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The influence of personality and demands of the environment of prospective memory performance Cuttler, Carrie 2004

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T H E I N F L U E N C E OF P E R S O N A L I T Y A N D D E M A N D S OF T H E E N V I R O N M E N T ON P R O S P E C T I V E M E M O R Y P E R F O R M A N C E by CARRIE CUTTLER B. A., The University of British Columbia, 2001 A THESIS SUBMITTED IN PARTIAL FULFILMENT O F T H E R E Q U I R E M E N T S FOR T H E D E G R E E O F M A S T E R OF A R T S in T H E F A C U L T Y OF G R A D U A T E STUDIES Department of Psychology, Cognitive Systems Programme We accept this thesis as conforming to the reqyrfed standard  T H E UNIVERSITY OF BRITISH C O L U M B I A July, 2004 © Carrie Cuttler, 2004  THE UNIVERSITY OF BRITISH COLUMBIA  FACULTY OF GRADUATE STUDIES  Library Authorization  In presenting this thesis in partial fulfillment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission.  Name of Author  ™Y  f T h 6 S i S :  (please  print)  r  lh  05/OS/goo -/ 1  i niter  iVMlWCr  Date (dd/mm/yyyy)  of  ^ r e o n o M /  Degree:  ^no<  r W ^ r k  rv£  Year:  Department of The University of British Columbia Q ' Vancouver, BC Canada  grad.ubc.ca/forms/?formlD=THS..  page 1 of 1  last updated: 20-M-04  II  Abstract Prospective memory is memory for recollecting intentions, plans, promises, and agreements. Individuals' performance on tasks requiring prospective memory varies a great deal. W e explored whether some of this variability stems from individual differences in personality and demands of the environment. A s a secondary objective we explored whether the age-related changes in prospective memory performance that have previously been attributed to declining cognitive resources can also be explained by age-related differences in personality and demands of the environment. Participants were community-dwelling healthy individuals (n = 141) between 18 and 81 years of age. Participants completed three different prospective memory tasks. Two of these tasks were lab-based - the intention had to be executed in the laboratory, while the third was field-based - the intention had to be executed in the context of the participants' daily life and activities. Participants also completed various indicators of personality, demands of the environment, and cognitive ability. The results indicated that personality and demands of the environment reliably predicted who will succeed and who will fail on all three prospective memory tasks. However, the best predictors of performance varied across the three prospective memory tasks. Specifically, conscientiousness predicted performance on the field task and one of the lab tasks while socially prescribed perfectionism and neuroticism each predicted performance on one of the lab tasks. Accordingly, the influence of personality and demands of the environment on the relationship between age and prospective memory performance also varied across the three tasks. On some prospective memory tasks age-related differences in personality and demands of the environment compounded with older adults' declining cognitive resources to impair prospective memory performance while  on other tasks they acted as a partial or a complete buffer against these declining cognitive resources.  iv Table of Contents Abstract  »  Table of Contents  iv  List of Tables  vi  List of Figures  vii  Acknowledgments  viii  Introduction Previous Research Current Directions Primary Objective Secondary Objective  1 4 8 9 10  Method Participants and Design Instruments Revised N E O Personality Inventory Revised (NEO Pl-R) Multidimensional Perfectionism Scale (MPS) Balanced Inventory of Desirable Responding (BIDR) Martin and Park Environmental Demands Inventory (MPED) Rey Auditory Verbal Learning Test (RAVLT) Trail Making Test (TMT) Color-Word Stroop Test (Stroop) Digit Span Backward Test (DSB) North American Adult Reading Test (NAART) Questionnaire Task Plug-In the Phone Task Confirmation Call Task Successful Interview Unsuccessful Interview Procedure  11 11 12 12 13 13 14 14 15 15 16 16 16 17 18 19 20 20  Data Analysis Data Preperation Descriptive Statistics N E O Pl-R MPS BIDR MPED RAVLT TMT Stroop DSB NAART  22 22 22 22 23 23 23 24 24 24 25 25  V  Prospective Memory Performance Instructional Manipulation Overall Performance Follow-up Interviews Inter-predictor Correlations Main Data Analysis Strategy Primary Objective Secondary Objective  26 26 27 28 29 30 30 31  Results Primary Objective Questionnarie Task Plug-In the Phone Task Confirmation Call Task Secondary Objective Questionnarie Task Plug-In the Phone Task Confirmation Call Task  33 33 33 34 35 35 35 37 39  Discussion Primary Objective Secondary Objective Limitations Conclusions  41 41 46 49 50  References  52  Figure Captions  70  Appendix  73  vi List of Tables Table 1: A List of all Instruments and Tasks Assigned to Participants, Arranged According to When they were Administered, with Time Required to Complete Each of Them ....57 Table 2: Basic Descriptive Statistics for Each of the Main Variables Indexed by Each of the Questionnaires 58 Table 3: Basic Descriptive Statistics for the Variables Assessed by Each of the Neuropsychological Tests  59  Table 4: The Results of a Principal Component Analysis of Performance on the Neuropsychological Tests, with Loadings on the First Component  60  Table 5: Correlations Among Age, Ten Aspects of Personality, and Two Demands of the Environment 61 Table 6: Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Personality and Demands of the Environment 62 Table 7: Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Age  63  Table 8: Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Cognitive Ability and Age 64 Table 9: Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Personality, Demands of the Environment, and Age  65  Table 10: Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Personality, Demands of the Environment, Cognitive Ability, and Age  67  vii List of Figures Figure 1: Instructional Condition x Prospective Memory Task  71  Figure 2: Overall Prospective Memory Task Success Rates  72  VIII  Acknowledgments There are so many people that assisted, guided, and supported me in various stages of this project that I would like to thank. First, I would like to acknowledge all of the participants for the time and energy they invested in the project. I am very grateful to Amanda LaMarre for taking the time out of her busy schedule to assist me in countless hours of participant testing and for sharing in that experience with me. I'd also like to thank Ankit Sondhi and Catriona Wright for their careful and dedicated data entry. I want to thank Ralph Hakstein for his dedication to statistics and his guidance with the statistical analyses. I am also grateful to the people in statistics consulting. Darcy Hallet, Mike Papsdorf, and Kevin Williams took me along a crazy path that finally led to logistic regression. I want to thank my friend and lab mate, Jess Gao, for helping me straighten out my thoughts, providing valuable feed-back, and making me smile. I thank all of my friends for listening to me ramble on about this project, for helping me take my mind off of it when I needed to, and at times for reminding me of its importance by frustrating me with their prospective memory failures. I also want to thank my family. Throughout the entire course of my academic career my parents have supported me emotionally and at times financially. My husband has always supported my passion for work and psychology. He took care of me when I didn't have the time to take care of myself and taught me the importance of putting my work aside and enjoying life. I am grateful to the Elizabeth Young Lacey foundation, the Natural Sciences and Engineering Council, the Michael Smith Foundation for Health Research, and my  ix supervisor, Peter Graf, for believing enough in my potential to financially support me and my research. I would like to thank my committee members, Geoff Hall and Paul Hewitt, for their thoughtful considerations of my thesis and for lending their time and expertise to help me improve it. Finally, I can't thank my supervisor Peter Graf enough for his time and patience in sharing his immense knowledge of prospective memory, experimental methodology, and statistics. He has taught me to think and write more clearly, laugh at myself, and enjoy my work. His tireless editing, revisions, and intellectual support made my thesis something I can be proud of. I am fortunate to have him as a mentor.  1 Introduction From relaying a message to picking up milk on the way home from work, our days are filled with delayed intentions. Often when we realize that something needs to be done we postpone it and form a plan or intention to carry out the action at a later time. Successfully completing these delayed intentions is dependent in part on our prospective memory. Prospective memory is the ability to remember to carry out tasks at a later time. It is memory for future actions including plans, promises/agreements, and intentions (Einstein & McDaniel, 1996; Graf & Uttl, 2001; Meacham & Dumitru, 1976). While there are many different varieties of prospective memory tasks, the present paper will focus on those intentions that require execution once, are generated by someone else, and that have a delay between forming the intention and executing it. These types of tasks are known as one-off, other-generated, prospective memory proper tasks. Individuals' performance on tasks requiring prospective memory varies a great deal. Some people consistently follow through with their agreements and intentions. They can be relied on to be where they said they would be and to be punctual. Other people readily break their agreements and fail to follow through with their intentions. They cannot be depended on and frequently show up late or miss scheduled appointments and social obligations. W e wanted to explore whether individuals who follow through with their agreements and intentions differ in terms of personality and demands of the environment from those who readily break their agreements and intentions. Therefore, the general goal of this paper is to explore whether individual differences in personality and demands of the environment can explain some of the variability in prospective memory performance.  2 Prospective memory failures can lead to a variety of consequences. These consequences may be trivial, for instance after you have settled in for the night you have to leave your home to pick up the milk you forgot to buy after work. Or they may be more serious, for instance failing to take an important medication, turn off the stove, or meet a crucial deadline at work. A s these examples illustrate prospective memory failures can impact our health, our safety, and our professional lives and their impact may be transient or more long lasting. Moreover, some types of prospective memory failures, namely broken promises/agreements, also have interpersonal consequences. Failures do things, such as, relay an important message, attend a social event, give medication to a sick child, or fulfill a commitment affect not only ourselves, but they affect others and can in turn affect our relationships with others. A variety of factors influence the way prospective memory failures are interpreted by others, including the consequences of the failure. Cuttler and Graf (2003) showed that when the consequences of a prospective memory failure are trivial, we attribute the failure to a lack of motivation, distraction, or carelessness. When the consequences of the failure are more serious however, we attribute the failure to uncontrollable external circumstances. In other words we tend to attribute low impact prospective memory failures to internal factors and high impact prospective memory failures to external factors. Munsat (1966) made a related observation, suggesting that when one fails to recall past information or events her/his memory is likely to be blamed. On the other hand, he suggests that when one fails to follow through with a future intention or agreement the failure is attributed to the character of the individual rather than to her/his memory. The individual is perceived as unreliable, untrustworthy, and irresponsible rather than as having an unreliable memory. In other words, prospective memory failures are attributed to personality and social dimensions rather than cognitive ability.  3 Winograd (1987) also remarked on the multidimensional nature of prospective memory performance suggesting that success also depends on many non-cognitive factors such as, motivation, compliance, reward, and conflicting goals (Winograd, 1987). From our own experience, it is evident that when the time comes to carry out an intention or follow through with an agreement we may remember and complete the activities, forget them, or purposefully abandon them. Between forming and executing intentions much can change and we may no longer be motivated to complete the activities, feel that they are no longer worthwhile/important, or we may become too busy and reprioritize our limited time and resources. To be successful on tasks requiring prospective memory, we need to remember the intentions and we need to follow through with them. Thus, prospective memory task performance requires much more than just memory While it is well recognized among prospective memory researchers that prospective memory performance has both social and cognitive elements the vast majority of investigations have focused on the latter. Researchers have been busy exploring cognitive aspects of prospective memory in an attempt to differentiate prospective memory from retrospective memory, to understand the underlying brain mechanisms, and to create a comprehensive theory of how intentions are stored and retrieved. Such research has focused on the influence of attention demands (Einstein, Smith, McDaniel, & Shaw, 1997; Otani, Landau, & Libkuman, 1997), sensory modality (Passolunghi, Bradimonte, & Cornoldi, 1995), retention interval (Hicks, Marsh, & Russell, 2000; Nigro & Cicogna, 2000), distinctiveness of retrieval cues (Cohen, Dixon, Lindsay, & Masson, 2003; McDaniel & Einstein, 1993; West, Wymbs, & Jukubek, 2003), brain damage (Cockburn, 1996; Schmitter-Edgecomb & Wright, 2004) and numerous other factors.  