong	negative		 	Your	doctor	tells	you	that	you	have	Bell’s	palsy,	in	which	a	problem	with	the	nerves	in	your	skull	results	in	complete	or	partial	facial	paralysis.		This	condition	has	a	number	of	side	effects,	including	not	being	able	to	move	at	least	50%	of	your	face,	to	blink,	smile,	or	frown	properly	for	weeks.		Bell’s	palsy	can	result	in	permanent	facial	problems.		Treatments	include	steroids,	surgery,	and	physiotherapy.				Bell’s	palsy:		weak	negative		 	Your	doctor	tells	you	that	you	have	Bell’s	palsy,	in	which	a	problem	with	the	facial	nerve	results	in	difficulties	in	moving	parts	of	the	face.		Bell’s	palsy	has	a	number	of	side	effects,	including	problems	making	facial	expressions,	winking,	lifting	one	eyebrow,	or	smiling	broadly.		In	most	cases,	Bell’s	palsy	disappears	in	a	few	weeks.			If	treatment	is	needed,	steroids,	physiotherapy,	and	in	very	rare	cases,	surgery	can	all	help.				Crohn’s	disease:		strong	negative		 	Your	doctor	tells	you	that	you	have	Crohn’s	disease,	a	severe	form	of	inflammatory	bowel	disease,	which	requires	immediate	treatment.		This	disease,	if	untreated,	will	lead	to	a	number	of	side	effects,	including	the	breaking	of	your	intestine.		Surgery	is	required,	and	a	number	of	different	surgical	options	must	be	considered.				Crohn’s	disease:		weak	negative	effect	 	Your	doctor	tells	you	that	you	have	Crohn’s	disease,	a	form	of	inflammatory	bowel	disease	in	which	your	digestive	system	does	not	function	properly.		Crohn’s	has	a	number	of	side	effects,	which	can	include	weight	loss,	low	iron,	and	damage	to	your	intestine.		By	and	large,	people	who	have	this	disease	can	live	full	and	productive	lives.				 40	Scenarios	used	in	study	1	by	condition	and	scenario	tone	Condition	and	Scenario	tone		 Scenario			Meningioma:		strong	negative		 	Your	doctor	tells	you	that	you	have	a	meningioma,	a	type	of	brain	tumour	that	in	your	case	requires	immediate	treatment.		If	untreated,	meningiomas	can	lead	to	serious	side	effects,	including	problems	with	brain	function.		Treatment	options	are	surgery	and	radiation.				Meningioma:		weak	negative		 	Your	doctor	tells	you	that	you	have	a	meningioma,	a	type	of	tumour	located	in	the	membranes	surrounding	the	brain	or	spinal	cord.		Meningiomas	have	a	number	of	side	effects;	however,	most	people	only	experience	these	side	effects	when	the	tumours	are	large.		Meningiomas	may	only	need	to	be	observed.				Lupus:		strong	negative		 	Your	doctor	tells	you	that	you	have	lupus,	a	chronic	inflammatory	disease	that	occurs	when	your	body	attacks	your	own	tissues	and	organs.		This	disease	has	a	number	of	side	effects,	including	brain	and	kidney	damage.		This	disease	will	require	you	to	significantly	adjust	your	lifestyle.				Lupus:		weak	negative	 	Your	doctor	tells	you	that	you	have	lupus,	a	chronic	inflammatory	disease	that	occurs	when	your	immune	system	does	not	function	properly.		Lupus	has	a	number	of	side	effects,	including	problems	with	your	kidneys	and	forgetfulness.		If	you	have	lupus,	it	can	be	managed	with	medication.			Table	3-2	Strong	and	weak	scenarios	3.4.3	 Participation	and	Recruitment		 201	participants,	111	men	and	90	women,	received	50	cents	for	completing	a	questionnaire,	which	took	approximately	5	minutes.		Another	8	participants	failed	to	complete	the	study;	these	people	did	not	receive	compensation,	and	these	data	were	discarded.		These	participants	were	recruited	primarily	from	among	MTurk	(2017)	workers	with	experience	(minimum	completion	of	500	previous	tasks)	and	high	rates	of	completion	of	tasks	started	(over	90%)	(https://www.mturk.com/mturk/welcome)3.		The	rate	of	payment	was	set	in	accordance	with	recommendations	from	MTurk	(2017)	documentation	and	prior	research	(Paolacci	&	Chandler,	2014).		In	accordance	with	the	same	documentation	and	research,	only	participants	who	completed	the	study	received	payment.		Additionally,	quality	control	in	the	form	of	a	basic	skill-testing	question	was	used	in	order	to																																									 																					3	I	relaxed	the	requirements	on	workers	for	the	final	survey	due	to	lower	levels	of	recruiting.	This	was	not	a	concern	as	a	quality	control	mechanism,	a	skill-testing	question	regarding	the	nature	of	disease,	was	built	into	the	survey.				 41	ascertain	that	participants	were	paying	attention	and	providing	relevant	responses.		198	participants	answered	this	question	correctly;	3	participants	did	not	and	their	data	were	discarded.		Thus,	the	final	total	of	participants	was	198.				The	study	sample	of	198	participants	included	110	(56%)	men	and	88	(44%)	women.		119	(60%)	had	a	college	diploma	or	higher	level	of	education.	The	majority,	166	(84%),	saw	their	health	as	good	or	better,	and	few	(16	or	8%)	indicated	a	negative	change	in	their	health	from	last	year.		Most	participants	were	familiar	with	Internet	searching,	with	over	80%	searching	regularly,	i.e.,	daily	or	a	few	times	per	day,	for	personal	interests,	entertainment	and	news	information.		Almost	two	thirds	(117	or	59%)	also	sought	health	information	monthly	or	a	few	times	per	year.		133	participants,	or	67%	of	the	survey	sample,	were	under	40,	with	only	10	or	5%	being	60	or	over.				All	participants	were	English-speaking	and	North	American,	although	only	language	was	a	criterion	of	participation.		English-speaking	participants	were	selected	as	the	survey	instrument	was	in	English.		The	skill-testing	question	asking	the	definition	of	the	word	“disease”	also	served	to	verify	people’s	knowledge	of	English	as	well	as	their	attention	to	the	survey	(Paolacci,	Chandler	&	Ipeirotis,	2010).		Country	of	origin	was	not	a	criterion.		Although	there	are	differences	in	local	and	national	health	care	systems,	these	differences	and	their	effect	on	people’s	information	seeking	were	deemed	outside	of	the	scope	of	this	research.		3.4.4	 Data	Analysis		 Data	analyses	were	conducted	using	SPSS	Statistics	for	Windows	(Version	20.0)	(2011),	and	MS	Excel	for	Mac	(Version	14.5.8)	(2011).		The	significance	threshold	for	all	tests	was	set	at	.05.		Bonferroni	corrections	were	used	when	necessary.				Need	for	Cognition	(NfC)	scores	were	determined	as	per	the	guidelines	(Cacioppo	&	Petty,	1982);	i.e.,	scores	were	assigned	to	each	point	on	the	Likert	scale,	and	these	scores	were	added,	with	some	reversed	scores	included	as	necessary.		Frequency	counts	were	calculated	for	the	question	asking	for	reported	information	seeking	in	response	to	the	scenarios	question.		All	characteristics	were	tested	for	associations	with	this	question;	i.e.		 42	Spearman’s	correlations	were	calculated	for	Information	Seeking	and	the	factors	Age,	Level	of	Education,	General	Health	Perception,	and	NfC.					 PANAS	scores	were	also	examined	as	per	guidelines,	total	scores	for	positive	and	negative	affect	being	calculated	separately.		Scores	are	assigned	to	points	on	the	Likert	scale,	and	scores	are	added	accordingly.		To	assess	the	impact	of	the	scenarios,	the	pre-	and	post-scenario	PANAS	scores	were	compared	using	Related	Samples	Wilcoxon	Signed	Rank	tests.		The	strong	and	weak	negative	pre-	and	post-scenario	PANAS	scores	were	also	compared	using	ANOVA	if	normally	distributed	and	Kruskal-Wallis	tests	if	not.				 Reported	information	seeking	in	response	to	separate	scenarios	was	also	examined	to	determine	whether	there	was	a	differential	impact	by	scenario	or	some	other	factor.		Spearman’s	correlations	were	employed	to	test	for	associations	between	overall	pre-	and	post-	positive	and	negative	PANAS	scores	as	well	as	for	the	individual	emotions	included	in	the	PANAS	scale.		Results	from	the	two	open	questions	were	analyzed	using	qualitative	content	analysis	(Sandelowski,	2000,	2010).		These	results	comprised	of	198	short	written	responses	to	the	question	‘what	do	you	think	of	when	you	hear	the	word(s)	____________?’	and	157	optional	comments	given	in	response	to	the	reported	information	seeking	question.		Qualitative	content	analysis	was	selected	as	it	has	been	identified	as	the	least	theoretical	form	of	qualitative	analysis	and	thus	most	suited	to	my	theoretical	stance	of	neopragmatism.		Related	to	grounded	theory,	qualitative	content	analysis	is	a	“dynamic	form	of	analysis	of	verbal	and	visual	data	that	is	oriented	toward	summarizing	the	informational	contents	of	that	data”	(Sandelowski,	2000,	p.	238).		Both	inductive	and	deductive	codes	are	employed;	thus	codes	included	the	pre-existing	codes	“information	seeking”	and	“information	avoidance”	but	also	comprised	data-driven	codes	such	as	“healthcare	professionals	as	sources.”				3.5	 Study	2:		Interview	and	Interaction	Study		The	Interview	and	Interaction	with	health	information	materials	study,	here	known	as	the	Interview	and	Interaction	Study,	took	the	form	of	a	user	study	in	which	participants	were	given	a	scenario	and	interacted	with	a	collection	of	health	information	material	and	were	then	interviewed	regarding	their	health	information	behaviour.	The	interviews	covered	both	their	behaviour	in	response	to	the	scenario	and	their	general	health-related		 43	information	behaviour.		This	study	was	an	extension	of	the	first	study	and	used	many	of	the	same	instruments,	including	the	demographic	and	health	demographic	questions,	as	well	as	selected	scenarios.		However,	in	this	study,	participants	had	the	opportunity	to	actually	select	and	interact	with	online	information	and	to	discuss	their	experiences	with	health	information	in	detail.		This	study	began	with	a	preliminary	test	of	the	procedures	and	instruments	with	one	participant.		I	had	originally	planned	to	perform	the	PANAS	survey	both	before	and	after	the	scenario,	as	I	did	in	the	Affect	and	Avoidance	study.		During	the	preliminary	test,	I	found	that	this	procedure	resulted	in	a	much	longer	computer	time.		Additionally,	the	participant	had	a	negative	response	to	repeating	the	scale	within	a	very	short	time	frame	and	often	did	not	change	the	scores	he	gave	various	emotions.		Given	that	the	Affect	and	Avoidance	study	had	already	validated	the	emotional	impact	of	the	hypothetical	scenarios,	I	decided	to	run	the	second	study	with	only	one	application	of	the	PANAS,	following	introduction	of	the	scenario.		3.5.1	 Procedure	and	Instruments		Study	sessions	were	conducted	individually	in	various	locations	in	the	downtown	area	of	a	major	city.		Sessions	were	conducted	in	a	private	space,	i.e.,	a	private	room	located	either	in	a	public	library	or	a	community	centre.		Participants	were	asked	whether	they	were	comfortable	in	this	space	before	the	commencement	of	the	session.		After	completing	a	consent	form	(see	Appendix	D),	participants	began	the	Interview	and	Interaction	Study	with	a	questionnaire	(see	Appendix	B),	presented	to	participants	on	a	laptop	computer.		The	questionnaire	included	demographic,	health	related,	and	information	seeking	questions	similar	to	those	in	the	Affect	and	Avoidance	Study.		Interview	and	Interaction	Study	participants	were	also	asked	to	complete	two	scales,	the	Need	for	Cognition	scale	(NfC)	and	the	Threatening	Medical	Situations	Inventory	(TMSI).				 	The	NfC	was	used	as	this	scale	indicates	one	motivation	for	information	seeking.		The	second	scale,	the	TMSI,	employs	Miller’s	(1980)	Blunting	and	Monitoring	categories	and	serves	as	a	general	indicator	of	attitudes	to	medical	threat	related	health	information	(Wakefield,	Homewood,	Mahmut,	Taylor	&	Meiser,	2007;	Nijhof,	ter	Hoeven,	de	Jong,	2008;	Lindberg,	2012).		Developed	by	van	Zuuren	and	colleagues	(van	Zuuren	&	Hanewald,	1993;	van	Zuuren	&	Muris,	1993),	the	TMSI	presents	participants	with	four	hypothetical	scenarios		 44	involving	varying	degrees	of	medical	threat	(e.g.,	“Imagine	you	have	suffered	from	headaches	and	dizziness	for	some	time	already.	You	visit	your	doctor.		He	or	she	tells	you	things	don’t	look	good	and	refer	you	to	a	specialist	for	a	rather	trying	medical	exam.”)		Threat	varies	according	to	two	stress	parameters,	predictability	and	controllability	(van	Zuuren,	Groot,	Mulder	&	Muris,	1996).	After	each	scenario,	participants	are	presented	with	three	statements	having	to	do	with	Monitoring	(e.g.,	“I	plan	to	ask	the	specialist	as	many	questions	as	possible.”		“I	plan	to	start	reading	about	headaches	and	dizziness.”),	and	three	concerning	Blunting	(e.g.,	“For	the	time	being,	I	try	not	to	think	of	unpleasant	outcomes.”	“I	am	not	going	to	worry;	such	an	examination	is	less	worse	than	suffering	from	headaches	all	the	time.”)		These	Monitoring	and	Blunting	statements	appear	in	a	different	order	for	each	scenario;	i.e.,	Monitoring	statements	are	sometimes	found	in	consecutive	order	and	sometimes	alternate	with	Blunting	statements,	in	order	to	eliminate	question	fatigue.		Participants	are	asked	if	these	statements	are	applicable	to	them,	measured	on	a	five-point	Likert	scale	ranging	from	“Not	at	all	applicable	to	me”	to	“Strongly	applicable	to	me.”		The	scale	is	considered	reliable,	with	Cronbach’s	alpha	scores	reported	at	between	0.70	and	0.90	(Muris,	van	Zuuren,	de	Jong,	de	Beurs	&	Hanewald,	1994).				 	After	completing	the	scales,	participants	were	given	a	hypothetical	scenario,	one	of	four	similar	scenarios	encouraging	participants	to	imagine	that	they	had	this	condition.			These	scenarios,	adapted	from	those	used	in	the	first	study	and	based	on	responses	from	that	study,	are	situations	that	might	stimulate	information	seeking	or	avoidance	(Williams-Piehota	et	al.,	2009;	Flight	et	al.,	2012;	Dawson,	Savitsky	&	Dunning,	2006;	Melnyk	&	Shepperd,	2012).				Next,	Interview	and	Interaction	Study	participants	returned	to	the	computer,	where	they	completed	an	information	interaction	session	involving	material	that	was	related	to	the	condition	described	in	the	scenario.		They	were	permitted	to	retain	the	paper	on	which	the	scenario	was	printed	and	to	refer	to	the	scenario	for	reference	and	were	instructed	to	behave	as	they	“normally	would,”	i.e.,	to	browse	and	consult	the	sources	if	faced	with	the	condition	in	real	life.		A	defined	set	of	resources	was	provided	for	each	scenario	in	a	format	simulating	a	web	portal	or	resource	page,	here	referred	to	as	a	MedBrowser.		Participants	were	asked	to	interact	with	the	resource	collection	for	no	more	than	15	minutes	but	were	allowed	to	stop	at	an	earlier	time	if	they	felt	they	were	done	searching.		Their	sessions	were		 45	recorded	through	screen	capture	and	transaction	logging	using	Morae	(TechSmith,	2014)	for	Mac	(Version	10.2.2	(1380))	(2014)	software.		After	the	health	information	interaction,	participants	were	again	given	the	Positive	and	Negative	Affect	Schedule	short	form	(PANAS),	to	measure	their	emotional	state	after	reading	the	scenario	and	interacting	with	the	condition-related	health	material.				They	were	then	asked	questions	in	a	semi-structured	interview	format,	recorded	using	a	portable	device.		Interviews	varied	in	length	from	45	minutes	to	1.5	hours.			3.5.2	 Scenarios		The	Interview	and	Interaction	scenarios	used	in	this	study	were	selected	based	on	the	results	of	the	Affect	and	Avoidance	Study	and	were	very	similar	to	the	scenarios	used	in	that	study.				Strong	negative	scenarios	were	employed	for	the	more	severe	conditions,	acoustic	neuroma	and	meningioma,	and	weak	negative	scenarios	for	the	milder	conditions,	Bell’s	palsy	and	Crohn’s	disease,	in	order	to	emphasize	the	division	of	severity	between	conditions.		Lupus	was	omitted	as	the	emotional	impact	of	this	scenario	had	proved	to	be	less	clear	and	consistent	than	that	of	the	others.		The	threat	of	possible	death	was	removed	as	it	was	felt	to	be	unspecific	to	the	situation;	i.e.,	death	can	be	caused	by	any	condition,	depending	on	the	circumstances	of	the	ill	person.		The	conditions	and	scenarios	used	in	this	study	are	presented	in	Table	3-3.		 		 46		Table	3-3			Scenarios	for	conditions	in	the	I	&	I	study	Condition	 Scenario		Acoustic	neuroma	 	Your	doctor	tells	you	that	you	have	an	acoustic	neuroma:	a	tumour	located	close	to	your	brain	that	requires	immediate	treatment.	The	doctor	tells	you	that	if	the	tumour	is	not	treated,	it	will	lead	to	a	number	of	side	effects	including	deafness	in	the	ear,	facial	paralysis,	and	brain	damage.		Treatment	options	are	surgery	or	radiation.				Bell’s	palsy		 Your	doctor	tells	you	that	you	have	Bell’s	palsy,	in	which	a	problem	with	the	facial	nerve	results	in	difficulties	in	moving	parts	of	the	face.		Bell’s	palsy	has	a	number	of	side	effects,	including	problems	making	facial	expressions,	winking,	lifting	one	eyebrow,	or	smiling	broadly.		In	most	cases,	Bell’s	palsy	disappears	in	a	few	weeks.			If	treatment	is	needed,	steroids,	physiotherapy,	and	in	very	rare	cases,	surgery	can	all	help.				Crohn’s	disease	 Your	doctor	tells	you	that	you	have	Crohn’s	disease,	a	form	of	inflammatory	bowel	disease	in	which	your	digestive	system	does	not	function	properly.		Crohn’s	has	a	number	of	side	effects,	which	can	include	weight	loss,	low	iron,	and	damage	to	your	intestine.		By	and	large,	people	who	have	this	disease	can	live	full	and	productive	lives.				Meningioma		 Your	doctor	tells	you	that	you	have	a	meningioma,	a	type	of	brain	tumour	that	in	your	case	requires	immediate	treatment.		If	untreated,	meningiomas	can	lead	to	serious	side	effects,	including	problems	with	brain	function.		Treatment	options	are	surgery	and	radiation.			Table	3-3	Scenarios	for	conditions	used	in	the	Interaction	and	Interview	study		 		 47		3.5.3	 MedBrowser	Portal		The	MedBrowser	portal	for	the	Interview	and	Interaction	Study	contained	health	information	material	separated	into	five	genres	that	were	presented	in	one	of	two	different	arrangements	to	reduce	order	effects.		Choice	of	material	can	be	understood	with	reference	to	the	literature	review.					 48		Figure	3-1	Screen	shot	of	Bell's	palsy	(order	1)		 49			Figure	3-2	Screen	shot	for	Bell's	palsy	(order	2)	Every	effort	was	made	to	present	consistent	information	across	conditions;	the	website	section,	for	example,	always	contained	material	from	the	same	five	sites:			 50	patient.co.uk,	MedScape,	Wikipedia,	eMedicineHealth,	and	Medline	Plus.		Attempts	were	made,	too,	to	include	material	that	ranged	from	potentially	emotionally	disturbing	(e.g.,	details	about	surgeries)	to	less	disturbing	(e.g.,	people	speaking	about	their	past	experiences	and	their	life	after	being	healed).		Videos	ranged	from	depictions	of	graphic	surgeries	(e.g.,	“Brain	surgery	removal	of	metastatic	tumor	high	power	surgical	microscope”)	to	personal	narratives	that	represented	either	a	short	time	after	surgery	and	an	uncertain	outcome,	(e.g.,	“24	hour	post-op	for	de-bulking	of	my	meningioma”)	to	a	long	time	after	surgery	and	a	positive	outcome	(e.g.,	“Acoustic	Neuroma:		Healing	path	2013”)	to	narratives	by	people	who	were	merely	describing	the	condition	in	a	clinical	manner	(e.g.,	“Leonard	Cerullo,	MD,	discusses	meningiomas”).		Blogs	followed	a	similar	path,	ranging	from	“My	seizure,	finding	the	meningioma	and	my	brain	tumor	surgery”	to	“3rd	tumor-versary.”		Journal	articles	ranged	from	those	written	for	medical	experts	(e.g.,	“Colonic	adenocarcinoma	revealing	Crohn’s	disease”)	to	those	written	for	a	more	general	audience	(e.g.,	“New	Crohn’s	disease	treatment	may	result	from	‘bodyguard	protein’	discovery”).		News	articles	chosen	contained	either	personal	stories	(e.g.,	“I	couldn’t	smile	at	my	newborn	babies	and	feared	my	face	scared	them”),	stories	about	celebrities	(e.g.,	“George	Clooney	says	smile”),	or	explanations	about	new	research	or	treatments	(e.g.,	“Steroids	help	unfreeze	Bell’s	palsy”).		See	Appendix	E	for	a	full	list	of	online	material	and	inclusion	rationales.			3.5.4	 Interview	Questions		Interview	questions	(see	Appendix	F)	for	the	Interview	and	Interaction	Study	were	developed	with	reference	to	prior	work,	including	McKenzie	(2001)	and	Lambert,	Loiselle,	and	Macdonald	(2009).		These	questions	were	also	shaped	with	the	aid	of	the	information-seeking	question	from	the	Affect	and	Avoidance	study.		For	example,	responses	such	as	“I	would	take	it	with	a	grain	of	salt	until	I	could	discuss	further	with	my	doctor”	alerted	me	that	attitudes	towards	healthcare	professionals	might	be	an	important	element	in	health	information	behaviour	and	informed	the	creation	of	such	questions	as	“Were	there	any	features	of	the	information	that	would	make	you	feel	better	or	worse?		For	example,	the	inclusion	of	material	from	doctors	or	other	healthcare	professionals?”			As	Bosk	(1979)	notes	in	a	metaphor,	qualitative	research	is	a	“body	contact”	(p.	ix)	sport,	in	which	importance	is	attached	to	the	participant-researcher	relationship;	thus	an		 51	interactive	style	of	active	interviewing	(Holstein	&	Gubrium,	1995)	was	used,	with	meaning	negotiated	between	interviewer	and	interviewee.		An	interview	guide	was	utilised,	but	with	reference	to	Maxwell	(2011)	and	Sandelowski	(2000,	2010),	a	flexible	approach	was	employed,	with	the	experimenter	asking	questions	that	arose	naturally	rather	than	strictly	following	that	guide	(see	also	Patton,	2002).		I	also	took	notes	on	participant	behaviour	while	answering	questions,	taking	care	not	to	make	judgments	about	this	behaviour,	e.g.,	“shifted	in	the	seat	while	answering,”	rather	than	“looked	uncomfortable.”									Participants	were	asked	to	review	their	information	seeking	session	prompted	by	the	scenario.		Questions	focused	on	why	they	selected	and	did	not	select	particular	materials	and	genres;	what	information	they	were	hoping	or	not	hoping	to	obtain;	whether	or	not	this	information	was	obtained;	what	caused	them	to	stop	searching;	and	their	overall	level	of	satisfaction	with	the	material.		Next,	participants	were	asked	about	their	own	health	behaviours.		Here,	questions	encompassed	topics	such	as	any	health	problems	they	had	experienced	and	their	information	searching	and	avoidance	behaviours	with	reference	to	these	problems.		3.5.5	 Participation	and	Recruitment			Thirty-five	members	of	the	general	public	between	the	ages	of	20	and	84	were	recruited	by	convenience	sampling,	defined	by	Kelly	(2009)	as	relying	on	available	elements	to	which	the	researcher	has	access	(p.	69)	(Miles	&	Huberman,	1984;	Miles,	Huberman	&	Saldana,	2014;	Maxwell,	2011).		Recruitment	was	carried	out	by	means	of	notices	posted	in	coffee	shops,	community	centres,	libraries,	and	a	hospital	in	the	downtown	area	of	a	major	urban	centre.		The	website	meetup.com,	a	social	networking	portal	that	supports	networking	and	allows	members	to	particulate	in	offline	meetings	was	also	used.		These	methods	of	recruitment	were	chosen	in	order	to	garner	a	broad	cross-section	of	the	population.		The	study	was	conducted	in	English	and	sessions	were	held	in	public	locations	in	the	downtown	area,	specifically	in	branches	of	the	public	library	and	in	a	community	centre.		(See	Appendix	C	for	the	recruitment	form.)				The	study	sample	was	almost	equally	split	along	gender	lines,	with	18	women	and	17	men.		Almost	two-thirds,	21	or	59%,	were	50	or	older,	with	the	rest,	14	participants,	being	between	20	and	49	(41%).		32	out	of	34	participants	possessed	some	post-secondary		 52	education	past	high	school,	and	11	(32%)	having	some	graduate	school.		One	person	chose	not	to	record	their	education.		Few	saw	their	health	as	less	than	good,	4	out	of	35	(11%),	and	over	half,	19,	(54%)	saw	their	health	as	very	good	or	better.		Only	one	person	saw	his/her	health	as	having	deteriorated	from	last	year,	while	a	third,	11	or	32%,	saw	their	health	as	having	improved.		Over	60%	of	participants	reported	searching	daily	(19	or	54%)	or	a	few	times	per	day	(7	or	20%)	for	online	information	regarding	personal	interests,	entertainment,	or	news.		Participants	also	reported	frequent	searching	for	health	information,	with	over	80%	searching	monthly	(8	or	24%)	or	more	often,	8	or	24%	searching	a	few	times	a	month,	13	or	38%	searching	daily,	and	2	or	6%	searching	a	few	times	per	day.		When	asked,	one	third	of	participants	(10	or	31%)	stated	that	they	were	“generally	healthy,”	with	some	of	these	healthy	participants	later	commenting	on	current	or	recent	health	problems.		In	the	course	of	the	interviews,	almost	all	participants	were	able	to	draw	upon	personal	experiences	with	health	issues	when	describing	their	health-related	information	behaviour.		3.5.6	 Data	Analysis		 Data	analyses	were	conducted	using	SPSS	Statistics	for	Windows	(IBM,	Version	20.0)	(2011),	MS	Excel	for	Mac	(Version	14.5.8)	(2011),	MS	Word	for	Mac	(Version	14.5.8)	(2011),	Morae	(TechSmith,	2014)	and	NVivo	(QSR	International	Pty	Ltd,	Version	10,	2014)	for	Mac	(Version	10.2.2	(1380)	(2014)).		Demographics	and	health	perception	were	summarized	using	frequency	counts.		Need	for	Cognition	scores	were	determined	as	per	the	guidelines	(Cacioppo	&	Petty,	1982),	with	the	results	indicating	a	positively	skewed	distribution,	with	an	average	of	3.88	(SD	6.46),	and	a	median	of	9.		Threatening	Medical	Situations	Inventory	scores	were	calculated	with	Monitoring	and	Blunting	scores	measured	separately,	in	accordance	with	van	Zuuren	and	colleagues	(van	Zuuren,	de	Groot,	Mulder	&	Peter,	1996),	who	consider	them	to	be	distinct	characteristics.		Positive	and	Negative	Affect	Schedule	scores	were	also	examined	as	per	guidelines,	with	total	scores	for	positive	and	negative	affect	being	calculated	separately	in	accordance	with	Cacioppo	and	Petty	(1982).		The	video	interaction	sessions	as	recorded	by	Morae	(TechSmith,	2014)	were	then	examined	using	the	Morae	Observer	component.		Frequencies	were	tallied	for	the	information	seeking	measures	of	number	of	items,	and	amount	of	time	spent	in	general	and	on	each	item,	and	correlation	analyses	were	performed	comparing	the	different	variables	and	the	demographics	with	the	information	seeking	measures.				 53	Interaction	data	from	8	participants	was	not	available	due	to	technical	difficulties,	i.e.,	an	unreliable	Internet	connection	in	the	location	of	the	interaction	session;	thus	this	section	reports	on	27	participants.		The	first	8	sessions	were	scheduled	within	a	short	time	frame,	and	attempts	to	ensure	that	the	Internet	connection	was	functioning	were	initially	unsuccessful.		Thus	these	sessions	went	ahead	even	though	the	ability	to	use	the	MedBrowser	was	compromised.		Full	interviews	were	conducted	with	these	participants.						The	decision	was	made	to	include	the	interviews	conducted	even	though	the	interaction	data	was	unavailable,	as	many	questions	focused	on	the	general	health	information	seeking	of	participants	rather	than	on	the	seeking	patterns	in	the	interaction	session.					Results	from	the	35	interviews	were	analyzed	using	qualitative	content	analysis	(Sandelowski,	2000,	2010).		Although	this	type	of	analysis	is	less	interpretive	than	other	forms	of	qualitative	analysis	such	as	phenomenology,	“descriptions	always	depend	on	the	perceptions,	inclinations,	sensitivities,	and	sensibilities	of	the	describer”	(Sandelowski,	2000,	p.	335).		Maxwell	(2011)	points	out	that	the	researcher	is	part	of	the	world	he	or	she	studies;	this	“reflexivity”	(p.	109)	indicates	that	the	interviewer	and	the	interview	situation	influences	interviewee	behaviour	and	comments.		Thus	it	is	crucial	to	position	myself	in	relation	to	this	research.					Fifteen	years	ago,	I	had	an	acoustic	neuroma	that	required	emergency	surgery	(otherwise	I	would	have	died)	and	about	which	I	did	not	seek	much	beyond	minimal	health	information.		My	lack	of	health	information	seeking	did	not	affect	the	outcome	of	this	health	concern;	the	surgery	was	(obviously)	successful.		Ten	years	ago,	I	returned	to	school	to	become	a	librarian.		During	this	Master’s	in	Library	and	Information	Science	degree,	I	encountered	a	negative	bias	against	information	avoidance	in	the	information	behaviour	literature	presented	in	my	classes,	a	bias	that	contradicted	my	own	experience.		These	various	events	inspired	my	choice	of	topic	for	this	dissertation	and	also	influenced	the	qualitative	analysis.		One	aim	of	this	project	was	to	counter	the	bias	in	the	field	of	library	and	information	science	against	information	avoidance.		My	interpretation	of	information	avoidance	is	different	than	that	of	some	other	researchers;	I	see	health	information	avoidance	as	less	problematic,	neutral,	even	positive,	whereas	the	interpretations	of	others	is	more	negative	(Johnson,	2014;	see	also	Williams-Piehota	et	al.,	2009;	Howell	&	Shepperd,	2013	for	examples).				 54		Analysis	began	after	all	interviews	were	completed.		Interviews	and	observations	were	fully	transcribed.		As	befitting	qualitative	content	analysis,	codes	are	both	imposed	by	the	researcher	and	data-derived.		Examples	of	imposed	codes	were	“information	seeking”	and	“information	avoidance;”	however,	I	made	certain	to	remain	flexible	and	ensure	all	codes	were	in	accordance	with	the	data.		The	data	was	also	summarized	numerically;	i.e.,	comments	in	each	category	were	counted.		Although	efforts	were	made	to	uncover	the	latent	content	of	the	data,	there	was	no	mandate	to	re-present	the	data	in	any	other	terms	but	those	of	the	participants	(Sandelowski,	2000,	2010).				The	material	was	examined	line	by	line,	using	the	coding	software	NVivo	(QSR	International	Pty	Ltd.,	2014).		Extraneous	material	was	deleted	with	reference	to	the	following	questions:		“Does	it	relate	to	the	research	concern?		Does	it	help	with	better	understanding	the	participants?		Does	it	clarify	experimenter	thinking?		Does	it	simply	seem	important,	even	if	the	reason	is	unclear?”	(Auerbach	&	Silverstein,	2003,	p.	48).			The	following	questions	were	then	used	to	assist	with	analysis:					What	are	people	doing?	What	are	they	trying	to	accomplish?	How,	exactly,	do	they	do	this?	What	specific	means	and/or	strategies	do	they	use?	How	do	members	talk	about,	characterize,	and	understand	what	is	going	on?	What	assumptions	are	they	making?	What	do	I	see	going	on	here?	What	did	I	learn?		(Emerson,	Fretz	&	Shaw,	1995,	p.	146)		 Repeated	ideas	were	then	grouped	together,	according	to	the	process	outlined	by	Auerbach	and	Silverstein	(2003).		Initial	ideas	consisted	of	actual	words	used	by	the	participants.		For	example,	“[Doctors	are]	not	kept	up	to	date	with	current	events,	and	the	current	health	information”	became	“Doctors	are	not	updated.”		Another	idea,	“Doctors	not	up	to	speed,”	stemmed	from	a	quote	“Doctors	are	not	necessarily	up	to	speed	in	very	specific	areas”	(P33).		All	ideas	were	then	examined	as	to	similarity,	and	similar	ideas	were	grouped	together.		Thus,	in	the	example,	both	“Doctors	are	not	updated”	and	“Doctors	are	not	up	to	speed”	were	grouped	together	in	“Doctors	are	not	updated.”		I	paid	special	attention	to	so-called	“orphans,”	ideas	that	did	not	repeat,	re-examining	the	texts	to	see	if	these	ideas	were	indeed	found	in	other	places.		The	decision	was	then	made	as	to	whether	these	ideas	were	kept	or	discarded.		The	resulting	list	contained	85	ideas,	approximately	consistent	with	Auerbach	and	Silverstein’s	(2003)	suggestion	of	between	40	and	80	ideas.		Repeated	ideas	were	then	named	with	codes.		Thus	“Doctors	are	not	updated”	was	grouped		 55	with	other	ideas	involving	healthcare	professionals	into	the	higher	level	codes	“Doctors-healthcare	professionals”	and	“Problems	with	doctors,	medical	system.”		Some	ideas	repeatedly	mentioned	by	participants	remained	as	lower	level	codes	to	indicate	a	strong	element	present	in	the	code.		