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Uncertainty, regret, and psychological pain : why it hurts to be unsure Benjamin, Rachele 2017

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Uncertainty, Regret, and Psychological Pain: Why it hurts to be unsure  by  Rachele Benjamin  B.A., Queen’s University, 2014  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF ARTS in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Psychology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2017  © Rachele Benjamin, 2017 ii  Abstract Theorists have noted that social rejection, uncertainty, error evaluation, regret, and cognitive dissonance all activate the same neural substrate as physical pain; specifically, the anterior cingulate cortex (ACC). Furthermore, studies have shown that acetaminophen, a painkiller that is used to treat aches and pains, attenuates sensitivity to social pain, as well as uncertainty and dissonance. Together, these findings suggest that there is a relationship between physically and psychologically painful experiences. However, there is little evidence that various distinct sources of psychological distress increase sensitivity to physical pain, as we would expect given that they have a common neural basis. In study 1, I explored the hypothesis that psychological pain is physically painful by investigating purchases of over-the-counter painkillers. I found that Americans are more likely to purchase painkillers during uncertain times. In study 2, I investigated whether uncertainty leads to increased sensitivity to physical pain in a cold pressor task. Using this procedure, I was unable to find evidence that uncertainty increases sensitivity to physical pain. I suggest various alternative approaches to the study of pain and uncertainty. In study 3, I explored the relationship between physical pain and a new candidate for psychological pain: regret. I determined whether acetaminophen attenuates people’s experience of regret, a psychological experience that is conceptually similar to dissonance and error evaluation. I did not find evidence that acetaminophen attenuates people’s responses to regret. Therefore, I propose a number of future directions for the study of regret, uncertainty, and physical pain.	    iii  Lay Summary The purpose of this research was to determine the effects of uncertainty on sensitivity to physical pain. Previous studies have identified a neural structure that is activated by both physical and psychological sources of pain: the anterior cingulate cortex, or ACC. As a result, research has shown that there is a relationship between psychological pain and physical pain processing. Though there is much evidence that uncertainty leads to ACC activation, there is no evidence that the experience of perceived meaninglessness, or feeling unsure about events in the world, can affect people’s sensitivity to physical pain. In studies 1 and 2, I determined if uncertainty increases people’s sensitivity to pain. In study 3, I determined whether regret, an experience that is commonly associated with distress, is a source of psychological pain. I tested if acetaminophen, a commonly-used painkiller drug, attenuates people’s experience of regret. iv  Preface Rachele Benjamin is the primary author of the work presented in this thesis. As such, she designed the experiments, collected the data, analyzed, and interpreted the results. As supervisor on this project, Dr. Steven Heine contributed to the design of each study as well as data collection and interpretation. In addition, Dr. Heine provided consistent guidance on this project and contributed to manuscript revisions. Two of the three studies presented in this thesis were covered by the UBC Behavioral Ethics Board certificate numbers H16-02290 and H16-00075. One study did not require ethics approval.   v  Table of Contents Abstract .......................................................................................................................................... ii	Lay Summary ............................................................................................................................... iii	Preface ........................................................................................................................................... iv	Table of Contents ...........................................................................................................................v	List of Figures ............................................................................................................................. viii	Acknowledgements ...................................................................................................................... ix	Dedication .......................................................................................................................................x	Chapter 1: Introduction ................................................................................................................1	1.1	 The Meaning Maintenance Model .................................................................................. 4	1.2	 Studies with Acetaminophen .......................................................................................... 8	1.3	 Pain and uncertainty ...................................................................................................... 10	1.4	 Regret ............................................................................................................................ 11	Chapter 2: The present research ................................................................................................14	2.1	 Study 1: Uncertainty and painkiller purchases ............................................................. 14	2.1.1	 Method .................................................................................................................. 14	2.1.1.1	 Panelists ............................................................................................................ 15	2.1.1.2	 Uncertainty Measures ....................................................................................... 15	2.1.1.2.1	 Economic Policy Uncertainty ..................................................................... 15	2.1.1.2.2	 Newspaper-Based Economic Policy Uncertainty ....................................... 16	2.1.1.2.3	 Unemployment ............................................................................................ 16	2.1.1.3	 Products............................................................................................................. 17	2.1.1.3.1	 OTC Painkillers .......................................................................................... 17	vi  2.1.1.3.2	 Alcohol ........................................................................................................ 18	2.1.2	 Results ................................................................................................................... 19	2.1.2.1	 Painkillers ......................................................................................................... 19	2.1.2.2	 Controls ............................................................................................................. 21	2.1.2.3	 Alcohol .............................................................................................................. 22	2.1.3	 Discussion ............................................................................................................. 25	2.2	 Study 2: Uncertainty and pain sensitivity ..................................................................... 26	2.2.1	 Methods................................................................................................................. 27	2.2.1.1	 Participants ........................................................................................................ 27	2.2.1.2	 Procedure .......................................................................................................... 27	2.2.2	 Results ................................................................................................................... 30	2.2.3	 Discussion ............................................................................................................. 31	2.3	 Study 3: Acetaminophen and regret .............................................................................. 33	2.3.1	 Methods................................................................................................................. 