4  Researchers have also used age to explore the cognitive demands of various types of prospective memory tasks (Dobbs & Rule, 1987; Maylor, 1993; 1996; Uttl, Graf, Miller, & Tuokko 2001). This line of research has been guided by Craik's (1983; 1986) suggestion that prospective memory performance places a high demand on processing or cognitive resources. Craik (1983; 1986) proposed that since processing or cognitive resources decline with age, prospective memory task performance should show large age-related declines. Research exploring prospective memory's cognitive demands is crucial to advance our understanding of this important cognitive function; however, it leaves much to be desired in advancing our understanding of the social factors that influence prospective memory performance. The present research was designed to complement previous research by exploring the influence of some of these social factors on prospective memory performance. Specifically we focused on exploring how prospective memory performance is influenced by various personality traits, such as, conscientiousness, perfectionism, and neuroticism and demands of the environment, such as, busyness. Previous  Research  To our knowledge there are only three previously published studies that have explored the influence of personality on prospective memory performance. Of these studies, two investigated actual prospective memory task performance whereas the third used a proxy of performance, a self-report measure of prospective memory. Searlman (1996) conducted one of the first and one of the most comprehensive explorations of the influence of personality on prospective memory performance. His study focused on the influences of Type A / B personality, obsessive compulsiveness, self-actualization, and self-monitoring behaviour on a variety of prospective memory tasks using an undergraduate sample. He found that Type A personality was correlated  5 with reminding an experimenter to place a phone call, r(58) = .28, p < .05, and that higher self actualization was related to giving this reminder more quickly, r(48) = -.35, p < .05. Type A personality was also found to be related to returning a card to the lab for credit more quickly, r(54) = - 29, p < .05, and with remembering to report the name of a favourite television show, x 6 . 4 5 , p < .05; n = 62. Searlman (1996) concluded that 2=  compared to Type B individuals, Type A individuals are more likely to succeed on interpersonal and personally important prospective memory tasks. Around the same time as Searlman reported his study, Goschke and Kuhl (1996) completed a study that explored individual differences in the persistence of intentions. This study appeared in a chapter in the first book on prospective memory and thus very little detail is provided. Nevertheless, Goschke and Kuhl (1996) categorized participants as either state or action orientated, and instructed them to learn two short scripts of action sequences. Half of the participants were told they would have to execute one of the scripts later (execution condition). The other half of the participants were told they would observe the experimenter performing one of the scripts later and that they should look for mistakes in the execution (observation condition). The second script served as a control for both groups. After learning the scripts, participants completed a word recognition test for words from the studied scripts and their reaction times were recorded. Prospective memory was assessed after the recognition test by measuring whether or not participants in the execution condition executed the script. The goal of the study was to explore the influence of state vs. action orientation on prospective memory performance and on a mental construct believed to underlie prospective memory - the intention superiority effect. Goschke and Kuhl (1996) define the intention superiority effect as the tendency for representations of intended actions to persist in a state of heightened activation. In other words, materials related to  6 an intention are held in memory in some privileged manner. Goschke and Kuhl (1996) found evidence in support of the intention superiority effect. That is, they found that reaction times were faster for words from the script that had to be executed as compared to words from the control script, but, there was no difference in reaction times for words from the script that had to be observed and words from the control script. More important to the current focus, Goschke and Kuhl (1996) found the intention superiority effect in state orientated participants only and concluded that action orientated participants deactivate intention related material relatively fast and focus attention on the current task. However, this did not reflect on actual prospective memory performance. Action orientated participants performed equivalently to state orientated participants on the prospective memory task. In a more recent study, Heffernan and Ling (2001) explored the relationship between extraversion and prospective memory performance using an undergraduate sample. The authors used a questionnaire, called the Prospective Memory Questionnaire, to assess prospective memory performance. This questionnaire asks participants to rate the frequency with which various prospective memory failures occur. It contains two subscales; one measures the frequency of short-term habitual prospective memory failures and the other measures the frequency of long-term episodic prospective memory failures. The authors found a main effect for personality; that is, individuals who scored high on extraversion rated their prospective memory better than individuals who scored high on introversion, F(1, 52) = 7.12, p < .01. Due to the self-report nature of the prospective memory measure these findings do not directly speak to the relationship between extraversion and actual prospective memory performance. A s the authors themselves suggest, other measures of prospective  7 memory are needed to confirm the relationship between extraversion and prospective memory performance A related line of research comes from the literature on the relationship between personality and retrospective memory performance. Again very little work has explored these relationships and most of the work that has been conducted has focused on extraversion and neuroticism. Extraversion is typically found to be modestly related to increased performance on word recall tasks with correlations ranging from about .03 to.22 while neuroticism is typically found to be modestly related to decreased performance with correlations ranging from about -.10 to -.23. (Ackerman & Heggestad, 1997; Arbuckle, Gold, Andres, Schwartemann, & Chaikelson, 1992; Hultsch, Hertzog, Small, & Dixon, 1999; Meier, Perrig-Chiello, & Perrig, 2002). These findings suggest that there is a connection between personality and memory. That being said, most prospective memory researchers will argue that prospective memory is a distinct form of memory (Graf & Uttl, 2001). Indeed, prospective memory generally shows only a weak relationship with retrospective memory (Einstein & McDaniel, 1990; Graf & Uttl, 2001). Although we do not directly compare the influence of personality on pro- vs. retrospective memory, due to the social dimensions of many prospective memory tasks, including the tasks employed in the present study, we would predict, that the relationships between personality and prospective memory will be stronger than those found with retrospective memory. To our knowledge Martin and Park's (2002) study is the only previous study that has explored the influence of demands of the environment on prospective memory performance. Demands of the environment were first introduced and operationalised in Martin and Park's (2002) study. The authors describe two aspects of environmental demands: Busyness and routine. Busyness is defined as how engaged people are.  8 Routine is defined as how frequently people's daily behaviours occur at the same time of day. The items used to measure busyness were designed to assess the density of day-to-day events and the amount of time the individual has available to perform them (Martin & Park, 2002). An example of an item measuring busyness is: "How often do you have too many things to do each day to actually get them all done?" The items used to measure routine were designed to indicate how frequently daily behaviours occur at the same time of day. A n example of an item measuring routine is: "How often do you eat all of your meals at the same time each day and night?" In their assessment of the psychometric properties of the Martin and Park Environmental Demands Questionnaire (MPED), Martin and Park (2002) explored the relationship between reported levels of busyness and medication taking errors in a sample of rheumatoid arthritis patients. The authors directly measured medication taking errors by having participants use medication bottles that track when medications are removed from the bottle. The authors found that medication taking errors were positively related to busyness, rfA 19) = .38, p < .001. Although participants' level of daily routine was measured, unfortunately its relationship with medication taking errors was not discussed. Current Directions The very small literature that has focused on the influence of various personality traits and demands of the environment on prospective memory performance suggest that this is an area ripe for exploration. While researchers have looked at some aspects of personality and demands of the environment, for instance, Type A / B personality, extraversion, and busyness, many questions have been left unanswered. For example, what other aspects of personality and demands of the environment are related to prospective memory performance? Do personality and demands of the environment account for age-related changes in prospective memory performance?  9 The present study was designed to expand our knowledge of the influence of personality and demands of the environment on prospective memory performance and to answer the above remaining questions. To this end, we recruited a sample of healthy community-dwelling adults and had them complete a series of questionnaires that measured various personality traits and demands of their environment. Participants also completed a battery of neuropsychological tests. During the course of the study participants were assigned three separate one-off, other-generated, prospective memory proper tasks. Primary Objective. Our primary objective was to explore whether prospective memory performance is influenced by personality and demands of the environment. Individuals vary a great deal in their prospective memory performance. While some individuals can be relied on to follow through with their intentions and agreements others cannot. W e believed that some of this prospective memory performance variability could be explained by differences in personality and demands of the environment. For instance, it seems highly likely that someone who is very conscientious would perform better on a prospective memory task than someone who is less conscientious. Similarly it seems reasonable to believe that someone who is very busy would perform worse on a prospective memory task than someone who is less busy. Our goal was to test these and other related intuitions. There are numerous personality traits that would be interesting to explore in relation to prospective memory performance. W e limited our exploration to nine personality traits: Conscientiousness, neuroticism, extraversion, agreeableness, openness to experience, self-oriented perfectionism, other-oriented perfectionism, socially prescribed perfectionism, and self-deceptive enhancement. A fuller description  10 of each of these personality traits is provided in the Appendix. In terms of demands of the environment we explored individuals' levels of busyness and routine. Secondary Objective. W e also had a secondary objective for this study. W e wanted to explore whether age-related changes in prospective memory performance can be accounted for by differences in personality and demands of the environment. A s discussed earlier, most prospective memory researchers have explored the influence of cognitive ability on prospective memory performance and many researchers have used age to explore such influences. Craik (1983; 1986) has suggested that more than other types of memory, prospective memory relies on the availability of processing or cognitive resources. He proposed that because processing or cognitive resources decline with age, prospective memory task performance should show the largest agerelated declines. Using lab tasks of prospective memory, researchers have found support for this theory (Dobbs & Rule, 1987; Maylor, 1993; 1996; Uttl, Graf, Miller, & Tuokko, 2001) and a recent meta-analysis concludes that older adults perform worse than younger adults on lab prospective memory tasks (Henry, MacLeod, Phillips, & Crawford, 2004). When the prospective memory task needs to be executed in the context of the participant's day-to-day life, however, older adults outperform their younger counterparts (Henry et al., 2004). This finding is clearly inconsistent with Craik's (1983; 1986) theory that prospective memory performance should show large age-related declines. Researchers have tried to explain this latter effect by attributing older adults' superior performance on field prospective memory tasks to numerous non-cognitive factors, including increased motivation to complete the task (Patton & Meit, 1993), increased experience using prospective memory in everyday life (Maylor, 1996), differences in lifestyle (Poon & Schaffer, 1982), and increased use of external memory aids  11 (Moscovitch, 1982). In other words, these authors suggest that older adults are able to overcome their limited processing or cognitive resources and improve their prospective memory performance in their natural environment through non-cognitive factors. The finding that older adults have superior performance on field prospective memory tasks and the use of non-cognitive factors to explain this superior performance points to the importance of exploring other ways that older adults differ from younger adults before attributing age-related changes in lab prospective memory performance to cognitive ability alone. Not only do older adults differ from younger adults in their availability of processing or cognitive resources but they also differ in terms of personality and demands of the environment. Conscientiousness and agreeableness increase across the lifespan while neuroticism decreases (Costa, McCrae, Zonderman, Barbano, Lebowitz, & Larson, 1986; Goldberg, Sweeney, Merenda, & Hughes, 1998; Srivastava, John, Gosling, & Potter, 2003). Further, Martin and Park (2001) found that older adults report being less busy than do younger adults. If indeed personality and demands of the environment influence prospective memory performance then differences in older adults' performance on prospective memory tasks may also be explained by differences in personality or demands of the environment across the lifespan. W e therefore also explored whether age-related changes in prospective memory performance can also be attributed to differences in personality and demands of the environment. Method Participants and Design W e recruited 141 community-dwelling adults through advertisements in a free local newspaper. Prior to testing, participants were screened for neurological conditions, psychiatric diagnoses, and developmental disabilities. Participants' age ranged from 18  12 to 81 years with a mean of 45.56 years (SD=16.02). Education ranged from 7 to 26 years with a mean of 15.36 years (SD=2.84). One hundred and two (72.34%) of the participants were Caucasian, 33 (23.40%) were Asian, 3 (2.13%) were First Nations, 2 (1.42%) were half-Caucasian and half-Asian, and 1 (.71%) was African Canadian. Forty participants (28.37%) learned English as a second language. Of those participants, the number of years they have spoken English ranged from 6 to 65 years with a mean of 31.78 years (SD=17.41). Forty-three of the participants were male and 98 were female. The overall design of the study was correlational. However, the design also included a 2 x 3 mixed factorial manipulation that had Instructional Condition (informed, naive) as a between subjects factor and Prospective Memory Task (Questionnaire task, Plug-In the Phone task, Confirmation Call task) as a within subject factor. In the informed condition participants were told that the prospective memory tasks were used to examine their ability to remember to do things at a later time. In the naive condition participants were not given this information. Participants were randomly assigned to one of the two conditions (informed, naive). The resulting groups did not differ in age, r(139) = 1.04, p > .05, gender, x = .94, p > .05, years of education, f(139) = 1.80, p > .05, 2  English as a second language, x = 02, p > .05, years speaking English, £(139)= -.80, p 2  > .05, or ethnicity, F(1, 140) = .03, p > .05. This research was conducted with the approval of the University of British Columbia behavioural ethical review board. Participation in the study required approximately 1 hour and 45 minutes and participants received a $25 honorarium. Instruments Revised NEO Personality Inventory (NEO Pl-R). The N E O P l - R is a standardized self-report personality inventory developed by Costa and McCrae (1992). The inventory contains 240 statements that participants have to rate using a 5-point scale, with scale  13 points marked: Strongly disagree, disagree, neutral, agree, strongly agree. There are five subscales within the inventory which assess five personality domains: Neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. Each of the subscales provides a reliable measure of its corresponding personality construct, as evidenced by high reliability coefficients (neuroticism =. 