Thus	“Doctors	are	not	updated”	is	present	as	a	lower	level	code	in	the	Code	rationale	(see	Appendix	G).		The	coding	schema	was	developed	over	a	number	of	weeks	through	an	iterative	process	that	included	regular	discussions	with	my	research	supervisor.		Codes	were	also	discussed	and	verified	with	members	of	the	supervisory	committee.		An	initial	version	of	the	Code	rationale	was	circulated	to	all	committee	members,	and	subsequent	versions	were	rewritten	with	input	from	the	committee.		Member	checking	was	not	performed.		While	member	checking	has	been	often	cited	as	an	important	validation	tool	that	supports	both	the	science	that	researchers	perform	and	participants’	rights	to	know	(Maxwell,	2011),	Sandelowski	(1993)	points	out	that	this	technique	can	create	difficulties	in	participants’	lives.		As	participants	alter	the	narratives	of	their	lives	in	order	to	fit	with	differing	situations,	they	may	not	wish	to	be	confronted	with	earlier	interpretations.		For	example,	if	participants	viewed	a	certain	situation	in	one	way	at	the	time	of	the	interview	and	this	view	altered	over	time,	it	may	not	be	ethical	or	practical	to	present	them	with	the	view	they	held	in	the	interview	(see	also	Sandelowski,	2000,	2010;	Maxwell,	2011).		Participants	were	invited	to	contact	me	regarding	the	results,	if	they	wished,	and	one	did	so	through	email.		Three	more	participants	met	me	by	chance	at	locations	in	my	neighbourhood	and	asked	for	results	and	updates	on	my	progress,	which	were	provided	verbally,	with	further	information	sent	through	email	if	desired.										 The	list	of	resulting	codes	was	re-examined,	then	grouped	into	themes,	with	attention	again	paid	to	orphans.		Themes	were	then	examined	to	see	how	they	fit,	in	order	to	establish	a	theoretical	construct.		The	first	theme	from	the	list	was	chosen	and	the	list	read	through	to	see	how	other	themes	connected	with	the	first.		Groups	of	themes	were	then	put	into	theoretical	constructs,	with	attention	paid	to	orphan	themes,	and	these	constructs	were	named.		Codes	were	re-examined	at	this	stage	as	a	form	of	intrarater	reliability,	to	verify	this	analysis	(Sandelowski,	2000,	2010).		The	re-examination	functioned	as	an	audit	of	analysis.		The	list	of	theoretical	constructs	was	then	examined	to	discern	if	a	theoretical	narrative	could	be	created,	using	constructs	that	fit	together.						 56	Themes	related	to	the	research	questions	and	thus	had	to	do	with	mechanisms	of	information	avoidance	and	the	factors	that	influenced	information	avoidance	behaviours.		Some	themes	related	directly	to	codes,	while	others	emerged	from	closer	examination	of	codes.		The	first	two	themes	were	two	mechanisms	that	came	from	the	results,	delegation	and	self-regulation.		Both	mechanisms	stemmed	from	examination	of	the	coding	category	6,	search	behaviour.		The	first,	delegation,	also	arose	from	close	inspection	of	the	coding	category,	10C	People	(as	information	source)	and	the	coding	category	8	Social,	particularly	with	reference	to	code	8B	Education	of	friends	and	family.		The	second	mechanism,	self-regulation,	came	from	the	coding	category	3	Coping,	especially	code	3A-B	Self-regulation	(see	Appendix	G).			Themes	regarding	the	factors	influencing	information	avoidance	consisted	of	three	beliefs	found	in	analysis	of	participant	comments:		a	belief	in	health	as	a	personal	responsibility	or	in	health	as	the	responsibility	of	healthcare	professionals	or	fate;	a	belief	in	healthcare	professionals	as	trustworthy	or	not;	and	a	belief	or	lack	thereof	in	health	information	seeking	as	a	social	responsibility.		All	three	themes	were	developed	with	the	aid	of	coding	category	1	Affect.		“Belief	in	health	as	a	personal	responsibility”	and	its	opposite,	“the	responsibility	of	healthcare	professionals	or	fate”	stemmed	from	an	examination	of	codes	in	category	12	Social	achievements,	particularly	codes	G	Self-efficacy	and	H	Taking	care	of	self,	and	codes	in	the	coding	category	10C	People	(as	information	source),	especially	10C-A	Doctor-healthcare	professional.		The	coding	category	10C	People	(as	information	source)	also	yielded	the	second	theme,	“Belief	in	healthcare	professionals	as	trustworthy	or	not.”		The	last	theme,	“Belief	in	health	information	seeking	as	a	social	responsibility,”	was	found	through	examination	of	the	coding	category	12	Social	achievements	(see	Appendix	G).			3.6		 Conclusion			 A	mixed	methods	approach	was	taken	in	which	two	studies,	an	online	survey	containing	qualitative	and	quantitative	elements	and	a	user	study	including	qualitative	interviews	were	employed	to	answer	the	two	research	questions.			1.		What	factors	contribute	to	information	avoidance?	More	specifically,	to	what	extent	do	personality	traits,	situational	affect,	and	the	nature	of	available	information	sources	influence	information	avoidance?	2.		What	are	the	mechanisms	of	information	avoidance?				 57	The	studies	were	conducted	in	2015	and	involved	198	participants	and	35	participants,	respectively.		I	chose	the	mixed	methods	approach	as	it	corresponded	both	to	my	neopragmatist	wish	to	find	more	practical	solutions,	and	as	it	allowed	me	to	examine	information	avoidance	comprehensively	from	multiple	angles.					 The	Affect	and	Avoidance	study	(Study	1),	consisted	of	an	online	survey	containing	measurements	of	personality	and	affect	and	self-reported	information	seeking	and	avoidance	questions	that	responded	to	ten	hypothetical	medical	scenarios	depicting	five	conditions	at	two	levels	of	severity	(see	Appendix	A	for	the	full	questionnaire	used	in	this	study).		The	crowd-sourcing	software	Amazon	Mechanical	Turk	(2017)	(MTurk)	was	used	for	recruitment,	as	it	was	deemed	appropriate	for	the	short	nature	of	the	survey	and	for	the	ability	of	MTurk	(2017)	to	reach	a	large	number	of	people	quickly	and	efficiently.		Care	was	taken	regarding	the	ethical	issues	of	this	software,	in	particular	with	regards	to	payment.		Instruments	of	measurement	used	were	a	questionnaire	and	two	scales,	the	Need	for	Cognition	Scale	(NfC)	and	the	Positive	and	Negative	Affect	Schedule	(PANAS).		NfC	served	to	measure	of	a	personality	trait	influencing	information	seeking	and	avoidance,	and	PANAS	to	measure	affect.		Scenarios	were	created	with	reference	to	previous	studies	and	included	much	of	the	same	wording,	with	dissimilar	conditions.		In	this	study,	conditions	were	acoustic	neuroma,	Bell’s	palsy,	Crohn’s	disease,	lupus,	and	meningioma.		The	data	from	198	participants,	functioned	as	the	base	for	analysis,	in	which	characteristics	were	tested	for	associations	with	reported	information	seeking	and	in	which	the	effect	of	scenarios	in	general	and	the	two	levels	of	severity	in	particular	were	also	examined.								 The	Interview	and	Interaction	study	(Study	2)	was	a	user	study	in	which	participants	interacted	with	health	information	material	relating	to	a	hypothetical	medical	scenario	and	were	then	interviewed	as	to	this	interaction	and	to	their	past	health	information	behaviour.		Three	scales	were	employed	in	this	study,	the	NfC	scale,	the	Threatening	Medical	Situations	Inventory	(TMSI),	and	the	PANAS	scale.		The	NfC	and	TMSI	served	to	test	for	personality	traits	related	to	information	seeking	and	avoidance	in	general	and	health	information	seeking	and	avoidance	in	particular.		PANAS	was	employed	to	test	for	affective	factors.		Scenarios	used	in	this	study	were	based	on	those	used	in	the	Affect	and	Avoidance	study;	these	were	the	strong	negative	scenarios	for	acoustic	neuroma	and	meningioma	and	the	weak	negative	scenarios	for	Bell’s	palsy	and	Crohn’s	disease.		A		 58	MedBrowser	website	was	created	with	health	information	material	with	reference	to	the	literature	(see	Appendix	E),	and	interview	questions	were	created	with	reference	to	responses	from	the	Affect	and	Avoidance	study	as	well	as	to	the	literature	as	well	(see	Appendix	F).		Data	from	35	participants	were	analyzed,	with	descriptive	statistics	used	for	responses	to	the	scales	and	to	data	from	the	interaction	session.		Data	from	the	interviews	were	analyzed	by	means	of	qualitative	content	analysis.							 	 		 59	4	 Affect	and	Avoidance	Study		The	following	chapter	will	present	the	results	of	the	Affect	and	Avoidance	study,	which	examined	the	influence	of	affect	and	personality	factors	on	participants’	stated	intent	to	seek	health	information,	and	to	test	the	influence	of	hypothetical	medical	scenarios	on	participants’	emotional	states.		I	will	begin	by	looking	at	evidence	of	information	seeking	and	avoidance	in	the	study	and	progress	to	an	examination	of	the	personal	characteristics	of	participants	and	their	influence	on	participants’	information	seeking.		I	will	then	look	at	the	situational	affect	demonstrated	by	participants	after	their	reading	of	hypothetical	medical	scenarios.					4.1	 Participants			 	 The	study	sample	consisted	of	198	participants,	of	whom	56%	(n=110)	were	men	and	44%	(n=88)	were	women.		Education	levels	varied,	with	39%	(n=76)	possessing	high	school	or	less	than	high	school;	21%	(n=42)	having	a	college	level	education,	some	college	or	an	associates	degree;	and	40%	(n=80)	holding	an	undergraduate	degree	or	higher.		Participants	were	experienced	Internet	searchers,	and	many	looked	for	subjects	such	as	research	and	studies,	news	and	current	events,	and	personal	interests	and	entertainment	a	great	deal.		Many	participants	reported	especially	frequent	searching	for	news	and	current	events,	with	54%	(n=107)	reporting	daily	searching	and	28%	(n=54)	reporting	searching	a	few	times	per	day,	28%	(n=54);	and	personal	interests	and	entertainment	with	46%	(n=92)	searching	daily	and	36%	(n=71)	reporting	searching	a	few	times	per	day.		Reported	health	information	searching	was	slightly	less	frequent,	with	the	majority	of	participants	looked	for	health	information	a	few	times	per	month,	40%	(n=80),	a	few	times	per	year,	27%	(n=54),	or	monthly,	22%	(n=43).					Participants’	age,	general	health	perception,	and	current	health	perception	are	summarized	in	Table	4-1.			 		 60	Table	4-1		Age,	general	health	perception	and	current	health	perception	of	participants	in	the	Affect	and	Avoidance	study	Characteristic	 Category	 Percentage	(number)	Age	 19-29	 31%	(n=61)		 30-39	 36%	(n=71)		 40-49	 15%	(n=30)		 50-59	 13%	(n=26)		 60-69	 5%	(n=10)		 	 	General	health	perception	 Poor	 3%	(n=5)		 Fair	 14%	(n=27)		 Good	 43%	(n=86)		 Very	good	 31%	(n=61)		 Excellent	 10%	(n=19)		 	 	Current	health	perception	 Much	worse	than	last	year	 0%		 Somewhat	worse	than	last	year	 9%	(n=18)		 About	the	same	 68%	(n=135)		 Somewhat	better	than	last	year	 20%	(n=39)			 Much	better	than	last	year	 4%	(n=6)	Table	4-1	Age,	general	health	perception,	and	current	health	perception	of	participants	in	the	Affect	and	Avoidance	study	4.2	 Information	Seeking	and	Avoidance		 	Upon	exposure	to	a	hypothetical	scenario	in	which	they	were	diagnosed	with	a	medical	condition,	an	overwhelming	amount	of	participants	reported	that	they	would	seek	a	large	amount	of	health	information	(Table	4-2	and	Figure	4-1).			The	majority	of	participants	(75%)	indicated	that	they	would	search	extensively,	regardless	of	the	medical	condition	or	the	relative	severity	of	this	condition;	they	all	selected	option	6:		“I	would	look	for	as	much	information	as	I	could	find”	(Table	4-2	and	Figure	4-1).		The	number	of	participants	who	indicated	they	would	seek	minimal	information	or	would	not	seek	at	all	(Options	1	or	2	in	Table	4-2	and	Figure	4-1)	was	very	low,	2.5%	overall.			 		 61	Table	4-2		Reported	likelihood	of	information	seeking	of	participants	in	the	Affect	and	Avoidance	study	Information	seeking	 Percentages	(n)		 	 	 	 	 	 	1						I	would	avoid	information	about	this	disease.			 1%	(n=1)	2						I	would	not	avoid	information	but	would	not	actively	look	for	it.			 2%	(n=4)	3						I	would	look	for	a	small	amount	of	information.			 2%	(n=3)	4						I	would	look	for	a	moderate	amount	of	information.			 8%	(n=15)	5						I	would	look	for	a	great	deal	of	information.			 12%	(n=24)	6						I	would	look	for	as	much	information	as	I	could	find.			 75%	(n=148)	Table	4-2	Reported	likelihood	of	information	seeking	of	participants	in	the	Affect	and	Avoidance	study	4.3	 Personal	Characteristics		 I	examined	a	number	of	personal	characteristics	including	Age,	Gender,	Level	of	Education,	Internet	usage,	General	Health	Perception,	and	Need	for	Cognition	(NfC).		All	characteristics	were	tested	for	associations	with	the	level	of	information	seeking	that	participants	reported	they	would	undertake	in	response	to	the	scenarios.		Spearman’s	correlations	were	calculated	for	Information	Seeking	and	the	factors	Age,	Level	of	Education,	General	Health	Perception,	and	NfC,	for	which	participants	in	this	study	obtained	a	mean	NfC	score	of	-0.09	(SD	5.84)	and	a	median	of	0.		I	used	Spearman’s	correlations	because	the	data	were	not	normally	distributed	and	performed	Bonferroni	corrections,	leading	to	a	significance	threshold	of	.0125.		A	weak	positive	correlation	was	found	between	Information	Seeking	and	General	Health	Perception	(r=.206,	p=.004,	n=196),	as	well	as	a	correlation	that	is	close	to	being	significant	between	Information	Seeking	and	Age	(r=.148,	p=.037,	n=198).		Spearman’s	correlations	were	also	performed	on	Information	Seeking	and	Gender;	no	correlations	were	found.		These	correlations	suggest	that	individuals	who	perceived	their	health	to	be	better	were	also	more	likely	to	claim	they	would	search	for	more	information.		Age	was	also	close	to	being	significantly	correlated	with	NfC	(r=.173,	p=.015,	n=197),	while	neither	Education	Level	nor	NfC	were	correlated		 62	with	Information	Seeking.			4.4	 Situational	Affect		I	also	examined	the	role	of	situational	affect	on	information	seeking.		The	Positive	and	Negative	Affect	Schedule	(PANAS)	was	administered	before	and	after	scenarios	were	shown	to	participants	and	results	indicate	that	the	scenarios	were	successful	in	engendering	affective	responses	among	participants.		Pre-scenario	participant	PANAS	scores	were	similar	to	other	reported	results	(Watson,	Clark	&	Tellegren,	1988).		The	overall	mean	positive	affect	(PA)	score	of	29.5	(SD	8.56)	is	consistent	with	Watson,	Clark	&	Tellegren’s	(1988)	mean	score	of	29.7	(SD	7.9).		The	overall	negative	score	(NA)	for	participants	was	12.9	(SD	8.49),	which	is	slightly	below	the	mean	of	14.8	found	by	Watson	et	al.,	but	given	the	standard	deviation	of	5.4,	it	is	in	the	same	range.		To	assess	the	impact	of	the	scenarios,	I	compared	the	pre-	and	post-scenario	PANAS	scores	using	Related	Samples	Wilcoxon	Signed	Rank	tests,	as	data	were	not	normally	distributed.		This	test	rejected	the	null	hypothesis	that	the	difference	between	these	two	measurements	for	both	positive	and	negative	affect	was	0;	I	concluded	that	the	scenarios	influenced	participants’	affect	(z=-8.355,	p=.000	for	positive;	z=-7.969,	p=.000	for	negative).		Results	for	individual	diseases	showed	significant	differences	in	affective	state	before	and	after	exposure	to	the	scenario	as	well	(acoustic	neuroma:		z=-3.672,	p=.000	for	positive,	z=-4.026,	p=.000	for	negative;	Bell’s	palsy:		z=-3.466,	p=.001	for	positive,	z=-3.127,	p=.002	for	negative;	Crohn’s	disease:		z=-3.967	for	positive,	z=-3.804,	p=.000	for	negative;	lupus:		z=-3.666,	p=.000	for	positive,	z=-2.859,	p=.004	for	negative;	meningioma:		z=3.851,	p=.000	for	positive,	z=-3.851,	p=.000	for	negative).									Mean	PA	and	NA	scores	are	summarized	in	Tables	4-2	and	4-3,	for	the	5	disease	scenarios	and	overall,	showing	that	following	reading	of	the	scenarios,	positive	emotion	scores	dropped	and	negative	emotion	scores	rose.		The	different	scenarios,	therefore,	influenced	participants’	negative	and	positive	affect,	i.e.,	a	lowering	of	positive	affective	scores	and	a	rise	in	negative	affective	scores.		This	impact	of	the	scenarios	also	varied	somewhat	according	to	the	severity	of	the	health	conditions	presented	in	the	scenarios,	with	higher	average	changes	in	pre	and	post-scenario	scores	occurring	for	acoustic	neuroma	and	meningioma,	the	more	serious	conditions.		Table	4-2	and	Table	4-3	list	the	scenarios	in	order	of	severity	from	lowest	to	highest,	beginning	with	Bell’s	palsy	(n=42),		 63	and	Crohn’s	disease	(n=40),	next	following	with	lupus	(n=38),	and	continuing	to	acoustic	neuroma	(n=39)	and	meningioma	(n=41).				 		 64				Table	4-2		Pre-	and	post-scenario	PANAS	scores	for	positive	affect	by	disease	Condition	 Mean	Positive	Affect	(SD)		 Pre	 Post	 Change	Bell’s	palsy	 25.8	(8.9)	 23.1	(6.0)	 -2.6	(5.6)	Crohn’s	disease	 29.3	(11.0)	 25.2	(8.3)	 -4.1	(6.3)	Lupus	 31.1	(9.4)	 27.9	(10.2)	 -3.6	(5.8)	Acoustic	neuroma	Meningioma	 29.8	(8.6)	31.0	(9.0)	 27.1	(8.7)	20.5	(11.3)	 -2.7	(4.4)	-6.8	(7.4)	Overall	 29.5	(9.3)	 23.0	(8.5)	 -3.6	(6.0)	Table	4-2	Pre-	and	post-scenario	PANAS	scores	for	positive	affect	by	disease		Table	4-3		Pre-	and	post-scenario	PANAS	scores	for	negative	affect	by	disease	Condition	 Mean	Negative	Affect		 Pre	 Post	 Change	Bell’s	palsy	 13.0	(7.0)	 16.8	(9.6)	 +3.7	(7.9)	Crohn’s	disease	 12.6	(8.1)	 16.1	(8.9)	 +3.6	(6.4)	Lupus	 12.9	(3.4)	 14.9	(6.0)	 +2.2	(4.5)	Acoustic	neuroma	Meningioma	 12.4	(6.4)	10.5	(6.2)	 18.4	(8.7)	24.5	(8.3)	 +4.7	(8.7)	+4.3	(10.4)	Overall	 12.9	(6.2)	 17.5	(9.2)	 +4.2	(8.0)	Table	4-3	Pre-	and	post-scenario	PANAS	scores	for	negative	affect	by	disease	I	had	anticipated	a	difference	between	the	emotional	impact	of	the	strong	negative	and	weak	negative	versions	of	the	scenarios;	however,	that	did	not	prove	to	be	the	case	(see	Table	4-3).		These	scores	were	compared	using	Kruskal-Wallis	tests.		Significant	results	were	not	found	between	these	strong	and	weak	negative	versions,	either	in	scores	for	positive	affect	(r=0.666,	p=.186)	and	for	negative	affect	(r=0.356,	p=.850)	overall.		As	evidenced	by	Table	4-4,	the	difference	between	strong	and	weak	scenario	tones	was	often	found	to	be	similar	(Bell’s	palsy)	or	having	an	opposing	effect	than	predicted	(acoustic		 65	neuroma	and	meningioma).		For	this	reason,	the	strong	negative	and	weak	negative	scenarios	were	combined	and	the	distinctions	were	not	considered	in	further	analysis.				 		 66	Table	4-4		Pre-	and	post-scenario	emotional	states	by	scenario	tone	Condition	and	scenario	tone		 Emotional	states		 Mean	Positive	Affect	 Mean	Negative	Affect	Pre	 Post	 Change	 Pre	 Post	 Change	Bell’s	palsy:		Strong	negative	 24.7	 22.1	 -2.6	 14.1	 18.6	 +5.1	Bell’s	palsy:		Weak	negative	 26.9	 24.3	 -2.6	 11.8	 14.9	 +3.1	Crohn’s	disease:		Strong	negative	 29.7	 23.8	 -5.9	 13.0	 18.9	 +5.9	Crohn’s	disease:		Weak	negative	 29.4	 26.6	 -2.8	 13.2	 15.0	 +1.8	Lupus:		Strong	negative	 32.8	 29.1	 -3.7	 14.0	 16.4	 +2.4	Lupus:	Weak	negative	 30.3	 27.1	 -3.2	 11.6	 13.7	 +2.1	Acoustic	neuroma:		Strong	negative	Acoustic	neuroma:		Weak	negative		Meningioma:		Strong	negative	29.2	30.5	31.2	27.5	26.6	29.1	-1.5	-3.9	-2.1	12.5	14.7	11.6	17.0	19.8	17.2	+4.5	+5.1	+5.6	Meningioma:		Weak	negative	 30.8	 25.0	 -5.8	 15.0	 22.9	 +7.9	Overall:		Strong	negative	 29.5	 26.3	 -3.2	 13.0	 17.6	 +4.6	Overall:		Weak	negative	 29.6	 25.9	 -3.7	 13.6	 17.3	 +3.7	Table	4-4	Pre-	and	post-scenario	emotional	states	by	scenario	tone		There	does	seem	to	be	some	differential	impact	on	Information	Seeking	between	the	disease	scenarios.		Table	4-5	summarizes	the	Information	Seeking	responses	by	disease	scenario.		For	the	more	severe	diseases,	Meningioma	and	Acoustic	Neuroma	(two	types	of	brain	tumours),	most	participants	indicated	the	highest	levels	of	Information	Seeking.		Responses	for	the	less	serious	conditions,	Bell’s	Palsy	and	Crohn’s	Disease	(a	temporary	form	of	facial	paralysis	and	a	chronic	inflammation	of	the	intestines),	included	a	broader	range	of	responses.		This	distinction	may	suggest	that	some	people	envision	themselves	more	likely	to	seek	greater	amounts	of	information	when	faced	with	more	serious	conditions.		Interestingly,	though,	the	sole	study	participant	claiming	that	s/he	would	completely	avoid	information	had	received	the	most	serious	condition,	Meningioma.		Here,	the	seriousness	of	the	disease	seems	to	have	prompted	an	opposite	effect,	although	for	one	participant	only.			 		 67		 Table	4-5		Likelihood	of	information	seeking	by	disease	scenario,	frequencies	and	percentages	Information	seeking		 Diseases		 Acoustic	neuroma	 Bell’s	palsy	 Crohn’s	disease	 Lupus	 Meningioma	 Overall	1	 0	 0	 0	 0	 1	(2%)	 1	(1%)	2	 0	 2	(5%)	 1	(3%)	 0	 1	(2%)	 4	(2%)	3	 0	 0	 3	(8%)	 2	(5%)	 1	(2%)	 6	(3%)	4	 2	(5%)	 6	(15%)	 1	(3%)	 5	(13%)	 1	(2%)	 15	(8%)	5	 5	(13%)	 8	(20%)	 6	(15%)	 4	(11%)	 1	(2%)	 24	(12%)	6	 32	(82%)	 24	(60%)	 29	(73%)	 27	(71%)	 36	(88%)	 148	(75%)	Total	 39	(100%)	 40	(100%)	 40	(100%)	 38	(100%)	 41	(100%)	 198	(100%)	Table	4-5	Likelihood	of	information	seeking	by	disease	scenario,	frequencies,	and	percentages	Figure	4-1	represents	the	same	data	in	a	chart	format.													Figure	4-1	Information	seeking	and	avoidance	of	participants	by	condition	0	5	10	15	20	25	30	35	40	 1	I	would	avoid	information	about	this	disease.			2	I	would	not	avoid	information	but	would	not	actively	look	for	it.			3	I	would	look	for	a	small	amount	of	information.			4	I	would	look	for	a	moderate	amount	of	information.			5	I	would	look	for	a	great	deal	of	information.			6	I	would	look	for	as	much	information	as	I	could	zind.				 68	To	test	for	a	possible	relationship	between	emotional	state	and	Information	Seeking,	Spearman’s	correlations	were	employed.		For	this	analysis,	I	considered	the	overall	pre-	and	post-	positive	and	negative	PANAS	scores	as	well	as	scores	for	the	individual	emotions	included	in	the	scale.		The	overall	positive	and	negative	affect	scores	were	not	correlated	with	information	seeking.		There	were	weak	positive	correlations	between	three	of	the	PANAS	scale	positive	emotions	and	Information	Seeking:		alertness,	r=.215,	p=.002,	n=197;	attentiveness,	r=.199,	p=.005,	n=194;	and	interest,	r=.188,	p=.008,	n=198.		However,	given	the	large	number	of	tests,	these	would	not	be	considered	significant	using	a	Bonferroni	correction.		No	correlations	with	negative	emotions	were	found.			4.5	 Qualitative	Data		 Two	sets	of	results	were	analyzed	qualitatively:		a	small	set	of	questions	testing	participants’	familiarity	with	the	diseases	in	question	and	a	follow	up	optional	comment	box	after	the	question	regarding	how	likely	they	were	to	seek	information	about	the	condition.		All	participants	answered	the	questions	concerning	familiarity;	79%	or	157	out	of	198	participants	answered	the	optional	question	looking	at	likelihood	of	seeking	information,	with	approximately	30	participants	from	each	condition	responding	to	the	question.		Results	indicate	that	personality,	affect,	and	source	format	were	all	influencing	factors	in	participants’	health	information	behaviour.				Responses	to	the	question	about	disease	perception	represent	some	negative	affective	connotations.		Responses	to	the	question	“what	do	you	think	of	when	you	hear	the	word(s)	____________?”	ranged	from	1	to	49	words,	with	an	average	of	10.49	words	(SD	21.26)	and	a	median	of	7.		Many	comments	signalled	negative	affect.		This	affect	was	due	less	to	worry	about	the	prognosis	of	the	disease	and	more	to	what	participants	appeared	to	believe	or	assume	about	the	condition.		More	participants	connected	words	present	in	the	name	or	description	of	the	conditions	with	severe	diseases.		“Acoustic	neuroma”	and	“meningioma,”	for	example,	were	related	to	cancers	due	to	the	“oma”	sound	in	their	names.		Many	participants	linked	these	conditions	with,	for	example,	“bad	cancer,	often	fatal,”	and,	in	the	case	of	meningioma,	“tumor	of	the	meninges,”	or	“a	deadly	tumor	in	the	lungs	or	heart.”		“Meningioma”	also	drew	associations	with	“meninges”	in	the	brain,	with	“membranes,”	and	with	“meningitis.”		One	participant	noted,	regarding	“meningioma,”	“It's	something	having	to	do	with	membranes.		It	doesn't	sound	too	good.”		Although	the	majority	of	these		 69	connections	appeared	in	conjunction	with	acoustic	neuroma	and	meningioma,	connections	were	present	also	in	the	less	severe	conditions,	as	“Bell’s	palsy”	was	linked	with	“cerebral	palsy.”		“I	think	of	someone	with	shriveled	[sic]	hands	and	pain/difficulty	with	their	joints,”	wrote	a	participant	about	“Bell’s	palsy.”				However,	not	all	connotations	of	the	conditions	inspired	negative	affective	reactions	in	participants.		Other	forms	of	affect,	neutral	and	even	positive,	were	also	present.		Some	participants	drew	conclusions	between	words	in	the	conditions	and	possible	meaning,	inferring	that	the	“acoustic”	in	“acoustic	neuroma”	for	example,	meant	that	the	condition	had	to	do	with	the	ear	or	with	hearing	difficulties.		A	few	participants	also	mentioned	humourous	or	incongruous	connotations,	particularly	in	connection	with	the	less	severe	conditions:		“a	cow	bell”	(BP);	“a	werewolf”	(LP).		Many	wrote	of	links	between	“lupus”	and	a	popular	televised	medical	drama,	“House.”		This	may	have	served	to	mitigate	unpleasant	associations	with	the	disease,	as	one	particular	participant	also	adds,	in	an	incongruous	connotation,	“I	think	of	wolves	and	of	the	show	House.”		It	is	tempting	to	link	these	negative	and	positive	affective	connotations	with	differing	levels	of	information	seeking,	in	that	participants	writing	about	humourous	associations	may	seek	less	information	as	they	might	not	take	the	condition	seriously.		However,	one	participant,	writing	about	meningioma,	also	expressed	a	positive	affective	reaction,	here	curiosity,	which	might	inspire	more	information	seeking:		“That’s	interesting.		I	wonder	what	it	is.”				 Out	of	the	participants	who	took	the	opportunity	to	comment	on	their	Information	Seeking	responses,	16	participants	made	mention	of	some	form	of	information	avoidance,	while	141	indicated	that	they	would	search.		Comments	were	brief,	with	an	average	of	20.24	(SD	10.25),	a	median	of	21,	and	a	range	of	1	to	55	words.		Analysis	of	these	comments	revealed	a	number	of	themes:		information	behaviour	(which	included	information	seeking	and	information	avoidance	as	subcodes);	sources	consulted	(including	healthcare	professionals,	libraries	and	library	staff,	the	Internet,	patients);	and	reasons	for	information	behaviour	(including	negative	affect,	positive	affect,	personality,	duty,	and	improvement	of	doctor-patient	relationship).						 		 Comments	indicated	that	affect	was	a	component	of	the	decision	to	look	for	or	avoid	information.		Both	negative	and	positive	affective	reasons	were	shown.		Fear	was	a		 70	component	of	both	information	seeking	and	information	avoidance,	with	some	participants	saying	that	fear	would	stimulate	their	health	information	seeking	and	others	indicating	that	fear	would	lead	to	avoidance.		One	participant,	for	example,	wrote	of	Bell’s	palsy	that	s/he	would	be	“scared	to	death	and	[would]	want	to	find	something	positive	about	it,”	while	another	wrote	of	lupus	that	s/he	would	be	“scared	and	looking	for	answers.”		Other	participants	indicated	that	information	seeking	needed	to	be	curtailed	to	prevent	fear;	they	viewed	searching	as	an	activity	that	might	lead	to	fear	or	loss	of	control.		Four	participants	with	various	conditions	noted	that	although	they	would	search	for	information,	their	information	searching	would	be	limited,	for	they	didn’t	want	to	make	themselves	“crazy”	or	“consume”	themselves	by	looking	up	too	much.		Several	participants	mentioned	that	they	would	delay	information	seeking	as	they	would	be	initially	frightened,	perhaps	after	diagnosis,	and	in	an	extreme	case,	regarding	meningioma,	one	participant	announced	that	fear	would	prevent	all	information	seeking,	although,	interestingly,	not	fear	of	health	outcomes:				I	would	be	too	scared	to	look	for	information.		Since	I	don't	have	insurance,	I'd	be	stuck	with	some	very	expensive	bills	for	the	next	year	at	least.		I'd	be	very	scared	and	wouldn't	go	looking	for	any	more	information.			Financial	worries,	then,	would	cause	an	added	burden	too	great	for	the	participant	to	handle.					 Some	participants	signalled	that	they	felt	disinterest,	a	form	of	negative	affect	that	would	hinder	information	seeking.		These	participants,	often	those	responding	to	the	milder	condition	Bell’s	palsy,	stated	that	the	condition	was	temporary	or	not	serious	and	thus	required	little	action	on	their	parts.		As	the	problem	was	expected	to	go	away,	these	participants	felt	no	need	to	“delve”	or	“dig	up”	information	about	it.		“Since	it	is	expected	to	go	away,	I	wouldn’t	delve	into	it	a	great	deal,”	explained	one.		For	these	participants,	health	outcomes	were	thus	not	serious	enough	in	this	condition	to	warrant	health	information	seeking	about	it.		Some	participants,	though,	noted	that	interest	or	curiosity	would	stimulate	searching.	“I	would	be	curious	to	know	everything,”	wrote	one	participant	about	Bell’s	palsy.		Another	participant,	also	describing	Bell’s	palsy,	noted	the	lesser	severity	of	this	condition.				 		 71		 It	isn't	a	life-threatening	disorder	and	it	would	go	away	in	a	few	weeks,	thus	I	wouldn't	need	to	dig	up	every	piece	of	information	possible.	But	I	would	be	rather	curious	as	to	what	causes	it	and	what	it	entails,	so	I	would	look	up	some	information.	Here	the	participant	clarified	his/her	lack	of	need	to	search	and	the	curiosity	that	would	partially	overcome	this	information	disinterest.					 Trust	in	medical	authorities	was	also	a	factor	cited	in	participants’	comments.		Some	participants	indicated	that	healthcare	professionals	were	the	primary	health	authority,	and	that	all	information	should	be	checked	with	them,	thus	limiting	outside	information	searching.		“I	would	take	it	with	a	grain	of	salt,”	said	one	participant	of	online	information	about	Bell’s	palsy,	“until	I	could	discuss	further	with	my	doctor.”		A	few	others	stated	that	they	would	allow	their	healthcare	professional	full	responsibility,	trusting	him/her	completely:		one	participant	with	Bell’s	palsy	would	“listen	but	not	look	it	up,”	while	another	with	the	condition	lupus	would	just	turn	to	“trusted	healthcare	professionals.”	Others	mentioned	doctors	but	stated	that	information	seeking	was	an	individual	activity,	happening	independently	from	doctors	and	often	stimulated	by	distrust.		As	an	example,	one	participant	stated	that	s/he	needed	to	find	information	about	acoustic	neuroma,	to	discover	“what	the	doctors	aren’t	telling	me.”					 Some	participants	made	comments	that	indicated	a	sense	of	personal	responsibility	for	their	health	and	their	health	information	searching.		These	participants,	with	varying	conditions,	tended	to	use	the	personal	pronoun	“I”:		“If	I	had	it	I	would	want	to	know	as	much	about	it	as	possible;”	“I	like	to	find	out	for	myself.”		Treatment	for	these	participants	was	in	their	own	hands;	as	one	participant	expressed,	s/he	had	to	“deal”	with	the	condition:			I	always	look	up	any	problem	or	disease	I	have	online	to	find	as	much	information	as	possible	to	be	able	to	deal	with	the	condition	in	the	best	way	possible,	find	alternative	ways	to	deal	with	it,	etc.,	and	find	others	with	the	same	problem.		So	I	would	do	it	in	this	case	too.							 Participants	thus	usually	indicated	affective	reasons	for	their	health	information	behaviour.		Affect	included	both	negative	affect,	such	as	fear,	distrust,	and	disinterest,	and	positive	affect,	such	as	trust	and	curiosity.		