93, extraversion = .90, openness to experience = .89, agreeableness = .95, conscientiousness = .92) and testretest reliabilities (neuroticism =. 87, extraversion = .91, openness to experience = .86, agreeableness = .63, conscientiousness = .79) (Costa & McCrae, 1992). Multidimensional  Perfectionism  Scale (MPS). The M P S is a standardized self-  report perfectionism inventory developed by Hewitt and Flett (1991). The scale contains 45 items that participants have to rate using a 7-point scale, that extends from disagree (1) to agree (7). It measures 3 dimensions of perfectionism: Self-oriented perfectionism, other-oriented perfectionism, and socially prescribed perfectionism. All three subscales are highly reliable as evidenced by their reliability coefficients (self-oriented perfectionism = .86 to .91, other-oriented perfectionism = .71 to .82, socially prescribed perfectionism = .85 to .87), and test-retest reliabilities (self-oriented perfectionism = .88, other-oriented perfectionism = .85, socially prescribed perfectionism = .75) (Enns & Cox, 2004; Hewitt & Flett, 1988; O'Connor & O'Connor, 2003). Balanced Inventory of Desirable Responding (BIDR). The BIDR (Paulhus, 1998) is a self-report inventory which assesses individuals' tendencies to respond in a socially desirable manner. The inventory contains 40 items that participants have to rate using a 7-point scale, where items 1, 5, and 7 are labeled not true, somewhat, and very true, respectively. The scale measures both impression management (i.e., the tendency to consciously respond in a socially desirable manner) and self-deceptive enhancement (i.e., the tendency to have illusions of control and overconfidence). Both components  14 are reliable as evidenced by their reliability coefficients (impression management = .77 to .85, self-deceptive enhancement = .67 to .77) (Paulhus, 1991). Martin and Park Environmental Demands Inventory (MPED). The M P E D , developed by Martin and Park (2002), is a self-report inventory which assesses the dayto-day demands of the environment, on an individual. More specifically, it measures how busy people are and how much their lives are governed by routine or recurrent activities. The scale contains 11 items that participants have to rate the frequency of using a 5-point scale, with scale points marked: Never, rarely, sometimes, often, very often. The scale yields two components: Busyness and routine. Both components are reliable as evidenced by their reliability coefficients (busyness = .88, routine = .74) (Martin & Park, 2002). Rey Auditory Verbal Learning Test (RAVLT). A slightly modified version of the standardized R A V L T (Lezak, 1995) was administered to assess retrospective memory. Participants were asked to listen to a list of 15 words (List A), and then to repeat back as many words as they could remember. In this test, List A was presented for a total of 3 study-test trials. After this phase, a new list of 15 words (List B) was presented and tested. When participants indicated that they could no longer recall any more words from List B, they were once again asked to recall all of the words from List A without renewed presentation. Twenty minutes later, participants were asked to recall the words from List A again (delayed recall test). Once they indicated that they could no longer recall any more words from List A, participants were given a recognition test. The recognition test consisted of a short paragraph that contained 30 underlined words, 15 of which were from List A and 15 of which were distracters. Participants were instructed to circle whichever of those 30 words were in List A. The number of words correctly recalled/recognized in each trial was scored. The R A V L T has been shown to be reliable;  15 test-retest reliabilities are between .63 and .84 for the immediate recall trials, between .57 and .78 for the delayed recall trial, and between .28 and .64 for the recognition trial (Schmidt, 1996). Trail Making Test (TMT). In Part A of this standardized test (Reitan, 1992) participants are given a page with encircled numbers (ranging from 1 to 25) on it. Participants are instructed to draw a line as quickly and as accurately as possible from 1 to 2, 2 to 3, and so on, until they reach the last number. Upon completion of Part A participants are administered Part B. In Part B participants are given a page with encircled numbers and letters on it (numbers ranging from 1 to 13; letters ranging from A to L). Participants are instructed to draw a line as quickly and as accurately as possible from 1 to A, A to 2, 2 to B, B to 3, and so on, in order until they reach the end. The amount of time it takes to complete each part of the task and the number of errors made in each part, are recorded. Reliability scores for the TMT range from moderate to excellent for each part (Part A =.46 to .98, Part B = .44 to .90) (Spreen & Strauss, 1998). Color-Word Stroop Test (Stroop). W e used Graf, Uttl, and Tuokko's (1995) version of the Stroop test (Stroop, 1935). In Part 1 of this standardized test participants are given a page with colour words printed in black ink and are asked to read the words out loud as quickly and as accurately as possible. In Part 2, participants are given a page with X X X s printed in various ink colours and are asked to name out loud the ink colour of the X X X s as quickly and as accurately as possible. Finally, in Part 3, participants are given a page with colour words printed in incongruent coloured ink (e.g., the word blue printed in red ink). Participants are asked to name the ink colour in which the words are printed. The time it takes to complete each part of the test, as well as, the number of corrected errors and the number of uncorrected errors made in each part are  16 recorded. The test-retest reliability of the Stroop test is excellent with reliability coefficients of .90, .83, and .91 for the respective three parts of the test (Spreen & Strauss, 1998). Digit Span Backward Test (DSB). In this standardized test (Wechsler, 1981) participants are read a sequence of numbers and are asked to repeat them in backwards order. The number of digits contained in the sequences begins with 2 and progress one number at a time to sequences of 8 numbers. There are two sets of numbers for each sequence length and testing ceases once both are failed. The total number of trials successfully completed is recorded. The average reliability coefficient is .88 (Spreen & Strauss, 1998) North American Adult Reading Test (NAART).  In this standardized (Blair &  Spreen, 1989) test participants are given a sheet of paper with 61 words printed on it and are asked to read the words out loud. Participants' pronunciation of each word is scored and the total number of words pronounced incorrectly is recorded. The N A A R T is highly reliable as evidenced by its reliability coefficient (.93 to .94) and its interscorer reliability (.93 to .99) (Blair & Spreen, 1989; Uttl, 2002). Questionnaire  Task. The Questionnaire prospective memory task was  developed specifically for the present study. Participants were told that we wanted to know which questionnaire they found the most interesting; they were instructed to write down the name of this questionnaire after they completed a set of them. Half of the participants, those in the informed condition, were also told that they were being asked to do this because we are interested in their ability to remember to do things at a later time. Participants received two scores, one for the prospective component of the task and one for the retrospective component. Those participants who wrote down the name of the questionnaire they found the most interesting prior to returning the questionnaires  17 to the experimenter were given a score of 1 on the prospective component and a score of 2 on the retrospective component. Those participants who failed to provide this information prior to returning the questionnaires to the experimenter, were given a score of 0 on the prospective component and were asked: "Was there anything else you were supposed to do?" If the response was affirmative they were given a 2 on the retrospective component. If the response was negative then participants were further prompted with, "I asked you to write something on the last questionnaire". If they recalled what they were supposed to do in response to this cue they were given a 1 on the retrospective component. If they still couldn't recall what they were supposed to write, they were given a score of 0 and were told that they were asked to write down the name of the questionnaire they found the most interesting. Plug-In the Phone Task. A second prospective memory task that was inspired by Kvavilashvili (1987) was also developed for the present study. Prior to neurocognitive testing, the experimenter informed the participants that she was about to begin a battery of memory and attention tests, and that she would unplug the phone to prevent any disruptions. After the phone was unplugged participants were asked to remind the experimenter to plug it back in. They were asked to give this reminder after the tests were complete but before the debriefing. Half of the participants, those in the informed condition, were also told that they were being asked to do this because we are interested in their ability to remember to do things at a later time. At the completion of all of the neurocognitive tests participants were informed that testing was complete. The experimenter took several seconds to tidy up her materials and then informed participants that she was going to begin the debriefing. Participants who reminded the experimenter to plug her phone back in after being informed that testing was complete but before the debriefing began were given a score of 1 on the prospective component  18 of the task and a score of 2 on the retrospective component. Those who failed to remind her before the debriefing began were given a score of 0 on the prospective component and after the debriefing was complete were asked: "Was there anything else you were supposed to do?" If their response was affirmative they were given a score of 2 on the retrospective component. If they indicated that they did not know, then they were further prompted with the statement: "I asked you to do something when we were done the testing, do you remember what?" If they remembered what they were supposed to do in response to this cue, they were given a score of 1 on the retrospective component, otherwise they were told that they were asked to remind the experimenter to plug the phone back in. The experimenter then plugged the phone back in and gave them a score of 0 on the retrospective component. Confirmation Call Task. W e also developed a field prospective memory task for the present study. All participants were required to complete a follow-up telephone interview one week after the in-lab testing session. Before participants left the lab they were reminded of the date and time of this follow-up interview and were asked to call to confirm the interview appointment. Half of the participants, those in the informed condition, were again reminded that we are interested in their ability to remember to do things at a later time. Participants were given the phone number to call and were asked whether they could call after lunch or after breakfast. Participants who indicated yes were asked what time they usually finish their lunch/breakfast and were given a onehour time period during which to call the lab. This time period began with the time they usually finish their lunch/breakfast. Many participants indicated that they don't eat at any regular time. In these instances the experimenter attempted to set the time after an event the participant had planned for the day and when that failed participants were asked to call between 12:00 and 1:00, roughly after they finish their lunch. After the time  19 was arranged participants were told that it is very important that they only call during that window of time because calling outside that time window could result in them disrupting a testing session or us not receiving the message. Participants who called the lab to confirm their interview appointment during the agreed upon one-hour time period were given a prospective score of 1 and a retrospective score of 2. Participants who called outside of the agreed upon one-hour time period were given a score of 0 on the prospective component and a score of 2 on the retrospective component. For individuals who did not call at all, a prospective score of 0 was assigned and the retrospective component of the task was assessed during the follow-up interview. They were first asked: "Was there something else you were supposed to do?" If their response was affirmative they were given a retrospective score of 2, if they didn't successfully remember, they were told: "Before you left the lab I asked you to do something. Do you remember what I asked you to do?" Those who now successfully recalled the Confirmation Call task in response to this cue were given a score of 1 and those who still could not remember were given a retrospective score of 0. Successful Interview. The first part of the Successful Interview was concerned with the reasons participants called to confirm their interview appointment. Participants were first asked this question in an open-ended manner. They were then asked to rate how strongly they agree or disagree with a series of statements concerning the reasons that they called, using a 4-point scale, with scale points named: Strongly disagree, disagree, agree, strongly agree. The second part of the interview was concerned with the memory aiding strategies that participants used to try to help them remember to call to confirm their interview appointment. First they were asked in an open-ended manner, which, if any, memory aiding strategies they used. They were then presented with a series of prospective memory aiding strategies and were asked to rate a series of  20  statements concerning the strategies they used to remember to place the Confirmation Call, using a 3 point scale, with scale points named: Disagree, somewhat agree, agree. Participants who placed the confirmation call outside of the one-hour time period were scored as failing the task but were administered the Successful Interview. Due to the nature of the questions concerning the reasons for failing to place the Confirmation Call it made little sense to administer the Unsuccessful Interview to individuals who called at the wrong time. Unsuccessful  Interview. The first part of the Unsuccessful Interview was  concerned with the reasons participants didn't call to confirm their interview appointment. They were first asked this question in an open-ended manner. They were then asked to rate how strongly they agree or disagree with a series of statements concerning the reasons that they didn't call, using a 4-point scale, with scale points named: Strongly disagree, disagree, agree, strongly agree. The second part of this interview was identical to the second part of the Successful Interview. Again, it was concerned with the memory aiding strategies that participants used to try to help them remember to call to confirm their interview appointment. Procedure Table 1 shows the order in which the instruments were administered to each participant and the approximate time required for each. The prospective memory tasks are highlighted. Participants were tested one at a time, in a quiet room. Upon receiving informed consent we collected demographic information. Participants were asked for their age, for their educational history, for their occupation or past occupation in the case of retirement, about their ethnicity, and about their first spoken/native language. If the participant's first spoken language was not English then s/he was asked for the number of years that s/he has been speaking English. Gender was also recorded.  21  Participants were then administered the questionnaires. They were given the N E O Pl-R, the M P S , the M P E D , and the BIDR in that order. They were given instructions on how to complete each questionnaire and were asked to complete the questionnaires in the order in which they were received. They were asked to read the instructions on the top of each questionnaire before filling it out, to read each item carefully, and to mark their responses carefully. They were also asked to respond openly and honestly and were reminded that their responses would be kept confidential and anonymous. After participants received these instructions but before they began to fill out the questionnaires, the first prospective memory task — the Questionnaire task — was assigned. Participants were given as much time as needed to complete all four questionnaires. Upon completion, participants' performance on the Questionnaire task was assessed and the next prospective memory task — the Plug-In the Phone task — was assigned. After receiving the instructions for the Plug-In the Phone task participants were administered the R A V L T immediate recall, the TMT, the Stroop, the D S B , the R A V L T delayed recall, the R A V L T recognition, and finally the NAART, in that order. After all of the neurocognitive tests had been completed the experimenter informed participants that the testing was complete. She took several seconds to tidy up and put her materials away and then informed participants that she was going to give a brief debriefing of the session. Participants were given a limited debriefing, performance on the Plug-In the Phone task was assessed, and participants were paid. Before participants left the lab they were assigned the Confirmation Call prospective memory task. One week following the in-lab testing session, participants were contacted for the follow-up interview. Those who had called the lab to confirm their interview appointment were given the Successful Interview. Those who had failed to  22 confirm their interview appointment were given the Unsuccessful Interview. At the conclusion of the follow-up interview, all participants were fully debriefed. Data Analysis Data  Preparation All of the data were checked and corrected for transcription errors until accuracy  was greater than 99%. There were 47 missing values on the questionnaires (<.001%), and each of these was replaced with a neutral response. On the rare occasion when a participant gave more than one response for a questionnaire item, the average of the two responses was computed and when necessary was rounded towards the mean. The data were examined for univariate outliers, defined as scores falling more than three standard deviations away from their mean. Twelve univariate outliers were discovered and replaced with the nearest non outlying value, either -3 or +3 standard deviations from the mean. W e conducted a multivariate outlier analysis on the data from the personality and demands of the environment inventories. No subjects were identified as multivariate outliers by means of the Mahalanobis distance statistic, with the criterion set at x (12) = 32.91, and p < .001. 2  Descriptive  Statistics  NEO Pl-R. Scores for each of the five N E O Pl-R subscales - conscientiousness, extraversion, neuroticism, agreeableness, openness to experience - were computed according to Costa and McCrae (1992). Possible scores on each subscale range from 48 to 240, higher scores indicate a higher level of the corresponding personality trait. Descriptive statistics for scores on each of the five personality traits are offered in Table 2. All of the traits were normally distributed and had standard deviations comparable to previously published norms (Costa & McCrae, 1992). However, the means on all five traits were higher than published norms (Costa & McCrae, 1992). The high mean on  23 neuroticism was particularly surprising given that participants were screened for any previous psychiatric diagnoses, including depression and anxiety. It is possible that our elevated N E O P l - R means reflect the fact that we used a Canadian sample, and/or they could be due to sampling error resulting from participants' self-selection to a memory study advertised in a free local newspaper. M P S . Scores for each of the three M P S subscales - self-oriented perfectionism, other-oriented perfectionism, socially prescribed perfectionism - were computed according to Hewitt and Flett (2004). Possible scores on each subscale range from 15 to 105, higher scores indicate a higher level of the corresponding dimension of perfectionism. Descriptive statistics for scores on each of these facets of perfectionism are offered in Table 2. All of the traits were normally distributed and the means and standard deviations were comparable to previously published norms (Hewitt & Flett, 1991). BIDR.  Scores for each of the two BIDR subscales - impression management,  self-deceptive enhancement - were computed according to Paulhus (1991). Possible scores on each subscale range from 0 to 20, higher scores indicate a higher level of the corresponding type of socially desirable responding. Descriptive statistics are offered in Table 2. Scores on each subscale were normally distributed and the means and standard deviations were comparable to previously published norms (Paulhus, 1991). MPED.  Scores for each of the two M P E D subscales - busyness, routine - were  computed according to Martin and Park (2002). Scores on the busyness subscale can range from 7 to 35, while scores on the routine subscale can range from 4 to 20. Higher scores on each subscale indicate a higher level of the corresponding demand of the environment. Martin and Park (2002) are the only previous researchers to provide descriptive statistics for busyness and routine, but they reported on a sample of  24 rheumatoid arthritis patients. W e , therefore, offer the first normative data for this scale from a healthy community-dwelling sample in Table 2. The scores on each subscale were normally distributed and the means and standard deviations we obtained were comparable to those reported in Martin and Park (2002). RAVLT. Our modified version of the R A V L T yielded seven scores, each out of a possible 15. Descriptive statistics for these seven scores are offered in Table 3. Higher scores indicate better retrospective memory performance. Two of the scores were significantly negatively skewed, List A (trial 3) and the recognition test. The remaining five scores were normally distributed. All of the mean scores and their standard deviations were comparable with those reported in Lezak (1995) and Vakil and Blachstein (1997). A s expected, age was related to worse performance on all seven parts of the R A V L T (List A, trial 1, r = -.23, p < .01, List A, trial 2,r-  -.39, p < .001, List  A, trial 3, r = -.42, p < .001, List B, r = -.47, p < .001, List A, trial 4, r = -.28, p = .001, Delayed Recall, r= -.28, p = .001, Recognition, r= -.21, p < .05). TMT. For the TMT we calculated a difference score by subtracting the amount of time participants' required to complete Part A from the amount of time they required to complete Part B. Higher TMT scores indicate poorer performance. Descriptive statistics are offered in Table 3. While the resulting data were significantly positively skewed, the mean TMT difference score we obtained was comparable to the means reported in Spreen and Strauss (1998). A s expected, age was related to higher TMT difference scores, r = .40, p < .001. Stroop. For the Stroop we calculated a time difference score by subtracting the amount of time participants required to name the ink colours of the X X X s from the amount of time they required to name the ink colours of the incongruent colour words. Higher scores indicate poorer performance. Descriptive statistics are offered in Table 3.  25 Again, the resulting data were significantly positively skewed. However, the mean Stroop score we obtained was comparable to the means reported in Graf, Uttl, and Tuokko (1995). A s expected, age was related to higher Stroop difference scores, r = .48, p < .001. DSB. For the D S B task we calculated the total number of trials accurately completed. Possible scores range from 0 to 14, higher scores indicate a greater backwards digit span. Descriptive statistics are offered in Table 3. D S B scores were also significantly positively skewed. However, the mean D S B score we obtained was comparable to the means reported in Anstey, Matters, Brown, and Lord (2000) given our younger and more heterogeneous sample. A s expected, age was related to lower D S B total scores, r= -.30, p < .001. NAART.  For the N A A R T we added up the total number of mispronunciations  participants made. Possible scores range from 0 to 61, higher scores indicate more mispronunciations. A s shown in Table 3 the distribution of N A A R T scores we obtained was significantly positively skewed. However, the mean and standard deviation we obtained for the N A A R T scores was comparable to the means and standard deviations reported in Uttl (2002). Age was not related to N A A R T performance, r= -.06, p > .05. W e created a composite cognitive ability score to use in subsequent analyses. W e created this composite score by taking the first principal component of all of the cognitive ability scores: The seven R A V L T scores, the TMT difference score, the Stroop difference score, the D S B total score, the total N A A R T score. The resulting first principal component accounted for 48.29% of the variance. Although two eigenvalues were larger than one, inspection of the scree plot indicated that the one component solution was optimal. A s depicted in Table 4 most of the scores load highly on the component. A s  26 expected, age was negatively related to the composite cognitive ability score, r= -.45, p < .001. Prospective Memory  Performance  Instructional Manipulation.  In the present study, half of the participants, those in  the informed condition, were told that the prospective memory tasks were being assigned due to our interest in their ability to remember to do things at a later time. The other half of the participants, those in the naive condition, were not given this information. W e believed that informing participants that the tasks were being assigned as an assessment of their memory would change participants' perceptions of the nature of the tasks and result in an increase in performance. W e therefore analyzed participants' prospective memory scores using a 2 x 3 mixed A N O V A with Instructional Condition (informed, naive) as a between subjects factor and Prospective Memory Task (Questionnaire, Plug-In the Phone, Confirmation Call) as a within subject factor. A s depicted in Figure 1 there was an influence of Instructional Condition on the Plug-In the Phone task. Results of the analysis confirmed that there were main effects for Instructional Condition, F(1, 139) = 4.45, p < .05, M S = 25, and Prospective Memory e  Task, F(2, 278) = 31.15, p < .001, MS = .18. There was also a significant interaction e  between the two factors, F(2, 278) = 6.03, p < .005, MS = .18. Follow-up independent e  sample t-tests confirmed that the Instructional Condition did not influence participants' performance on the Questionnaire task, f(139) = -.41, p > .05, or on the Confirmation Call task, f(139) = .24, p > .05, but it had a large influence on the Plug-In the Phone task, f(139) = -3.80, p < .001. Informing participants that the task was meant to test their memory increased performance on the Plug-In the Phone task. W e suggest that the interaction between tasks and instructions occurred because naive participants already perceived both the Questionnaire task and the Confirmation Call task as part of the  27 study and its requirements. On the other hand, naive participants likely perceived the Plug-In the Phone task as a favour to the experimenter rather than as a test or a part of the study's requirements. Informing participants that the request was part of the study changed this perception and thus the nature of the task. It appears that this, in turn, resulted in elevated performance. Due to the strong effect of the Instructional Condition on the Plug-In the Phone task, subsequent analyses on the prospective memory tasks control for its influence. Overall Performance.  