Fear	functioned	as	a	hindrance	and	stimulant	to	information	seeking,	while	distrust	in	doctors	worked	to	encourage	and	disinterest	to		 72	discourage	searching	for	health	information.		In	terms	of	positive	affect,	trust	in	doctors	functioned	to	somewhat	limit	participants’	information	seeking,	while	curiosity	was	a	stimulus	to	participants	to	look	for	information.		Participants	also	expressed	beliefs	about	their	responsibilities	with	respect	to	their	health	and	health	information	seeking,	which	influenced	their	information	seeking	and	avoidance	behaviours.				4.6	 Conclusion			 This	chapter	presented	and	examined	the	results	of	the	Affect	and	Avoidance	study,	an	online	survey	that	tested	participants’	responses	to	hypothetical	medical	scenarios	in	light	of	personality	and	affective	characteristics.		Reported	information	seeking	in	this	study	was	very	high,	with	three	quarters	of	participants	claiming	they	would	search	for	the	maximum	amount	of	information	possible.		Reported	instances	of	information	avoidance	were	low	(2.5%).		There	was	some	evidence	to	suggest	that,	when	they	received	the	hypothetical	scenarios	depicting	more	serious	conditions,	participants	may	have	envisioned	seeking	more	information	in	response.		Results	also	indicated	that	affect	may	have	had	an	influence	on	participants’	stated	intent	to	look	for	information;	those	participants	who	felt	more	alert,	attentive,	and	interested	were	also	more	likely	to	claim	they	would	seek	more	information,	although	the	correlations	are	weak.		There	were	no	overall	correlations	between	positive	or	negative	emotional	state	and	likelihood	to	seek	information.		Analysis	of	the	brief	comments	did	identify	both	negative	and	positive	affect	and	personal	responsibility	as	motivations	for	the	health	information	behaviour	claimed	by	participants.		One	limitation	of	this	study	was	that	the	lack	of	variation	in	the	responses	to	the	information-seeking	question	curtailed	the	usefulness	of	this	measure	as	an	outcome	variable.				 Aspects	of	this	study	informed	the	design	and	implementation	of	the	Interview	and	Interaction	study.		The	hypothetical	medical	scenarios	had	a	clear	influence	on	the	emotional	state	of	participants	and	were	used	in	the	second	study.		Changes	in	the	wording	of	the	scenarios	to	create	strong	negative	and	weak	negative	versions,	however,	had	no	apparent	effect;	thus	the	distinction	between	these	versions	was	omitted	from	the	second	study.		Findings	from	this	study	informed	the	interview	guide	employed	in	the	second	study.		For	example,	comments	referencing	participants’	affect	as	well	as	the	findings	regarding	positive	affect	and	its	influence	on	information	seeking	were	influential	in		 73	creating	questions	regarding	how	participants’	emotions	related	to	their	information	seeking.		The	overwhelming	response	regarding	information	seeking,	i.e.	that	the	majority	of	participants	in	the	Affect	and	Avoidance	study	claimed	they	would	seek	the	maximum	amount	of	information,	was	also	useful.		This	response	informed	the	interview	guide	in	that	further	questions	were	asked	regarding	participants’	health	information	seeking	with	relation	to	the	scenarios,	to	verify	this	striking	response.		Results	of	the	second	study	are	presented	in	Chapter	5,	followed	by	a	discussion	of	the	results	of	both	studies.			 		 74	5	 Results	from	the	Interview	and	Interaction	Study		 This	chapter	presents	the	results	of	the	Interview	and	Interaction	study.		This	study	built	on	the	Affect	and	Avoidance	survey,	which	previously	examined	the	influence	of	affect	and	personality	factors	on	participants’	stated	intent	to	seek	health	information	and	tested	the	influence	of	hypothetical	medical	scenarios	on	participants’	emotional	states.		This	Interview	and	Interaction	study	continued	this	work	by	employing	the	same	scenarios	and	asking	participants	to	search	for	information	using	a	customized	online	collection	of	documents.		An	in-depth	interview	on	personal	health	information	seeking	behaviour	followed	the	interactive	session.				The	purpose	of	the	second	study	was	to	triangulate	findings	such	as	the	stated	response	of	most	Affect	and	Avoidance	study	participants	regarding	information	seeking	and	the	influence	of	positive	and	negative	affect	on	information	seeking,	as	well	as	to	provide	more	in-depth	information	about	how	participants	avoided	and	sought	information.		This	study	thus	aided	in	responding	further	to	the	research	questions:			1.	What	factors	contribute	to	information	avoidance?	More	specifically,	to	what	extent	do	personality	traits,	situational	affect,	and	the	nature	of	available	information	sources	influence	information	avoidance?	2.	What	are	the	mechanisms	of	information	avoidance?					I	will	begin	this	chapter	by	portraying	quantitative	and	qualitative	results	from	the	interaction	session	and	from	the	scales.		A	section	presenting	the	themes	resulting	from	the	qualitative	analysis	of	the	interviews	will	follow.			5.1	 Demographic	Data			 	 The	study	sample	consisted	of	35	participants,	of	whom	51%	(n=17)	were	men	and	49%	(n=18)	were	women.		Education	levels	varied,	with	6%	(n=2)	at	or	below	high	school	level;	26%	(n=9)	having	a	college	diploma,	some	college	or	an	associates	degree;	and	68%	(n=23)	holding	an	undergraduate	degree	or	higher.		One	person	chose	not	to	record	their	education.		All	participants	reported	searching	for	health	information.		The	majority	searched	monthly,	24%	(n=8),	a	few	times	per	month,	24%	(n=8),	or	daily,	38%	(n=13).		Other	participants	searched	a	few	times	per	day	9%	(n=3)	or	a	few	times	per	year,	6%		 75	(n=2).		These	amounts	of	searching	are	much	higher	than	those	reported	in	the	Affect	and	Avoidance	study	and	may	indicate	self-selection	for	a	health	information	seeking	study.					 Participants’	age,	general	health	perception,	and	current	health	perception	are	summarized	in	Table	5-1.		Table	5-1		Age,	general	health	perception	and	current	health	perception	of	participants	in	the	Interview	and	Interaction	study	Characteristic	 Category	 Percentage	(number)	Age	 19-29	 11%	(n=4)		 30-39	 20%	(n=7)		 40-49	 11%	(n=4)		 50-59	 37%	(n=13)		 60-69	 11%	(n=4)		 70+	 9%	(n=3)		 	 	General	health	perception	 Poor	 3%	(n=1)		 Fair	 9%	(n=3)		 Good	 34%	(n=12)		 Very	good	 28%	(n=10)		 Excellent	 26%	(n=9)		 	 	Current	health	perception	 Much	worse	than	last	year	 0		 Somewhat	worse	than	last	year	 3%	(n=1)		 About	the	same	 66%	(n=23)		 Somewhat	better	than	last	year	 26%	(n=9)		 Much	better	than	last	year	 6%	(n=2)	Table	5-1	Age,	general	health	perception,	and	current	health	perception	of	participants	in	the	Interview	and	Interaction	study		 In	the	course	of	the	interviews,	many	participants	described	health	conditions	that	prompted	information	searching	or	avoidance.		Please	see	Table	5-2	for	a	list	of	the	conditions	discussed,	which	vary	from	severe	to	mild.		This	table	uses	participants’	own	words;	thus	when	participants	described	themselves	as	“generally	healthy,”	this	is	noted.		Additionally,	conditions	are	listed	as	indicated	by	participants;	thus	Participant	11	has	“HIV,”	while	Participant	20	is	“HIV	positive).							 76	Table	5-2	Health	of	participants		Participant	 Health	Participant	1	 Goitre	Participant	2	 Early	onset	of	deafness	(cured),	hernia	Participant	3	 Thyroid	difficulties;	hysterectomy	when	younger	Participant	4	 Pregnancy	Participant	5	 Itchy	scalp	condition	Participant	6	 Generally	healthy	(deviated	septum)	Participant	7	 Generally	healthy	(cystitis,	potential	for	stroke,	IT	band	issues)	Participant	8	 Benign	tumour	on	finger	Participant	9	 Generally	healthy	(gave	up	sugar)	Participant	10	 Severe	arthritis	Participant	11	 HIV,	drug-induced	schizophrenia	Participant	12	 Heat	stroke	Participant	13	 Generally	healthy	(past	problems	with	concussions	and	tropical	fever)	Participant	14	 Runner’s	knee	(believed	it	to	be	necropsis)	Participant	15	 Arthritis	and	hip	replacement	Participant	16	 Bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis	Participant	17	 Childhood	scoliosis	Participant	18	 Post-Traumatic	Stress	Disorder	and	accompanying	anxiety	and	depression,	learning	disorder	Participant	19	 Generally	healthy	(rash	on	chest,	backaches)	Participant	20	 Generally	healthy	(HIV	positive)	Participant	21	 Chronic	pain	in	stomach,	back		Participant	22	 Generally	healthy	(hypothyroidism)	Participant	23	 Transient	ischemic	attack	(mini-stroke),	depression,	hypertension	Participant	24	 Cardiac	issues	(arrhythmia)		Participant	25	 Genetic	potential	for	diabetes,	overweight	Participant	26	 H	pylori	bacteria	in	stomach	Participant	27	 Detached	retina	(4	times)	and	glaucoma	Participant	28	 Anxiety	and	depression	Participant	29	 Myopic	degeneration	Participant	30	 Generally	healthy	(colonoscopy	with	undiagnosed	digestion	problems;	low	iron;	discoloured	toe)	Participant	31	 Generally	healthy	(vegetarian,	hypothyroidism)	Participant	32	 Food	intolerances	Participant	33	 Post-Traumatic	Stress	Disorder	Participant	34	 Generally	healthy	(lost	tooth	when	younger,	scraped	knee)	Participant	35	 Generally	healthy	(bad	experience	with	tetracycline)	Table	5-2	Health	of	participants		 77	5.2	 Health	Information	Seeking	and	Avoidance			Participants	were	presented	with	a	health	scenario	indicating	that	they	had	just	been	diagnosed	with	a	particular	health	condition	and	were	then	provided	access	to	a	customized	collection	of	documents	relating	to	the	condition	and	asked	to	interact	with	this	collection,	if	they	wished,	for	a	maximum	of	15	minutes.		Measures	from	this	session	thus	include	time	spent	browsing	each	item	of	health	information	material,	time	spent	browsing	the	health	information	material	overall,	and	number	of	items	looked	at	overall.		Difficulty	with	Internet	connections	resulted	in	lower	numbers	of	participants	(see	section	3.5.6.);	thus	this	section	reports	on	data	from	27	participants.				Table	5-3	reports	on	the	measures	in	the	interaction	session.				Table	5-3		Interaction	session	measures		 Mean	 St	Dev	 Median	 Mode	Time	spent	per	item	(mins:	secs)	 1:19	 1:02	 1:35	 N/A	Total	time	spent	 12:06	 5:36	 10:17	 N/A	Number	of	items	 7.23	 3.18	 6.5	 8	Table	5-3	Interaction	session	measures	for	the	Interview	and	Interaction	study	On	average,	participants	spend	10	to	12	minutes	interacting	with	items,	viewing	6	to	8	items	and	spending	a	little	more	than	a	minute	per	item.		As	revealed	by	analysis	of	the	screen-capture	videos	and	of	the	interviews,	participants	followed	several	patterns	in	their	selection	of	materials.		Some	participants	searched	for	health	information	from	patients,	while	others	looked	for	information	they	associated	with	traditional	medical	authorities,	such	as	healthcare	professionals	or	associations.		Many	participants	relied	on	the	genre	groupings	provided	in	the	MedBrowser	interface	to	aid	their	selection.		Some	genres	were	seen	as	indicative	of	patients’	viewpoints	and	others	as	representing	medical	opinions.		The	most	popular	genre	of	material	was	websites,	followed	by	videos,	then	blogs,	and	finally,	news	and	journal	articles;	however,	participants’	comments	noted	that	genres	were	perceived	as	indicative	of	either	patients’	viewpoints	or	traditional	medical	authoritative	viewpoints	and	reacted	to	accordingly.		Blogs,	videos	and	news	stories	were	seen	as	indicating	patients’	viewpoints,	and	were	selected	by	participants	who	wanted	this	type	of		 78	information.		Participants	who	wanted	more	medically	authoritative	knowledge	sought	out	websites,	journals,	and	sometimes	videos.		A	small	number	of	participants	also	linked	to	material	outside	of	the	MedBrowser	site.				Table	5-4	shows	the	number	of	items	of	health	information	material	viewed	and	the	genre	distributions	of	items	for	all	participants.			Table	5-4		Number	of	items	of	health	information	material	viewed	per	genre	category	per	genre	category	per	session		 Mean	 St	Dev	 Median	 Mode	Blogs	 1.81	 0.83	 1.5	 2	Journal	articles	 1.53	 0.74	 1	 1	News	articles	 2.00	 0.71	 2	 2	Videos	 2.06	 1.11	 1.5	 1	Websites	 2.52	 1.21	 2.5	 2	All	genres	 7.11	 3.18	 8	 8	Table	5-4	Number	of	items	of	health	information	material	viewed	per	genre	category	per	session	5.3	 Need	for	Cognition	(NfC),	Threatening	Medical	Situations	Inventory	(TMSI)	and	Positive	and	Negative	Affect	Schedule	(PANAS)		 Participants’	Need	for	Cognition	(NfC),	Monitoring	and	Blunting	coping	styles,	and	situational	affect	in	response	to	a	hypothetical	medical	scenario	and	related	health	information	were	all	measured.		Three	scales	were	used,	the	NfC,	the	Threatening	Medical	Situations	Inventory	(TMSI),	and,	after	participants	read	a	hypothetical	scenario	and	interacted	with	the	health	information	material,	a	Positive	and	Negative	Affect	Schedule	short	form	(PANAS)	(see	Table	5-5).		Descriptive	statistics	are	reported,	as	the	number	of	participants	was	deemed	too	low	for	inferential	statistics;	comments	are	used	to	illustrate	interpretations.		Table	5-5	reports	the	summary	descriptive	statistics	for	the	three	scales	used.				 		 79		Table	5-5		Interview	and	Interaction	study	scales		 Mean	 St	Dev	 Median	 Mode	Need	for	Cognition	 3.88	 6.46	 2.5	 0,7		 	 	 	 	Monitoring	 43.76	 7.29	 48.5	 51	Blunting	 38.18	 7.49	 38	 40,50		 	 	 	 	Positive	affect	 20.06	 6.88	 18.50	 13,15	Negative	affect	 15.76	 7.00	 13.50	 10	Table	5-5	Interview	and	Interaction	study	scales	The	following	sections	examine	these	results	more	closely,	along	with	representative	comments	from	the	participants.			5.3.1		 Need	for	Cognition	(NfC)		The	following	table	shows	NfC	scores	compared	with	the	measures	used	in	the	Interview	and	Interaction	study	(see	Table	5-6).		As	the	scores	were	positively	skewed,	I	divided	the	participants	into	three	equal	groups.		Scores	were	deemed	low,	middle	and	high	according	to	their	place	in	this	scheme,	with	low	scores	ranging	from	-4	to	0,	middle	scores	from	1	to	7,	and	high	scores	from	8	to	21.			Table	5-6		NfC	scores	compared	with	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed			 Time	spent	per	item	 Total	Time	spent	 Number	of	items	viewed		Low	NfC		 2:12	(1:10)	 13:14	(5:55)	 7.22	(3.23)	Middle	NfC		 1:44	(0:53)	 11:33	(4:48)	 7.33	(3.02)	High	NfC			 2:06	(1:04)	 11:20	(3:52)	 6.57	(3.51)	Table	5-6	NfC	scores	compared	with	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed	There	is	no	evidence	that	participants	with	high	NfC	scores	were	more	likely	to	interact	more	fully	with	the	collection	of	health	information	material	given.		The	means	in	this	table	are	quite	similar,	and	the	highest	mean	time	per	item,	and	time	spent	in	total	were	found	in	the	low	NfC	category.		The	analysis	of	participants’	comments	raises	further	doubts	that	a	relationship	between	NfC	and	the	information	behaviour	of	these	participants	exists,	as		 80	well.		Participant	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever)	illustrates	some	of	those	concerns.		This	participant	had	a	high	NfC	score	of	8.		He	believed	strongly	that	he	could	overcome	most	health	problems,	negating	the	need	for	health	information	searching	or	consulting	a	healthcare	professional.		He	described	his	reaction	to	a	potential	concussion:		“If	you’re	knocked	out,	and	you	come	to;	you	get	a	ringing	for	a	few	hours	and	then	you’re	okay	[laughs].		I	do,	and	I	seem	fine.		I’m	a	pretty	healthy	guy…I’m	pretty	in	touch	with	my	body.“				This	participant	did	reveal	that	he	would	seek	some	health	information;	however,	this	information	would	be	more	directed	at	the	experience	of	other	patients,	rather	than	traditionally	medical	information.		He	explained,	“This	is	someone	who’s	gone	through	it,	so	I’m	very	interested	in	their	experience.		And	maybe	some	of	that	is	some	distrust	of	medicine.”			 Trust	was	also	a	factor	in	another	example	of	a	participant	whose	NfC	score	did	not	seem	to	influence	her	health	information	searching.		Participant	21	(chronic	pain	in	stomach,	back)	possessed	a	NfC	score	of	-1	and	indicated	a	strong	desire	to	look	for	health	information.		She	browsed	for	16	minutes	52	seconds,	slightly	longer	than	the	time	allotted	and	looked	at	9	items.		The	following	quotation	also	illustrates	her	stated	desire	to	search:			If	it	was	something	that	I	had	or	someone	in	my	family	had,	I	would	spend	probably	hours	researching:	what	causes	it;	what	different	kinds	of	treatments	there	are;	different	people	who’ve	had	it;	what	they’ve	said	about	it;	what	the	outcome	was.		I	think	that’s	normal.		To	me	it	is.				She	attributed	this	desire	to	search	to	a	lack	of	trust	in	healthcare	professionals,	expressing	her	belief	that	doctors	are	not	trustworthy,	due	to	their	experimental	techniques.		She	spoke	of	people	she	met	who	did	not	search	for	health	information,	pointing	to	what	she	saw	as	their	lack	of	responsibility	and	misplaced	trust	in	healthcare	professionals:			You’re	taking	pills	and	you	don’t	know	what	it	is…Wow,	you	really	trust	doctors	a	lot.		You	have	no	initiative	to	look	after	your	own	health?		I	find	it’s	everybody’s	responsibility	to	do	that.		I’ve	seen	many	doctors	in	my	life	and	doctors	only	do	trial	and	error.					 		 81		5.3.2	 Monitoring	and	Blunting	(Threatening	Medical	Situations	Inventory	or	TMSI)		The	following	tables	show	TMSI	scores	compared	with	the	measures	used	in	the	Interview	and	Interaction	study	(see	Table	5-7,	5-8).		Here	the	scores	are	again	divided	into	three	groups	of	equal	intervals	for	monitoring	and	three	for	blunting.		In	this	grouping,	low	monitoring	and	blunting	scores	range	from	29	to	39,	middle	monitoring	and	blunting	scores	from	40	to	49,	and	high	monitoring	and	blunting	scores	from	50	to	59.						 		 82		Table	5-7		Monitoring	scores	and	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed		 Time	spent	per	item	 Total	Time	spent	 Number	of	items	viewed		Low	Monitoring		(n=6)	 1:36	(0:54)	 10:34	(4:09)	 8.00	(4.30)	Middle	Monitoring		(n=8)	 2:00	(0:58)	 14:21	(4:41)	 8.14	(3.08)	High	Monitoring		(n=13)	 2:05	(0:59)	 11:29	(4:57)	 6.33	(2.82)	Table	5-7	Monitoring	scores	and	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed	Table	5-8		 	 	 	Blunting	scores	and	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed		 Time	spent	per	item	 Total	Time	spent	 Number	of	items	viewed		Low	Blunting	(n=8)	 2:23	(1:13)	 14:25	(4:48)	 7:38	(3.66)	Middle	Blunting	(n=11)	 1:35	(0:40)	 9:15	(3:21)	 6.80	(3.01)	High	Blunting		(n=8)	 1:39	(0:34)	 11:23	(5:24)	 6.20	(2.77)	Table	5-8	Blunting	scores	and	the	time	spent	per	item	of	health	information	material,	the	total	time	spent,	and	the	number	of	items	of	health	information	material	viewed	Some	of	the	monitoring	and	blunting	data	aligns	with	expectations.		High	monitors,	that	is,	those	people	who	are	most	likely	to	concentrate	on	finding	a	solution	to	a	problem	in	a	situation	of	stress,	have	the	highest	mean	time	for	item	score,	as	well	as	a	high	time	spent	overall.		Blunters	in	the	lowest	category,	that	is	those	people	who	are	least	likely	to	concentrate	on	their	emotions	when	in	a	situation	of	stress,	had	the	highest	mean	scores	in	all	categories;	on	average,	they	spent	the	most	time	per	item,	the	most	time	overall,	and	viewed	the	greatest	number	of	items.		High	blunters,	those	people	who	were	most	likely	to	concentrate	on	their	emotions,	viewed	the	lowest	number	of	items	on	average.					 83	This	pattern,	that	of	high	monitors	and	low	blunters	looking	at	more	information,	echoes	that	in	comments	made	by	participants	about	their	health	information	seeking	and	avoidance	behaviours.		Participant	20	(generally	healthy;	HIV	positive)	provides	one	example.		This	participant	had	a	high	Blunting	score	of	50	and	browsed	the	given	health	information	for	a	total	of	7	minutes	33	seconds,	looking	at	5	items	of	health	information.		He	spoke	about	wanting	to	limit	his	health	information	searching:			At	some	point,	my	time	becomes	more	valuable,	and	I	don’t	want	to	just	spend	three	hours	to	learn	two	new	things;	I’ve	had	enough.		A	saturation	point.		[Anything	else]	might	influence	my	interpretation	of	experience	and	not	make	me	worry,	but	it’d	make	me	maybe	blame	the	wrong	thing	for	what	I’m	experiencing.		Here	this	participant	indicated	that	after	a	significant	period	of	time	with	a	chronic	illness,	HIV,	he	had	become	tired	of	searching.		He	explained:		“I	look	a	little	bit.		Initially,	I	did.		[Now]	I	just	plod	along,	and	I	have	no	reason	to	investigate	anything.		I	trust	the	medicines	that	I’m	taking.”				 However,	participant	9’s	(generally	healthy;	gave	up	sugar)	results	show	some	contradictions.		This	participant	also	had	a	high	Blunting	score	of	50;	he	searched	for	a	total	of	9	minutes	20	seconds,	looking	at	a	total	of	13	items	of	health	information.		However,	he	spoke	of	wanting	to	look	for	alternative	health	information	over	medically	authoritative	material.		He	declared	that	the		menu	here	was	insufficient;	I	thought	there’d	be	more	stuff…there	wasn’t	no	shaman;	there	wasn’t	no	witch	doctor…in	my	own	line	of	thinking	there’s	always	more…There’s	a	lot	of	things	that	seem	illogical,	but	then	when	you	look	at	the	real	world	there’s	effects,	E-ffects,	real	world	effects.				Here	the	participant’s	lack	of	trust	of	healthcare	professionals	had	led	to	a	rejection	of	medically	authoritative	information.		He	commented:		I	don’t	believe	anything	the	doctors	say.	I	don’t	think	some	doctors	are	out	to	deliberately	deceive	you.		It’s	just	that	some	of	them	have	bad	datasets.”		Rather	than	depend	on	healthcare	professionals	and	their	potentially	incorrect	knowledge,	the	participant	would	rather	see	a	range	of	health	information;	anything,	he	said,	that	had	an	“effect.”					5.3.3		 Situational	Affect				The	following	tables	show	positive	and	negative	affect	scores	based	on	the	PANAS	scale	compared	with	the	measures	used	in	the	Interview	and	Interaction	study	(see	Table	5-	 84	9,	Table	5-10).		These	scores	are	divided	into	three	groups.		Low	positive	and	negative	affect	scores	range	from	0-10,	middle	scores	from	11	to	19,	and	high	scores	from	20	and	higher.		Table	5-9		Positive	affect	compared	with	time	spent	per	item	of	health	information	material,	total	time	spent,	and	number	of	items	of	health	information	material	viewed		 Time	spent	per	item	 Total	Time	spent	 Number	of	items	viewed		Low	positive	affect		(n=2)	 4:03	(0:55)	 13:53	(4:21)	 3.50	(0.71)	Middle	positive	affect		(n=14)	1:40	(0:42)	 11:44	(4:54)	 7.71	(2.73)	High	positive	affect		(n=11)	 1:59	(0:59)	 12:08	(5:28)	 7.00	(3.56)	Table	5-9	Positive	affect	compared	with	total	time	spent	per	item	of	health	information	material,	total	time	spent,	and	number	of	items	of	health	information	material	viewed		Table	5-10			 	 	 	Negative	affect	compared	with	time	spent	per	item	of	health	information	material,	total	time	spent,	and	number	of	items	of	health	information	material	viewed		 Time	spent	per	item	 Total	Time	spent	 Number	of	items	viewed		Low	negative	affect		(n=8)	 1:48	(1:04)	 12:20	(5:10)	 7.87	(3.52)	Middle	negative	affect		(n=	15)	2:12	(1:09)	 11:31	(6:16)	 5.61	(2.59)	High	negative	affect	(20+)	(n=4)	1:58	(1:02)	 11:56	(4:55)	 7.63	(4.25)	Table	5-10	Negative	affect	compared	with	time	spent	per	item	of	health	information	material,	total	time	spent,	and	number	of	items	of	health	information	material	viewed	Participants	with	low	positive	affect	spent	the	highest	total	time	and	had	the	highest	time	spent	per	item;	however,	these	participants	also	had	the	lowest	number	of	items	viewed.		There	were	no	clear	patterns	relating	to	negative	affect.			 85	The	analysis	of	comments	may	also	shed	some	light	on	how	affect	influences	information	seeking.		Participant	29	(myopic	degeneration),	who	possessed	the	highest	positive	affect	score	(37),	also	held	high	scores	of	5	for	interest,	alertness	and	attentiveness.		Her	comments	indicated	that	interest	functioned	as	a	strong	motivator	for	information	seeking.		She	declared	that	she	sought	information	because	her	interaction	with	her	healthcare	professional	did	not	provide	enough	medical	information.			I’m	far	more	interested	in	all	of	the	angles	of	it	than	my	doctor	has	the	time	to	explain	to	me…	I	should	have	been	a	doctor,	actually,	in	another	lifetime	but	because	I	got	born	in	the	wrong	age,	in	the	wrong	place,	nobody	ever	suggested	it	to	me	or	it	was	never	a	possibility,	but	I’m	really	interested	in	this	stuff.			 However,	the	interviews	also	suggested	other	interpretations	for	the	positive	and	negative	affect	scores.		Participant	28	(anxiety	and	depression),	who	achieved	the	lowest	positive	affect	score	(9)	also	cited	her	numerous	problems	with	depression	and	anxiety.		Participant	8	(benign	tumour	on	finger),	who	scored	a	high	negative	affect	score	(35),	commented	that	his	searching	would	be	limited,	but	that	he	did	seek	out	some	information.		When	given	his	hypothetical	scenario,	this	participant	declared:		“I	would,	first	of	all,	want	to	know	about	the	disease	just	general,	medically	grounded	information.”		Later	he	did	add	that	this	searching	would	not	be	extensive:		“I	don’t	need	to	know	everything.”		He	gave	several	reasons	for	searching,	i.e.,	curiosity,	the	current	health	climate	(an	abundance	of	resources),	and	distrust	of	healthcare	professionals:			I’m	just	curious	by	nature,	and	I	like	to	have	the	best	information.		We’re	in	an	era	of	health	literacy	where	there’s	a	lot	of	resources	out	there.		I’m	hesitant	too,	off	the	bat,	to	talk	to	the	doctor	too	much	about	it	‘cause	I	don’t	know	what	he	knows.					 These	preceding	sections	gave	details	about	the	demographics,	scales	and	interaction	session	measures	from	the	Interview	and	Interaction	study.		Participants	showed	patterns	in	material	selection,	with	some	participants	searching	for	information	from	patients,	while	others	searched	for	information	associated	with	more	traditional	medical	authorities.		There	was	very	little	indication	that	participants’	NfC	scores	had	an	effect	on	health	information	seeking.		With	respect	to	Monitoring	and	Blunting,	there	does	seem	to	be	some	effect,	particularly	at	the	high	and	low	ends	of	the	TMSI	scale.		However,	attitudes	about	health	and	healthcare	systems	also	play	a	role	and	seem	to	confound	these	results.		In	terms	of	affect,	there	is	some	evidence	that	those	participants	with	low	positive	affect	spent	more	time	per	item,	but	it	is	not	clear	whether	this	is	the	result	of	a	general	mood.				 86		5.4	 Themes	Identified	in	the	Interviews				 This	next	section	presents	results	from	the	interview	portion	of	the	Interview	and	Interaction	study.		Data	from	all	35	participants	was	included	in	this	analysis.		As	described	in	Chapter	3,	the	interview	transcripts	underwent	an	extensive	coding	process,	leading	to	the	identification	of	a	number	of	high-level	themes	in	response	to	the	research	questions.		The	full	set	of	codes	is	provided	in	Appendix	G.		I	will	begin	by	examining	two	methods	of	information	avoidance,	self-regulation	and	delegation,	revealed	by	the	analysis	of	participants’	comments.		I	will	then	move	to	the	factors	that	influence	these	behaviours,	again	unveiled	by	the	analysis	of	participants’	comments.		These	factors	consist	of	beliefs	and	attitudes	conveyed	by	participants	about	their	own	health,	the	role	of	healthcare	professionals,	and	health	information	seeking.					 For	clarity,	the	themes	and	sub-themes	presented	in	the	sections	to	follow,	are	summarised	here	in	point	form:						• Self-regulation	• Delegation	o Delegation	to	family	members	o Delegation	to	healthcare	professionals	• Factors	that	influence	information	avoidance	o Belief	in	one’s	health	as	a	personal	responsibility	o Belief	that	one’s	health	is	in	the	hands	of	healthcare	professionals	or	fate	o Belief	in	healthcare	professionals	as	trustworthy	o Belief	in	healthcare	professionals	as	not	trustworthy	o Belief	in	information	seeking	as	a	social	responsibility	o Belief	in	information	seeking	as	not	a	social	responsibility	5.5	 Self-regulation		Twenty-one	participants	described	themselves	as	avoiding	some	information.		This	avoidance	typically	took	the	form	of	self-regulation,	in	which	participants	limited	or		 87	curtailed	looking	at	some	(usually	online)	information.		Codes	associated	with	this	theme	were	the	coding	category	3	Coping,	particularly	code	3A	Managing	emotions,	with	subcodes	3A-A	Avoidance	of	regret,	and	especially	3A-B	Self-regulation,	with	3A-B-a	Preference	for	easy	information.		Code	3B	Planning	and	preparation	also	clarified	details	about	the	opposite	coping	preference	(See	Appendix	G	for	full	codebook).				Participant	33’s	(Post-Traumatic	Stress	Disorder)	comments	were	typical,	in	that	she	applied	“very	specific	parameters…because	you	could	search	forever,	but	then	you	have	to	decide,	alright,	is	it	this?		Is	it	that?		Or	is	it	open	ended?”		Eight	of	these	participants	specifically	stated	that	these	limits	enabled	them	to	avoid	distress.		Participant	33	noted	that	“you	can	see	how,	you	can	dig,	dig,	dig,	dig,	dig	yourself	into	a	hole,”	a	problem	her	limits	are	designed	to	prevent.		Participant	20	(generally	healthy;	HIV	positive)	stated	that	limits	on	his	searching	for	information	about	his	HIV	constituted		a	heavy	dose	of	ignorance	as	a	coping	strategy.		So	when	I’m	told	that	there’s	a	difference	between	viral	load	and	detectability,	I	don’t	really	care.		Are	things	okay?	Yes,	they’re	okay,	and	I	feel	okay,	that’s	great.		 Participants’	comments	pointed	to	the	emotional	stress	resulting	from	interactions	with	health	information,	especially	when	coping	with	actual	health	concerns,	and	emphasized	the	care	that	some	individuals	took	to	balance	out	the	benefits	and	negative	effects	of	exposure	to	this	type	of	information.		When	participants	indicated,	for	instance,	that	they	would	limit	the	amount	of	online	searching,	they	often	gave	as	the	explanation	their	impression	that	too	much	searching	would	result	in	extreme	negative	affective	reactions:		getting	“freaked	out”	(P19	(generally	healthy;	rash	on	chest,	backaches)),	“overwhelm[ed]”	(P13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever),	P27	(detached	retina	(4	times),	glaucoma)),	or	“crazy”	(P23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)),	reaching	the	point	of	confusion	and	“throw[ing]	up”	further	information	(P33	(Post-Traumatic	Stress	Disorder)).		Participant	19	(generally	healthy;	rash	on	chest,	backaches)	spoke	of	the	joys	of	ignorance.			Because	by	the	time	you	read	so	much	medical	stuff,	sometimes	you	get	freaked	out	because	you	have	all	this	conspiracy	theories	that	everything	will	keep	getting	worse	so	sometimes,	the	less	you	read	about	the	fine	prints,	the	better.				 Participants	spoke	of	using	a	number	of	approaches	to	self-regulation.		Participants	limited	the	time	spent	on	searching	or	avoided	certain	types	of	content.		Five	participants		 88	spoke	of	limiting	information	searching	by	time.		Participant	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	specified	that	she	would	do	a	large	amount	of	searching	all	at	once,	“until	I’d	tired	myself	or	upset	myself	enough.”		The	other	four	participants	spoke	about	regulating	the	time	spent	searching,	so	as	to	avoid	this	final	break.		Participants	3	(thyroid	difficulties,	hysterectomy	when	younger),	5	(generally	healthy;	deviated	septum),	and	27	(detached	retina	(4	times),	glaucoma)	declared	that	they	would	do	only	a	small	amount	of	searching	at	one	time.			