Figure 2 shows participants' overall success rates on each  of the three prospective memory tasks. The depicted success rates highlight the performance differences among the three tasks. These differences were not surprising. W e intentionally developed the three tasks to have different properties in order to gain a broader understanding of the potential relationships between prospective memory performance and personality and demands of the environment. While all three tasks were one-off, other-generated, prospective memory proper tasks the difficulty of the ongoing tasks, the relationship between the on-going tasks and the prospective memory tasks, the salience of the cues, the length of the retention intervals, and the tasks' relevance to the study differed across the three prospective memory tasks. Figure 2, shows success rates were the highest on the Questionnaire task. W e suggest that rates of success were highest on this task for three reasons. First, the task was related to the on-going activities, filling out the questionnaires. It is likely that participants were actively evaluating the questionnaires as they filled them out to determine which they found the most interesting. Second, the questionnaires, which would serve as a cue, were always in front of the participant. Finally, all participants, informed and naive, likely perceived the task as part of the study's requirements and hence placed more importance on completing it.  28 Performance on the Plug-In the Phone task was lowest. W e suggest that performance on this task was lowest because during the retention interval participants were engaged in unrelated activities, cognitive assessment. These on-going activities were not only unrelated but they would also have placed heavier demands on the participants' cognitive resources than would filling out the questionnaires. Further, the phone was on a different desk, off to the side of the participant. Its location would make it a less salient cue than the questionnaires were for the first prospective memory task. Finally, participants in the naive condition likely perceived the task as more of a favour to the experimenter rather than one of their duties as a participant and therefore placed less importance on it. Performance on the Confirmation Call task was intermediate. A s this task was executed while the participants were in the context of their daily life we cannot assess the tasks relationship with the on-going activities. Further, we cannot speak to the salience of the reminders the participants set up for themselves. However, we believe that performance on the task is between performance on the other two prospective memory tasks because it was perceived as both a favour to the experimenter and part of the study's requirements. Follow-Up Interviews W e used the follow-up interviews primarily for methodological reasons, in order to give purpose to the field prospective memory task - the Confirmation Call task. W e also used these interviews to explore potential avenues for future research. The interviews were a first attempt at designing telephone interviews to assess participants' use of prospective memory aiding strategies and the reasons that they give for succeeding and failing on a field prospective memory task. However, data resulting from these  29 interviews are not a focus of the present investigation, and thus they will not be discussed in this paper. Inter-predictor  Correlations  In Table 5 we display the inter-predictor correlations. These correlations are offered for two reasons. First, they demonstrate the relationships between age and personality and demands of the environment that need to be considered when investigating age-related changes in prospective memory performance. Second, the logistic regression analyses we used to analyze these data take correlations among the predictors into account and, similar to standard multiple regression, use only the unique variance accounted for by each predictor. A s expected, we found a variety of relationships between age and personality and demands of the environment. Specifically, older adults were found to be significantly less neurotic, more agreeable, and their lives follow more routine. W e did not, however, replicate Martin and Park's (2002) finding that older adults report being less busy. Also, as expected from the previous literature (Costa & McCrae, 1992; Enns & Cox, 2002; Paulhus & Reid, 1991) many of the personality traits we assessed were correlated with each other. For instance neuroticism was positively related to selforiented and socially prescribed perfectionism and was negatively related to extraversion, agreeableness, and conscientiousness. Conscientiousness was positively related to extraversion, agreeableness, self-oriented and other-oriented perfectionism. Further busyness and routine were negatively correlated with each other and were significantly correlated with several of the personality traits. For instance busyness was positively related to neuroticism, extraversion, and the three dimensions of  30 perfectionism, while routine was negatively related to neuroticism, openness to experience, and conscientiousness. Main Data Analysis  Strategy  The present study had two objectives. Our primary objective was to explore the influence of personality and demands of the environment on prospective memory performance. Our secondary objective was to explore whether age-related changes in prospective memory performance are mediated by cognitive ability, by personality and demands of the environment, or by a combination of these factors. Primary Objective. In order to address our primary objective we conduct three separate sequential logistic regression analyses, regressing each of the three prospective memory tasks onto the various predictors. In order to control for impression management - the tendency to consciously respond in a socially desirable manner and Instructional Condition, impression management and Instructional Condition were entered into the first step of each of the three analyses. The set of personality and demands of the environment predictors were entered into the second and final step. To assess the ability of the set of predictors to predict performance on each of the tasks we report the successful classification rates, the fit of each of the models, and the effect sizes. To explore which predictors were significantly related to task performance, we report and interpret the significant odds ratios in each of the three models. W e used logistic regression to address our questions because this is the standard method of regression analysis for dichotomous outcome variables (Hosmer & Lemshaw, 1989). This technique is a special case of standard regression but with some noteworthy differences. First, because the technique logarithmically transforms the dependent variables there are no assumptions of linearity, normality, or homoscedasticity (Tabachnick & Fidell, 2001). Second, logistic regression evaluates the  31 fit of the model with a chi-squared statistic rather than with an F statistic. Third, logistic regression yields a statistic called Nagelkerke R that is analogous to R . However, 2  2  Nagelkerke R should be interpreted as an effect size rather than as the amount of 2  variance accounted for, because the variance of a dichotomous dependent variable depends on the frequency distribution of that variable (Garson, n.d.). Similar to discriminant function analysis, logistic regression provides the rates of successful classification into each group based on the predictors. While other forms of multiple regression provide beta weights or semipartial correlations to assess the direction and strength of the relationship between the individual predictors and criterion, logistic regression provides odds ratios. A n odds ratio above one signifies a positive relationship between the predictor and criterion while an odds ratio below one signifies a negative relationship (Tabachnick & Fidell, 2001). For ease of communication we translated the negative odds ratios into the same metric as the positive ones by dividing one by the negative odds ratios. W e report both transformed and untransformed negative odds ratios in the data tables. Further, we standardize the independent variables before entering them into the logistic regression analyses. Standardizing the variables allows us to interpret the odds ratios as the amount the odds of a specific outcome are increased for every one standard deviation increase in a variable. Secondary Objective. The secondary objective of this study was to explore whether age-related changes in prospective memory performance are mediated by cognitive ability, by personality and demands of the environment, or by a combination of these factors. To assess whether age reliably predicts performance on each of the three prospective memory tasks we conduct three separate sequential logistic regression analyses, regressing performance on each of the three prospective memory tasks onto  32 age. In order to control for Instructional Condition and impression management, these variables are entered into the first step of the analyses as covariates. A g e is entered into the second and final step. To assess whether the relationships between prospective memory task performance and age are mediated by cognitive ability we conduct another three sequential logistic regression analyses, regressing performance on each of the three prospective memory tasks onto cognitive ability and age. Instructional Condition and impression management are entered into the first step of the analyses as covariates. Cognitive ability is entered into the second step and age is entered into the third and final step of the analyses. W e explore whether the change in the chi-squared statistic, after adding age, is significant. In order to assess whether the relationships between age and performance on the prospective memory tasks are mediated by personality and demands of the environment we conduct another series of sequential logistic regression analyses, regressing performance on each of the three prospective memory tasks onto personality, demands of the environment, and age. Again in order to control for Instructional Condition and impression management, these variables are entered into the first step of the analyses as covariates. Personality and demands of the environment are entered into the second step and age is entered into the third and final step of the analyses. W e explore whether the change in the chi-squared statistic, after adding age, is significant. Finally, we conduct three additional sequential logistic regression analyses, regressing performance on each of the three prospective memory tasks onto personality, demands of the environment, cognitive ability, and age. Information condition and impression management are entered into the first step of the analyses as  33 covariates. Personality and demands of the environment are entered into the second step, cognitive ability is entered into the third step, and age is entered into the fourth and final step of the analyses. Again, we explore whether the change in the chi-squared statistic, after adding age, is significant. Since this study is exploratory an alpha level of .05 was set for each part of each analysis. There has been so little work done in this area that the majority of these relationships have never been previously explored. W e felt it would be worse to miss potentially interesting relationships than to have inflated Type I error that replication would bear out. Results Primary  Objective  The primary objective of the present study was to explore the influence of personality and demands of the environment on prospective memory performance. To this end, we assessed whether a set of personality and demands of the environment variables were able to predict performance on each of three prospective memory tasks. W e also explored which specific personality traits and which specific demands of the environment were the best predictors of performance on each of the prospective memory tasks. Questionnaire  Task. For the Questionnaire task participants had to write the  name of the questionnaire that they found the most interesting after they had completed the entire questionnaire set. To assess whether the personality and demands of the environment variables reliably predict performance on this task we conducted a sequential logistic regression analysis. Impression management and Instructional Condition were entered into the first step of the analysis as covariates. The set of personality and demands of the environment variables - conscientiousness,  34 extraversion, neuroticism, agreeableness, openness to experience, self-oriented perfectionism, other-oriented perfectionism, socially prescribed perfectionism, selfdeceptive enhancement, busyness, routine - were entered into the next step of the analysis. The analysis was successful; it predicted 16.7% of the failures and 99.1% of the successes correctly, for an overall prediction success rate of 85.1%. The remaining results of the analysis are displayed in Column 1 of Table 6; they confirm that the set of personality and demands of the environment variables reliably predict performance on this task. The odds ratios show that only one of the predictors was significant, revealing that socially prescribed perfectionism was negatively related to performance. All else being equal, for every one standard deviation increase in socially prescribed perfectionism the odds of failing the task are multiplied by 2.70, that is, they are nearly tripled. Plug-In the Phone Task. For the Plug-In the Phone task participants had to remind the experimenter to plug the phone back in after all of the tests were completed but before the start of the debriefing phase. To assess whether the personality and demands of the environment variables reliably predict performance on this task we repeated the preceding analysis with the data from the Plug-In the Phone task. The analysis was successful; it predicted 78.8% of the failures and 68.9% of the successes correctly, for an overall prediction success rate of 74.5%. The remaining results of the analysis are displayed in Column 2 of Table 6; they confirm that the set of personality and demands of the environment variables reliably predict performance on this task. Further, the odds ratios show that two of the predictors, conscientiousness and neuroticism, achieved significance. All else being equal, for every one standard deviation increase in conscientiousness the odds of succeeding on the task are  35 multiplied by 2.22. Similarly, for every one standard deviation increase in neuroticism the odds of succeeding are multiplied by 4.37. Confirmation Call Task. For the Confirmation Call task participants had to call the lab to confirm the time and date of their follow-up interview during a one-hour time period. To assess whether the personality and demands of the environment variables reliably predict performance on this task we repeated the preceding analysis with the data from the Confirmation Call task. The analysis was successful; it predicted 54.4% of the failures and 81.0% of the successes correctly, for an overall prediction success rate of 70.2%. The remaining results of the analysis are shown in Column 3 of Table 6; they confirm that the set of variables reliably predict performance on this task. The odds ratios show that only one of the predictors contributed significantly to prediction of performance on the Confirmation Call task: Conscientiousness was positively related to performance. All else being equal, for every one standard deviation increase in conscientiousness the odds of succeeding on the task are multiplied by 1.92. Secondary  Objective  The secondary objective of this study was to explore whether age-related changes in prospective memory performance are mediated by cognitive ability, by personality and demands of the environment, or by a combination of these factors. To this end we first examined the relationship between age and performance on each of the three prospective memory tasks. W e then assessed whether age adds significant predictive ability after cognitive ability is controlled for, after personality and demands of the environment are controlled for, and after both of these factors are controlled for. Questionnaire  Task. To assess whether age reliably predicts performance on the  Questionnaire task we conducted a sequential logistic regression analysis predicting performance on the Questionnaire task. In order to control for Instructional Condition  36 and impression management, these variables were entered into the first step of the analysis. Age was entered into the second and final step. The results of the analysis are shown in Column 1 of Table 7; they reveal that age is a significant predictor of performance on the Questionnaire task. W e next explored whether the negative relationship between age and performance on this task is mediated by cognitive ability. To this end, we conducted a sequential logistic regression analysis predicting performance on the Questionnaire task. In order to control for Instructional Condition and impression management, these variables were entered into the first step of the analysis as covariates. Cognitive ability was entered into the second step and age was entered into the third and final step of the analysis. The results of the analysis are shown in Column 1 of Table 8; they reveal that cognitive ability is a significant predictor of performance on the Questionnaire task and that age does not add significant predictive value beyond that of cognitive ability. This pattern of results suggests that the negative relationship between age and performance on this task is mediated by cognitive ability. To assess whether the negative relationship between age and performance on the Questionnaire task is also mediated by personality and demands of the environment, another sequential logistic regression analysis was performed, predicting performance on the Questionnaire task. Instructional Condition and impression management were entered into the first step of the analysis as covariates, the personality and demands of the environment variables were entered into the second step, and age was entered into the third and final step of the analysis. The results of the analysis are shown in Column 1 of Table 9; they reveal that age does add significant predictive value beyond that of personality and demands of the environment. Further in the presence of age, agreeableness becomes a significant predictor of performance.  37 This pattern of results suggests that the personality and demands pf the environment variables do not mediate the relationship between age and performance on this task. W e next explored whether age adds significant predictive ability beyond personality, demands of the environment, and cognitive ability. Another sequential logistic regression analysis was performed, predicting performance on the Questionnaire task. Instructional Condition and impression management were entered into the first step of the analysis as covariates, personality and demands of the environment were entered into the second step, cognitive ability was entered into the third step, and age was entered into the fourth and final step of the analysis. The results of the analysis are displayed in Column 1 of Table 10. They reveal first that cognitive ability adds significant predictive value above personality and demands of the environment. Second, they reveal that age adds significant predictive value after personality, demands of the environment, and cognitive ability are controlled for. The overall pattern of results on the Questionnaire task suggests to us that cognitive ability mediates the negative relationship observed between age and prospective memory performance and that the personality and demands of the environment variables suppress the negative relationship between age and prospective memory performance. A s agreeableness became a significant predictor in the presence of age, we suggest that agreeableness is suppressing the negative relationship between age and performance on the Questionnaire task. That is, older adults' increased levels of agreeableness are partially compensating for the negative impact their declining cognitive resources have on performance on this task. Plug-In the Phone Task. To assess whether age reliably predicts performance on the Plug-In Phone task we repeated the sequential logistic regression analysis described in the first section of the preceding Questionnaire task analyses, this time  38 predicting performance on the Plug-In the Phone task. The results are displayed in Column 2 of Table 7; they reveal that age is a significant predictor of performance on the Plug-In the Phone task. In order to explore whether the negative relationship between age and performance on this task is mediated by cognitive ability we repeated the sequential logistic regression analysis described in the second section of the preceding Questionnaire task analyses, this time predicting performance on the Plug-In the Phone task. The results are displayed in Column 2 of Table 8; they reveal that cognitive ability is a significant predictor of performance on the Plug-In the Phone task and that age does not add significant predictive value beyond that of cognitive ability. This pattern of results suggests that the negative relationship between age and performance on this task is mediated by cognitive ability. To assess whether the negative relationship between age and performance on this task is also mediated by personality and demands of the environment, we repeated the sequential logistic regression analysis described in the third section of the preceding Questionnaire task analyses, this time predicting performance on the Plug-In the Phone task. The results are displayed in Column 2 of Table 9; they reveal that age does not add significant predictive value beyond that of personality and demands of the environment. These results suggest that personality and demands of the environment also mediate the negative relationship between age and performance on this task. W e next explored whether age adds significant predictive ability beyond personality, demands of the environment, and cognitive ability. The sequential logistic regression analysis described in the fourth section of the preceding Questionnaire task. analyses was repeated, predicting performance on the Plug-In the Phone task. The results of the analysis are displayed in Column 2 of Table 10. The results reveal first  39 that cognitive ability does not add significant predictive value above personality and demands of the environment. Second, they confirm that age does not add significant predictive value after personality, demands of the environment, and cognitive ability are controlled for. The overall pattern of results on the Plug-In the Phone task suggests that both cognitive ability and personality and demands of the environment mediate the relationship between age and prospective memory performance. Further, they suggest that cognitive ability does not add significantly to the prediction of performance on this task above personality and demands of the environment. Confirmation Call Task. To assess whether age reliably predicts performance on the Confirmation Call task we repeated the sequential logistic regression analysis described in the first section of the preceding Questionnaire task analyses, this time predicting performance on the Confirmation Call task. The results are displayed in Column 3 of Table 7; they reveal that age is not a significant predictor of performance on the Confirmation Call task. However, in contrast to the negative relationship between age and prospective memory performance observed in the two analyses of the lab tasks, age shows a positive, albeit non significant (p = .08), influence on performance on this field task. In order to explore whether the non significant positive relationship between age and performance on this task is mediated by cognitive ability we repeated the sequential logistic regression analysis described in the second section of the preceding Questionnaire task analyses, this time predicting performance on the Confirmation Call task. The results are displayed in Column 2 of Table 8; they reveal that cognitive ability is not a significant predictor of performance on the Confirmation Call task and that after cognitive ability is controlled for age is a significant predictor of performance on this  40 task. This pattern of results suggests that the positive relationship between age and performance on this task is suppressed by cognitive ability. In order to assess whether the non significant positive relationship between age and performance on the Confirmation Call task is mediated by personality and demands of the environment, we repeated the sequential logistic regression analysis described in the third section of the preceding Questionnaire task analyses, this time predicting performance on the Confirmation Call task. The results are displayed in Column 3 of Table 9; they reveal that age does not add significantly to the prediction of performance on this task beyond personality and demands of the environment. Further, in the presence of the personality and demands of the environment predictors, age loses its trend toward significance (p = .58). These results suggest that personality and demands of the environment mediate the positive, albeit non significant, influence of age on this task. W e next explored whether age adds significant predictive ability beyond personality, demands of the environment, and cognitive ability. The sequential logistic regression analysis described in the fourth section of the preceding Questionnaire task analyses was repeated, predicting performance on the Confirmation Call task. The results of the analysis are displayed in Column 3 of Table 10. The results confirm first that cognitive ability does not add significant predictive value above personality and demands of the environment. Second, they confirm that age does not add significant predictive value after personality, demands of the environment, and cognitive ability are controlled for. The overall pattern of results on the Confirmation Call task suggest to us that the personality and demands of the environment variables mediate the non significant positive relationship observed between age and prospective memory performance and  41 that cognitive ability suppresses the positive relationship between age and prospective memory performance. Discussion The primary objective of this study was to explore the influence of personality and demands of the environment on prospective memory performance. The secondary objective was to explore whether age-related changes in prospective memory performance are mediated by cognitive ability, by personality and demands of the environment, or by a combination of these factors. Primary  Objective  With respect to the first objective we found that personality and demands of the environment can reliably predict who will succeed and who will fail on prospective memory tasks. However, the specific personality traits that were significant predictors of performance varied across the three prospective memory tasks. Conscientiousness was positively related to performance on the field task and to performance on one of the lab tasks, neuroticism was positively related to performance on one of the lab tasks, and socially prescribed perfectionism was negatively related to performance on one of the lab tasks. Our study extends Heffernan and Ling's (2001) study. Heffernan and Ling (2001) explored the relationship between extraversion and prospective memory, using a selfreport measure of prospective memory and an undergraduate sample. They found that extraverts rate their prospective memory better than do introverts. Our investigation extends Heffernan and Ling's (2001) study in three ways. First, we explored a broader range of personality traits; second, we observed actual prospective memory performance; third, we used a community-dwelling sample. Unlike Heffernan and Ling (2001), we were not able to find a relationship between extraversion and prospective  42 memory performance. This could be due to the differences in our methods of measuring prospective memory or in the type of samples we used. Heffernan and Ling's (2001) result may reflect differences in self-reporting biases across the personality dimension or an effect specific to undergraduate students. Similarly, our results could be specific to the type of prospective memory tasks that we used. The relationship between extraversion and prospective memory is intriguing. A s Heffernan and Ling (2001) suggest, because extraverts are more social beings they are more likely to engage in behaviour requiring planning for future events. Therefore extraverts may be more motivated to develop their prospective memory skills and/or be more practiced with prospective memory tasks. Future research should further investigate the potential relationship between extraversion and prospective memory performance. Our study also extends Martin and Park's (2002) study. Their main objective was to introduce and validate a new scale to measure demands on individuals' environments, but they also explored the relationship between busyness and performance on a habitual prospective memory task, medication taking. They found that rheumatoid arthritis patients who reported being busier also had more medication taking errors. W e extended this study again in three ways. First, we explored the influence of busyness and routine on prospective memory performance; second, we used one-off tasks, that is, tasks that require execution only once; finally we used a healthy community-dwelling sample. Our results were also inconsistent with Martin and Park's finding (2002) that busyness is positively related to prospective memory performance. Indeed, in our study neither of the demands of the environment, busyness or routine, were significantly related to performance on any of our prospective memory tasks. Our inability to find a relationship between busyness and prospective memory performance could be due to differences in the type of prospective memory tasks we used.  43 Remembering to take a medication that prevents pain is much different than remembering to report an interesting questionnaire, reconnect a phone, or place a phone call. For instance, the consequences of failing to take a medication are more serious and more salient. Further, medication taking is a habitual prospective memory task. That is, it is a task that individuals must perform repeatedly and often on a fixed schedule. It may be that busyness is related specifically to habitual prospective memory tasks or even more specifically to medication taking. The potential relationship between busyness and prospective memory is also intriguing. On the one hand, one may think that busy individuals would be more likely to forget future intentions due to their hectic lifestyle. On the other hand, busyness implies that the individual is getting things done; therefore, busy individuals may perform better on prospective memory tasks. It is possible that both hypotheses are correct and that depending on the precise nature of the prospective memory task one of these factors has a stronger influence than the other, or that they interact with other individual difference variables, for instance organizational skills. Future research should explore whether business is related to other types of habitual prospective memory tasks, for instance brushing one's teeth and whether there are further individual difference variables that mediate the relationship between busyness and prospective memory performance. To our knowledge no previous investigation has explored the influences of conscientiousness, socially prescribed perfectionism, or neuroticism on prospective memory performance. W e found that each of these personality traits was