Participant	31	(generally	healthy;	vegetarian,	hypothyroidism),	more	explicitly,	stated	that	she	would	search	“forty	minutes	at	a	time...I	would	probably	spread	it	out	over	a	week,	and	a	half	an	hour	at	a	time,	and	make	a	few	notes.		Otherwise,	it	would	be	just	too	heavy.”		Three	participants	attributed	this	limited	searching	to	a	need	for	time	away	from	the	computer,	to	process	the	affective	elements	of	health	information.		Participants	3	(thyroid	difficulties,	hysterectomy	when	younger)	and	31	(generally	healthy;	vegetarian,	hypothyroidism)	spoke	of	needing	to	“absorb”	the	information.		Participant	31	explained:		“I	don’t	think	I	learn	or	take	it	in	as	effectively	if	I’m	sitting	there	for	hours.		Breaking	it	down,	partly,	it’s	upsetting,	but	it’s	also,	I	want	to	really	absorb	it	properly.”		Participant	5	(itchy	scalp	condition)	spoke	more	explicitly	about	the	process	of	absorption	and	why	she	chose	to	take	time	between	searching	sessions:			I	know	about	emotional	health…and	how	you	have	to	pace	yourself...I	expect	most	of	this	information	is	gonna	be	negative?	(laughs)		So,	if	I’m	diagnosed	with	the	illness,	I’m	already	feeling	really	blue.		It’s	good	to	get	information…but	then	you	have	to	go	sit	with	it…It	gets	out	of	my	head	and	gets	more	into	my	bones	(laughs).			Seven	participants	also	limited	their	information	searching	by	content.		These	participants	also	cited	the	affective	elements	of	health	information	and	attempted	to	select	that	information	which	was	less	affectively	burdensome.		Participant	11	(HIV,	drug-induced	schizophrenia)	declared	that	he	would	“get	always	the	names	of	the	easy	things.		But	I	will	never	go	into	the	real	thing.		I	will	never	read	the	whole	thing;	maybe	I	will	be	so	afraid.”		Participant	16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis),	too,	reported	that	she	did	not	plan	to	search	for	a	lot	of	information	about	her	recently	diagnosed	kidney	condition;	she	said	she	would	“probably	look	up,	as	well,	but	I	just	don’t	want	to	scare	myself.”		Participant	19	(generally	healthy;	rash	on	chest,	backaches),	too,	asserted,				 89	I	believe	getting	negative	information	can	make	you	to	react	negatively	to	a	situation…If	somebody	said,	if	you	had	Bells	Palsy,	you’re	gonna	die	in	two	months	and	you’ve	had	Bells	Palsy	for	a	month	that	would	freak	you	out…That	would	be	scary.				Participant	24	(cardiac	issues	(arrhythmia))	explained	that	this	need	to	limit	negative	information	might	change	over	time:			I	might	check	out	what’s	gonna	happen…but	maybe	not	my	first	go	around.		I’m	probably	still	in	shock.		Might	be	too	frightening.		I	might	not	be	ready	for	it:		“whoo,	don’t	tell	me	yet;	I’ll	tell	you	when	I’m	ready	to	go	into	that	room.”			Three	of	the	seven	participants	gave	examples	of	information	they	believed	would	cause	negative	affective	information,	commenting	that	this	information	would	usually	take	the	form	of	participants’	stories	found	in	blogs.		Participant	20	(generally	healthy;	HIV	positive)	commented	on	blogs:		“I	don’t	want	that	to	plant	seeds	in	my	mind	about	what	may	or	may	not	go	right	or	wrong….	In	some	ways,	I	stick	my	head	in	the	sand.”		Participant	21	(chronic	pain	in	stomach,	back),	too,	demurred	when	asked	about	blogs,	saying	that	she	would	prefer	not	to	listen	to	“someone	rant	about	how	difficult	it	is…I	think	that	would	make	me	feel	worse…oh,	my	God,	I’m	going	to	be	like	this	for	six	months…and	then	I	would	get	quite	upset.”		Participant	26	(H	pylori	bacteria	in	stomach)	did	not	look	at	information	that	he	felt	might	contain	unpleasant	outcomes	of	his	condition,	bacteria	in	his	stomach.		“‘Cause	there	can	be	a	bad	outcome…you	can	get	stomach	cancer	from	it.		I	knew	that	that	was	one	of	the	outcomes,	and	I	didn’t	want	to	find	out	more	about	it.”				Three	of	the	seven	participants	noted	preferences	for	information	that	would	cause	positive	affective	reactions	over	more	negative	reactions.		Participant	24	(cardiac	issues	(arrhythmia))	stated	that	she	always	ended	a	health	information	search	on	a	positive	note:			I	always	want	to	end	my	time	at	the	golf	course,	after	having	hit	a	really	good	shot;	you	never	leave	when	you’ve	just	duffed	one.		Same	thing	here	–	I	don’t	want	to	leave,	shut	my	computer	with	some	negative	note.					Participant	19	(generally	healthy;	rash	on	chest,	backaches)	and	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee)	gave	further	examples	of	the	benefits	of	health	information	that	generated	positive	affective	reactions.		Participant	19	believed	that	this	positive	information	would	help	patients	to	get	better:		“being	able	to	have	a	positive	view	of	the	problem,	puts	me	in	a	better	situation	to	solve	it.”		Participant	34	commented	that		 90	such	information	would	give	her	a	sense	of	confidence	and	“help	me	engage	in…my	own	health,”	rather	than	information	which	caused	negative	affective	reactions.			The	most	extreme	example	of	avoidance	by	self-regulation	due	to	potential	negative	affective	reactions	was	the	refusal	by	eleven	participants	to	look	at	videos	of	surgeries.		Rather	than	fear,	though,	this	negative	affective	reaction	was	disgust.		“I’m	a	little	squeamish,”	said	Participant	29	(myopic	degeneration).		“I	don’t	like	gore.”		Similarly,	participants	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever),	16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis),	and	33	(Post-Traumatic	Stress	Disorder)	described	surgeries	as	“yucky”	(P13),	“graphic,”	(P16),	and	“gory”	(P33).		Participant	12	(heat	stroke)	spoke	of	a	physical	reaction	to	the	unpleasantness	of	videos:		“I	definitely	wouldn’t	watch	anything	on	Mt	Sinai.		They	got	pictures	of	operations.		And	I’d	throw	up.”		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression),	too,	expressed	disgust:		“The	videos?		I	don’t	want	to	see	photography	of	someone’s	troubled	anus.”	Participant	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	was	in	accord.			I	don’t	know	how	I’d	feel	watching	someone’s	head	being	cut	open	knowing	that	their	heart	is	still	beating;	they’re	still	awake	in	there.		I	don’t	know	if	I’d	really	want,	and	especially	knowing	that	I’d	go	through	that.		Three	participants	did	add	that,	although	they	too	found	the	videos	unpleasant,	they	would	overcome	this	reaction	if	surgery	could	not	be	averted.		Participant	6	(generally	healthy;	deviated	septum)	declared	that	if	he	had	to	get	his	head	operated	on,	and	initial	questions	were	over,	then	“yes,	I’d	probably	be	interested.		Just	to	see	what	would	happen.”		Participants	27	(detached	retina	(4	times),	glaucoma)	agreed,	saying	that	he	would	watch	the	video,	“if	this	is	what’s	going	on	right	now.”				 Participants	22	(generally	healthy;	hypothyroidism),	26	(H	pylori	bacteria	in	stomach),	30	(generally	healthy;	colonoscopy	with	undiagnosed	digestion	problems,	low	iron,	discoloured	toe)	and	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee)	were	also	exceptions,	saying	they	would	watch	the	surgeries.		Participants	26	and	30	seemed	drawn	in	by	the	disgusting	elements.		Although	Participant	26	found	surgeries	“gross”	she	wanted	to	watch:		“It	is	disturbing.		It’s	gross,	but	I	also	wanted	to	see	what	was	happening.”		Participant	30	also	evinced	this	fascination:		“it’s	just	like	carving	a	turkey,”	he		 91	said	of	a	video	depicting	brain	surgery.		Other	participants	indicated	that	this	interest	in	watching	surgical	videos	was	a	common	occurrence	in	their	lives.		Participants	22	and	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee)	said	they	were	not	disgusted.		“I	am	fine	with	it…I	don’t	get	scared	or	have	any	objections	to	it.		I’m	fine	with	looking	at	things	from	a	gross	level.”		Participant	22	explained	that	she	enjoyed	watching	surgeries:		“I	probably	should	really	have	been	a	clinician.”				While	much	of	this	self-regulation	was	due	to	fear,	five	participants	discussed	avoiding	detailed	medical	information	out	of	boredom	or	disinterest.		Four	participants	expressed	preferences	for	Wikipedia,	as	it	is	written	in	“layman’s	terms”	(P15	(arthritis	and	hip	replacement)),	in	a	“basic”	(P19	(generally	healthy;	rash	on	chest,	backaches))	language,	or	in	“English,”	i.e.,	not	as	complex	and	detailed	as	other	more	medical	sites	(P18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder),	P23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)).		Participant	18	declared	that	in	Wikipedia,	there’s	“no	[sic]	too	much	jargon	and	plain	English.”		Participant	19	emphasized	that	in	Wikipedia,	“I’ll	get	the	most	general	information	which	wouldn’t	particularly	be	anybody’s	point	of	view	but	just	try	to	describe	all	the	basic	stuff	about	the	disease	or	the	condition.		The	most	basic	thing.”		Participant	23’s	comments	were	also	typical	here:		“The	other	ones	slow	me	down.		Because	I	don’t	speak	in	six-syllable	words,	and	I	trip	over	drug	names.”		   	Ten	participants	spoke	about	information	that	they	would	avoid	due	to	anticipation	of	boredom.		Eight	of	those	participants	referred	to	journals,	described	as	“dry”	(P5	(itchy	scalp	condition),	P18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression)),	“very	wordy”	(P5	(itchy	scalp	condition)),	“specialized”	(P26	(H	pylori	bacteria	in	stomach)),	“gibberish”	(P23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)),	and	the	opposite	of	plain	language	or	“shit	as	shit”	(P15	(arthritis	and	hip	replacement)).		Participant	5	commented	on	this	notion	of	boredom	to	explain	his	refusal	to	choose	a	journal	article	as	a	health	information	source:		“it’s	too	busy	right	off	the	bat…I’m	thinking,	oh	my	God,…ten	million	pages	of	that.”		“I	think	it’s	very	detailed;"	noted	Participant	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee),	commenting	on	the	avoidance	of	journal	articles	by	others.					I	think	that	people…when	they	read	about	very,	very	long	detailed	information,	they	tend	to	get	lost;	they	can	get	their	self	lost,	and	they	may	not	want	to	go	any	further		 92	reading	for	the	information…When	you’re	given	large	amounts	of	information,	you	tend	to	drift	off.		One	participant	(P7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues))	commented	that	she	was	unable	to	comprehend	the	medical	jargon.	“I	would	probably	get	bored	and	frustrated	with	the	fact	that	I	don’t	understand,”	she	said.		However,	two	participants	spoke	about	how	they	could	understand;	they	were	simply	unwilling	to	do	so.		“While	I	claimed	to	like	thinking	in	the	other	interview,”	said	Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression),	speaking	about	the	Need	for	Cognition	scale,	“that’s	not	the	kind	of	thinking	I	like	to	do.”		Similarly,	Participant	18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder)	said,		 I	do	have	the	academic	background.		I	have	a	degree	so	I	know	you	have	to	depend	on	journal	articles	for	a	paper.		I	don’t	usually	go	for	those	when	it	comes	to	medical	disease	because	it’s	too	dry	[laughs].				Three	participants	also	cited	blogs	as	being	uninteresting	and	causing	boredom.		Blogs	were	described	by	these	participants	as	overly	lengthy	and	detailed:		“flowery”,	“very	wordy,”	(P3	(thyroid	difficulties,	hysterectomy	when	younger)),	written	by	people	who	tend	to	“run	off	at	the	keyboard”	(P23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)),	and	lacking	a	good	writing	style	(P2	(early	onset	of	deafness	(cured),	hernia))	all	of	which	would	cause	participants	to	avoid	this	material.		Participant	3’s	(thyroid	difficulties;	hysterectomy	when	younger)	comments	were	typical	here:		“I	want	to	go	in	there	and	look	around	a	bit	but	if	it	gets	too	flowery	for	me,	then	I	lose	interest.		I	lose	interest	very	quickly	in	things	like	the	blog.”				5.6	 Delegation		 Delegation	was	one	of	the	information	avoidance	mechanisms	that	emerged	from	analysis	of	participants’	comments.		Delegation	was	one	of	the	information	avoidance	mechanisms	that	emerged	from	analysis	of	participants’	comments.		In	delegation,	participants	reported	behaviours	in	which	others	were	allowed	to	act	on	behalf	of	patients,	performing	health	information	seeking	and	other	duties.		Delegates	were	both	family	members	and	healthcare	professionals.				Codes	associated	with	delegation	were	the	coding	category	10C	People	(as		 93	information	source)	and	the	coding	category	8	Social.		With	regards	to	10C,	the	following	subcodes	also	indicated	further	information	about	participants’	opinions	and	ideas	about	people:		10C-A	Doctor-healthcare	professional,	with	further	divisions	into	subcodes	10C-A-a	Doctor	as	authority,	Conversation	with	doctor,	and	Friend	as	authority;	10C-A-b	Problems	with	doctors,	medical	system,	with	divisions	Conflict	between	doctors,	Doctors	have	inadequate	info,	No	life	info,	Not	updated,	and	Doctors	have	suspect	motives.		In	category	8	Social,	subcodes	that	elucidated	participants’	viewpoints	were	8A	Connection	with	others,	8C	Independence,	8D	Maintenance	of	social	norms,	and	especially	8B	Education	of	friends	and	family	(See	Appendix	G	for	full	codebook).			5.6.1		 Delegation	To	and	On	Behalf	of	Family	Members		Eight	participants	noted	that	family	members	are	often	the	delegates	chosen	or	self-appointed	to	seek	health	information	on	behalf	of	others.		In	two	of	those	cases,	the	participants	themselves	delegated;	in	the	rest,	they	acted	as	delegates.		Participants	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	and	11	(HIV,	drug-induced	schizophrenia)	delegated	to	family	members.		The	mother	of	Participant	7	made	appointments:		“I	was	depressed,	essentially	when	I	was	at	home.		So	she	booked	me	in	for	an	appointment.		And	then	she’d	just	come	back	and	tell	me	about	these	appointments.”		Participant	11	said	of	his	ex	partner:			He	was	the	one…I	been	lucky…Very	lucky	to	have	always	somebody	who	knows	more	than	me	or	who	goes	and	do	the	research	for	me	and	say	“look	at	this”	and	I	say	“oh.”		“See?		So	you	have	to	do	this	and	then	do	this.”		And	I	say,	“Okay,	so	I	will	do	it.”				Six	participants	spoke	of	being	the	delegate.		Here	health	information	seeking	could	be	considered	an	extension	of	the	role	of	caregiver	taken	on	by	a	partner,	parent	or	child.			The	caregiving	role	was	illustrated	by	several	examples	given	by	participants.		Participant	6	(generally	healthy;	deviated	septum)	spoke	of	his	mother,	who	was	diagnosed	with	lupus.		She	“didn’t	read	anything	about	it…my	dad	probably	went	with	her	[to	the	doctor]	and	asked	everything.”		Participant	3	(thyroid	difficulties;	hysterectomy	when	younger)	told	of	acting	as	the	delegate	for	her	elderly	mother;	this	participant	searched	for	information	when	her	mother	was	diagnosed	with	breast	cancer.		“My	mom’s	88,	so	she	doesn’t	do	any	of	that…I	do	that	for	her.		Her	medication	and	her	health	care	searching	and	things	like	that.		I	write	letters	to	her	doctor.”		Participant	20	(generally	healthy;	HIV	positive)	searched	for	information	for	his	parents,	“to	inform	myself	in	order	to	educate	them.		And	to	make	sure		 94	that	they	were	asking	the	right	questions.		That	they	were	interpreting	the	information	the	correct	way.”			Four	participants	gave	examples	of	informed	caregivers	who	provided	informational	support	for	ill	people.		Delegation	thus	can	allow	the	ill	person	to	practise	information	avoidance	in	order	to	deal	with	his/her	emotions,	usually	fear.		Participant	6’s	(generally	healthy;	deviated	septum)	father	learned	all	about	his	mother’s	lupus,		because	he	wanted	to	know	everything	he	possibly	could	about	lupus	so	that	he	could	talk	to	the	doctors	and	know	how	to	take	care	of	her.		Whereas,	mom	was	“I’m	gonna	do	what	the	doctor	tells	me,	and	I	don’t	need	to	know”	and	find	out	anything	that	might	scare	me	or	make	me	unhappy.				Participant	5	(itchy	scalp	condition),	too,	searched	for	information	for	her	mother:					I	had	to	do	all	the	research	for	her	about	what	her	options	might	be	and	she	doesn’t	even	want	to	hear	the	word	‘cancer’	said	out	loud.		She’s	an	extreme	case	of	someone	who	believes,	the	more	you	talk	about	it,	the	worse	it’s	gonna	get		--	the	condition.		 Information	given	by	caregivers	was	often	carefully	selected	so	the	recipients	were	better	able	to	manage	it;	this	information	thus	became,	as	Participant	20	(generally	healthy;	HIV	positive)	portrayed	it,	a	“filter	between	the	numbers	and	the	science	and…experience.”		Participant	11	(HIV;	drug-induced	schizophrenia)	spoke	about	reading	only	material	selected	by	his	ex-partner	and	his	friends:		“I	don’t	read	anything	so	most	of	the	time	people	looking	and	saying	look,	read	this.		And	then	I	read	it.”		Similarly	Participant	20	spoke	of	finding	positive	information	for	his	parents,	who	he	described	as	being	overwhelmed	with	depression	over	his	father’s	Parkinson’s	disease.		This	participant	searches	for	information	“that	would	contradict	that	picture.		Because	what	they’re	telling	me	is	pretty	much	a	death	sentence.”		Similarly,	this	participant	searches	for	information	about	his	own	HIV	status	to	give	to	his	parents.		Both	sets	of	information,	this	participant	noted,	were	selected	for	factual	veracity	but	also	to	give	his	parents	hope.		The	participant,	in	choosing	information	about	Parkinson’s,	attempted	to	choose	positive	information;	the	information	he	reported	sending	about	his	own	HIV	status	was	equally	hopeful.		“I’m	gonna	give	them	a	picture	that	is	gonna	fly	in	the	front	of	something	tragic	that	they	may	have	read.”		 	 	Delegation,	participants	explained,	thus	took	place	when	people	were	too	fearful	to	search	or	could	only	search	in	a	limited	fashion;	however,	other	reasons	for	delegation	were	present	as	well.		A	delegate	might,	declared	participants,	have	stepped	into	this	role	because		 95	of	better	information	skills	or	knowledge.		Participants	3	(thyroid	difficulties;	hysterectomy	when	younger),	5	(itchy	scalp	condition),	and	25	(genetic	potential	for	diabetes,	overweight)	both	spoke	of	searching	for	parents	who	are	part	of	a	different,	less	technologically	able	generation.		Participant	25’s	comments	are	representative:			I	feel	like	I	have	more	expertise.		And	I	know	who	to	look	for,	because	they	would	probably	be…looking	at	Wikipedia	and	stuff.		Why	would	you	do	that	if	we	can	do	a	better	search	now	just	through	me?			Here	this	delegation	seemed	less	a	result	with	the	parents’	fear	and	more	to	do	with	the	participants’	own	better	knowledge.		In	some	cases,	this	form	of	delegation	implied	a	lack	of	interest	in	searching	for	health	information.		Participant	25	reported	that	her	parents	are	disinterested	in	learning	how	to	search	for	health	information,	even	in	a	situation	where	they	were	personally	affected.		“There’s	also	social	media	and	my	parents	see	a	lot	of	it	–	let’s	say	Twitter	--	and	then	my	parents	would	say,	‘Oh,	I	saw	this	and	can	you	look	it	up?’”		The	participant	noted	that	she	had	taught	her	parents	how	to	use	Twitter,	at	which	they	were	now	skilled.		Her	parents,	though,	did	not	want	lessons	in	how	to		“look	[things]	up,”	as	their	daughter	could	accomplish	this	task	for	them.			5.6.2	 Delegation	to	Healthcare	Professionals					 Delegates	could	also	be	healthcare	professionals	who	were	in	this	case	allowed	to	perform	all	healthcare	duties	for	the	patient	without	much	patient	input.		Three	participants	told	stories	that	illustrated	this	sort	of	delegation	on	the	part	of	others	to	healthcare	professionals.		Delegation	in	this	format	may	be	likened	to	the	traditional	model	of	medicine;	however,	patients	practising	delegation	to	healthcare	professionals	avoided	searching	for	outside	information	or	refused	information	offered	by	others.		Thus	although	this	delegation	could	represent	deference	to	the	knowledge	and	experience	of	healthcare	professionals,	it	might	also	indicate	information	avoidance	due	to	fear	on	the	part	of	the	ill	person.		Participant	15	(arthritis	and	hip	replacement)	spoke	of	his	brother	who,	when	faced	with	the	prospect	of	bypass	surgery,	followed	medical	guidance	without	question.			“Once	they’d	diagnosed	it,”	said	the	participant	of	his	brother,	“he	found	that	this	was	what	was	needed,	and	he	went	forward	with	it.”		The	parents	of	Participant	20	(generally	healthy;	HIV	positive)	“rely	solely	upon	the	messenger	being	their	primary	physician.”		Participant	2	(early	onset	of	deafness	(cured),	hernia)	spoke	of	his	brother,	who	accepted	treatment	from	healthcare	professionals	for	a	tendon	problem	but	refused	all	other	information.					 96	I	tell	him	there’s	really	easy	exercises	you	can	do	to	get	blood	moving	down	there,	and	he	totally	doesn’t	want	to	hear	about	it.		I	think	he	sees	it	as	a	life	sentence	and	the	doctors	know	best,	and	he’s	going	to	do	what	the	doctor	tells	him	to	do.				Three	participants	explained	that	they	themselves,	like	the	family	members	of	participants	above,	also	rely	on	healthcare	professionals,	usually	general	practitioners	(“doctors”)	and	specialists,	seeking	independently	only	minimally	or	not	at	all.		These	participants	were	more	explicit	about	the	fear	they	felt.		Participant	11	(HIV,	drug-induced	schizophrenia)	spoke	of	being	“guided	a	very	little”	by	the	doctor	during	his	experience	being	treated	for	his	HIV.		Participant	11	said	elsewhere	that	his	experience	with	HIV	was	very	frightening:		“it	was	hard	at	the	beginning;	it	was	just	terrible.		It	was	very	scary.”		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression),	too,	stated	that	for	various	difficulties,	appointments	with	doctors	would	replace	extensive	searching.		Instead,	he	“would	look	but…wouldn’t	spend	days.		It	would	make	me	crazy.”		Participant	16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis)	declared	of	her	as-yet-undiagnosed	kidney	difficulty:		“I	do	have	a	follow-up	with	the	nephrologist	and	I’m	gonna	write	more	questions	(laughs)	to	ask	him,	and	I’ll	probably	look	up,	as	well,	but	I	just	don’t	want	to	scare	myself.”		Her	information	searching,	she	implied,	would	be	limited.	 	This	association	between	this	form	of	delegation	to	healthcare	professionals	and	situations	of	extreme	fear	is	reinforced	by	other	examples	from	participants.		Five	other	participants	spoke	of	similar	delegation	in	reference	to	hypothetical	situations	that	might	generate	fear.		When	given	the	scenario	of	meningioma,	Participant	4	(pregnancy)	declared	that	her	searching	about	this	condition	would	be	limited	only	to	alternative	medicine,	as	she	would	“just	let	the	doctor	do	the	thinking	for	the	medical	side.		‘Cause	I	feel	that	they	have	the	most	knowledge,	and	that	they’re	going	to	give	you	the	best	answer.”		Four	participants	claimed	that	they	would	delegate	information	seeking	if	they	were	faced	with	the	possibility	of	having	surgery.		Participant	20	(HIV	positive)	declared	that	he	would	not	search	for	information	about	surgery:		“I’m	not	concerned	about	the	process	of	surgery…I	just	will	go	with	the	flow.”		Participant	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	talked	of	a	television	program	in	which	young	women	were	shown	breast	implantation	surgeries	in	their	entirety,	so	they	would	understand	what	the	procedure	involved.		The	participant	asserted	that	she	herself	thought,	“ignorance	is	bliss…I	think	I’d		 97	rather	go	in	and	blindly	have	it	done.		Just	entrust	that	whatever	the	doctors	were	doing	was	what	needed	to	be	done.”  Participant	11	(HIV,	drug-induced	schizophrenia)	echoed	this	passivity,	continually	repeating	the	word	“wait:”		“for	me,	if	you	say	I’m	going	to	do	an	operation	right	now,	I	will	just	sit	and	wait.		I	will	not	go	looking;	I	will	just	sit	and	say	I	will	wait.		And	say	I	will	wait.”				Two	participants	told	of	not	contributing	to	their	healthcare	out	of	satisfaction	with	the	healthcare	professional(s)	rather	than	out	of	fear.		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	said	he	did	not	look	for	information	regarding	his	repeated	small	strokes	because	he	trusted	his	doctor	and	specialists.		“The	neurologist	he	referred	me	to,	I	was	comfortable	with.		And	so	once	I	met	him,	I	don’t	think	I’ve	been	back	online	to	look	for	stuff.”		Participant	30	(generally	healthy;	colonoscopy	with	undiagnosed	digestion	problems,	low	iron,	discoloured	toe),	who	had	low	iron,	measured	the	doctor’s	thoroughness	in	considering	all	possibilities	as	to	the	nature	of	the	problem.		This	participant	did	not	look	for	information	outside	of	the	doctor-patient	communication.	“No,	I	didn’t	look	it	up	that	way,	because	I	did	feel	that	the	GP	was	helping	consider	all	the	possibilities,	and	she	was	flummoxed	as	well	(laughs)…I	was	satisfied	with	that.”			Two	participants	also	discussed	times	when	they	felt	their	attendant	healthcare	professional	did	not	display	enough	expertise	or	attention	to	serve	as	the	sole	information	source.		Participant	11	(HIV,	drug-induced	schizophrenia)	spoke	of	a	time	when	he	demanded	more	information	after	his	doctor	commented	on	his	weight	loss.		He	said:			And	if	she	say,	oh,	you’re	okay;	I’ll	get	upset	and	I’ll	say	no,	no,	I	want	you	to	look,	because	you	tell	me	that	I	look	so	skinny…you	told	me	something	and	now	you	have	to	pay	attention;	what	is	the	next	comment,	and	you	have	to	tell	me	what	is	the	next	comment.	  	This	participant	later	received	the	response	he	wanted	from	his	doctor,	her	attention	and	information	as	to	whether	his	weight	gain	plan	had	worked.		Participant	26	(H	pylori	bacteria	in	stomach),	by	contrast,	after	years	of	seeing	his	doctor’s	uncertainty	about	a	digestive	difficulty	the	participant	was	having,	began	to	search	for	alternative	explanations,	albeit	not	online.		“I	was	disappointed	about	the	care	I	was	receiving,	and	then	that’s	why,	at	the	beginning	of	this	year,	I	started	seeing	a	naturopath	as	well.”				 		 98	5.7	 Factors	that	Influenced	Information	Avoidance		Thematic	analysis	of	the	interviews	and	comments	made	while	interacting	with	online	information	identified	a	number	of	factors	that	seem	to	influence	the	decisions	of	participants	to	avoid	or	seek	health	information.			Principal	among	these	factors	were	three	sets	of	beliefs	held	by	participants	in	part	or	in	whole.		The	first	set	of	beliefs	centred	on	health	and	responsibility;	some	participants	felt	that	health	was	their	own	personal	responsibility,	a	belief	that	often	changed	when	conditions	were	more	serious.		Others	expressed	the	belief	that	their	health	was	in	the	hands	of	others,	either	healthcare	professionals	or	fate.		A	second	set	of	beliefs	had	to	do	with	trust	in	healthcare	professionals:	some	participants	reported	feeling	healthcare	professionals	to	be	trustworthy	and	other	participants	reported	the	opposite,	that	healthcare	professionals	lacked	trustworthiness.		Again,	comments	from	participants	clarified	that	this	second	belief	could	be	situation-specific.		A	third	belief	focused	on	the	position	of	health	information	seeking	in	society,	in	which	some	participants	expressed	the	belief	that	health	information	seeking	is	a	social	responsibility	and	that	seeking	made	one	a	good	patient	and	often	a	good	citizen,	while	others	did	not	express	this	belief.						 These	themes	were	associated	with	the	codes	in	category	12	Social	achievements,	with	codes	12D	Information	seeking,	12G	Self-efficacy,	and	12H	Taking	care	of	self	being	associated	with	the	first	belief,	in	health	as	a	personal	responsibility.		The	category	12	Social	achievements	was	also	used	in	connection	with	10C	People	and	10C-A	Doctor-healthcare	professional	to	result	in	the	second	belief,	in	the	trustworthiness	of	healthcare	professionals.		The	third	belief,	in	the	social	responsibility	of	health	information	seeking	was	developed	in	association	with	12	Social	achievements,	particularly	codes	12A	Abuse	of	system,	12C	Gender,	and	12D	Information	seeking	(see	Appendix	G	for	the	full	codebook).			5.8	 Belief	in	One’s	Health	as	a	Personal	Responsibility				 Twelve	participants	made	statements	indicating	they	saw	their	health	as	a	personal	responsibility,	in	which	they	themselves	were	responsible,	at	least	in	part,	for	maintaining	their	own	health.		These	participants	often	reported	performing	various	health	tasks,	including	exercising	and	eating	healthily,	tasks	that	eliminated	or	reduced	to	many	the	need	for	health	information	seeking.			 99		Ten	participants	talked	of	their	“preventative”	(P8	(benign	tumour	on	finger))	lifestyles,	designed,	at	least	in	part,	to	ensure	their	health.		These	participants	talked	of	exercising	(P8,	P20	(generally	healthy;	HIV	positive),	P27	(detached	retina	(4	times),	glaucoma),	P29	(myopic	degeneration),	P31	(generally	healthy;	vegetarian,	hypothyroidism),	P33	(Post-Traumatic	Stress	Disorder),	P34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee),	P35	(generally	healthy;	bad	experience	with	tetracycline));	eating	healthily	(P19	(generally	healthy;	rash	on	chest,	backaches),	P20,	P35);	and	maintaining	their	emotional	health	by	reducing	their	stress	(P24	(cardiac	issues	(arrhythmia),	P35),	staying	confident	(P19)	and	positive	(P19,	P20),	and	by	building	and	maintaining	social	networks	(P19,	P20,	P35).		Participant	20’s	comments	are	representative:			I	go	the	gym;	I	eat	perfectly	well;	I	maintain	an	optimistic	attitude;	I	have	a	strong	work	ethic;	I	keep	myself	busy;	I	keep	myself	socially	active.		I	know	I’m	a	little	bit	reckless	but	I	do	wear	a	helmet	(laughs)…I	don’t	do	drugs.		That’s	what	I	do	to	keep	myself	healthy.				Three	of	these	ten	participants	also	searched	for	wellness	information,	here	defined	as	information	about	healthy	lifestyles,	healthy	food,	and	exercise,	as	part	of	their	healthy	behaviours.		Participant	24	(cardiac	issues	(arrhythmia)	was	planning	on	searching	for	information	about	meditation:			“I	must	say	that	what	I	would	like	to	do	more	of	–	and,	once	again,	this	is	just	choice	--	is	find	out	more	about	the	neuroscience	of	meditation.”		Participant	19	(generally	healthy;	rash	on	chest,	backaches),	too,	sought	information:		“I	look	at	a	lot	of	things	online…more	of	how	to	live	a	healthy	life	or	how	to	eat	healthy…I	look	up	things	like	benefits	of	oranges,	strawberries.”		Participant	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee),	too,	searched	for	wellness	information.		“I	do	find	out	things	that	will	help	me	to	better	my	lifestyle...have	better	sleep	or	sometimes	to	decrease	stress	levels…[I]	look	at	websites,	health	websites.”					Seven	participants	gave	comments	that	described	these	activities	as	effortful,	“work”	(P29	(myopic	degeneration),	P30	(generally	healthy;	colonoscopy	with	undiagnosed	digestion	problems,	discoloured	toe)),	an	“effort”	(P8	(benign	tumour	on	finger)),	something	people	“have	to	do”	(P20	(generally	healthy;	HIV	positive)),	linking	these	good	health	behaviours	with	the	concept	of	“healthwork”	(Mykhalovskiy	&	McCoy,	2002).		“I	try	to	work	two	hours	a	day	on	physical	activity,”	said	Participant	29,	while	Participant	30		 100	echoed	this	emphasis	on	“work”:		“I	need	to	work	at	it,	be	vigilant	about	what	I	eat	and	be	somewhat	vigilant	about	exercising.”		Participant	11	(HIV,	drug-induced	schizophrenia)	discussed	his	labour-intensive	attempts	to	gain	weight.		He	spoke	of	the	discomfort	he	feels	from	eating	more.		  I	have	my	goal…And	the	fact	is	that	I’m	eating	more	than	I	can;	there’s	nothing	funny	at	all…I’ve	been	eating	like	crazy,	you	know?		Yeah,	it’s	very	discomforting…I	been	pushing	myself;	I	been	eating	and	eating.		 Two	of	these	seven	participants	referenced	this	notion	of	healthy	activities	as	work	as	they	discussed	their	guilt	over	not	performing	important	health	tasks,	eating	healthy	food	and	exercising.		Participant	25	(genetic	potential	for	diabetes,	overweight)	talked	of	how	her	laziness	stops	her	from	following	health	dictates	she	finds	online.			Interviewer:		So	you	mainly	look	for	yourself	for	nutrition	and	exercise	and	lifestyle.		How	does	that	make	you	feel	when	you	look	for	that	kind	of	stuff?	Participant:		Most	of	the	time,	it	makes	me	feel	like	I	should	really	do	a	better	job	(laughs).		But	then	my	habits	don’t	really	change.		Although,	when	I	do	read	it,	it	makes	me	feel	guilty.			Participant	28	(anxiety	and	depression)	explained	that	she	too	feels	guilty.		“I	gained	fifty	pounds...	I’ve	just	been	kind	of	lazy	to	lose	the	weight	and	to	take	care	of	myself.”		This	idea	of	guilt	implied	a	sense	of	responsibility;	these	participants	conveyed	a	feeling	that	they	were	responsible	for	their	own	health	and	thus	should	be	seeking	health	information.				 Nine	participants	explicitly	linked	this	lifestyle	and	their	healthwork	to	a	prevention	of	illness,	stating	that	their	health	strategies	were	sufficiently	effective	to	overcome	most	(if	not	all)	forthcoming	health	difficulties.		Exercising	and	eating	healthy	were	referred	to	as	being	“proactive”	(P31	(generally	healthy;	vegetarian,	hypothyroidism))	or	“preventative”	(P8	(benign	tumour	on	finger),	P19	(generally	healthy;	rash	on	chest,	backaches),	P29	(myopic	degeneration))	behaviour.		Participant	8’s	comments	were	typical:		“I	have	a	role	to	play	in	my	health	care,	and	that’s	preventative	medicine…if	I	don’t	[exercise],	well,	then,	I’ll	probably	suffer	or	I’ll	have	more	issues.”		Two	of	these	participants	gave	examples	of	the	strategies	they	felt	would	be	particularly	effective	in	preventing	illness.		Participant	33	(Post-Traumatic	Stress	Disorder)	declared	that	healthy	food	was	important:		“I	believe	that	food	is	medicine.”		Participant	35	(generally	healthy;	bad	experience	with	tetracycline)	spoke	of	his	low	risk	lifestyle,	which	he	felt	contributed	to	his	lack	of	illness.				 101	I	don't	put	myself	in	high-risk	behaviour,	like	play	hockey	or	scuba	diving.		Jumping	out	of	the	plane.		My	life	is	just	very	calm	and	stable.		If	you	are	like	this…You	are	not	going	to	be	sick.				Two	participants	went	further	in	reporting	beliefs	that	a	healthy	lifestyle	would	also	restore	health	in	the	case	of	illness	or	in	maintaining	health	during	dangerous	activities.		Participant	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever)	explained:			I’ve	been	through	horrible	tropical	diseases.		Yes.		Paralyzed	in	the	jungle	for	days	with	a	crazy	fever…But	if	you’re	healthy,	if	you’re	a	healthy	person,	the	body	can	heal	itself	a	lot	of	the	time.			Participant	4	(pregnancy)	described	her	belief	that	a	baseline	of	health	would	prevent	dangerous	side	effects	experienced	by	children	after	receiving	vaccinations.		I	read	several	articles	about	why	vaccinations	might	have	an	effect	or	why	certain	people	are	more	susceptible	to	the	side	effects…with	that	information,	I	now	believe	that	you	can	ensure	that	you’re	healthy	enough,	that	the	vaccinations	work	as	they	should.		 Two	participants	reported	their	belief	that	these	good	health	behaviours	allowed	them	to	avoid	not	merely	illness	but	what	they	saw	as	the	emotional	difficulties	of	health	information	searching.		Participant	29	(myopic	degeneration),	although	she	herself	sought	health	information,	advocated	searching	wellness	information	to	friends	of	hers	who	have	experienced	negative	affective	reactions	to	information	regarding	illness.		“My	girlfriend	who’s	really	health	oriented,	the	one	that	freaks	out…maybe	she	shouldn’t	be	looking…she	doesn’t	handle	it	well…I	tell	my	friends,	find	out	as	much	as	you	can	preventatively.”		Participant	19’s	(generally	healthy;	rash	on	chest,	backaches)	comments	also	note	the	link	between	good	health	behaviour	and	an	ability	to	avoid	emotionally	difficult	health	information	seeking.			Because	I	come	from	the	school	of	thought	that	prevention	is	better	than	cure.		So,	I	look	up	how	to	not	fall	sick	so	that	I	don’t	have	to	look	up	how	to	treat	myself.		I	feel	better	that	way	because	then	I	don’t	have	to	worry	about	what	to	do	when	I’m	sick.			 Comments	by	four	participants	indicated	that	their	beliefs	in	health	as	a	personal	responsibility	could	be	situational,	and	that	in	some	cases	information	seeking	was	unnecessary.		Participant	2	(early	onset	of	deafness	(cured),	hernia),	for	example,	felt	that	his	hernia	was	not	serious	enough	to	warrant	much	information	searching:		“I	didn’t	think	it	was	a	serious	enough	problem.		There	wasn’t	recurring	pain.”		Participant	34	(generally		 102	healthy;	lost	tooth	when	younger,	scraped	knee)	spoke	of	a	minor	health	problem	that	she	felt	was	not	serious	enough	to	warrant	any	health	information	searching.			I	fell	and	I	scraped	my	knee,	but	I	was	able	to	handle	it.		I	didn’t	go	looking	for	anything	on	the	website.		I	felt	I	could	treat	this	skin	abrasion	myself.		Putting	an	ice	pack,	and	putting	a	band-aid	on	it,	and	letting	it	sit	for	a	couple	of	days.	Participant	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever),	after	playing	sports	and	having	had	a	“few	whacks,”	felt	that	any	subsequent	concussion,	could	be	easily	overcome.		When	he	experienced	what	he	believed	to	be	another	concussion	when	snowboarding,	he	brushed	it	off,	rather	than	looking	for	information	about	it.			I	lay	there.		I	was	out	for	some	time.		And	there	were	30	people	around	going	oh	my	God,	we	heard	your	head	hit	the	ice	from	the	chairlift.		Yeah,	it	was	pretty	bad,	but	it	was	a	concussion...I	was	with	some	guys.		It	was	party	time	at	the	moment,	so	we	all	went	back	and	[laughs]	drank	some	beers.				Two	participants	spoke	of	how	they	could	get	over	some	conditions,	but	for	more	serious	conditions,	information	would	need	to	be	sought.		“Would	I	Google	a	problem?”	asked	Participant	35	(generally	healthy;	bad	experience	with	tetracycline).		“Depends	on	how	serious	it	is.”		Participant	13	agreed.		“I’m	not	self-destructive.		I	may	be	borderline	reckless,	but	not	if	I	think	it’s	something	that	requires	attention.”						 Some	participants	thus	demonstrated	belief	in	the	idea	of	health	as	a	personal	responsibility,	one	that	they	maintained,	sometimes	with	effort,	by	exercising	and	eating	healthily,	and	at	times	by	researching	wellness.		This	healthwork	was	motivated	in	part	as	a	means	to	avoid	illness	and	other	health	problems,	and,	in	addition,	the	emotionally	difficult	task	of	health	information	seeking.		There	was	some	evidence	to	suggest	that	participants	holding	this	belief	were	more	conscientious	about	staying	healthy	than	they	were	about	dealing	with	health	difficulties,	especially	when	these	problems	were	deemed	“minor.”			5.9	 Belief	that	One’s	Health	is	in	the	Hands	of	Healthcare	Professionals	or	Fate	 	In	contrast	to	these	participants	whose	comments	revealed	a	belief	that	they	were	responsible	for	their	own	health,	there	were	eight	participants	whose	comments	expressed	a	belief	that	their	health	was	in	the	hands	instead	of	healthcare	professionals	(usually	doctors)	or	fate.		Generally,	this	belief	was	associated	with	less	reported	information		 103	seeking,	as	participants,	believing	that	they	themselves	could	do	little	to	help	the	condition,	left	details	of	their	health	to	healthcare	professionals	or	fate.		For	some,	but	not	all	participants,	this	acceptance	and	consequent	lack	of	agency	was	a	result	of	having	a	condition	for	an	extended	period	of	time.			Four	participants	spoke	of	“acceptance”	(P27	(detached	retina	(4	times),	glaucoma))	of	their	condition.		These	participants	expressed	the	belief	that	their	own	actions	were	useless	in	the	face	of	health	conditions,	leading	to	a	need	for	this	acceptance.		“Nothing	I	can	do	to	change	it,”	as	Participant	27	said	of	his	glaucoma.		Participant	16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis),	similarly,	spoke	about	a	problem	with	her	kidneys	that	she	attributed	to	prolonged	use	of	lithium,	which	she	felt	she	needed	to	treat	her	bipolar	disorder.		I	can’t	change	the	lithium	aspect…there’s	nothing	I	can	do;	I’ve	just	got	to	accept	it	…It’s	just	that	it	happens	that	the	medication	that	benefits	us,	also	causes	these	bad	side	effects…staying	well	comes	with	side	effects.		Anyway,	nothing	I	can	do	(laughs).	Participant	32	(food	intolerances)	said	of	the	hypothetical	scenario	she	was	presented	with,	“If	I’m	close	to	dying,	then	there’s	not	much	I	can	do	(laughs).”		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	felt	that	his	conditions	were	attributable	to	a	lack	of	care	when	he	was	younger,	which	he	could	not	change.  “When	you	get	old,	you	get	old,”	he	said.		“And	if	you	don’t	live	well	when	you’re	not	old,	it’s	there.”		As	a	contrast,	Participant	15	(arthritis	and	hip	replacement),	whose	rheumatologist	suggested	a	similar	cause	for	the	participant’s	illnesses,	reacted	not	with	acceptance	but	with	anger.		“He	said,	‘You’ve	had	an	alternative	life,’	and…‘Now	you’ve	got	to	pay.’		I	felt	he	was	ignoring	my	pain,	why	I	had	come	to	him.”				Acceptance	seemed	thus	to	signify	that	participants	felt	less	self-efficacy	and	ability	to	change	their	health	conditions	with	the	result	that	they	reported	engaging	in	less	information	seeking	about	these	conditions.		“I	just	have	to	take	my	drops,”	said	Participant	27	(detached	retina	(4	times),	glaucoma)	of	his	eye	condition.		“Once	in	a	while	I	might,	if	I’m	looking	at	something	else	and	if	I	hear	–	see	something	about	glaucoma…I’ll	give	it	attention,	but	generally	not.”		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	spoke	of	stopping	information	seeking.		“I’d	been	poking	at	my	depression,	or	having	it	poked	at	by	other	people,	for	a	long	time.		This	is	what	it	is;	this	is		 104	what	I	got.		This	is	what’s	got	me.”		For	participants	23	and	32	(food	intolerances),	information	seeking	was	associated	with	searching	for	a	cure;	as	they	believed	their	illnesses	did	not	have	cures,	they	did	not	search.		“Given	up?”	asked	Participant	23.		“Sure…I	think	there’s	a	lot	of	myth	in	the	word	‘cure.’		For	some	things	there	aren’t	any.”		Participant	32,	too,	associated	information	seeking	with	finding	a	cure,	something	that	she	did	not	believe	was	possible	for	her	condition.			Interviewer:		I	was	interested	in	how	you	did	not	look	for	medical	information	for	your	food	intolerances.		Participant:		How	to	cure	it?		I	didn’t	really	believe	there	was	a	way	to	cure	it.		‘Cause	I	was	always	told	you	just	don’t	eat	the	type	of	food.			Comments	by	two	participants	indicated	that	this	type	of	acceptance	and	lack	of	information	seeking	for	one	condition	might	translate	into	similar	behaviours	for	other	conditions.		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	indicated	that,	because	he	had	been	afflicted	with	his	chronic	condition,	depression,	for	a	long	period	of	time,	he	might	seek	less	information	for	other	such	conditions.		After	receiving	a	hypothetical	scenario	about	Crohn’s	disease,	this	participant	said	of	the	condition,		I	figure	Medline	and	even	the	MedScape	that	I	gave	up	scrolling	through;	they	talked	about…a	disease	for	which	there	is	no	cure	and	not	much	treatment.		It’s	not	debilitating…I’ll	get	on	with	things…They	call	them	chronic	conditions	for	a	reason.		  Here	“getting	on	with	things”	meant	not	searching	for	information	to	change	the	condition.		Similarly,	Participant	16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis),	already	diagnosed	with	bipolar	disorder,	spoke	of	her	osteoporosis,	for	which	she	did	not	seek	a	great	deal	of	information:			Did	I	look	it	up	much?		I	didn’t	really	go	to	a	lot	of	extent	looking	it	up…I	think	I’ve	got	information	but	I	don’t	remember	really	researching	about	it	extensively,	actually.		It’s	just	something	I	got—yet	another	thing	(laughs).				 For	six	participants,	this	acceptance	and	consequent	lack	of	agency	was	a	result	of	having	a	condition	for	an	extended	period	of	time.			These	participants	spoke	of	a	change	in	their	searching;	initially	they	had	searched	for	information,	but	over	time,	this	searching	had	ceased.		Participant	16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis),	in	a	typical	comment,	contrasted	an	initial	searching	period	with	her	current	lack	of	information	seeking.		“Definitely,”	she	said,	“I	looked	it	up	a	lot	in	the	beginning.		I	don’t	look	at	it	much	now,	actually,	with	my	medication	or	my	bipolar	disorders.”		As	a		 105	contrast,	Participant	31	(generally	healthy;	vegetarian,	hypothyroidism),	whose	own	thyroid	condition	had	been	diagnosed	much	more	recently,	was	actively	engaged	in	information	searching.		“This	is	what	I’m	gonna	prescribe	to	you.”		And	that	was	it,	and	I	said,	“Well,	is	there	anything	else	I	can	do,	or	do	you	know	why	I	got	it?”,	and	she	said,	“I	have	no	idea”…I	was	extremely	disappointed.		So,	since	then	I	have	gone	online	to	find	out	how	I	can	better	support	my	thyroid	to	be	healthier.			While	self-efficacy	or	agency	seemed	to	play	a	major	role	in	the	drive	to	seek	or	avoid	health	information,	other	factors	were	also	involved.		Information	seeking	was	mentioned	as	taking	place	in	one	instance	unrelated	to	agency,	when	inspired	by	curiosity	or	“fun”	(P16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis)).		Eight	participants	who	looked	at	some	information	in	the	interaction	session	gave	as	the	reason	curiosity	or	interest.		During	his	interaction	session,	Participant	35	(generally	healthy;	bad	experience	with	tetracycline)	spoke	of	a	general	interest	in	all	health	material	present	on	the	site:				Interviewer:		The	information	you	looked	at;	you	looked	at	lots;	you	looked	at	blogs;	you	looked	at	news;	you	looked	at	websites.			Participant:		I	don’t	want	to	miss	any	interesting	thing.				Participants	2	(early	onset	of	deafness	(cured),	hernia),	4	(pregnancy),	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever),	21	(chronic	pain	in	stomach,	back),	22	(generally	healthy;	hypothyroidism),	and	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee)	also	spoke	of	interest.		The	comments	of	Participant	2	are	representative:		“I’d	want	to	know	what	the	bright	side	was.		I’d	be	curious	and	interested.”		Two	other	participants	spoke	of	being	interested	specifically	in	looking	for	aspects	of	a	health	condition	that	they	could	not	change,	either	how	the	problem	could	have	been	prevented	(P16	(bipolar	disorder,	lithium-related	problems	with	kidneys,	osteoporosis)	or	the	“cause”	(P34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee)).		Participant	16	declared	that	she	would	look	for	information	on	how	her	kidney	problem	could	have	been	averted,	despite	the	fact	that	she	felt	she	could	do	nothing,	as	she	already	had	this	problem:						 I	thought,	what	use	could	that	be?		But	I	still	might	look	it	up	(laughs).		Just	for	the	fun	of	it	(laughs).		Just	to	see	what	it	would	say.		They	would	have	said	maybe	regular	testing.		Interest,	fun,	interest.					 106	Similarly,	Participant	34	(generally	healthy;	lost	tooth	when	younger)	searched	for	information	about	the	cause.		“I’m	interested	to	know	what	is	the	major	cause	of	this	–	just	general	interest	–	what	causes	meningioma	on	a	general	level.”			One	striking	example	of	interest	and	information	seeking	came	in	the	comments	of	Participants	5	(itchy	scalp	condition),	22	(generally	healthy;	hypothyroidism),	26	(H	pylori	bacteria	in	stomach),	30	(generally	healthy;	colonoscopy	with	undiagnosed	digestion	problems,	low	iron,	discoloured	toe),	and	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee),	who	served	as	exceptions	to	the	typical	avoidance	of	surgical	videos.		These	participants	stated	their	interest	in	surgeries	as	a	reason	to	watch.	During	the	interaction	session,	Participant	26,	although	she	concurred	with	the	previously	stated	belief	among	the	participants	that	videos	caused	disgust,	admitted	that	videos	were	also	intriguing,	and	her	interest	caused	her	to	continue	watching	longer	than	other	participants.		Her	comments	are	also	representative	of	many	participants.		“I	find	it	interesting…I	was	intrigued	by	it.”		Participant	22	expressed	the	strongest	fascination	with	surgeries,	stating	that	she	was		just	really	interested.		I	should	really	have	been	a	clinician.		When	my	cat	was	having	some	surgery,	me	and	the	veterinarian	were	pushing	heads	‘cause	I	wanted	to	see	what	was	doing…I’m	just	interested;	I	find	it	very	interesting.		I’m	just	interested.		Here	her	repetition	of	the	word	“interested”	emphasizes	the	strength	of	this	affective	reaction	for	this	participant.					5.10	 Belief	in	Healthcare	Professionals	as	Trustworthy			 A	belief	in	healthcare	professionals	as	trustworthy	also	influenced	participants’	reported	amounts	of	information	seeking.		This	suggested	trust	was	associated	with	two	factors,	according	to	interpretations	of	participants’	comments:		a	faith	in	traditional	medical	knowledge,	and	a	credence	that	healthcare	professionals	cared,	that	they	were	giving	appropriate	amounts	of	attention	to	participants.		Faith	in	medical	knowledge	seemed	to	be	associated	with	reported	information	seeking,	as	participants	declared	that	they	searched	for	information	that	they	believed	to	be	associated	with	the	trustworthy	medical	profession.		The	credence	in	caring,	on	the	other	hand,	was	linked	to	reported	information	avoidance,	as	participants	testified	that	they	felt	no	need	to	usurp	the	professional’s	role	and	thus	no	need	to	seek	information.			 			 107	Ten	participants	exhibited	faith	in	medical	knowledge,	sometimes	citing	medical	knowledge	as	being	in	some	way	better	or	more	authoritative	than	other	knowledge,	for	example,	their	own	or	that	of	other	laypeople.		Three	of	these	participants	referred	to	face-to-face	information	from	healthcare	professionals.		Participant	24	(cardiac	issues	(arrhythmia))	described	herself	as	amazed	when	asked	her	opinion	about	whether	or	not	she	should	go	on	hormone	replacement:			You	go	to	your	doctor	and	you	talk	about,	‘Well,	should	I	go	on	estrogen	replacement	or	should	I	not?’,	and	they	go,	‘What	do	you	think?’,	and	I	go,	‘Well,	you’re	the	guy	that	knows	what’s	going	on,	and	you’re	asking	me	what	I	should	do’.		Participant	11	(HIV,	drug-induced	schizophrenia)	also	lauded	healthcare	professionals,	specifically	doctors	and	their	knowledge.		“The	doctor	is	the	one	who	knows,”	he	said,	clarifying	that	only	a	doctor	could	diagnose	the	participant’s	schizophrenia.		“It’s	like	somebody	tells	me,	‘are	you	crazy?’	‘Are	you	a	doctor?’	‘No,	I’m	not.’		I	tell	him,	‘You	cannot	diagnose	me.’”		Here	the	participant	contrasts	medical	and	lay	knowledge,	determining	that	from	his	perspective,	medical	knowledge	is	more	authoritative.		Participant	32	(food	intolerances)	commented	that	she	would	like	to	solve	medical	problems	by	herself	but	sees	value	in	going	to	a	healthcare	professional.				 Sometimes	going	there,	it’s	a	reassurance.		‘Cause	then	you	might	doubt	yourself,	and	then	going	there,	it	might	make	it	better…if	I	can	do	it	myself	then	I	probably	would,	but	I	don’t	know	any	medical	stuff.		This	trust	resulted	in	more	reported	instances	of	information	seeking,	as	the	remaining	seven	participants	also	expressed	preference	for	traditional	medical	authority	in	health	information	material	and	indicated	that	they	would	search	these	sites	for	health	information,	as	discussed	above.		Participant	12	(heat	stroke)	compared	the	site	he	chose	with	other,	less	authoritative	sites.				 And	this,	of	course,	looked	official.		Yes	it	did.		Because	it	didn’t	have	any	cutesy	things	like	Jenny’s	Guts	Blog.		This	looked	like	it	had	a	heading	just	like	your	UBC	thing	has	a	heading.		Participant	33	(Post-Traumatic	Stress	Disorder)	noted	that	her	preferred	information	sources	had	some	medical	authority:		“It’s	not	from	a	medical	site,”	she	said	of	a	TED	talk	she	watched,	“but	it	is	a	medical	researcher.		He	is	now	known	as	one	of	the	world’s	foremost	leading	researchers	on	trauma.”		During	the	interaction	session,	Participants	2	(early	onset	of	deafness	(cured),	hernia)	and	12	both	noted	with	approval	that	one	site	was		 108	the	property	of	the	National	Library	of	Medicine:		“Excellent,”	said	Participant	2,	clicking	on	it.		Participant	33	said	while	looking	at	one	site,	“the	Mayo?	That	would	be	good.”				Interestingly,	while	these	seven	participants	cited	the	“source”	(Participant	27	(detached	retina	(4	times),	glaucoma))	or	similar	signifiers	of	the	authority	of	health	material,	only	five	of	them	were	confident	in	their	ability	to	judge	which	sources	were	superior.		Comments	from	Participant	27	were	typical.		Interviewer:		You	thought	that	was	very	authoritative?	Participant:		Yes,	I	thought,	yes.		Because	it	comes	from	academics,	from	respectable	institutions	in	our	society.		I	saw	the	source,	and	the	sources	were	Acoustic	Neuroma	Association,	etc.						Participant	27’s	stress	on	the	academic	nature	of	his	chosen	health	information	material	is	contrasted	with	that	of	Participant	9	(generally	healthy;	gave	up	sugar)	who	cited	a	similar	academic	provenance	for	his	material	but	with	much	less	certainty.						They	seemed	more	academic.	[laughs]…I	was	looking	at	a	variation	of	PubMed…I	didn’t	know	if	these	were	real	or	fake;	I	thought	maybe	they	were	fake	because	I	noticed	a	spelling	error,	right	here.		So	that	threw	me	off	a	bit.				Participant	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	spoke	of	trusting	whether	material	was	medically	authoritative,	but	said	that	this	trust	could	easily	be	unfounded.		You	just	have	to	trust	that	what’s	been	put	onto	this	website…actually	I	can’t	tell.		That’s	really	bad…It’s	just	when	you	look	at	websites	they	can	be	super	professional,	but	anybody	can	learn	how	to	do	Wordpress…When	you	sit	and	think	about	it,	that	you	actually	put	your	trust	and	faith	into	things	when	you	really	have	no	idea.				 Four	participants	contrasted	material	they	believed	to	be	medically	authoritative	with	blogs	and	news	stories	of	celebrities.			Participant	3	(thyroid	difficulties,	hysterectomy	when	younger)	did	not	want	to	see	a	news	story	about	a	celebrity:		“I	don’t	want	to	see…this	guy	on	the	news	from	Pearl	Jam…I’m	just	more	directed	towards	what	I	feel	is	highly	medical	knowledged.”		Participant	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	spoke	about	what	she	saw	as	the	lack	of	authority	of	blogs:			There	are	people	out	there	who	know	nothing.		And	they	write	blogs…to	me	a	blog	is	something	that	I	could	go	off	and	write	one	this	afternoon	about	the	things	I	do	during	my	day.				This	participant	also	spoke	disparagingly	of	a	news	article	detailing	the	experience	of	an	English	journalist:	“Five	years	ago	is	a	long	time	ago,	and	I	have	no	idea	who	Tom	Bible	is.”										 109		 Two	other	participants	agreed,	both	citing	disinterest	in	the	stories	of	patients.		“I	don’t	care	what	somebody	else	did,”	said	Participant	12	(heat	stroke).		“I	couldn’t	care	less	about	this	guy.”		Participant,	20,	too,	was	not	interested	in	patient	stories.		“There	is	stuff	that	I	choose	to	ignore,”	he	said.		“I	don’t	really	know	if	there’s	much	relevant	in	Sheryl	Crow’s	self	report.		I	don’t	really	care,	and	that’s	hearsay.		That’s	anecdotal.”						Three	participants	gave	another	reason	for	trust	of	medical	authority;	they	spoke	of	trusting	individual	healthcare	professionals,	noting	that	they	felt	a	personal	connection	with	their	family	doctors.		“I	feel	she’s	an	ideal	doctor,”	said	Participant	15	(arthritis	and	hip	replacement)	of	the	doctor	who	had	treated	his	arthritis	and	other	conditions.			I	have	a	personal	contact…and	I	have	all	my	questions	ready.		If	I’m	going	for	an	annual	check	up,	I	have	all	of	the	things	that	have	happened	to	me	through	that	the	year	that	I’d	just	like	little	answers	on.				Length	of	time	and	familiarity	with	a	healthcare	professional	were	both	associated	by	patients	with	trust;	Participant	12	(heat	stroke)	and	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	stressed	that	their	relationships	with	their	doctors	were	long-term	and	close	due	to	the	amount	of	time	these	people	had	known	each	other.		Participant	23’s	comment	is	typical:		“I	really	trust	my	GP.	I’ve	known	him	for	25	years.”		As	contrasts,	two	participants	reported	their	dissatisfaction	with	healthcare	professionals,	a	feeling	due	not	to	a	lack	of	skill,	but	to	an	absence	of	this	personal	connection.		Participant	24	(cardiac	issues	(arrhythmia)	commented	that	she	did	not	like	her	current	doctor:		“He’s	very	businesslike…I’m	sure	he’s	fine,	but	I	am	fussy	about	my	medical	people...I’m	just	not	this	inert	person	in	a	plastic	gown.”		This	feeling,	implied	the	participant,	led	to	a	lack	of	trust.			 Relationships	with	individual	doctors	also	related	to	information	seeking.		Two	participants	discussed	how	their	searches	for	information	about	conditions	were	brief,	giving	as	reasons	trust	in	his	healthcare	professionals.		The	following	comments	are	illustrations.		“I	probably	spent	more	than	15	minutes,	but	not	a	long	time.		And	some	of	that	is…I	really	trust	my	GP”	(Participant	23).	“I	put	the	faith	that	the	doctors	would	know	what	they	need…I	trust	the	medicines	that	I’m	taking”	(Participant	20	(generally	healthy;	HIV	positive)).		Seven	participants	searched	for	information	to	prepare	questions	for	their		 110	healthcare	professionals;	this	information	searching	seemed	limited,	as	it	would	always	be	verified	with	a	healthcare	professional.		As	Participant	24	(cardiac	issues	(arrhythmia))	said,	“we’re	doing	this	together,”	a	sentiment	echoed	by	other	participants	(3	(thyroid	difficulties,	hysterectomy	when	younger),	4	(pregnancy),	21	(chronic	pain	in	stomach,	back),	22	(generally	healthy;	hypothyroidism),	29	(myopic	degeneration),	34	(generally	healthy;	lost	tooth	when	younger,	scraped	knee))	who	felt	that	medical	treatment	was	a	joint	process.		Three	participants	spoke	of	searching	for	information	in	order	to	ask	questions	of	the	ultimate	authority,	a	healthcare	professional.	Participant	24	spoke	of	engaging	with	her	doctor:		“I	like	to	engage	with	them…What’s	the	best	way	of	us	handling	this,	and	why?...I	want	to	be	able	to	ask	questions	about	what’s	happening.		What’s	this	and	that?”		Participant	34	spoke	of	joint	work	performed	by	herself	and	the	doctor:			I	think	it’s	both	parts	–	the	doctor	and	yourself.		I	can	work	[with	the]	doctor…Try	to	find	out	ways	myself.		From	that,	then	I	can	talk	with	my	doctor,	with	“This	is	what	I	found.”		It’s	like	a	two-way	situation.		Participant	3	spoke	of	how	she	would	like	a	“part”	of	her	treatment:	I	want	to	have	part	of	the	treatment	plan,	not	under	my	control,	but	I	want	to	be	a	part	of	it	[laughs].		I	just	take	it	from	a	point	of	I’m	here	for	you	to	tell	me	what	it	is	and	take	a	step	towards	what	we’re	going	to	do	about	it.			One	participant	believed	information	seeking	to	be	not	merely	something	she	“want[ed]”	(P24,	P3)	to	do,	but	that	it	was	necessary	in	order	to	achieve	proper	medical	care.			I	think	you	build	a	better	relationship	with	your	doctor	that	way;	I	think	you	get	better	care	if	the	doctor	knows	that	you	are	paying	attention,	and	you’re	not	just	a	talking	head	or	a	walking	body	who	doesn’t	understand	the	reality.	(Participant	33)		5.11	 Belief	in	Healthcare	Professionals	as	Not	Trustworthy		 Thirteen	participants	indicated	a	lack	of	trust	in	healthcare	professionals	or	their	knowledge.		This	lack	of	trust	was	sometimes	due	to	what	participants	viewed	as	a	failure	of	medical	knowledge,	as	two	participants	commented	on	the	lengthy	process	of	tests	and	attempts	to	find	a	diagnosis,	which	led	to	some	loss	of	trust	in	healthcare	professionals.		Participant	21	(chronic	pain	in	stomach,	back)	comments:			There’s	no	epiphany;	this	is	what	you	have…and	now	you	can	take	this	and	this	and	now	you’re	going	to	be	fine…Over	the	course	of	20	years,	I’ve	seen	probably	10	gastro	doctors	and	many	tests	and	x-rays	and	scopes	and	they’ve	never	seen	anything.				 111	Participant	26	(H	pylori	bacteria	in	stomach)	was	in	accord.		“When	I	had	illnesses	that	weren’t	cured	right	away	or	maybe	the	doctor	provided	treatment	that	wasn’t	effective	the	first	time,	it	did	make	me	trust	the	doctor	a	little	bit	less.”		Three	participants	also	criticised	their	treatment	plans	and	diagnoses.		Participant	17	(childhood	scoliosis)	spoke	of	a	time	when	healthcare	professionals	had	advocated	what	he	felt	was	an	unnecessary	treatment,	a	bolt	in	his	spine:				 When	I	was	younger,	doctors	wanted	to	put	in	that	bolt	thingy	to	help	straighten	my	spine.		I	had	to	fight	tooth	and	nail	for	them	not	to	do	that.		I	actually	had	to	get	the	government	on	my	side	to	step	in.		Otherwise	they	were	gonna	do	it...I	did	not	want	that.	Participant	18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder)	and	33	(Post-Traumatic	Stress	Disorder),	both	with	mental	illnesses,	spoke	of	their	healthcare	professionals	as	“out-dated,	old	school”	(P18),	refusing	to	acknowledge	their	health	conditions.		The	following	comments	are	illustrative.		“Mental	health	is	one	of	the	areas	that	you	don’t	really	talk	about.		And	in	family	practice	it’s	almost	like	the	extreme…I	go,	‘I	think	I’m	depressed.’		The	doctor’s	‘no	you’re	not’” (Participant	18).		“Doctors	are	not	necessarily	up	to	speed	in	very	specific	areas,”	added	Participant	33.		“There	are	very	many	old	school	people	out	there	too.”				 Criticisms	of	diagnoses	also	occurred	in	cases	where	the	participant	had	already	self-diagnosed	through	information	seeking.		Two	participants	described	occasions	where	they	were	angry	with	a	healthcare	professional	for	this	reason.		Participant	2	(early	onset	of	deafness	(cured),	hernia)	described	his	annoyance	with	his	family	doctor	upon	receiving	the	diagnosis	of	his	hernia:		“it	was	irritating.		Because	I	had	already	known	for	a	long	time	what	the	problem	was.		And	that	I	was	okay	and	that	I	would	get	better.”		Participant	18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder)	described	her	diagnosis	of	Post-Traumatic	Stress	Disorder	as	a	confirmation	of	her	own	self-diagnosis,	for	which	she	had	to	struggle:			I	went	from	self-informing,	self-diagnose	and	I	took	it	to	the	doctor.		And	then	to	the	point	where	I	think	I’m	PTSD,	because	I	have	all	the	symptoms	of	this,	and	they’re	sceptical	and	well,	okay,	if	you	say	so	I’ll	refer	you	to	a	psychiatrist.		 Six	participants	pointed	to	the	suspect	nature	of	the	motives	of	healthcare	professionals,	commenting	on	how	these	professionals,	usually	doctors,	were	motivated	by	finances	rather	than	a	desire	to	see	people	healthy.		Participants	2	(early	onset	of	deafness		 112	(cured),	hernia)	and	17	(childhood	scoliosis)	talked	of	healthcare	professionals,	here	doctors,	who	advocated	treatments	for	financial	gain.		In	a	typical	example,	Participant	2	criticized	the	treatments	offered	for	his	hypothetical	condition	of	acoustic	neuroma:			Doctors	do	this	all	the	time.		What	are	your	options?		And	do	nothing	is	never	one	of	them.		