significantly related to performance on at least one of the three prospective memory tasks. W e found that conscientiousness is positively related to performance on the Confirmation Call field prospective memory task and the Plug-In the Phone lab task. These findings are consistent with intuition. The traits that characterize conscientious individuals - being  44 reliable, dependable, and following through tasks to completion (Costa and McCrae, 1992) - are all highly relevant to prospective memory performance. W e found a negative relationship between socially prescribed perfectionism and performance on the Questionnaire lab prospective memory task. Contrary to society's characterization of perfectionism as desirable and adaptive it is a maladaptive trait that can lead to procrastination, self-doubt, anxiety, and depression (Flett & Hewitt, 2002). Anxiety and depression are known to have a negative impact on prospective memory performance (Harris & Cumming, 2003; Harris & Menzies 1999; Rude, Hertel, Jarrold, Covich, & Hedlund, 1999) and it seems highly likely that procrastination would also have detrimental implications. W e suggest that these factors played a role in the negative relationship observed between socially prescribed perfectionism and prospective memory performance. Why prospective memory performance was related to socially prescribed perfectionism and not self-oriented perfectionism is not immediately evident. The difference in these two dimensions of perfectionism is to whom the perfectionist expectations are attributed (Hewitt & Flett, 1991). Individuals high in self-oriented perfectionism expect that they should be perfect, while individuals high in socially prescribed perfectionism believe that others expect them to be perfect (Hewitt & Flett, 1991). W e speculate that the observed relationship between prospective memory performance and socially prescribed but not self-oriented perfectionism is linked to the other-generated tasks we used. That is, we suggest that socially prescribed perfectionism is related to our task because someone else assigned the task and evaluated their performance. It would be interesting to explore whether performance on self-generated prospective memory tasks, where the task is self-assigned and selfevaluated, would show a different relationship with the dimensions of perfectionism. For  45 instance, perhaps self-generated tasks would show a relationship with self-oriented perfectionism rather than socially prescribed perfectionism. While it would be interesting for future research to address this speculation, presently no method for evaluating performance on self-generated prospective memory tasks in an experimental context exists. In the present study we also found a highly significant positive relationship between performance on the Plug-In the Phone lab task and neuroticism. In light of previous research, this finding was somewhat counterintuitive. Neurotic individuals are prone to experience negative affect including depression and anxiety (Costa and McCrae, 1992). Both of these factors generally impair prospective memory performance (Harris & Cumming, 2003; Harris & Menzies 1999; Rude et al., 1999). W e suggest that neuroticism led to increased vigilance or monitoring of the task and that this led to increased task performance. Future research could explore this speculation by observing participants' monitoring behaviour during the retention interval of the prospective memory tasks (see Ceci & Bronfenbrenner, 1985). In our study we found that the specific personality traits that significantly predicted prospective memory performance differed across the three tasks. This interaction probably reflects the unique properties of the three tasks. For instance, the relevance of the on-going tasks to the prospective memory tasks, the difficulty of the ongoing tasks, the salience of the cues, the length of the retention intervals, and the participants' perception of the tasks' relevance to the study differed across our three measures of prospective memory performance. A s so little work has been conducted in this area we are unable to explain the precise nature of the interactions between personality and the task properties. Future research should more systematically vary factors, such as, on-going task difficulty,  46 salience of the cue, length of the retention interval, and participants' perceptions of the task's relevance, in order to explore more deeply the mediating influences of these and other properties on the relationship between personality and prospective memory performance. Future research should also vary the method of measuring prospective memory. For instance, it would be interesting to explore whether similar results would be obtained using computerized prospective memory tasks. Similarly, it would be interesting to explore how the relationships between personality and prospective memory performance change with manipulations in motivation, incentive, feed-back, and task importance. Secondary  Objective  Our secondary objective was to explore whether age-related changes in prospective memory performance are mediated by cognitive ability, by personality and demands of the environment, or by a combination of these factors. In accord with previous research we found that age is negatively related to prospective memory performance on the lab tasks and that it is positively, albeit non significantly, related to increased performance on the field task (Henry et al., 2004). Also consistent with previous research we found that older adults' decreased performance on the lab tasks is, at least partially, mediated by cognitive ability (Henry et al., 2004). Previous research in the field of retrospective memory has recognized the importance of exploring the possible mediating effects of personality on the relationship between age and retrospective memory (Meier et al., 2002). To our knowledge the present investigation is the first to extend this line of research to prospective memory. In doing so we found that personality and demands of the environment are important to understanding the relationship between age and prospective memory performance. In the lab, age-related changes in personality and demands of the environment were found  47 to suppress the negative relationship between age and prospective memory performance on one task and they were found to mediate the negative relationship between age and prospective memory performance on the other task. In the field, despite older adults' declining cognitive resources, age-related differences in personality and demands of the environment were found to mediate older adults' superior prospective memory performance. Therefore age-related differences in personality and demands of the environment may compound with declining cognitive resources to impair prospective memory performance or they may act as a partial or complete buffer against these declining cognitive resources. On the Questionnaire task, we found that personality and demands of the environment suppressed the negative influence of older adults' declining cognitive resources on prospective memory performance. W e suggest that it was specifically older adults' increased levels of agreeableness that buffered the negative influence of their declining cognitive resources on this task. In the preliminary correlation analyses we found that agreeableness was positively related to age. When age was entered into the logistic regression analysis after the personality and demands of the environment predictors, we found that age added significant predictive ability and that agreeableness became a significant predictor of performance in the presence of age. When age was entered into a logistic regression analysis after controlling for personality, demands of the environment, and cognitive ability, it added significant predictive ability. This pattern of results suggests to us that older adults' increased levels of agreeableness partially compensated for the negative influence of their declining cognitive resources. Further, the results suggest that agreeableness is positively related to performance on this task. The influence of agreeableness was masked in the first analysis because of the positive relationship between age and agreeableness and their conflicting relationships with the  48 prospective memory task. A s agreeable individuals are characterized as altruistic, sympathetic, considerate of others, and eager to help them (Costa & McCrae, 1992) the relationship between agreeableness and prospective memory performance was anticipated. W e also found that personality and demands of the environment and cognitive ability mediate the negative relationship between age and performance on the Plug-In the Phone task. W e suggest that it in terms of personality it was specifically older adults' decreased levels of neuroticism that impaired their performance on this task. The preliminary correlation analyses revealed a negative relationship between age and neuroticism. Further, we found that neuroticism showed a strong positive relationship with performance on the Plug-In the Phone task. W e therefore suggest that older adults' decreased levels of neuroticism compounded with their declining cognitive resources to impair their performance on this task. Before we can predict whether age-related differences in personality will suppress or mediate the influence of age on a given prospective memory task, future research is needed. From previous research we know that older adults tend to be more conscientious, more agreeable, and less neurotic (Costa, McCrae, Zonderman, Barbano, Lebowitz, & Larson, 1986; Goldberg, Sweeney, Merenda, & Hughes, 1998; Srivastava, John, Gosling, & Potter, 2003). In the present investigation we found support for the latter two relationships but failed to find a significant relationship between age and conscientiousness. Our results show that the personality traits that best predict performance interact with the properties of the prospective memory task. On our field prospective memory task conscientiousness was related to performance, on one of our lab prospective memory tasks both conscientiousness and neuroticism were related to prospective memory performance, and on our other lab task agreeableness was related  49 to prospective memory performance. Until future research explores how personality interacts with the various properties of prospective memory tasks we cannot determine whether older adults' decreased levels of neuroticism and increased levels of conscientiousness and agreeableness will improve or impair their performance on a given prospective memory task. Limitations  There are several limitations to the current investigation. First due to our selfselected, paid, relatively small sample and our choice to abandon a Bonferroni adjustment our results should be taken as exploratory. A s our participants were recruited through advertisements in a free local newspaper and were paid for their participation they may not be a representative sample of the general population. However, there was a great deal of variability in our participants' demographic characterizations. Further, our samples' performance on almost all of the instruments we used was comparable to previously published norms. The exception was their increased mean scores on the N E O Pl-R. These increased mean scores could reflect the fact that our sample was Canadian or that our sample was not representative of the general population with regards to the five personality traits elucidated from the N E O Pl-R. Due to our choice to abandon a Bonferroni adjustment and the large number of statistical analyses we used, our Type I error rate is inflated. However, because so little research has explored the relationship between prospective memory performance and personality and demands of the environment we thought that missing potentially interesting relationships would be more costly than having inflated Type I error rate that replication would bear out.  50  Our primary objective was to explore the relationship between prospective memory and personality and demands of the environment. Exploring whether personality and demands of the environment and/or cognitive ability mediates the relationship between age and prospective memory performance was secondary. Due to this, we used limited measures of cognitive ability. While taking the first principal component of the scores resulting from the cognitive ability measures we used maximized the variance in the cognitive ability scores and made them better predictors than they would have been as a set of individual predictors, future research exploring the mediating influences of cognitive ability and personality should use equally sensitive and reliable measures of cognitive ability and personality. Conclusions Personality is useful as a predictor of who will succeed and who will fail on prospective memory tasks. The findings of the present study suggest that those individuals who don't show up on time, stand you up, and readily break their commitments do differ in terms of personality with those who are punctual and honor their commitments. Further, age-related changes in personality may suppress or mediate the relationship between age and prospective memory performance. The predictive ability of specific personality traits varies depending on the properties of the prospective memory task. Accordingly, the influence of personality on the relationship between age and prospective memory performance also varies depending on the properties of the prospective memory task. Our findings may have practical and theoretical implications. If our results are borne out by future research, businesses could use quick personality screening inventories to help decide who to hire for jobs demanding reliability and responsibility for the completion of tasks on time. Similarly, doctors could spend more or less time  51 explaining the importance of medication compliance with individuals who possess certain personality traits (Searlman, 1996). W e could even use this information in our daily lives to choose who we will rely on to do things like pick us up from the airport or relay a message. Theoretically, our findings lend support to the multidimensional nature of prospective memory performance. Prospective memory performance depends on attention, memory, motivation, importance, and personality, to name just a few factors. Thus, prospective memory falls into a domain of social cognition. Most of the research in the field of prospective memory has focused on exploring cognitive factors. While this research is necessary to give us a better understanding of the underlying brain mechanisms and the "process pure" aspects of prospective memory performance we should not abandon social factors. These factors can tell us a lot about prospective memory performance. Indeed, the results of our investigation suggest that, cognitive ability cannot predict performance on field prospective memory tasks and that on at least some lab tasks, cognitive ability cannot predict anything unique to what personality can predict. At the very least, researchers should consider personality variables when studying prospective memory, particularly when studying age-related changes in prospective memory performance. Personality may have more of an influence on prospective memory performance than cognitive ability and personality variables may be suppressing, mediating or confounding the influence of other variables, such as age.  52 References Ackerman, P. L , & Heggestad, E. D. (1997). Intelligence, personality, and interest: Evidence for overlapping traits. Psychological Bulletin, 121, 219-245. Anstey, K. J., Matters, B., Brown, A. K., & Lord, S. R. (2000). Normative data on neuropsychological tests for very old adults living in retirement villages and hostels. Clinical Neuropsychologist, 14(3), 309-317. Arbuckle, T. Y., Gold, D. P., Andres, D., Schwartzman, A., & Chikelson, J . (1992). The role of psychological context, age, and intelligence in memory performance of older men. Psychology and Aging, 7, 25-36. 