Just	something	where	they	can	bill	you	for	services	or	a	pharmaceutical	company	can	profit	from	the	procedure	or	whatever	it	is.		Participant	17,	too,	spoke	of	doctors:				Doctors	don’t	always	give	you	the	right	information…There’s	actually	plants	and	foods	that	can	cure	pretty	much	everything,	but	they	won’t	tell	you	that.		They’d	rather	give	you	pills	because	that’s	how	they	make	money.			Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	talked	of	doctors’	reluctance	to	advocate	treatments	given	by	other	healthcare	professionals	such	as	nurses.			They’ve	continuously	fought,	and	continue	to	fight,	nurse	practitioners,	which	would	mean	a	fee	for	service	health	professional	that	costs	less	than	docs…They	have	turf;	I	get	that.		Doesn’t	make	them	bad.		Just	makes	them	human.			 	 This	dearth	of	trust	in	healthcare	professionals	functioned	as	a	rationale	for	seeking	health	information,	for	six	participants.		Two	participants	spoke	of	how	healthcare	professionals	merely	gave	a	diagnosis,	rather	than	discussing	how	participants,	as	complete	individuals,	could	integrate	the	condition	into	their	lives.		Participant	23	(transient	ischemic	attack	(mini-stroke),	hypertension,	depression)	spoke	of	his	goal	in	information	seeking:		“I	need	to	know	how	I’m	going	to	live	with	this…What	I’m	going	to	have	to	do	on	a	day-to-day	basis,	year	by	year	to	live	with	it.		Participant	18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder)	described	her	doctor’s	limited	diagnosis	of	her	learning	disability	and	discussed	how	this	diagnosis	led	her	to	find	other	information	resources.		“It’s	like	okay,	now	I	have	the	diagnosis,	what	do	I	do…	It	was	later	that	I	found	the	school	that	specialized	in	the	learning	disability…versus	here’s	the	label;	have	fun.”		Participant	21	(chronic	pain	in	stomach,	back)	and	26	(H	pylori	bacteria	in	stomach)	stressed	that	their	searching	was	due	to	a	failure	of	the	part	of	healthcare	professionals	to	diagnose	and	treat	health	difficulties	effectively.	Participant	21	declared:				I’ve	been	told	“I	don’t	know	what’s	wrong.”...So,	over	many	many	many	years,	I’ve	learned	that	I	really	need	to	stay	on	top	of	things	and	take	responsibility	for	my	own	health	and	read	about	it.			 113	Participant	26,	too,	points	to	a	lack	of	treatment	as	stimulation	searching	sessions:		“Some	of	the	treatments	that	I’ve	gotten	from	the	doctor,	it	didn’t	work	immediately;	that’s	why	that	spurred	me	to	find	information	from	other	sources	too.”		Negative	assumptions	about	doctors	were	also	motivation	for	searching:		Participant	17	(childhood	scoliosis)	announced:		“I	like	to	find	where	the	doctors	aren’t	telling	people.		Because	I	like	to	tell	the	doctor	to	smarten	up.“		Participant	33	(Post-Traumatic	Stress	Disorder)	pointed	to	her	assumptions	about	problems	in	the	medical	system:		“You	cannot	lie	down	and	roll	over	and	play	dead	just	because	you’ve	got	a	condition…it	helps	everybody	–	yourself,	your	own	doctor,	the	entire	system	–	if	you	can	educate	yourself.”		Here	the	passivity	of	roll[ing]	over	and	play[ing]	dead”	equates	in	the	participant’s	mind	with	not	information	seeking.				 Four	participants	who	expressed	a	lack	of	trust	for	healthcare	professionals	often	searched	for	information	outside	traditional	medicine.		Participants	1	(goitre)	and	2	(early	onset	of	deafness	(cured),	hernia)	preferred	alternative	medicine.		Participant	2’s	comments	are	typical:		“I	would	probably	look	for	holistic	or	alternative	medicine.		I	would	search	on	the	keyword,	and	then	I	would	first	start	with	esoteric	or	alternative	meaning.”		Participant	18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder)	searched	for	information	for	community	resources:		 if	I’ve	a	lung	tumour	or	cancer,	if	I	know	there’s	a	lung	association	locally,	then	I’ll	be	like,	okay,	I’m	done	this.		If	I	really	want	legit	scientific	or	medical	treatment,	I’ll	just	call	the	agency	or	the	support	group.					Participant	33	(Post-Traumatic	Stress	Disorder)	reported	a	preference	for	websites	and	TED	talks	from	researchers	and	trauma	specialists	to	assist	her	in	dealing	with	her	PTSD.					Bigthink.com,	TED,	Brain	Pickings	Weekly,	The	Edge…Some	Bessel	Vanderkolk,	a	five	minute	video,	did	me	a	world	of	good	versus	going	to	the	doctor	who	gives	me	a	very	strong	sleeping	pill.		I	needed	that,	but	I’m	not	getting	the	information	from	him	that	I	am	online,	which	is	putting	pieces	of	the	puzzle	together	for	me.		Seven	participants	were	interested	in	hearing	from	other	patients,	rather	than	searching	for	traditionally	authoritative	medical	information.		Participant	17	(childhood	scoliosis)	described	his	method	of	discovering	patients’	viewpoints:		“Go	sit	in	the	waiting	room	and	talk	to	the	other	patients.		Then	you	can	find	out	if	the	doctor’s	a	pill	pusher,	if	they	ask	questions	or	just	automatically	assume	to	cure	it	this	way.”		Often,	as	discussed	above,	these	participants	looked	at	the	materials	rejected	by	others	as	representing	patients’	viewpoints:		blogs	with	personal	stories	and	news	articles	depicting	patients’	and		 114	celebrities	with	illnesses.		Participant	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever)	wanted	to	look	at	blogs,	explaining,	“It’s	the	people’s	view.		It	empowers	the	patients;	the	physicians,	sometimes	they	have	too	much	power.		So	by	reading	a	lot	of	these	blogs,	I	piece	together	the	picture.”		Participant	18	(Post-Traumatic	Stress	Disorder	with	accompanying	anxiety	and	depression,	learning	disorder)	showed	a	preference	for	news	stories	about	celebrities.		“Sheryl	Crow,	oh,	wow,	someone	public	actually	went	and	spoke	about	it.		So	it	makes	it	more	realistic.”		Participants	27	(detached	retina	(4	times),	glaucoma),	28	(anxiety	and	depression)	and	32	(food	intolerances)	searched	for	information	on	discussion	forums.		Participant	28’s	comments	are	typical	here:		“Other	people	have	it	too,	so	we’re	like	a	group;	we	can	share	all	our	thoughts,	and	then,	we	can	just	share	our	tips.”		For	participant	4	(pregnancy),	this	searching	for	patient	information	was	only	performed	in	select	situations:				 if	it	was	something	different—general—say	weight	loss--I’d	be	more	interested	in	other	peoples	stories	(laughs).		Because…you	can	follow	similar	guidelines	for	your	own	weight	loss	journey	or	pregnancy.			 For	three	participants,	this	lack	of	trust	regarding	healthcare	professionals	and	traditional	medical	information	served	as	a	rationale	for	not	seeking	information	or	even	treatment.		Participant	32	(food	intolerances)	commented:		“Sometimes	I	feel	like	what	they	say	is	not	really	useful…I	felt	like	I	just	wasted	my	time.”		Participant	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever)	agreed,	speaking	of	a	concussion	he	believed	he	had:						It	was	pretty	bad,	but	it	was	a	concussion…I	just	figured	what	are	they	going	to	do?		Tell	me	to	rest?		So	I	just	rested.		That’s	what	I	imagined;	I	don’t	think	they	can	really	do	much	for	a	concussion;	I	don’t	know	if	there’s	treatment.		Participant	9	(generally	healthy;	gave	up	sugar)	was	also	in	accord.		“I	don’t	think	health	practitioners	are	the	go-to	authorities	anymore.		Just	because	they	have	the	authority	doesn’t	mean	they	have	the	right	answer.”			5.12	 Belief	in	Information	Seeking	as	a	Societal	Responsibility			 Evidence	from	the	interviews	suggested	that	participants’	perceptions	of	the	social	value	of	health	information	seeking	played	a	role	in	their	seeking	and	avoidance	behaviour.	Some	comments	indicated	views	by	participants	of	health	information	seeking	as	a	societal	responsibility,	noting	their	skills	at	performing	this	task	and	indicating	the	problems	that		 115	arrive	when	people	do	not	search.		Other	comments	pointed	to	the	understanding	of	patients	that	health	information	seeking	could	cause	difficulties	with	the	medical	system	and	with	people’s	emotions.		Both	of	these	viewpoints	seemed	to	influence	reported	information	seeking	behaviour.				 Inherent	in	the	comments	of	twelve	participants	was	the	belief	that	health	information	seeking	has	social	value.		Two	participants	indicated	that	they	do	not	blindly	follow	the	dictates	of	the	doctor	but	perform	their	own	searches.		Participant	20’s	(generally	healthy;	HIV	positive)	comments	here	are	typical:		“I’m	gonna	take	control	of	my	own	health;	I’m	going	to	do	my	own	research,	and	not	just	swallow	pills	that	people	tell	me	to	swallow…keeping	myself	informed	is	a	healthy	way	to	be	that	will	lead	to	a	better	health	outcome.”		Participant	3	(thyroid	difficulties;	hysterectomy	when	younger)	likened	healthcare	to	a	consumer	environment	with	a	buyer	beware	mentality:	It’s	just	like	going	to	a	used	car	salesman;	if	you	don’t	know…the	market	price	of	the	vehicle	you’re	going	to	be	purchasing,	you	can	be	blindsided…	health	care	these	days	…you’re	not	just	relying	on	the	doctor.		I	think	you	have	to	have	your	own	information	to	make	the	choices	you	have	to	make.			One	participant	elaborated	that	information	seeking	was	necessary	in	the	current	medical	system.		Participant	33	(Post-Traumatic	Stress	Disorder)	commented:		“I	think	we	have	to	be	our	own	advocates...Because	you	cannot	count	on	getting	the	help	that	you	need	in	the	medical	system.”			 This	belief	appeared	to	be	linked	to	a	sense	of	pride,	a	sense	that	these	participants	were	in	a	better	situation	than	others	who	did	not	practise	this	behaviour.		Participant	13’s	(generally	healthy;	past	problems	with	concussions	and	tropical	fever)	comments	were	representative:			It’s	more	of	a	preventative	lifestyle	that	if	you’re	healthy;	you’re	active;	you	eat	right;	you	have	a	positive	mental	attitude	that	I	believe,	maybe	naively	so,	gives	you	an	edge	on	people	who	don’t	eat	right,	don’t	exercise,	smoke,	drink	excessively,	abuse	their	body,	and	run	to	the	doctor	when	they	have	any	issue.			Comments	revealed	that,	for	three	participants,	this	belief	seemed	to	be	associated	with	confidence	in	health	information	seeking	skills,	particularly	as	compared	with	others.		Participant	33	(Post-Traumatic	Stress	Disorder)	spoke	of	the	reaction	of	healthcare	professionals	to	her	searching:				 116	They’re	all	quite…surprised	at	what	I	knew	and	what	I	came	in	with.		Versus	I	suspect	they’re	seeing	a	lot	of	people	who	are	not	even	remotely	at	our	capacity	to	research	and	digest	and	understand.		Participant	9	(generally	healthy;	gave	up	sugar),	as	well,	spoke	of	being	an	outlier,	declaring,	“Most	people	would	probably	weigh	more	closely	what	the	healthcare	professional	would	say.”		Participant	20	(generally	healthy;	HIV	positive),	too,	reported	being	“a	different	thinker…very	self-reliant.”		Participant	20	and	33	also	described	various	skills	that	they	felt	led	to	better	health	information	seeking	on	the	Internet:		critical	reading	(P20)	and	scanning	(P33).			Participant	20	reported	that	he	possessed		an	ability	to	look	for	consistency	across	websites,	across	information	sources;	it	gives	me	an	option	to	be	thorough	and	explore	things…to	look	at	abstract,	complex	multi-factorial	contributors…this	gives	me	an	option	to	look	at	the	whole	picture.		Participant	33	also	reported	having	skills:				I’m	very	comfortable	and	very	happy	with	how	quickly	I	can	research…It	makes	a	lot	of	difference.		If	you	are	a	snail	moving	through	the	web,	you’re	screwed.		If	you	are	a	cheetah,	then	you’re	in	much	better	shape.		Three	participants	raised	concerns	about	people	who	did	not	search	for	information,	either	online	or	from	a	healthcare	professional.		Participant	32	(food	intolerances)	spoke	of	not	seeking	information	or	treatment:			I	feel	that’s	not	facing	reality.		If	your	thing	is	severe,	and	you	wait	just	because	you	didn’t	want	to	see	it,	what	if	when	you	go	later	on,	they’ll	be	like,	“You’re	probably	in	stage	two,	and	then	you	could	have	been	a	stage	one,	but	you	didn’t	come	here.”			Participant	5	(itchy	scalp	condition)	spoke	of	her	grandmother,	who	refused	treatment	when	she	had	elephantitis,	to	the	point	of	not	allowing	ambulance	attendants	to	bring	her	to	the	hospital,	a	refusal	to	which	the	participant	attributes	her	grandmother’s	early	demise:		“she	ended	up	dying	really	young,	60	or	61,	because	she	wouldn’t	doctor.”		Participant	21	spoke	of	the	avoidance	of	health	information	and	treatment	by	men.			Men	are	in	denial	about	illness	because	illness	is	a	feminine;	it’s	not	a	masculine	thing...that’s	why	there’s	actually	a	high	rate	of	men	who	are	actually	diagnosed	with	something	and	they	never	seek	treatment	early	enough	and	that’s	why	they	die	from	it.					 		 117		5.13	 Information	Seeking	as	Not	a	Societal	Responsibility		Comments	by	eleven	participants	showed	that	in	some	ways,	information	seeking	was	not	a	societal	responsibility.		Six	participants	expressed	their	opinion	that	information	seeking	could	be	problematic,	resulting	in	personal	problems.		Participant	29	(myopic	degeneration)	spoke	of	the	emotional	danger:			Participant:		[If]	you	look	at	the	operation	–	and	you’re	gonna	be	a	basket	case	before	the	operation,	that’s	really	not	smart.	Interviewer:		So	it	should	be	done…	Participant:		Judiciously.		Depending	who	you	are	and	how	you	handle	information.	(P29)		Participants	3	(thyroid	difficulties;	hysterectomy	when	younger),	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	and	20	(generally	healthy;	HIV	positive)	worried	that	others	would	think	they	would	be	viewed	as	making	big	deals	of	nothing.		Participant	7’s	comments	were	typical:		“I	just	don’t	want	to	be	a	drama	queen	about	it,	really.”		Participant	20	agreed:		“I’m	not	a	catastrophic	thinker	whatsoever.”		Participant	8	(benign	tumour	on	finger),	referring	to	the	health	concern	he	discussed,	a	benign	tumour	on	his	hand	that	resulted	in	a	broken	finger,	said:		 It	just	seemed	a	stupid	incident…insignificant.		You	have	a	broken	bone;	they	want	a	big	story	that	something	exciting	happened	to	you;	you	fell	off	a	cliff…I	couldn’t	provide	anything.				Comments	made	by	five	participants	also	touched	on	problems	with	information	seeking	in	a	societal	context.		Participant	4	(pregnancy)	commented	on	people	who	follow	the	wrong	sources	to	gain	information	for	their	health:		“people	are	listening	to	other	people	as	a	guide,	who	don’t	necessarily	have	any	sort	of	formal	education.”		Participant	13	(generally	healthy;	past	problems	with	concussions	and	tropical	fever)	described	health	care	difficulties:		“I	think	a	lot	of	people	are	so	quick	to	run…	Think	of	the	billions	of	dollars	of	health	care	costs	that	are	spent	on	things	that	are	completely	unnecessary.”		Participant	33	(Post-Traumatic	Stress	Disorder)	agreed:					I’m	thinking	of	people	who	are	jumping	from	doctor	to	doctor	or	trying	to	extend	the	timeframes…and	coming	back,	repeatedly,	very	quickly,	just	because	they’ve	learned	something	new…that’s	what	I’m	thinking	about	in	terms	of	abusing	the	system.			 118	5.14	 Profile	of	Information	Avoiders		 In	this	section,	I	describe	two	study	participants	who	most	fit	the	profile	of	information	avoiders.		Here	I	draw	upon	the	stories,	comments,	and	demographic	information	of	participants	7	(generally	healthy;	cystitis,	potential	for	stroke,	IT	band	issues)	and	11	(HIV,	drug-induced	schizophrenia)	as	a	means	of	illustrating	information	avoidance	patterns.		Participant	7	was	a	woman	in	her	early	thirties	who	perceived	her	health	as	being	very	good	and	the	same	as	last	year.		She	had	a	Need	for	Cognition	(NfC)	score	of	-4,	a	low	Monitoring	score	of	37,	and	a	high	Blunting	score	of	52.		Her	positive	and	negative	affect	scores	were	both	low,	at	10.				Participant	7	reported	having	no	chronic	conditions,	but	she	did	speak	of	her	information	behaviour	with	regards	to	three	health	problems:		cystitis,	iliotibial	band	strain	from	running,	and	a	potential	for	stroke	that	she	believed	could	be	genetic.		She	described	how	she	avoided	information	for	this	last	issue,	avoidance	that	took	the	form	of	not	seeking	information	online	or	going	to	a	doctor	for	tests.		“When	I	think	about	it	now	I	should	go	to	the	doctor…	I’ve	just	mentally	worried	about	it	and	left	it…I	know	that	I	have	issues.		It’s	like	burying	my	head	in	the	sand,	essentially.”		For	this	participant,	information	avoidance	could	also	be	linked	with	negative	affect,	as	she	spoke	of	worry	and	fear	causing	avoidance:		“I’ve	just	mentally	worried”	(italics	mine).		This	participant	saw	genetic	potential	for	stroke	as	a	serious	condition,	one	that	has	killed	members	of	her	family.		She	described	the	death	of	her	aunt	with	whom	she	was	close.		“She	sat	up	to	go	get	some	water,	put	the	glass	back	down,	and	that	was	it.		She	started	screaming	in	pain…I	don’t	even	know	if	she	made	it	to	the	hospital.”		The	participant,	when	asked,	was	unaware	of	any	solution.		“I	just	assume…you’d	have	blood	thinners…but	it	sounds	vile,	doesn’t	it?		I	have	an	arts	degree	so	let’s	be	honest.		I’m	not	a	doctor,	so	I’m	just	using	my	imagination;	it’s	all	just	guesswork.”		 		The	participant	saw	her	avoidance	of	information	and	treatment	as	a	pattern	that	ran	through	her	family,	in	particular	her	grandfather,	who	also	may	have	suffered	from	the	same	condition.		She	commented:			My	granddad	was	horrendous	for	that…I	think	that’s	why	he	ended	up	dying.	…I	think…he	knew	there	was	stuff	wrong.		But	the	only	time	he’d	ever	go	to	the	doctor’s	was	when…people	would	force	him	to	go…	My	granddad	was	a	huge	worrier.  			 119	Instead	of	going	to	the	doctor	or	seeking	information,	her	grandfather	would	take	the	drug	paracetemol,	everyday,	by	the	boxful:		“I	think	it	prevents	worry,”	explained	the	participant.					The	participant	had	her	own	strategy	for	worry	prevention.		She	explained:		“I	know	I	have	issues…I	use	here	or	being	here	[in	Canada],	as	an	excuse	to	bury	my	head.”     The	participant’s	cystitis	elicited	similar	information	behaviour.		When	faced	with	unpleasant	and	embarrassing	symptoms,	this	participant	searched	online	for	possible	diagnoses.		This	searching	resulted	in	extreme	negative	affect,	as	the	participant’s	eye	was	drawn	to	the	diagnosis	“bladder	cancer.”		She	explained:		“I	Googled	it,	and	one	of	the	things	that	came	up	was	bladder	cancer.		[I]	literally	melted	down…I’m	sure	the	word	cystitis	was	in	there	somewhere,	but	my	brain	automatically	goes	to	cancer.”		Another	comment	further	linked	her	negative	affect	with	information	searching:			I	get	myself	worked	up	and	stressed	out	because	the	more	things	I	read	about,	the	more	upset	I	get	about	it,	the	more	I	start	worrying	about	it,	and	that’s	when	I	go	off	into	a	oh	my	God	it’s	drastic.					In	this	case,	the	participant’s	information	searching	ceased,	and	she	remained	in	a	terrified	state	until	her	boyfriend	came	home	and	insisted	she	go	to	the	doctor.		“I	couldn’t	tell	anyone	else	beforehand,	and	I	told	him,	like,	what	I	had	found.		And	he	was	why	haven’t	you	been	to	the	doctor?…I	hoped	it	would	go	away.”		Here	the	negative	affect	felt	by	the	participant	prevented	her	from	seeking	further	information	or	treatment	until	assisted	by	another	person.					 For	the	third	condition	referenced	by	the	participant,	iliotibial	(IT)	band	strain	from	running,	the	participant	searched	a	great	deal,	asking	friends	with	similar	problems	and	browsing	a	Facebook	runner’s	forum.		She	also	sought	multiple	forms	of	treatment:		“I	felt	like	I	needed	to	do	something	to	make	it	go	away.		I’ve	been	to	the	physios,	all	the	usual	whatevers.”		For	this	problem,	information	searching	did	not	seem	to	cause	the	paralyzing	fear	of	bladder	cancer	or	stroke	potential;	the	participant	described	her	exhaustive	search	for	a	remedy:		“For	this	particular	thing,	I’d	be	open	to	anything.”		Here	she	spoke	of	the	negative	affect	not	running	caused:		“When	I’m	not	active;	I’m	not	running,	running	specifically,	craziness.		Bodies	under	the	patio	craziness.		Oh	my	God	it	drives	me	nuts.	I	get	irritable.”		However,	for	this	problem,	this	negative	affect	served	to	drive	the	participant’s	search	for	information,	rather	than	causing	avoidance.		She	commented:				 120	I	have	tried	some	weird	stuff.		Whatever	fixes	me…For	example	my	friend,	she	has	IT	band	issues;	she’s	going	to	this	guy;	he	uses	big	iron	bars	that	have	curves	and	bends	in	them	in	certain	places…I	was	thinking	oh	wow,	is	this	a	thing?		So	I’ve	Googled	it,	and	looked	into	it…it	cost	$65-$100.				Here	it	was	finances,	rather	than	fear,	that	instigated	the	participant’s	hesitation.		Participant	11	was	another	participant	who	reported	practising	some	information	avoidance.		This	participant,	who	was	a	Spanish-speaking	man	of	45	with	a	high	school	education,	perceived	his	health	to	be	very	good	and	about	the	same	as	last	year.		He	achieved	a	high	NfC	score	(11),	a	high	Monitoring	score	of	51,	and	a	middle	Blunting	score	of	49.		After	looking	at	health	information,	he	obtained	a	high	positive	affect	score	of	21	and	a	middle	negative	affect	score	of	16.		During	the	interaction	session,	he	looked	at	a	total	of	3	items	of	information	for	a	total	time	of	11	minutes	29	seconds.						 This	participant	discussed	two	chronic	health	problems,	an	HIV	infection	and	schizophrenia	caused	by	substance	abuse.		For	both	health	difficulties,	the	participant	reported	tending	to	rely	on	other	people	for	information,	whether	friends	or	healthcare	professionals.		He	described	his	typical	information	behaviour:			I	will	ask	to	some	people	first…I	will	ask	the	doctor…but	most	of	the	time	I	have	always	people	guiding	me	to	information.		And	I	don’t	read	anything	so	most	of	the	time	people	looking	and	saying	look,	read	this.		And	then	I	read	it.		And	that’s	how	it	be.				In	the	case	of	HIV,	this	information	behaviour	seemed	to	have	allowed	the	participant	to	concentrate	on	the	negative	affect	brought	upon	by	the	diagnosis.		He	noted:		“I	was	angry	at	the	beginning…Am	I	going	to	look	like	these	people?...If	I’m	going	to	look	like	that,	then	I	don’t	want	to	look	like	that.”		The	participant	described	the	context	of	his	diagnosis,	in	which	fear	was	rampant	in	his	community:			It	was	very	shocking	for	everybody.		But	they	came	out	to	talk.		And	everything	was	very	scared	[sic],	no?		I	didn’t	know	whether	I	was	supposed	to	drink	wine	from	their	glasses	or	not?		I	didn’t	know	anything	and	I	was	very	scared,	and	I	didn’t	want	them	to	get	infected,	no?	This	extreme	negative	affect	caused	some	further	limits	to	the	participant’s	information	searching.		He	remarked	about	online	searching:		“Sometimes	on	the	computer,	this	disease…sometimes	it	scares	me	to	see…	Sometimes	I	just	don’t	want	to	go	in	some	things.		I’m	just	in	denial.		In	denial	about	some	things.”		This	caution	regarding	information		 121	searching	also	related	to	his	questioning	of	the	doctor:		“Sometimes	I	ask	about	this	medication	or	that	medication.		And	things	like	that.		But	not	too	much,	no.”				 One	cause	of	the	participant’s	information	behaviour	appeared	to	be	a	strong	respect	for	medical	authority.		He	stated	his	preference	for	information	from	his	healthcare	professional:		“the	doctor	is	the	one	who	knows.		If	the	doctor	tells	me,	there	is	something	wrong	with	you,	I	do	pay	attention.”		Here	the	participant	seemed	to	feel	as	if	his	health	was	the	doctor’s	responsibility.		He	did	state	that	he	himself	would	have	to	become	more	informed	in	the	following	quote:		“I	know	I	should	do	more.		It’s	one	of	the	goals	that	I’m	trying	to	bring	to	myself,	to	get	more	involved	with	my	health,	to	get	more	informative.”		However,	his	directives	to	the	doctor	were	much	more	forceful.		In	the	following	example, the	participant	demanded	attention	from	his	doctor.		With	regards	to	a	recent	weight	gain,	this	participant	declared:		“You	tell	me	I	look	very	skinny;	okay,	perfect,	you	are	my	doctor.		But	if	in	three	months…	if	you	don’t	look	[sic]	a	change;	you	don’t	see	a	change	then	I’ll	get	upset	and	I’ll	say	I	want	you	to	look	at	it.”						 	When	faced	with	his	schizophrenia,	the	participant	continued	his	policy	of	relying	on	healthcare	professionals.		As	above,	the	participant	emphasized	that	his	doctor	should	help,	as	illustrated	by	the	following	quote,	which	repeated	the	phrase	“do	something.”:		“So	do	something.		I	say	you	do	something.		So	these	are	my	voices,	you	do	something…So	do	something.		He	say,	what	you	want	me	to	do?		I	say,	I	don’t	know.		I	hear	voices.		Do	something.”		In	this	case,	this	respect	for	a	healthcare	professional	appeared	to	have	been	the	driving	force,	as	the	participant’s	schizophrenia	caused	less	negative	affect	than	his	HIV.		He	commented:		“I	have	schizophrenia,	yeah?		I	have	the	psychosis.		Me	better	than	to	get	scared,	I	just	go	to	the	doctor.”		This	lack	of	negative	affect	may	have	been	caused	by	the	more	simple	solution	to	the	schizophrenia:		“Is	it	because	of	the	drugs?		And	I	say	okay,	perfect.		Done.”			 5.15	 Conclusion		 Participants	described	methods	of	information	avoidance,	which	were	grouped	into	two	main	approaches:	self-regulation,	especially	with	respect	to	time	spent	searching	and	avoidance	of	certain	types	of	content,	and	delegation,	either	to	family	members	or	to	healthcare	professionals.		Delegation	was	usually	the	result	of	fear	or	the	need	to	reduce		 122	anxiety	in	the	person	with	the	health	condition	but	was	also	sometimes	due	to	this	person’s	lack	of	skill	or	knowledge.		Sets	of	beliefs	held	by	participants	were	identified	as	factors	that	contribute	to	information	avoidance	and	seeking	patterns.		One	set	of	beliefs	was	focused	on	health,	responsibility,	and	a	sense	of	personal	agency	or	self-efficacy	relating	to	health.		Comments	revealed	that	participants	could	feel	responsibility	for	their	own	health	and	be	confident	in	their	own	ability	to	change	their	health	conditions,	while	others	felt	less	responsibility	and	confidence.		Another	set	of	beliefs	related	to	the	trustworthiness	of	healthcare	professionals,	the	health	system	and	traditional	medicine,	which	varied	considerably	among	the	study	participants.		A	final	set	of	beliefs	related	to	the	societal	value	or	importance	of	health	information	seeking	perceived	by	patients,	which	again,	varied	within	this	group.		These	various	beliefs	were	expressed	by	participants	in	their	stories	of	health	information	seeking	and	avoidance	and	seemed	to	play	a	role	in	shaping	both	those	behaviours	and	participants’	accounts	of	those	behaviours,	but	not	always	in	consistent	ways.					 		 123	6	 Discussion			 This	chapter	will	discuss	the	results	presented	in	the	two	previous	chapters.		I	will	begin	with	a	summary	of	the	results,	and	then	move	to	a	discussion,	commencing	with	the	view	of	information	avoidance	as	informed	by	this	research.		Next,	I	will	move	to	discussing	the	individual	findings,	in	particular	the	responses	to	the	research	questions	regarding	the	mechanisms	of	information	avoidance	and	the	factors	that	influence	this	phenomenon.		I	will	then	move	to	the	implications	of	this	research	for	theory,	method,	and	practice.					6.1	 Summary	of	Results		Information	avoidance	is	a	challenging	topic	to	study.		First	of	several	reasons	is	that	avoidance	can	be,	and	often	is,	construed	as	non-behaviour:		something	that	cannot	be	observed,	an	absence	of	seeking.		It	is	problematic	to	study	what	people	are	not	doing	as	opposed	to	actual	activities,	a	fact	reflected	by	this	research,	in	which	participants	were	questioned	about	their	health	information	seeking	in	order	to	reveal	instances	of	avoidance.		This	fact	raised	the	question	of	the	extent	to	which	not	seeking	is	equivalent	to	avoidance	stemming	from	intention.		A	further	challenge	is	that	overt	information	avoidance	runs	counter	to	current	social	norms	regarding	health	information	seeking,	in	which	this	seeking	is	viewed	as	a	positive	and	desirable	behaviour.		Thus,	people	have	an	incentive	to	over-report	seeking	and	to	conceal	or	minimize	instances	of	avoidance	as	inappropriate	or	shameful,	even	to	deny	to	themselves	that	they	engage	in	these	behaviours.					 	 Results	reflect	these	issues.		Few	participants	admitted	practising	information	avoidance	in	either	a	hypothetical	or	simulated	context.		This	fact	that	participants	failed	to	mention	information	avoidance	was	particularly	striking	in	the	Affect	and	Avoidance	study	(Study	1),	which	asked	if	people	would	search	for	information	in	the	context	of	a	scenario	that	invited	them	to	imagine	themselves	in	an	unpleasant	or	life-threatening	health	situation.		In	this	study,	a	large	majority	of	participants	claimed	they	would	search	for	the	maximum	amount	of	information	possible,	and	very	few	indicated	that	they	would	avoid	information.		By	contrast,	analysis	of	data	from	the	Interview	and	Interaction	study	(Study	2),	in	which	participants	were	given	the	opportunity	to	interact	with	health	information	in	real	time	and	were	interviewed	as	to	their	interactions	and	past	health	information	behaviour,	found	more	evidence	of	information	avoidance,	although	few	participants		 124	characterized	their	behaviour	as	such.		This	difference	was	likely	due	in	part	to	the	methods	of	data	collection	and	the	more	realistic	nature	of	the	second	study.		It	may	have	been	amplified	further	by	the	different	recruitment	strategies	used;	in	the	Affect	and	Avoidance	study,	participants	were	recruited	using	a	crowdsourcing	software,	Amazon	Mechanical	Turk,	while	in	the	Interview	and	Interaction	study,	recruitment	took	place	by	means	of	convenience	sampling,	both	word	of	mouth,	and	virtual	and	print	recruitment	notices.		The	samples	themselves	differed;	Affect	and	Avoidance	study	participants	reported	being	on	average	younger	than	the	Interview	and	Interaction	participants.		This	age	difference	may	be	an	indication	that	Affect	and	Avoidance	study	participants	were	also	healthier,	as	researchers	have	suggested	that	age	can	lead	to	more	health	concerns	(Ahluwalia,	Gross,	Chaudhry,	Ning,	Leo-Summers,	Van	Ness	&	Fried,	2012).		The	convenience	sample	may	have	led	to	self-selection	in	the	Interview	and	Interaction	study	for	participants	who	wished	to	discuss	this	particular	health	behaviour,	as	participants	in	this	study	reported	searching	more	frequently	for	health	information.		The	highest	percentage	of	Affect	and	Avoidance	participants	searched	a	few	times	per	month	(40%,	n=80),	as	compared	with	the	highest	percentage	of	Interview	and	Interaction	participants,	who	searched	daily	(38%,	n=13).		Additionally,	while	the	Affect	and	Avoidance	study	participants	may	have	had	health	concerns,	the	format	of	the	Interview	and	Interaction	study	may	have	led	participants	to	recall	and	think	about	these	concerns	in	more	depth,	leading	to	more	grounded	and	experience-based	responses.						Despite	this	disparity,	similarities	did	exist	between	the	two	studies.		Questions	and	instruments	between	the	two	studies	were	similar,	and	findings	from	the	Affect	and	Avoidance	study	such	as	responses	to	the	optional	comment	on	the	likelihood	of	information	seeking	echoed	findings	from	the	Interview	and	Interaction	study.		Thus	although	it	is	certainly	conceivable	that	the	samples	diverged	in	ways	that	may	have	affected	information	seeking	and	avoidance	behaviours,	comparing	the	two	samples	is	a	feasible	strategy	and	can	lead	to	discoveries	about	how	information	avoidance	is	viewed.				In	the	Interview	and	Interaction	study,	the	information	avoidance	uncovered	was	mostly	selective	filtering	of	information	rather	than	a	complete	refusal	to	engage	with	information.		Here	results	demonstrated	that	participants	employed	various	strategies	to	restrict	and	filter	their	health	information	seeking	and	thus	exposure	to	information,	rather		 125	than	utilizing	a	broad	brushstroke	approach	to	capture	all	possible	information	as	suggested	by	responses	in	the	Affect	and	Avoidance	study.		Analysis	of	these	Interview	and	Interaction	study	data	found	participants,	as	well	as	the	friends	and	relatives	these	participants	spoke	about,	used	two	main	filtering	strategies:		self-regulation	and	delegation.		In	self-regulation,	individuals	themselves	perform	filtering	of	information	related	to	their	health	problems;	in	delegation,	this	filtering	is	conducted	by	a	delegate,	whether	family,	a	friend	or	a	healthcare	professional.				Both	studies	identified	results	indicating	factors	that	influenced	health	information	behaviour,	either	stimulating	or	hindering	information	seeking.		Several	beliefs	emerged	regarding	participants’	health,	health	care,	and	health	information	seeking,	including	beliefs	as	to	the	responsibility	for	their	own	health	and	activities	participants	believed	they	should	be	performing.		Situational	affect,	including	fear,	disgust	and	disinterest,	were	identified	as	factors	influencing	health	information	behaviour.		Disgust	and	disinterest	were	associated	with	the	filtering	of	information,	and	fear	was	linked	to	filtering	and	to	its	opposite,	the	expressed	intent	to	seek	the	maximum	amount	of	information	possible.		Participants’	attitudes	to	information	sources	were	another	influence	on	health	information	behaviour.		For	example,	some	sources	were	viewed	as	untrustworthy	or	capable	of	invoking	negative	affective	reactions;	such	reactions	may	prompt	participants	to	filter.									Further	sections	in	this	chapter	will	discuss	these	concepts	in	more	detail,	beginning	with	information	avoidance	as	a	whole,	and	continuing	to	the	mechanisms	and	influencing	factors	found	by	this	research.					 		 126		6.2	 Information	Avoidance		Information	avoidance	is	commonly	portrayed	by	researchers	in	accordance	with	Sweeny	and	colleagues	(2010)	as	“any	behaviour	intended	to	prevent	or	delay	the	acquisition	of	available	but	potentially	unwanted	information’’	(p.	341).		This	portrayal	has	tended	to	focus	on	methods	of	avoidance	that	consist	of	the	opposite	of	seeking,	of	a	complete	refusal	to	engage	with	information	such	as	declining	to	ask	questions	and	neglecting	to	make	appointments	(Miller,	1980;	Barbour	et	al.,	2012).		However,	in	this	research,	filtering,	a	strategic	and	selective	approach	to	avoiding	information,	emerged	as	the	most	common	method.		Participants	who	spoke	of	filtering	reported	engaging	with	some	information	but	not	all,	a	partial	rather	than	complete	information	avoidance.		On	this	basis,	I	have	amended	the	definition	of	information	avoidance	to	“any	behaviour	intended	to	prevent	or	delay	the	partial	or	complete	acquisition	of	available	but	potentially	unwanted	information.”				This	research	therefore	indicates	that	information	avoidance	exists	on	a	continuum,	in	which	individuals	employ	a	range	of	behaviours	that	regulate	seeking,	and	allow	for	the	avoidance	of	varying	amounts	of	information.		At	either	end	of	the	continuum,	there	are	complete	behaviours,	complete	avoidance	and	complete	seeking:		attempts	to	maximize	and	minimize	access	and	exposure	to	the	maximum	and	minimum	amounts	of	information	available.		In	the	middle,	there	are	situations	where	people	are	avoiding	to	some	degree,	but	letting	in	some	information	(delegation	is	a	good	example	of	how	people	accomplish	this),	and	situations	where	they	are	mostly	seeking,	but	limiting	and	managing	their	access	and	exposure	to	information	(the	good	example	here	is	self-regulation).					Another	contribution	of	this	research	relates	to	the	motivations	for	information	avoidance.		The	definition	stated	above	does	not	include	a	rationale	for	information	avoidance;	indeed,	Miller	(1980)	conceptualized	information	avoidance	as	an	innate	tendency,	a	function	of	personality	rather	than	of	situational	factors.		However,	more	recent	work	often	points	to	situational	affect,	particularly	fear	as	the	essential	ingredient	for	avoidance	(Howell	&	Shepperd,	2013).		In	this	research,	the	situational	factors	tested	showed	more	of	an	association	with	information	avoidance	than	the	personality	traits		 127	assessed,	Need	for	Cognition	and	Monitoring	and	Blunting	coping,	that	the	research	also	examined.		There	is	also,	though,	the	question	of	what	situational	factors	influence	information	avoidance.		Lambert	and	colleagues	(Lambert,	Loiselle	&	Macdonald,	2009)	call	for	information	avoidance	to	be	distinguished	from	“information	disinterest”	(p.	26).		This	disinterest,	they	explain,	is	dissimilar	from	true	information	avoidance	in	that	it	is	characterized	by	a	lack	of	fear	and	a	presence	of	disinterest	or	a	disinclination	to	search.		Information	disinterest	was	suggested	in	this	research	where	participants	who	expressed	disinterest	in	some	health	information	material	reported	not	consulting	that	material.				Both	information	disinterest	and	information	avoidance,	though,	can	be	prompted	by	information	that	in	some	way	invokes	threat.		Researchers	of	information	avoidance	note	that	some	form	of	physical	threat—an	upcoming	surgery,	a	dangerous	diagnosis—is	often	present	about	which	people	avoid	learning	(Howell	&	Shepperd,	2013).		Threat	can	also	be	present	in	information	disinterest.			This	disinterest	can	be	related	to	cognitive	dissonance,	a	theory	which	posits	that	people’s	viewpoints	take	time	and	effort	to	establish;	thus	people	can	be	unwilling	to	engage	with	information	that	may	disagree	with	and	thus	threaten	these	viewpoints	(Festinger,	1957,	1961).		Due	to	the	presence	of	threat	in	both	information	disinterest	and	avoidance,	I	have	decided	to	include	information	disinterest	under	the	umbrella	of	information	avoidance.		This	inclusion	reflects	the	notion	that	a	conscious	or	subconscious	desire	to	avoid	information	for	many	different	reasons	may	be	expressed	in	the	form	of	disinterest.	On	this	basis,	I	propose	a	second	amendment	to	the	definition	so	that	it	now	reads:		“any	behaviour	intended	to	prevent	or	delay	the	partial	or	complete	acquisition	of	available	but	potentially	unwanted	information	for	reasons	including	fear	and	disinterest.”				6.3	 Mechanisms	of	Health	Information	Avoidance				 The	first	research	question	concerns	the	nature	of	health	information	avoidance	and	asks	what	the	mechanisms	are	that	make	up	the	tangible	expression	of	this	concept.		This	research	identified	two	such	mechanisms:		self-regulation	and	delegation,	both	ways	of	filtering	information	to	reduce	exposure	to	unwanted	information.		Much	of	the	identification	and	detailing	of	the	mechanisms	stemmed	from	the	results	of	the	Interview		 128	and	Interaction	study,	in	which	participants	interacted	with	health	information	and	described	their	situational	and	personal	health	information	behaviour	in	an	interview.		6.3.1	 Self-regulation		Study	participants	reported	limiting	their	acquisition	of	information	through	self-regulation.		Regarding	this	mechanism,	participants	told	of	filtering	out	information	that	which	they	believed	to	be	overly	negative	such	as	videos	of	surgeries	or	explanations	of	what	would	occur	in	a	surgical	operation,	or	overly	detailed	such	as	complex	journal	articles	or	websites	containing	medical	jargon.		These	instances	of	self-regulation	can	be	understood	through	the	theory	of	Selective	Exposure.		In	this	theory,	related	to	cognitive	dissonance,	people	avoid	information	in	situations	where	such	information	may	generate	some	form	of	negative	affect,	whether	disagreement	or	fear.	Selective	Exposure	is	frequently	referenced	in	studies	of	responses	to	preventative	health	material	designed	to	warn	about	risky	health	behaviours	(Knobloch-Westerwick,	Johnson	&	Westerwick,	2013).				Some	participants	reported	self-regulation	by	means	of	setting	time	limits	on	their	search	and	refusing	to	exceed	these	limits	for	fear	of	going	“crazy”	(P23).		These	time	limits	could	be	considered	a	way	of	preventing	information	overload	(Toffler,	1970).		In	this	information	reaction,	people	can	become	overwhelmed	or	exhausted	by	information	searching.		Information	overload	is	particularly	prevalent	when	information	is	present	in	large	amounts	and	when	these	large	amounts	are	highly	scattered	rather	than	concentrated	(Bawden	&	Robinson,	2009).		Both	of	these	conditions	are	present	in	the	current	health	situation,	in	which	vast	amounts	of	information	are	now	present	on	the	Internet	(Zhang,	Broussard,	Ke	&	Gong,	2014),	and	where	people	have	reported	searching	for	topics	ranging	from	directions	to	medical	facilities	to	details	of	surgeries	(Bhavnani	&	Peck,	2010).		The	similarity	of	the	results	to	Selective	Exposure	and	information	overload	indicates	that	many	people	avoid	information	in	situations	where	they	anticipate	feeling	negative	affect.			6.3.2	 Delegation		Delegation	is	another	mechanism	identified	by	this	research.		While	it	may	be	suggested	that	delegation,	especially	delegation	to	healthcare	professionals,	could	be	viewed	as	an	information	seeking	mechanism	similar	to	traditional	roles	of	health	information	seeking	(Henwood,	Harris	&	Spoel,	2011),	comments	by	participants	indicate		 129	that	delegation	is	used	as	an	information	avoidance	mechanism.		Comments	by	participants	note	that	delegation	was	performed	when	a	need	for	information	was	present	but	that	they	themselves	or	their	friends	or	relatives	chose	to	delegate	the	searching	required	to	fill	that	need	to	another.		Participants	or	friends/relatives	could	then	choose	to	receive	none	or	only	a	filtered	part	of	the	looked-for	information.		The	emphasis	here	was	not	on	seeking	but	on	avoidance	of	certain	types	of	information,	e.g.,	frightening	medical	procedures.		Participant	7,	for	example,	spoke	of	her	desire	to	place	her	trust	in	healthcare	professionals	rather	than	discover	details	about	surgery,	declaring	“ignorance	is	bliss.”			 Although	delegation	as	avoidance	was	the	primary	aim	of	participants,	some	participants	may	have	chosen	delegation	as	a	means	of	letting	in	some	information.		Research	indicates	that	choice	of	health	information	source	can	be	related	to	views	of	authority,	whether	personal,	i.e.,	family	and	friends	(Wathen	&	Harris,	2007)	or	medical	(Johnson,	1997).		These	authorities	may	be	selected	as	enablers	of	information	avoidance	for	similar	reasons.		Information	behaviour	researchers	note	that	people	prefer	to	receive	information	from	their	friends	and	family	(Wathen	&	Harris,	2007).		This	preference	is	based	on	ease	of	access	and	a	social	bond	that	aids	in	information	acquisition;	those	who	know	and	care	about	you	are	also	those	who	know	what	information	you	do	not	want	but	also	what	information	you	do	want.		By	allowing	or	asking	a	family	member	or	friend	to	search	on	their	behalf,	delegators	in	this	research	could	ensure	that	the	proper	content	of	information	was	delivered	and	avoided.		Individuals	tending	towards	medically	authoritative	sources	for	information	may	also	be	reliant	on	a	social	bond,	this	time	to	provide	emotional	rather	than	informational	support,	as	it	may	be	reassuring	to	consult	healthcare	professionals	rather	than	friends	and	family.		Such	consultation	may	also	allow	people	to	relax	into	traditional	and	more	passive	patient	roles,	facilitating	some	information	avoidance	but	also	allowing	some,	perhaps	necessary,	information	to	filter	through.					6.3.3	 Filtering	Mechanisms		The	findings	of	this	research,	the	mechanisms	of	self-regulation	and	delegation,	assist	in	the	understanding	of	how	people	avoid	information	overall.		In	this	way	these	findings	complement	other	studies	that	focused	on	individual	behaviours	such	as	controlling	conversations	or	not	asking	questions	(Miller,	1980;	Barbour	et	al.,	2012)	and		 130	serve	also	to	show	a	greater	range	of	information	avoidance	behaviours.		One	reason	for	this	range	may	be	the	changes	in	technology	and	social	norms	regarding	health	information	seeking.		Health	information	seeking	is	now	more	widespread	and	is	considered	a	normative	and	desirable	behaviour,	particularly	in	the	context	of	health	difficulties	(Wyatt,	Harris	&	Wathen,	2010).		Thus	it	may	be	that	the	participants	who	chose	to	complete	either	of	the	two	studies	were	unwilling	or	unable	to	admit	to	complete	avoidance,	a	respondent	bias.		However,	it	may	also	be	that	partial	avoidance	is	increasingly	common	because	information	is	so	prevalent	through	so	many	channels,	that	situations	previously	resulting	in	complete	avoidance	now	lead	to	partial	avoidance,	such	as	these	mechanisms	of	self-regulation	and	delegation.					6.4	 Influencing	Factors	Associated	with	Health	Information	Avoidance		The	second	research	question	considered	the	extent	to	which	three	factors,	personality,	affect,	and	information	source,	prompted	information	avoidance.		Quantitative	data	gathered	in	both	studies	using	various	scales	and	metrics	showed	little	impact	of	these	factors,	particularly	in	the	Affect	and	Avoidance	study	(Study	1)	likely	due	in	part	to	the	very	low	levels	of	information	avoidance	reported.		The	interviews	conducted	in	the	Interview	and	Interaction	study	(Study	2)	proved	more	useful	in	revealing	the	nuanced	connections	between	these	factors	and	information	avoidance.			 		 131	6.4.1	 Personality		Personality	traits	initially	believed	to	have	a	strong	impact	on	information	avoidance	and	seeking	behaviours,	such	as	Need	for	Cognition	(NfC)	and	Monitoring	and	Blunting	orientation,	were	not	shown	to	be	associated	with	information	avoidance.		One	explanation	for	this	lack	of	association	may	be	the	changing	nature	of	health	information	seeking	since	these	scales	were	initially	developed.		These	scales	may	not	be	appropriate	in	the	context	of	new	technologies	and	their	impact	on	seeking	behaviours.		For	example,	neither	scale	makes	reference	to	the	Internet	or	to	portable	technologies	such	as	smart	phones	that	have	altered	health	information	seeking	(Barbarin,	Klasnja	&	Veinot,	2016).		An	opportunity	exists	to	redesign	these	scales	to	account	for	such	changes.		Research	shows	that	traits	such	as	NfC	can	be	linked	to	education	and	intellectual	inquiry	(Putte	et	al.,	2012).		Yet	health	information	seeking	particularly	in	this	research	appears	less	about	this	intellectual	curiosity	and	more	about	the	pragmatic	task	of	maintaining	health	(Wyatt,	Harris	&	Wathen,	2010).		As	such,	the	health	information	seeking	behaviours	reported	in	this	research	appeared	to	be	associated	more	in	participants’	minds	with	the	task	of	searching	for	health	information	about	a	particular	condition.		Participants	may	have	been	acting	primarily	out	of	the	belief	that	they	were	responsible	for	their	own	health	information	searching,	rather	than	out	of	an	intellectual	desire	to	learn	about	the	world	around	them.			Health	motivation	and	health	perception	were	personality	traits	that	did	emerge	as	influential,	and	can	be	connected	to	information	seeking	as	personal	responsibility	for	one’s	health.		Health	motivation,	a	strong	personal	interest	in	health	subjects	and	in	taking	care	of	one’s	health,	surfaced	in	the	interviews	through	the	accounts	of	participants	such	as	P21,	P22,	and	P29,	who	noted	their	great	interest	in	health	and	correspondingly	high	levels	of	information	seeking.		By	contrast,	other	participants	expressed	lower	levels	of	health	motivation,	often	commenting	on	their	need	to	“accept”	(P16)	health	difficulties	rather	than	attempt	to	change	their	health	situations.		An	important	consideration	is	the	central	role	health	information	seeking	has	in	healthcare.		Patients	perform	the	duty	of	health	information	seeking	as	a	part	of	being	involved	in	their	own	health	(Wyatt,	Harris	&	Wathen,	2010).		This	notion	of	health	information	seeking	responsibility	was	accepted	at	varying	levels	by	participants,	with	some	reporting	seeking	health	information,	some	reporting	instead	performing	the	lesser	emotional	task	of	wellness	seeking,	and	still	others		 132	adhering	to	a	more	traditional	allocation	of	health	responsibility	in	which	healthcare	professionals	or	fate	are	responsible	for	health.				Health	perception	also	emerged	as	an	influence	on	participants’	reported	health	information	behaviour.		Prior	research	has	established	that	people	with	positive	perceptions	of	their	own	health,	often	described	as	an	optimistic	bias,	tend	to	search	less	for	health	information	than	those	with	negative	perceptions,	as	they	believe	themselves	less	likely	to	fall	victim	to	illnesses	(Shepperd,	Klein,	Waters	&	Weinstein,	2013).		Such	was	the	case	in	this	research	as	Interview	and	Interaction	study	participants	often	stated	their	confidence	in	a	protective	“baseline”	(P4)	of	health.		These	participants	noted	that,	because	they	were	already	healthy,	they	had	less	chance	of	becoming	ill	and	a	greater	chance	of	defeating	any	health	difficulties	they	encountered.		Thus	these	participants	had	less	need	to	search	for	health	information	(P13,	P20	for	example).			6.4.2	 Affect			 Of	the	situational	affect	examined	in	this	research,	particular	emotions	were	notable	in	their	influence:		fear,	disgust,	and	disinterest.		Fear	shaped	participants’	health	information	behaviour	in	contradictory	ways;	although	some	participants	cited	fear	as	a	reason	for	their	reported	avoidance	behaviours	(P7,	P11),	other	participants,	particularly	in	the	Affect	and	Avoidance	study,	seemed	to	indicate	that	fear	was	an	impetus	to	seek	information,	saying	that,	for	example,	the	more	serious	the	problem,	the	greater	likelihood	they	would	search	for	health	information.		Many	researchers	comment	on	the	central	role	of	fear	in	information	avoidance	(Howell	&	Shepperd,	2013,	2017),	but	others	posit	that	serious	and	fear-inducing	health	conditions	can	act	as	stimuli	for	health	information	seeking	(Persoskie,	Ferrer	&	Klein,	2014).		This	dual	effect	recalls	the	theory	of	uncertainty	management,	in	which	researchers	attribute	information	seeking	and	avoidance	to	differing	reactions	to	uncertainty.		When	people	fear	bad	news	and	thus	prefer	uncertainty	to	certainty,	they	avoid	information;	on	the	other	hand,	when	people	fear	they	will	imagine	worse	scenarios	than	the	truth,	the	preference	is	for	certainty	over	uncertainty	and	information	is	sought.		In	this	research,	participants	who	report	avoiding	information	also	report	that	their	uncertainty	regarding	their	health	is	to	be	preferred	(P7,	P20).		As	the	stimulating	influence	of	fear	is	seen	mainly	in	the	Affect	and	Avoidance	study	in	response	to		 133	hypothetical	scenarios,	it	may	be	that	those	participants	miscalculated	their	reactions	to	uncertainty.						 The	influence	of	disgust	was	more	straightforward.		Participants	in	the	Interview	and	Interaction	study	who	reported	feelings	of	disgust	also	reported	avoiding	that	health	information	that	evoked	those	feelings.		The	avoided	health	information	was	often	videos	of	surgeries,	which	participants	referred	to	as	“gross”	(P26),	“gor[y]”	(P33),	“yucky”	(P13).  Reynolds,	McCambridge,	Bissett	and	Consedine	(2014)	point	out	that	few	studies	have	looked	at	disgust	as	an	arbiter	of	information	avoidance,	but	that	this	emotion,	often	stemming	from	penetration	of	the	physical	envelope,	can	be	linked	to	anticipated	avoidance	of	health	stimuli.		This	connection	suggests	that	images	and	videos	of	graphic	events	may	be	avoided	in	the	same	way	as	physical	objects	like	needles	(Reynolds,	Consedine	&	McCambridge,	2014;	Reynolds,	Lin,	Zhou	&	Consedine,	2015).		However,	not	all	participants	avoided	videos	of	surgery.		Curtis,	Barra	and	Aunger	(2011)	suggest	that	disgust	is	a	learned	reaction	and	can	be	overcome	with	habituation	(see	also	Reynolds,	Consedine	&	McCambridge,	2014;	Reynolds,	Lin,	Zhou	&	Consedine,	2015).		Participants	who	did	look	at	videos	often	gave	as	a	reason	a	prolonged	“interest”	in	either	surgeries	(P26)	or	health	(P22),	suggesting	that	this	affective	reaction	might	function	as	a	sort	of	conditioning,	inuring	these	participants	to	health	information	that	would	normally	prompt	disgust	and	avoidance.         		Disinterest	was	another	negative	affective	reaction	that	was	often	mentioned	in	context	with	information	avoidance.		The	opposite	reaction,	interest,	was	also	present	as	an	association	with	information	seeking.		Note	that	interest	and	disinterest	are	distinguished	here	from	high	and	low	health	motivation.		Participants	exhibiting	the	latter	exhibited	a	general	disinclination	that	prevented	them	from	looking	for	most	or	all	health	information,	whereas	disinterested	participants	reported	feeling	that	emotion	in	response	to	a	particular	item	of	health	information.		Disinterest	was	reported	in	two	notable	cases:		when	participants	were	faced	with	complex	medical	information,	and	when	they	were	faced	with	further	information	regarding	a	chronic	condition	they	had	had	for	a	prolonged	period	of	time.		The	appraisal	theory	of	interest	suggests	that	interest	comprises	two	elements,	novelty	and	a	still	comprehensible	complexity	that	allows	users	to	be	challenged	but	not	overwhelmed	(Silvia,	2005;	van	der	Sluis,	van	den	Broek,	Glassey,	van	Dijk	&	de	Jong,	2014).			 134	The	reaction	of	several	participants	to	medical	jargon—“I	trip	over	drug	names”	(P23)—suggests	that	the	material	was	not	at	the	proper	level	of	complexity.		The	absence	of	novelty	may	also	go	some	way	to	explain	the	disinterest	of	chronically	ill	participants,	some	of	whom	indicated	they	were	or	had	been	extremely	familiar	with	the	health	information	regarding	their	condition.		It	may	be	that	either	they	had	simply	had	enough	and	felt	this	topic	held	no	more	new	information	for	them	or	believed	that	their	condition	would	persist	and	that	no	novel	information	would	appear	regarding	changes.		This	supposition	may	indicate	another	way	in	which	health	information	seeking	in	this	study	was	not	influenced	by	Need	for	Cognition	(NfC);	participants	with	chronic	conditions	expressed	disinterest	in	information	seeking	regardless	of	NfC	scores.															6.4.3	 Information	Source			 The	information	source	was	also	a	factor	in	participants’	information	avoidance,	as	evidenced	primarily	by	interview	data	and	participants’	comments	regarding	choices	made	in	the	interaction	sessions	in	the	Interview	and	Interaction	study.		With	reference	to	the	theory	of	Selective	Exposure	(Festinger,	1957,	1961),	I	identified	information	avoidance	when	participants	selected	one	source	or	one	type	of	source	instead	of	another,	citing	problems	with	the	latter	source	as	a	reason	for	this	choice.		Avoidance	of	videos	to	limit	exposure	to	graphic	content	is	one	example	of	such	tactics,	but	more	commonly,	participants	avoided	certain	types	of	sources	on	the	basis	of	authorship	and	authority,	with	some	seeking	more	traditional	medical	authorities,	such	as	journal	articles	and	medical	websites,	and	others	avoiding	those	in	favour	of	alternative	medical	information.		Participants	who	preferred	non-traditional	sources	explained	this	avoidance	by	noting	that	representatives	of	traditional	medical	authority	such	as	doctors	were	in	some	way	flawed,	either	because	they	had	suspect	motives	or	because	the	treatments	these	doctors	had	proposed	were	unsuccessful	or	unsatisfactory.		Substituted	material	was	of	two	types,	health	information	participants	deemed	“alternative”	(P4),	and	information	participants	connected	with	the	viewpoints	of	patients	such	as	blogs	and	videos	of	patients’	stories	(P13,	P17).				 The	avoidance	of	this	health	information	material	is	related	to	self-regulation,	in	which	participants	avoided	negative	or	complex	information.		These	assumptions	regarding		 135	genres	and	authority	also	show	a	link	between	distrust	of	the	information	source	and	information	avoidance.		Participants	who	reported	judging	sources	as	untrustworthy	also	reported	avoiding	these	sources.		Here	trust	may	here	be	associated	to	different	definitions	of	medical	authority.		Other	studies	indicate	that	this	last	can	be	defined	in	other	ways	than	it	has	traditionally	been,	the	traditional	definition	of	authority	being	a	legitimate	sanctioning	of	knowledge	or	skill	(Foucault,	1980).		Researchers	note	that,	in	health,	authority	is	increasingly	being	interpreted	in	ways	other	than	legal	sanctioning	(Wilcox,	2010;	Huber,	Knottnerus,	Green,	van	der	Horst,	Jadad,	Kromhout,	Smit	et	al.,	2011).		Some	participants	revealed	that,	in	certain	situations,	dwindling	trust	in	traditional	medical	authorities	led	them	to	believe	in	other	authorities,	patients	or	alternative	health	practitioners.		This	redefining	of	authority	may	have	caused	participants	to	alter	selection	preferences,	to	avoid	traditional	medically	authoritative	information	in	favour	of	information	representative	of	other	definitions	of	authority.						6.5	 Theoretical	Implications		 This	research	and	the	expanded	notion	of	information	avoidance	afforded	by	this	work	can	contribute	both	to	the	redesign	of	instruments	used	to	measure	information	avoidance	and	to	the	redesign	and	elaboration	of	theoretical	models	of	information	behaviour.		In	this	section,	I	will	examine	the	instruments	used,	and	I	will	also	discuss	the	implications	for	two	theoretical	models,	both	of	which	focus	on	the	decisions	to	seek	or	not	to	seek	information:		Johnson’s	(1997)	Comprehensive	Model	of	Information	Seeking	(CMIS),	and	Wilson’s	(1999)	General	Model	of	Information	Seeking	Behaviour.								 As	stated	in	section	6.4.1,	results	of	this	research,	in	particular	the	difference	between	quantitative	and	qualitative	findings,	point	to	possible	difficulties	with	the	measures	utilized.		Although	the	Need	for	Cognition	and	Monitoring	and	Blunting	scales	are	commonly	used	to	indicate	motivations	for	information	seeking,	the	difference	between	the	quantitative	results,	e.g.,	the	comparison	between	Blunting	scores	and	interaction	session	measures,	were	notably	dissimilar	than	the	qualitative	results,	e.g.,	comments	by	participants	in	that	study.		Thus	the	Monitoring	and	Blunting	and	Need	for	Cognition	scores	were	not	supported	by	participants’	descriptions	of	their	own	health	information	behaviour	or	the	attitudes	regarding	health	information	seeking	and	avoidance	expressed	in	the	interviews.		Thus	the	scales	did	not	aid	in	indicating	how	much	participants	would	search,	a		 136	flaw	due	certainly	in	part	to	the	failure	of	these	scales	to	encompass	the	complexity	of	the	health	information	sphere.		As	aforesaid,	one	clear	example	is	the	omission	of	the	Internet	as	a	health	information	source,	which	also	points	to	the	need	to	update	these	scales	to	reflect	the	current	reality	of	information	seeking.		Another	example	is	the	failure	of	the	Monitoring	and	Blunting	scale	to	mention	the	full	range	of	health	information.		Statements	such	as	“I	will	get	more	information	at	other	medical	centers	first”	seem	inclusive	but	fail	to	mention	directly	information	sources	such	as	alternative	health	practitioners,	sources	that,	as	indicated	by	participants’	comments,	were	clearly	consulted	at	certain	times.			This	fact	points	to	the	need	for	further	testing	of	these	scales,	to	determine	the	extent	to	which	they	are	measuring	a	consistent	human	trait	or	a	particular	state	brought	about	by	circumstances.			These	difficulties	with	the	scales	may	also	indicate	that	personality	is	less	a	factor	in	information	avoidance	than	factors	that	stem	from	the	situation.		Information	avoidance	behaviours	varied	greatly	from	situation	to	situation,	depending	both	on	information	sources	and	emergent	affect	not	taken	into	consideration	by	these	scales	such	as	disgust	stemming	from,	as	one	example,	visualization	of	surgeries.		Thus	the	health	information	behaviours	identified	by	this	research	seem	more	nuanced	than	these	personality	measures	would	suggest.		Instruments	such	as	the	survey	used	in	this	research	that	include	these	scales	should	be	retested	and	revalidated	to	ensure	greater	reliability	and	validity.							 The	scenarios	employed	in	this	research	to	present	situations	in	which	information	might	be	sought	or	avoided	also	warrant	re-examination.		Although	the	scenarios	in	this	research	were	based	on	those	employed	by	previous	researchers,	the	scenarios	varied	in	meaningful	ways,	notably	in	their	presentation	of	different	numbers	of	decision-making	options	(Evans	et	al.,	2014).		For	example,	the	Affect	and	Avoidance	“acoustic	neuroma	strong	negative”	scenario	treatment	sentence	reads,	“Treatment	options	are	observation,	surgical	removal,	or	radiation,	“	while	the	“acoustic	neuroma	weak	negative”	scenario	treatment	sentence	is,	“If	you	do	need	treatment,	surgery	and	radiation	are	options.”		This	variability	in	decision	choices	was	included	in	order	to	vary	controllability	and	treatability,	associated	with	health	information	seeking	and	avoidance,	as	well	as	to	maintain	verisimilitude,	as	the	scenarios	were	intended	to	resemble	real	situations	as	closely	as	possible	(Dawson,	Savitsky	&	Dunning,	2006;	Evans	et	al.,	2014).		However,	the	decision	choice	variability	is	noteworthy	in	that	the	resultant	complexity	of	the	decision	task	facing		 137	study	participants	may	have	influenced	information	seeking	and	avoidance	patterns,	rather	than	perceptions	of	controllability	and	treatability;	i.e.,	some	of	the	difficulties	with	the	strong	and	weak	negative	divisions	in	the	Affect	and	Avoidance	study	may	have	been	due	to	the	differences	in	treatment	options	(Bystrom	&	Hansen,	1995;	Kryworuchko	et	al.,	2012;	Feenstra	et	al.,	2014).		Consistency	in	decision	options	should	be	examined	in	future	scenarios	in	order	to	measure	whether	the	number	of	decision	options	alters	information	seeking	and	avoidance.							 This	research	also	suggests	amendments	to	models	of	information	behaviour.		Johnson’s	(1997)	CMIS	identifies	factors	that	come	into	play	when	people	are	deciding	whether	or	not	to	seek	information	but	does	not	mention	information	avoidance	as	a	behaviour	in	itself.		The	CMIS	details	the	decisions	people	make	as	binary;	people	can	choose	to	seek	or	not	to	seek	information,	an	explanation	that	implies	information	avoidance	is	the	opposite	of	information	seeking.		Yet	information	avoidance	has	been	revealed	by	this	research	to	be	located	on	a	range	or	continuum	of	information	behaviours.		While	some	information	avoidance	and	some	information	seeking	is	absolute,	participants	were	more	commonly	employing	strategies	such	as	filtering	or	delegation	to	limit,	manage	or	narrow	their	information	acquisition.		Factors	cited	as	reasons	for	information	seeking	decisions	by	the	CMIS	are	also	brought	into	question	by	this	research.		These	factors	include	demographics,	experience,	personal	relevance	or	salience,	and	beliefs.		For	the	last	factor,	Johnson	(1997)	lists	beliefs	that	appear	in	this	research	such	as	a	credence	in	the	efficacy	of	good	health	behaviours	and	the	efficacy	of	treatment,	both	beliefs	that,	if	held	strongly,	could	allow	people	to	make	the	decision	not	to	seek	information.		