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New York: John Wiley & Sons.  Table 1 A List of all Instruments and Tasks Assigned to Participants, Arranged According to When they were Administered, with Time Required to Complete Each of Them Instrument/Task Approximate Time to Complete 5mins  Demographic Information Questionnaire Prospective Memory Task Assigned Questionnaires N E O Personality Inventory Revised Multidimensional Perfectionism Inventory Martin & Park Environmental Demands Inventory Balanced Inventory of Desirable Responding  1min  25mins 12mins 3mins 10mins  1  2  3  4  Plug-In the Phone Prospective Memory Task Assigned Neuropsychological Tests Rey Auditory Verbal Learning Test Immediate Recall Trail Making Test Color-Word Stroop Test Digit Span Backward Rey Auditory Verbal Learning Test Delayed Recall Rey Auditory Verbal Learning Test Recognition North American Adult Reading Test  5  6  7  8  5  5  9  1min  7mins 5mins 8mins 7mins 2mins 2mins 4mins  Limited Debriefing  2min  Confirmation Call Prospective Memory Task Assigned  2mins  Follow-up Interview  10mins  Full Debriefing  3mins  1 2 3 4 5  Costa and McCrae (1992) Hewitt and Flett (2004) Martin and Park (2002) Paulhus (1991) Adapted from Lezak (1995)  6 7 8 9  R e i t a n (1992) Graf, Uttl, and Tuokko (1995) Wechsler(1981) Blair & Spreen (1989)  58 Table 2 Basic Descriptive Statistics for Each of the Main Variables Indexed by Each of the Questionnaires PeTsonality/Deman^dsofthe ~ Me^n SD Stew^eTs RaTrJe" Environment Variables onewnebb Kange NEO Pl-R Neuroticism Extraversion Openness to Experience Agreeableness Conscientiousness MPS Self-Oriented Perfectionism Other-Oriented Perfectionism Socially Prescribed Perfectionism BIDR Self-Deceptive Enhancement Impression Management MPED Busyness Routine  134.57 157.57 171.96 171.46 166.11  23.96 19.63 18.34 17.41 19.98  -.05 -.00 -.60 -.12 -.14  69.00 --207.00 104.00 - 204.00 129.00 - 2 1 2 . 0 0 122.00 - 2 1 9 . 0 0 104.00 - 2 1 2 . 0 0  61.19 54.46 48.31  15.74 12.30 13.74  -.26 -.05 .15  15.00 - 102.00 30.00 - 9 2 . 0 0 15.00 - 8 8 . 0 0  5.44 6.09  2.85 2.88  .09 -.46  0 -13.00 0 - 13.00  21.14 13.28  5.34 3.03  .14 -.16  8.00 - 34.00 4.00 - 2 0 . 0 0  59 Table 3 Basic Descriptive Statistics for the Variables Assessed by Each of the Neuropsychological Tests Mean SD Skewness Cognitive Ability Variables  Range  RAVLT  7.53 10.39 11.77 6.95 9.35 9.31 12.96  2.02 2.35 2.26 2.15 3.03 3.19 2.29  .37 -.36 -.77* .09 -.23 -.35 -1.11*  3.00-13.00 4.00-15.00 5.00 -15.00 1.00-12.00 1.00-15.00 0-15.00 6.00-15.00  TMT  38.10  33.01  1.92*  -35.00-171.11  Stroop  38.06  17.48  1.29*  10.00-94.98  7.57  2.31  .47*  3.00-14.00  23.15  10.91  .42*  3.00-53.00  List A (trial 1) List A (trial 2) List A (trial 3) List B List A (trial 4) Delayed Recall Recognition  DSB NAART  indicates a significant degree of skewness  Table 4 The Results of a Principal Component Analysis of Performance on Neuropsychological Tests, with Loadings on the First Component Cognitive Ability Variable Loading R A V L T List A (trial 1)  .75  R A V L T List A (trial 2)  .87  R A V L T List A (trial 3)  .89  R A V L T List B  .66  R A V L T List A (trial 4)  .87  R A V L T Delayed Recall  .89  R A V L T Recognition  .67  TMT  -.48  Stroop  -.49  DSB NAART  .50 -.24  * 00 CO  T -  * CD CM  CM  CO  CO CO  CM  LO  CD CM  CM  CO  o  c <D CO  LO  CM  CD  o  CD O  CM O  CM  O O  CM  * o  CD  o  CD  OJ  o  CM  CO  o * *  o  CO CO  co o  o  LO  o *  CO  CO CM  o * oo  o  CO  o  o  CD CM  CD LO  CO LO  o o  LO  CO  CO O  CM CO  o  CO  LO  E c  o i > c  LU  oo  CD .  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CD C  to  '•+—» 13  C O  cc  CM  CO  o  (0 _CD ro g  62 Table 6 Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Personality and Demands of the Environment Prospective Memory Task Plug-In the Phone Confirmation Call Questionnaire Odds Ratio Odds Ratio Odds Ratio Step and Predictor Step 1 1.10  1.93**  .99 (1/.99 = 1.01) .17 .00  1.28 15.38** .14  .81 (1/.81 = 1.23) .99 (1/.99 =1.01) .06 .00  Conscientiousness  1.08  2.22*  1.92*  Extraversion  1.44  1.17  Neuroticism  1.71  4.37**  .65 (1/.65 = 1.54) 1.18  Agreeableness  1.67  1.08  1.34  .92 (1/.92 = 1.09) 1.39  1.36  .83  .79 (1/.79 = 1.27) 1.28  .71 (1/.71 = 1.41) 1.20 .67 (1/.67 = 1.49) 1.12  Instructional Condition Impression Management Model (df=2) Nagelkerke R 2  Step 2  Openness to Experience Self-Oriented Perfectionism Other-Oriented Perfectionism Socially Prescribed Perfectionism  .88 (1/.88 = 1.14) .37* (1/.37 = 2.70) .62 (1/.62 = 1.61) 1.46  Routine  1.41  .61 (1/.61 = 1.64) .74 (1/.74 = 1.35) .88 (1/.88 = 1.14) 1.02  Instructional Condition  1.48  2.44*  Impression Management  1.17  1.35  21.58*  29.78*  .94 (1/.94 = 1.06) 21.60*  .24  .23  .19  Self-Deceptive Enhancement Busyness  Model  (df=11)  Nagelkerke A R  2  indicates p < .05; ** indicates p < .001  .90 (1/.90 = 1.11) .92 (1/.92 = 1.09) 1.05  63 Table 7 Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Age Prospective Memory Task Plug-In the Phone Confirmation Call Questionnaire Odds Ratio Odds Ratio Odds Ratio Step and Predictor Step 1 Instructional Condition Impression Management Model £ (df=2) Nagelkerke R 2  1.10  1.93**  .96 (1/.96 = 1.04) .99 (1/.99 = 1.01) .06 .00  .99 (1/.99 = 1.01) .17 .00  1.28 15.38** .14  .60* (1/.60 = 1.67) 1.05  .64* (1/.64 = 1.56) 1.91**  .97 (1/.97 = 1.03) 4.90*  1.28  .93 (1/.93 = 1.08) 1.00  5.80*  3.04  .06  .05  .03  Step 2 Age Instructional Condition Impression Management Model  (df=1)  Nagelkerke A R *  2  indicates p < .05; ** indicates p < .001  1.36  64 Table 8 Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Cognitive Ability and A g e Prospective Memory Task Plug-In the Phone Confirmation Call Questionnaire Odds Ratio Odds Ratio Odds Ratio Step and Predictor Step 1 1.10  1.93**  .99 (1/.99 = 1.01) .17 .00  1.28 15.38** .14  .96 (1/.96 = 1.04) .99 (1/.99 = 1.01) .06 .00  Cognitive Ability  1.58*  1.83*  1.09  Instructional Condition  1.09  2.03**  .97 (1/.97 = 1.03) 4.25*  1.30 9.63*  .96 (1/.96 = 1.04) .99 (1/.99 = 1.01) .27  .05  .14  .00  .69 (1/.69 = 1.45) 1.34  .78  1.55*  1.64*  1.33  1.07  2.00** 1.29  .99 (1/.99 = 1.01) 1.00  1.41 .01  4.90* .05  Instructional Condition Impression Management Model •£ (df=2) Nagelkerke R 2  Step 2  Impression Management Model  (df=1)  Nagelkerke A R  2  Step 3 Age Cognitive Ability Instructional Condition Impression Management  .96 (1/.96 = 1.04) Model Ljf (df=1) 1.97 Nagelkerke A R .02 * indicates p < .05; ** indicates p < .001 2  65 Table 9 Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Personality, Demands of the Environment, and Age Prospective Memory Task Plug-In the Phone Confirmation Call Questionnaire Odds Ratio Step and Predictor Odds Ratio Odds Ratio Step 1 1.10  1.93**  .99 (1/.99 = 1.01) .17 .00  1.28 15.38** .14  .96 (1/.96 = 1.04) .99 (1/.99 = 1.01) .06 .00  Conscientiousness  1.08  2.22*  1.92*  Extraversion  1.44  1.17  Neuroticism  1.71  4.37**  .65 (1/.65 = 1.54) 1.18  Agreeableness  1.67  1.08  1.34  .92 (1/.92 = 1.09) 1.39  1.36  .83  .79 (1/.79 = 1.27) 1.28  .71 (1/.71 = 1.41) 1.20 .67 (1/.67 = 1.49) 1.12  Instructional Condition Impression Management Model (df=2) Nagelkerke R 2  Step 2  Openness to Experience Self-Oriented Perfectionism Other-Oriented Perfectionism Socially Prescribed Perfectionism  .88 (1/.88 = 1.14) .37* (1/.37 = 2.70) .62 (1/.62 = 1.61) 1.46  Routine  1.41  .61 (1/.61 = 1.64) .74 (1/.74= 1.35) .88 (1/.88 = 1.14) 1.02  Instructional Condition  1.48  2.44*  Impression Management  1.17  1.35  21.58*  29.78*  .94 (1/.94 = 1.06) 21.60*  .24  .23  .19  Self-Deceptive Enhancement Busyness  Model A x (df=11) 2  Nagelkerke A R  2  .90 (1/.90 = 1.11) .92 (1/.92 = 1.09) 1.05  66 Step 3 .42* (1/.42 = 2.38) 1.00  .71 (1/.71 = 1.41) 2.09*  Extraversion  1.38  1.09  Neuroticism  1.46  3.99**  .67 (1/.67= 1.49) 1.21  Agreeableness  2.42*  1.91  1.29  .80 (1/.80 = 1.25) 1.24  1.31  .84 (1/.84 = 1.19) .72 (1/.72 = 1.39) 1.15  Age Conscientiousness  Openness to Experience Self-Oriented Perfectionism  1.24  Other-Oriented Perfectionism  Routine  1.46  .58 (1/.58 = 1.72) .77 (1/.77 = 1.30) .89 (1/.89= 1.12) 1.06  Instructional Condition  1.56  2.41**  Impression Management  1.14  1.34  Socially Prescribed Perfectionism Self-Deceptive Enhancement Busyness  Model Ax^ (df=1) Nagelkerke A R indicates p < .05; 2  .31* (1/.31 = 3.23) .73 (1/.73 = 1.37) 1.44  .79 (1/.79 = 1.27) 1.40  7.75* .08 indicates p < .001  2.13 .01  1.13 1.94*  .68 (1/.68 = 1.47) 1.09 .90 (1/.90 = 1.11) .92 (1/.92 = 1.09) 1.06 .95 (1/.95 = 1.05) .31 .00  67 Table 10 Results of the Sequential Logistic Regression Analyses Predicting Performance on Each of the Three Prospective Memory Tasks Using Personality, Demands of the Environment, Cognitive Ability, and Age Prospective Memory Task Questionnaire Plug-In the Phone Confirmation Call Odds Ratio Odds Ratio Odds Ratio Predictor Step 1 1.10  1.93**  .99 (1/.99 = 1.01) .17 .00  1.28 15.38** .14  .96 (1/.96 = 1.04) .99 (1/.99 = 1.01) .06 .00  Conscientiousness  1.08  2.22*  1.92*  Extraversion  1.44  1.17  Neuroticism  1.71  4.37**  .65 (1/.65 = 1.54) 1.18  Agreeableness  1.67  1.08  1.34  .92 (1/.92 = 1.09) 1.39  1.36  .83  .79 (1/.79 = 1.27) 1.28  .71 (1/.71 = 1.41) 1.20 .67 (1/.67 = 1.49) 1.12  Instructional Condition Impression Management Model (df=2) Nagelkerke R 2  Step 2  Openness to Experience Self-Oriented Perfectionism Other-Oriented Perfectionism  .88 (1/.88 = 1.14) .37* (1/.37 = 2.70) .62 (1/.62 = 1.61) 1.46  Routine  1.41  .61 (1/.61 = 1.64) .74 (1/.74 = 1.35) .88 (1/.88 = 1.14) 1.02  Instructional Condition  1.48  2.44*  Impression Management  1.17  1.35  21.58*  29.78*  .94 (1/.94 = 1.06) 21.60*  .24  .23  .19  Socially Prescribed Perfectionism Self-Deceptive Enhancement Busyness  Model Ax" (df=11) Nagelkerke A R  2  .90 (1/.90 = 1.11) .92 (1/.92 = 1.09) 1.05  68 Step 3 1.48  1.44  1.27  2.08*  1.89*  Extraversion  .99 (1/.99 = 1.01) 1.58  1.20  Neuroticism  1.40  3.94**  .67 (1/.67 = 1.49) 1.12  Agreeableness  1.79  1.13  1.39  .79 (1/.79 = 1.27) 1.46  1.26  .79 (1/.79 = 1.27) .70 (1/.70 = 1.43) 1.21  Cognitive Ability Conscientiousness  Openness to Experience Self-Oriented Perfectionism Other-Oriented Perfectionism  .89 (1/.89 = 1.12) .37* (1/.37 = 2.70) .73 (1/.73 = 1.37) 1.45  .78 (1/.78 = 1.28) 1.29  Routine  1.49  .63 (1/.63 = 1.59) .79 (1/.79 = 1.27) .87 (1/.87 = 1.15) 1.06  Instructional Condition  1.48  2.48**  Impression Management  1.10  1.35  3.98* .04  2.34 .02  .49* (1/.49 = 2.04) 1.38  .79 (1/.79 = 1.27) 1.31  1.27  2.03*  1.89*  Extraversion  .99 (1/.99 = 1.01) 1.45  1.14  Neuroticism  1.36  3.78**  .70 (1/.70 = 1.43) 1.15  Agreeableness  2.39*  1.20  1.30  .76 (1/.76 = 1.32)  1.25  .78 (1/.78 = 1.28)  Socially Prescribed Perfectionism Self-Deceptive Enhancement Busyness  Model Ax" (df= 1) Nagelkerke A R 2  .68 (1/.68 = 1.47) 1.21 .89 (1/.89 = 1.12) .96 (1/.96 = 1.04) 1.04 .92 (1/.92 = 1.09) 1.30 .01  Step 4 Age Cognitive Ability Conscientiousness  Openness to Experience  1.39  69 .78 (1/.78 = 1.28) 1.37  .70 (1/.70 = 1.43) 1.14 .70 (1/.70 = 1.43) 1.17  1.44  .60 (1/.60 = 1.67) .81 (1/.81 = 1.23) .87 (1/87 = 1.15)  1.51  1.08  1.55  2.45  1.11  1.34  Self-Oriented Perfectionism  1.28  Other-Oriented Perfectionism  2.19  Socially Prescribed Perfectionism Self-Deceptive Enhancement Busyness Routine Instructional Condition Impression Management  .31* (1/.31 = 3.23) .79 (1/.79 = 1.27)  Model (df=1) 4.79* Nagelkerke A R .05 indicates p < .05; ** indicates p < .001 2  .87 .01  .90 (1/.90 = 1.11) .95 (1/.95 = 1.05) 1.06 .93 (1/.93 = 1.08) 1.11 .01  70 Figure Captions Figure 1. Instructional Condition x Prospective Memory Task. Success rates for naive (n = 71) and informed (n = 70) conditions across the three prospective memory tasks. Figure 2. Overall Prospective Memory Task Success Rates. Overall rates of success for the Questionnaire task, Plug-In the Phone task, and Confirmation Call task (n = 141)  Figure 1. Instructional Condition x Prospective Memory Task. Success rates for naive = 71) and informed (n = 70) conditions across the three prospective memory tasks.  72  100 90 80 70 ro 60 CU w 50 to (D 40 o o 30 CO 20 10 0  at  I  59.6 i  Questionnaire Task  Plug-In the Phone Task  Confirmation Call Task  Figure 2. Overall Prospective Memory Task Success Rates. Overall rates of success for the Questionnaire task, Plug-In the Phone task, and Confirmation Call task (n = 141)  73 Appendix Descriptions of Personality Traits Conscientiousness. Conscientious individuals are characterized as dependable, reliable, diligent, and good at organizing, planning, and following through tasks to completion (Costa & McCrae, 1992). Extraversion. Extraverted individuals are characterized as sociable, upbeat, energetic, and optimistic. They seek excitement, are affectionate, and tend to experience positive emotions (Costa & McCrae, 1992). Neuroticism. Neurotic individuals are characterized as prone to negative affect including anger, depression, and anxiety. They are also impulsive, self-conscious, and vulnerable to stress (Costa & McCrae, 1992). Agreeableness. Agreeable individuals are characterized as altruistic, sympathetic, considerate of others, and eager to help them. Further, they tend to believe that others are honest and will be equally helpful in return (Costa & McCrae, 1992). Openness to experience. Individuals who are open to experience are characterized as imaginative, attentive to inner feelings, and intellectually curious. They are willing to entertain unconventional ideas, are moved by poetry and art, are willing to try new things, and they experience positive and negative emotions more keenly than others (Costa & McCrae, 1992). Self-Oriented Perfectionism. Self-oriented perfectionists feel a need to be perfect without any shortcomings. They have a need to avoid failure and strive to attain perfection in their own endeavors (Hewitt & Flett, 1991). Other-Oriented Perfectionism. Other-oriented perfectionists have unrealistically high standards for significant others, place importance on other people being perfect, and stringently evaluate others performance (Hewitt & Flett, 1991). Socially Prescribed Perfectionism. Socially prescribed perfectionists perceive a need to attain standards and expectations prescribed by significant others. They believe or perceive that significant others have unrealistic standards for them, evaluate them stringently, and exert pressure on them to be perfect (Hewitt & Flett, 1991). Self-Deceptive Enhancement. Individuals high in self-deceptive enhancement show more illusions of control, believe they are safe drivers, and claim familiarity with nonexistent products. Further, they show more hindsight bias, more proneness to love, and excessive confidence in memory judgments (Paulhus, 1991).  

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