Similar	beliefs	with	similar	consequences	were	also	held	by	participants	in	this	research,	as	participants’	faith	in	the	effectiveness	of	a	“preventative”	(P19)	level	of	health	or	their	trust	in	healthcare	professionals	indicates.		Yet	here,	too,	the	list	of	beliefs	is	not	as	inclusive	as	this	research	demonstrates.		One	belief	present	in	this	research	that	is	not	mentioned	by	Johnson	(1997)	is	the	beliefs	participants	had	about	the	health	information	seeking	as	a	social	responsibility,	which	may	be	related	to	ideas	from	the	consumer	health	movement,	in	which	access	to	health	information	is	said	to	grant	much-needed	power	to	patients.		The	CMIS,	created	in	1997,	does	not	take	into	consideration	these	beliefs	found	here	to	be	a	factor	influencing	the	seeking	decisions	of	participants.		These	omissions—the	belief	or	lack	of	belief	in	health	information	seeking	as	a	social		 138	responsibility	and	the	addition	of	information	avoidance	as	part	of	the	range	of	information	behaviour—suggest	that	the	CMIS	could	be	expanded	to	represent	health	information	seeking	more	fully.				.		 The	range	of	health	information	interaction	shown	in	this	research	may	also	be	employed	to	elaborate	upon	and	suggest	redesign	of	Wilson’s	(1999)	Model	of	General	Information	Seeking	Behaviour.		Wilson	(1999)	explains	that	between	people’s	recognition	of	an	information	need	and	the	seeking	of	information	to	fill	this	need	stand	several	activating	mechanisms	and	intervening	variables.		The	choice	to	seek	and	the	manner	of	seeking	vary	in	this	model,	such	that	people	may	not	seek,	may	seek	passively,	may	search	actively	and	may	perform	an	ongoing	search.		However,	these	behaviours	do	not	include	information	avoidance	mechanisms.		Though	Wilson	(1999)	defines	the	information	behaviour	depicted	in	this	model	as	the	“totality	of	human	behaviour	in	relation	to	sources	and	channels	of	information,	including	both	active	and	passive	information	seeking	and	information	use”	(p.	249),	he	omits	strategies	such	as	filtering	that	permit	the	partial	avoidance	of	information.		Rectifying	this	omission	is	essential	to	render	this	model	more	clearly	representative	of	the	“totality”	of	information	behaviour.						6.6	 Implications	for	Practice			 This	study	of	information	avoidance	was	conducted	in	the	domain	of	information	science;	however,	the	subject	of	the	information	behaviour	studied	is	health,	and	thus	there	are	practical	implications	for	professionals	who	are	employed	in	libraries	and	other	information-intensive	environments	including	healthcare	settings.		One	note	here	is	that	information	professionals	and	others	who	work	in	information-intensive	environments	should	be	aware	of	information	avoidance	and	the	common	motivations	and	methods	of	avoiding	information.		Previous	research	indicates	that	such	professionals	may	not	be	mindful	of	such	behaviour	(Case	&	Johnson,	2012;	Johnson,	2014).		Professionals	should	be	aware	of	information	avoidance	and	its	ties	to	various	factors	including	personality,	affect,	and	information	source,	as	people	with	whom	these	professionals	associate	could	exhibit	this	behaviour.		Professionals	should	display	sensitivity	and	tact	while	dealing	with	people	practising	this	behaviour	either	in	its	absolute	or	partial	forms	as	these	people	may	be	embarrassed	or	attempt	to	hide	the	fact	that	they	avoid	health	information.						 139		 Another	important	implication	of	this	research	is	that	there	may	be	a	stigma	associated	with	information	avoidance	that	may	cause	misleading	claims	and	assumptions	about	health	information	seeking.		Study	participants	in	the	Affect	and	Avoidance	study	(Study	1)	made	claims	that	they	would	search	a	great	deal;	however,	in	the	Interview	and	Interaction	study,	when	given	the	opportunity	to	browse	health	material,	participants	often	chose	not	to	do	so	for	the	maximum	amount	of	time	or	to	scan	all	the	information.		In	the	Affect	and	Avoidance	study,	only	one	participant	admitted	that	s/he	would	avoid	information	entirely.		However,	the	Interview	and	Interaction	study	(Study	2)	revealed	that	participants	employed	various	information	avoidance	and	filtering	strategies.		Even	in	this	smaller	sample,	two	participants	admitted	to	a	great	deal	of	avoidance.		Thus	the	assumptions	of	some	participants	about	amounts	of	searching	were	not	matched	by	the	amounts	of	searching	that	other	participants	demonstrated.		This	disparity	may	have	been	due	to	the	differing	recruitment	strategies	employed	by	these	two	studies,	which	may	have	caused	a	corresponding	and,	here,	important	difference	in	samples.		Despite	this	possibility,	the	fact	that	the	Affect	and	Avoidance	study	asked	questions	about	participants’	assumptions	about	their	information	seeking	while	the	Interview	and	Interaction	study	presented	participants	with	the	opportunity	to	browse	information	in	real	time,	this	difference	in	findings	may	indicate	a	disconnection	between	participants’	intentions	and	behaviours	and	demonstrates	that	the	position	of	seeking	warrants	further	consideration	by	practitioners.							 Another	implication	arises	from	comments	of	participants	in	the	Interview	and	Interaction	study	regarding	the	societal	value	of	health	information	seeking.		Certain	participants	revealed	their	belief	that	health	information	seeking	was	an	important	societal	responsibility,	comparing	themselves	favourably	with	others	who	did	not	search	or	whose	searches	were	less	effective	(P3,	P32,	P33)	and	commenting	on	the	benefits	to	searching	in	the	current	healthcare	system	(P33).		Yet	many	participants,	upon	reflection,	commented	on	limitations	in	their	searching	strategies,	pointing	to	the	fact	that	they	did	not	know	which	sources	were	medically	authoritative	(P7,	P9).		These	comments	recall	Competency	Theory,	which	notes	that	people	engaged	in	a	new	area	tend	to	overestimate	their	abilities;	as	they	have	no	understanding	of	what	the	area	entails,	they	have	no	means	to	judge	ability,	a	situation	called	the	“dual	curse”	(Kruger	&	Dunning,	1999,	p.	1121).		Studies	have	shown		 140	that	competency	theory,	also	known	by	the	flattering-to-researchers	name	of	the	Dunning-Kruger	effect,	translates	to	the	information	literacy	sphere	where	people	often	overestimate	their	skills	and	abilities	in	searching	for	information	regarding	many	topics	(Gross	&	Latham,	2007,	2009,	2011,	2013).		Comments	by	Interview	and	Interaction	study	participants	reveals	that	this	application	may	also	be	present	in	some	health	information	behaviour,	a	problematic	conclusion	for	those	who	may	rely	in	part	on	an	understanding	of	people’s	abilities	in	this	area.			6.7	 Conclusion		 The	information	avoidance	mechanisms,	as	well	as	the	factors	that	influence	the	use	of	these	mechanisms,	add	to	the	understanding	of	information	avoidance	and	information	behaviour.		In	self-regulation,	study	participants	reported	limiting	and	filtering	the	information	for	which	they	searched	when	that	information	was	deemed	negative	or	detailed.		Delegation	was	present	when	information	searching	was	allocated	to	another	who	could	also	be	nominated	to	filter	the	information	received.		These	mechanisms,	both	of	which	point	to	a	filtering	of	information,	indicate	a	partial	avoidance	of	information	that	expands	the	notion	of	information	avoidance	as	simply	not-seeking.				Personality,	affect,	and	information	source	were	all	implicated	as	motivations	for	information	avoidance.		Personality	traits,	operationalized	here	as	Need	for	Cognition	and	Monitoring	and	Blunting	orientation,	had	much	less	of	an	effect	than	anticipated	on	participants’	health	information	behaviour.		Two	other	personality	traits,	health	motivation	and	health	perception,	did	emerge	as	influential	from	the	analysis	of	results	from	the	Information	and	Interaction	study.		Health	motivation,	a	strong	interest	in	health	and	health	maintenance,	was	noted	as	some	participants	displayed	this	trait,	while	others,	less	likely	to	search,	felt	instead	that	they	should	“accept”	(P16)	ill	health.		Health	perception	and	often	the	accompanying	optimistic	bias	was	also	present	in	this	research	as	some	participants	felt	that	their	good	health	made	them	in	some	way	immune	to	either	illness	or	any	strong	side	effects	of	illness.				Thus	three	forms	of	affect	were	an	influence	on	participants’	health	information	behaviour:		fear,	disgust,	and	disinterest.		Fear	generally	functioned	as	a	cause	of	information	avoidance,	an	effect	much	seen	in	literature	about	this	topic	and	perhaps		 141	stemming	from	situations	in	which	uncertainty	was	a	desirable	rather	than	undesirable	affective	condition.		Participants	also	avoided	information	that	provoked	disgust,	often	videos	of	surgeries,	while	participants	who	evaluated	medical	information	as	too	complex	or	lacking	in	novelty	avoided	this	information	as	well.		The	latter	form	of	affect,	disinterest,	was	significant,	as	some	researchers	note	that	information	disinterest	is	separate	from	information	avoidance.		However,	this	research	found	that	information	disinterest	and	information	avoidance	both	function	as	a	means	of	avoiding	threat.							Information	avoidance	of	sources	was	determined	to	have	occurred	when	participants	who	cited	problems	with	one	source,	usually	those	sources	associated	with	traditional	medical	authority,	expressed	preferences	for	other	sources	in	lieu.		This	choice	of	sources	may	have	taken	place	as	participants	may	hold	definitions	of	medical	authority	that	differ	from	those	in	traditional	medicine.				This	research	also	suggests	that	measures,	in	particular	Need	for	Cognition	and	Monitoring	and	Blunting,	previously	employed	to	indicate	motivations	for	information	seeking	may	not	be	suitable	in	this	context.		The	general	usefulness	of	instruments	that	contain	these	scales	should	be	assessed.		Scenarios,	as	well,	vary	in	the	number	of	decision	options	they	present,	which	may	have	affected	findings.		Consistency	in	decision	options	should	be	further	examined.				This	research	suggests	the	redesign	of	Johnson’s	(1997)	Comprehensive	Model	of	Information	Seeking	(CMIS)	and	Wilson’s	(1999)	General	Model	of	Information	Seeking.		With	regards	to	Johnson’s	(1997)	CMIS,	factors	that	contribute	to	people’s	avoidance	are	also	elaborated	upon,	with	beliefs	influencing	information	avoidance	expanded	to	include	those	surrounding	health	information	seeking	and	responsibility.		Both	the	CMIS	and	Wilson’s	(1999)	model,	which	provides	an	overview	of	information	seeking	processes	including	passive	attention	and	ongoing	searching,	are	lacking	mention	of	information	avoidance.		Without	this	behaviour,	neither	model	presents	the	full	range	of	information	interaction.								Implications	for	practice	include	a	greater	understanding	of	the	notion	of	health	information	seeking	and	responsibility,	which	may	be	responsible	for	participants’	wrongful		 142	belief	that	they	would	search	for	the	maximum	amount	of	information	possible	when	faced	with	health	difficulties.		This	last	idea	is	worthy	of	more	attention	from	practitioners,	who	may	be	faced	with	people	who	believe	fully	that	information	searches	will	be	more	extensive.		This	belief	in	health	information	seeking	may	also	be	responsible	for	an	assumption	that	people	search	better	than	they	actually	do,	a	finding	that	recalls	competency	theory	that	posits	people	encountering	a	new	area	do	not	have	the	knowledge	to	gauge	their	capacity.								 		 143			7	 Conclusion		 The	following	chapter	concludes	this	dissertation.		I	will	begin	by	giving	an	overview	of	the	research	conducted,	and	a	summary	of	both	its	implications	and	the	contributions	it	has	made.		I	will	then	look	at	directions	for	future	research.					7.1	 Overview		Through	this	research,	I	sought	to	understand	information	avoidance,	the	mechanisms	by	which	people	avoid	information	and	the	extent	to	which	personality,	affect,	and	information	source	factors	influence	avoidance	behaviours.		A	greater	comprehension	of	these	elements	is	essential.		Information	is	considered	in	general	extremely	beneficial;	it	follows	that	seeking	information	is	viewed	as	a	natural	drive	that	all	possess	(Case	et	al.,	2005).		In	the	field	of	health,	the	lens	through	which	I	explored	information	avoidance,	information	is	painted	as	a	vital	component	of	being	healthy,	with	health	information	seeking	increasingly	depicted	as	important	for	good	health.		Information	avoidance,	due	at	least	in	part	to	these	views	of	information	and	information	seeking,	is	often	ill	defined	as	a	negation	of	behaviour,	a	not-seeking.			This	research	revealed	that	people	employ	filtering	mechanisms,	delegation	and	self-regulation,	to	partially	avoid	health	information.		Thus	information	avoidance	as	depicted	here	can	be	found	on	a	continuum,	contrary	to	the	current	image	of	avoidance	as	a	simple	negation	of	information	seeking,	as	a	not-seeking.		One	reason	for	this	continuum	might	be	the	current	view	of	health	information	seeking	as	a	desirable	behaviour,	which	may	have	encouraged	participants	to	search	more	than	previous	studies	in	which	participants	in	other	situations	may	have	been	more	likely	to	simply	avoid.		However,	it	may	also	be	that	this	continuum	of	information	avoidance	indicates	that	this	reaction	to	information	should	be	included	within	the	range	of	people’s	information	behaviour,	instead	of	being	placed	outside	of	this	range	as	a	simple	negative	mirror	of	seeking.		This	more	comprehensive	view	of	information	avoidance	could	be	used	to	amplify	such	macro-models	of	information	behaviour	as	those	of	Johnson	(1997)	and	Wilson	(1999)	that	purport	to		 144	show	information	behaviour	on	a	larger	scale	and	allow	for	a	fuller,	better	understanding	of	how	people	interact	with	information.				This	research	also	makes	an	important	contribution	to	views	of	health	information	seeking.		It	has	previously	been	noted	that	health	information	seeking	is	currently	in	a	position	of	desirability,	a	behaviour	that	people	should	engage	in	if	they	are	more	properly	to	care	for	their	health	and	existing	as	a	base	for	many	health	initiatives.		This	research	makes	evident	that	this	attitude	can	obscure	the	reality	of	how	people	interact	with	health	information	even	to	those	people	who	are	interacting	themselves.							This	research	also	sheds	light	on	the	motivations	for	information	avoidance,	finding	that	while	personality	and	information	source	factors	do	influence	information	avoidance,	situational	factors	such	as	affect	seemed	to	be	yet	more	influential	for	these	participants	and	in	response	to	these	scenarios.		Here,	these	situational	affective	factors	that	sway	information	behaviour	in	this	study	are	fear,	disgust,	and	disinterest.		These	particular	factors	are	indicative	of	a	threat	to	people,	whether	to	their	viewpoint	or	their	physicality.			7.2	 Limitations		This	research	was	limited	in	several	ways.		As	mentioned	in	section	3.5.6,	I	am	a	former	patient	who	had	emergency	surgery	for	an	acoustic	neuroma	in	2003,	for	which	concern	I	sought	only	minimal	information.		I	am	also	a	librarian	who	encountered	a	negative	bias	against	information	avoidance,	an	information	behaviour	that	I	myself	engaged	in.		These	perspectives	influenced	my	choice	of	dissertation	topic,	and	also	affected	the	qualitative	analysis,	as	this	analysis	is	interpretive	and	reliant	on	the	individual	researcher.		Such	experiences	led	to	my	identification	of	behaviours	as	information	avoidance;	additionally,	it	gave	me	a	more	neutral	and	sometimes	positive	view	of	information	avoidance,	contrary	to	that	expressed	by	some	other	researchers	(Johnson,	2014).		I	also	approached	information	avoidance	with	an	information	science	lens,	rather	than	looking	at	this	phenomenon	as	a	health	researcher	would;	for	example,	I	took	a	broad	approach	to	health	information,	including	screening	and	diagnoses	under	this	umbrella.		Although	this	approach	allowed	me	to	look	at	information	avoidance	from	a	more	comprehensive	standpoint,	I	was	unable	to	examine	more	situation-based	differences	that	may	have	affected	avoidance	of	particular	information	in	particular	contexts.				 145	In	this	research,	I	have	concentrated	consistently	on	the	seeking	of	health	information	by	patients	on	their	own	behalf.		Admittedly,	some	research	does	not	treat	searching	for	oneself	and	searching	for	others	differently	(see	Sweeny	&	Miller,	2012;	Miller,	1980	for	examples).		However,	the	separate	role	of	the	caregiver	in	assisting	people	who	are	in	crisis	with	information	seeking	and	other	activities	has	been	the	subject	of	some	study	(Barbarin,	Klasnja	&	Veinot,	2016;	Veinot,	Kim	&	Meadowbrooke,	2011;	Hepworth,	2004).		Health	decisions	are	also	not	made	in	a	vacuum,	with	many	patients	weighing	factors	such	as	the	perceived	opinion	of	the	healthcare	professional	administering	treatment	before	making	a	health	decision	(Aronson,	2013;	Kryworuchko	et	al.,	2012;	Nouvet	et	al.,	2016).		Social	exclusion	may	also	be	a	factor	in	health	information	avoidance	(Howell	&	Shepperd,	2017).		More	focused	work	is	needed	to	enable	a	better	understanding	of	information	avoidance	within	these	different	contexts	and	situations.				Another,	related,	limitation	is	that	I	concentrated	on	information	avoidance	as	a	general	phenomenon,	rather	than	looking	at	specific	demographic	differences.		Such	demographics	have	been	linked	to	variations	in	health	information	seeking.		In	particular,	researchers	have	noted	that	older	people	have	more	health	concerns	and	thus	can	search	for	more	health	information	(Ahluwalia	et	al.,	2012).		Still	other	studies	show	that	concerns	of	older	people	tend	to	be	more	complex	and	thus	people,	intimidated	by	the	resulting	and	daunting	task,	may	be	reluctant	to	search	(Agree,	King,	Castro,	Wiley	&	Borzekowski,	2015).		Similar	paradoxes	are	visible	in	research	regarding	gender	and	its	influence	on	health	information	seeking	(Warner	&	Procaccino,	2007;	Manierre,	2015;	Lund-Nielsen	et	al.,	2011).		Women	have	been	labelled	the	“gatekeepers”	of	health	information	(Warner	&	Procaccino,	2007,	p.	787);	often	being	the	primary	caregivers,	they	tend	to	seek	out	health	information	as	part	of	that	care	(see	also	Manierre,	2015).		Despite	this	fact,	research	also	shows	that	caregiving	for	others	can	be	such	an	onerous	task	that	it	may	lead	to	women	neglecting	their	own	health	(Lund-Nielsen	et	al.,	2011).		In	this	research,	little	evidence	of	either	gender	or	age	as	an	influencing	factor	was	found:		in	the	Affect	and	Avoidance	study,	Spearman’s	tests	were	performed	between	Age	and	Information	Seeking,	and	Gender	and	Information	Seeking.		There	were	no	significant	results	found.		Thus,	relationships	between	demographic	characteristics	and	health	were	deemed	outside	the	scope	of	the	research.		However,	while	not	a	focus	of	this	research,	there	is	a	need	for	further	investigation	of	information	avoidance	that	considers	the	role	of	gender	and	age.		 146		Recruitment	tools	included	an	online	labour	market,	Amazon’s	Mechanical	Turk	(AMT).		Online	labour	markets	in	general	and	AMT	are	currently	commonly	used	in	social	science	and	other	research	(Zhu	&	Carterette,	2010),	and	AMT	in	particular	has	been	much	lauded	for	its	ability	to	link	up	“requestors”	who	need	a	large	number	of	people	to	complete	a	Human	Intelligence	Task	(HIT)	with	“workers”	who	are	willing	to	do	so	(Paolacci,	Chandler,	&	Ipeirotis,	2010;	Rand,	2011).		However,	critics	point	out	that	the	online	and	impersonal	format	of	the	survey	may	allow	for	participants	to	waver	in	their	attention	(Paolacci	&	Chandler,	2014).		In	addition,	this	method	of	recruitment	was	different	from	the	method	used	in	the	Interview	and	Interaction	study,	which	resulted	in	dissimilar	samples.		I	added	an	attention-seeking	question	regarding	the	nature	of	the	disease;	however,	it	is	impossible	to	know	if	participants	maintained	a	similar	level	of	attention	throughout	the	survey,	a	problem	not	present	in	the	Interview	and	Interaction	study,	in	which	the	interviewer	was	physically	present.								 			 Another	issue	present	in	this	research	is	the	use	of	hypothetical	scenarios	to	simulate	situations	in	which	health	information	seeking	and	avoidance	can	occur.		The	use	of	hypothetical	scenarios	has	been	criticized	as	people	may	respond	differently	to	hypothetical	scenarios	than	they	do	to	real	situations.		This	limitation	of	using	hypothetical	scenarios	was	mitigated	in	the	Interview	and	Interaction	study,	as	the	interviews	covered	both	the	assigned	scenarios	and	participants’	health	experiences,	often	allowing	the	scenarios	to	function	as	starting	points	for	discussions	about	health	(Evans	et	al.,	2014).			Participants	in	the	Interview	and	Interaction	study	responded	to	general	questions	about	health	information	seeking	in	a	manner	that	indicated	they	considered	the	hypothetical	disease	assigned	as	well	as	their	own	real	health.		A	concern	with	the	use	of	such	scenarios	is	that	they	have	the	potential	to	lead	to	real	distress	on	the	part	of	participants.		Hypothetical	scenarios	have	been	used	extensively	in	studies	of	information	avoidance	(Melnyk	&	Shepperd,	2012;	Dawson,	Savitsky	&	Dunning,	2006)	with	no	ill	effects	reported;	however,	steps	were	taken	in	the	second	study	to	ensure	that	the	study	took	place	in	a	quiet	and	private	space,	and	that	interviews	were	flexible	enough	to	allow	participants	to	address	or	not	address	their	emotional	responses	to	the	scenarios.		No	signs	of	emotional	distress	were	observed	in	reaction	to	the	scenarios;	however,	the	scenarios	may	have	had	unseen	effects,	with	reference	both	to	participants’	responses	and	to	their	comfort	and	mental		 147	health.		This	is	an	important	and	persistence	issue	in	health	information	research,	given	the	need	to	study	human	behaviour	in	response	to	stressful	health	conditions.						7.3	 Future	Work		It	is	notable	in	this	research,	constituting	studies	of	information	avoidance,	its	mechanisms	and	influencing	factors,	that	despite	the	focus	on	this	challenging	topic,	evidence	of	information	avoidance	was	found.		It	seems	clear	that	the	concentrations	on	information	seeking	shown	in	information	behaviour	and	health	care	have	their	limits	and	that	further	work	on	information	avoidance	is	needed	in	both	disciplines.		One	question	that	remains	is	the	extent	to	which	these	results	on	health	information	avoidance	can	be	translated	into	the	avoidance	of	other	subjects.		It	is	certain	that	information	is	avoided	on	many	occasions	and	yet	thus	far	those	who	study	this	subject	have	by	and	large	concentrated	on	the	avoidance	of	health	information.		Miller’s	(1980)	seminal	Monitoring	and	Blunting	scale	suggested	that	Monitoring	and	Blunting	behaviours	were	found	in	a	variety	of	stressful	situations	in	which	the	spectre	of	economic	loss	was	present	as	well	as	personal	danger;	later	studies	point	to	societal	and	romantic	rejection	as	another	circumstance	(Sweeny	&	Miller,	2012).		Yet	few	researchers	have	attempted	to	examine	stressful	situations	at	a	higher	level,	focusing	on	all	such	occurrences	that	may	result	in	information	avoidance.		This	research,	which	itself	addressed	information	avoidance	at	one	such	macro-level,	that	of	the	avoidance	of	all	health	information,	suggests	that	other	scenario-driven	studies	might	approach	the	topic	of	information	avoidance	at	another	higher	level,	in	order	to	garner	a	clearer	and	more	universal	picture	of	this	behaviour.						Gaps	are	additionally	present	in	the	study	of	health	information	avoidance.		One	of	the	pressing	questions	in	this	research	is	the	extent	to	which	the	individual	health	care	systems	influences	the	likelihood	and	effect	of	health	information	avoidance.		Much	of	the	literature	including	Miller’s	(1980)	seminal	study	was	American,	as	were	participants	in	the	Affect	and	Avoidance	study,	and	thus	based	in	a	private	health	care	system.		Problems	with	private	systems	are	suggested	by	the	comment	from	one	participant	in	the	Affect	and	Avoidance	study:		“I	would	be	too	scared	to	look	for	information.		Since	I	don't	have	insurance,	I'd	be	stuck	with	some	very	expensive	bills	for	the	next	year	at	least.”					However,	Veinot	(2008)	noted	that	public	health	care	systems	have	difficulties	as	well.	In		 148	her	study	of	governmental	health	websites	from	Canada	and	the	United	Kingdom,	she	found	that	health	information	seeking	can	be	as	much	a	burden	as	an	empowerment,	a	task	people	must	complete	to	be	“good	citizens”	(p.	30),	a	fact	also	denoted	in	part	by	the	concept	of	“healthwork”	(Mykhalovskiy	&	McCoy,	2002)	used	in	this	research.		Other	shortcomings	in	the	Canadian	system	that	may	contribute	to	health	information	avoidance	are	long	wait	times	and	a	shortage	of	treatment	options	in	some	areas	(Standing	Committee	on	Health,	2016).				7.4	 Summary		This	research	demonstrates	that	information	avoidance	is	present	in	quantities	and	in	circumstances	largely	unsuspected	by	much	research	and	many	who	advocate	the	benefits	of	information	seeking.		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Participant	demographics	The	following	questions	ask	you	to	give	some	basic	information	about	your	age,	gender,	and	education	level.	1.	Gender	Please	indicate	your	gender.	Choose	one	of	the	following	answers.		 	 		Male		 	 		Female		 	 		Other		 	 		No	answer	2.	Age	Please	indicate	your	age	group.	Choose	one	of	the	following	answers.		 	 		19-29		 	 		30-39		 	 		40-49		 	 		50-59		 	 		60-69		 	 		70+		 	 		No	answer	3.	Level	of	education	Please	indicate	your	highest	level	of	education.	Choose	one	of	the	following	answers.		 	 		Less	than	high	school		 	 		High	school		 	 		College	diploma		 	 		Undergraduate	degree		 	 		Master's	degree		 	 		Doctorate	degree	Other	______________________________________________________________________________		 169	No	answer	Health	demographics	The	following	questions	ask	you	to	give	some	basic	information	about	your	health.	4.	General	health	Please	rate	your	general	health.	Choose	one	of	the	following	answers.		 	 		Poor		 	 		Fair		 	 		Good		 	 		Very	good		 	 		Excellent		 	 		No	answer	5.	General	health	comparison	to	last	year	Please	rate	your	general	health	as	compared	to	last	year	at	this	time.	Choose	one	of	the	following	answers.		 	 		Much	worse	than	one	year	ago		 	 		Somewhat	worse	than	one	year	ago		 	 		About	the	same		 	 		Somewhat	better	than	one	year	ago		 	 		Much	better	than	one	year	ago				 No	answer	Knowledge	of	disease	The	following	question	will	test	your	knowledge	of	a	disease.			6.		Please	indicate	which	of	the	answers	best	fits	the	question.			What	is	the	definition	of	a	disease?			a.	An	abnormal	and	debilitating	condition	of	a	part,	organ,	or	system	of	an	organism	resulting	from	various	causes	b.	A	condition	leading	to	death	or	incapacitation	c.	The	relative	incidence	of	conditions	within	a	community	d.	A	condition	in	which	felines	experience	discomfort	Information	demographics	Part	I		The	following	question	asks	about	your	use	of	online	information	of	various	subjects.	Choose	from	the	answers	below.		 170	5. Please	indicate	how	frequently	you	use	the	Internet	to	find	information	related	to	the	following	subjects.	Health	and	wellness	Research	and	studies		Government	information	and	services	Personal	interests	and	entertainment	News	and	current	events	Questions	were	rated	on	a	7-point	Likert	scale:		Never,	A	few	times	per	year,	Monthly,	A	few	times	per	month,	Daily,	A	few	times	per	day,	No	answer		Information	demographics	Part	II	The	following	question	will	ask	about	how	much	you	like	to	think.	Please	choose	from	the	following	answers.		7.		The	following	scale	asks	you	to	rate	the	extent	to	which	you	agree	with	each	of	18	statements	about	the	satisfaction	you	gain	from	thinking.	Sample	statements	include	"I	find	satisfaction	in	deliberating	hard	and	for	long	hours,"	"The	notion	of	thinking	abstractly	is	appealing	to	me,"	and	"Thinking	is	not	my	idea	of	fun".		I	prefer	complex	to	simple	problems.			I	like	to	have	the	responsibility	of	handling	a	situation	that	requires	a	lot	of	thinking.	Thinking	is	not	my	idea	of	fun.	I	would	rather	do	something	that	requires	little	thought	than	something	that	is	sure	to	challenge	my	thinking	abilities.	I	try	to	anticipate	and	avoid	situations	where	there	is	a	likely	chance	I	will	have	to	think	in	depth	about	something.			I	find	satisfaction	in	deliberating	hard	and	for	long	hours.			I	only	think	as	hard	as	I	have	to.			I	prefer	to	think	about	small	daily	projects	to	long	term	ones.			I	like	tasks	that	require	little	thought	once	I’ve	learned	them.			The	idea	of	relying	on	thought	to	make	my	way	to	the	top	appeals	to	me.			I	really	enjoy	a	task	that	involves	coming	up	with	new	solutions	to	problems.			Learning	new	ways	to	think	doesn’t	excite	me	very	much.				 171	I	prefer	my	life	to	be	filled	with	puzzles	I	must	solve.		The	notion	of	thinking	abstractly	is	appealing	to	me.			I	would	prefer	a	task	that	is	intellectual,	difficult,	and	important	to	one	that	is	somewhat	important	but	does	not	require	much	thought.				I	feel	relief	rather	than	satisfaction	after	completing	a	task	that	requires	a	lot	of	mental	effort.			It’s	enough	for	me	that	something	gets	the	job	done;	I	don’t	care	how	or	why	it	works.			I	usually	end	up	deliberating	about	issues	even	when	they	do	not	affect	me	personally.				Questions	were	rated	on	a	5	point	Likert	scale:		Extremely	uncharacteristic	of	me,	Somewhat	uncharacteristic	of	me,	Uncertain,	Somewhat	characteristic	of	me,	Extremely	characteristic	of	me,	No	answer		Emotional	state	The	following	question	will	ask	you	questions	about	your	current	emotional	state.			8.		This	question	asks	you	how	you	feel	right	now.		Please	look	at	the	emotion	words	and	rate	the	extent	to	which	this	word	applies	to	you	in	this	moment.		Interested	 	 	 Irritable	Distressed	 	 	 Alert	Excited	 	 	 Ashamed	 	Upset		 	 	 Inspired	Strong	 	 	 Nervous	Guilty		 	 	 Determined	Scared	 	 	 Attentive	Hostile	 	 	 Jittery	Enthusiastic	 	 	 Active	Proud		 	 	 Afraid		Questions	were	rated	on	a	5	point	Likert	scale:		Very	slightly	or	not	at	all,	A	little,	Moderately,	Quite	a	bit,	Extremely,	No	answer	 		 172	Health	condition	knowledge		The	following	questions	will	test	your	knowledge	of	a	health	condition.			9.				Have	you	heard	of	the	condition	________________________?			acoustic	neuroma,	Bell’s	palsy,	Crohn’s	disease,	lupus,	meningioma		_________________________________________________________________________		10.		What	do	you	think	of	when	you	hear	the	words	________________________?			acoustic	neuroma,	Bell’s	palsy,	Crohn’s	disease,	lupus,	meningioma	________________________________________________________________________		Health	condition	The	following	question	asks	you	to	read	a	scenario	involving	a	health	condition.			11.		Please	read	the	scenario	and	answer	the	question	below.			Your	doctor	tells	you	that	you	have	an	acoustic	neuroma,	a	noncancerous	tumour	located	in	your	ear	and	close	to	your	brain.		It	has	a	number	of	side	effects,	the	most	common	being	hearing	loss	in	the	tumour	ear;	others	include	facial	paralysis,	loss	of	brain	function,	and	even	death.		The	tumour	grows	at	a	rate	of	1.5mm/yr.		Treatment	options	are	observation,	surgical	removal	or	radiation.				 173	Please	indicate	whether	you	have	read	the	scenario.			Yes	No	No	answer		Post-scenario	emotional	state	The	following	question	will	ask	you	about	your	current