33	2.3.1.1	 Participants ........................................................................................................ 33	2.3.1.2	 Procedure .......................................................................................................... 34	2.3.1.2.1	 Regret vignettes .......................................................................................... 35	2.3.1.2.2	 Cognitive reflection task ............................................................................. 36	2.3.1.2.3	 Personality measure of regret ...................................................................... 37	2.3.2	 Results ................................................................................................................... 37	2.3.2.1	 PANAS ............................................................................................................. 38	2.3.2.2	 Personality measure of regret ............................................................................ 38	2.3.2.3	 Job regret ........................................................................................................... 38	vii  2.3.2.4	 Course regret ..................................................................................................... 40	2.3.3	 Discussion ............................................................................................................. 42	Chapter 3: General Discussion ...................................................................................................44	3.1	 Limitations .................................................................................................................... 45	3.1.1	 A unifying definition of uncertainty ..................................................................... 45	3.1.2	 Acetaminophen in the brain .................................................................................. 46	3.2	 Future Directions .......................................................................................................... 48	3.2.1	 Neural evidence .................................................................................................... 48	3.2.2	 Laboratory evidence .............................................................................................. 50	3.3	 Conclusion .................................................................................................................... 52	References .....................................................................................................................................53	Appendices ....................................................................................................................................68	Appendix A ............................................................................................................................... 68	Appendix B ............................................................................................................................... 69	B.1	 Job vignette ............................................................................................................... 69	B.2	 Course vignette ......................................................................................................... 69	B.3	 Scale to measure regret from course and job vignette .............................................. 71	 viii  List of Figures	Figure 2.1. Painkiller purchases and EPU .................................................................................... 20	Figure 2.2. Painkiller purchases and news-based EPU ................................................................. 21	Figure 2.3. Alcohol purchases and EPU ....................................................................................... 23	Figure 2.4. Alcohol purchases and news-based EPU ................................................................... 25	Figure 2.5. Uncertainty condition and cold pressor time .............................................................. 31	Figure 2.6. Pill condition and job regret ....................................................................................... 39	Figure 2.7. Pill condition and course regret .................................................................................. 41	 ix  Acknowledgements Thank you to all of the supportive staff and faculty members at UBC who helped make this project a success. I am deeply grateful for your ongoing efforts to make the psychology department a positive environment. I am also grateful to all of my friends at UBC. You inspire me to think differently about the world, and are always ready with advice and support when I need it. Thank you for making Vancouver feel like home. I owe particular thanks to my committee members, Todd Handy, Ara Norenzayan, and Steven Heine. I am very grateful for your guidance and expertise.   Thank you to the many research assistants who helped with these projects: Jessica Tong, Alicia Wong, Winnie Tse, Mona Claes, Hui Chia, Diana Lee, Candy Chua, Laura Spong, Jiwan Sanghaa, YunHaYoung, and Sheila Wee. You were all invaluable to the completion of this project. Thank you for bringing your insights and enthusiasm to each and every assignment. I am deeply grateful for all of your contributions.    I am especially grateful to my advisor, Steven Heine, whose support I could not have done without. Whenever I was anxious or unsure about the work I was doing, you were always there to lift my spirits. Thank you for your positivity throughout this process, and for all of your direction. Your help went above and beyond what anyone can expect from a supervisor.  x  Dedication I dedicate this thesis to my parents, David and Angela Benjamin, and my sisters two sisters, Marisa and Micaela Benjamin. You are the reason why I decided to pursue psychology. From a very young age, I was exposed to many complex ideas, and the full spectrum of human emotions and behaviours. Thank you for being the most fascinating people I know.  1  Chapter 1: Introduction Psychological pain is a source of much academic interest, and much bewilderment. There would seem to be no reason for our pride to “hurt”, or our hearts to feel “broken”, and yet theorists have noted that when people talk about experiences that are upsetting or psychologically distressing they often use pain-related words (Eisenberger, 2003; Eisenberger & Lieberman, 2004; Leary & Springer, 2001; Panksepp, 2003). At the very least, there is a symbolic relationship between the experiences of psychological and physical pain, although it is not obvious why this relationship should exist. Nevertheless, most people would tell you that the feeling of being broken up with is traumatic in much the same way as being punched in the stomach. These two experiences have very little in common besides that they can both be described as painful.  Some theorists propose that human beings are just as vigilant to events that can cause damage to our social relationships as we are to events that might damage our physical bodies. Given the many protective and reproductive benefits of maintaining positive social networks, social exclusion is believed to pose a threat to our survival not unlike the threat posed by physical damage (Baumeister & Leary, 1995; Baumeister & Tice, 1990). For this reason, humans have evolved to be sensitive to relationship harm just as they are sensitive to physical harm. There is even evidence that physical and social sources of pain produce activation in the same neural regions; in particular, the dorsal anterior cingulate cortex (dACC; for a review, see Eisenberger, 2012) or ACC more generally, as many theorists have observed that specific areas of the ACC are not functionally distinct from one another (Shackman et al., 2011; see also Price, 2000). The ACC is associated with the affective responding to physical pain (Tolle et al., 1999) as well as the general experience of social exclusion (Eisenberger, 2003). The consequence of 2  this shared neural circuitry is that in many cases, events that cause psychological harm are motivating and distressing in much the same way as events that cause physical harm. Another consequence of the shared neural substrates between physical and psychological pain is that in many cases, psychological pain can affect people’s experiences of physical pain, and vice versa. There is evidence that people who have more sensitivity to psychological pain also have more sensitivity to physical pain. Eisenberger (2006) demonstrated that participants who experienced more physical pain when receiving a heat stimulus also experienced greater self-reported distress when they were socially-excluded in a cyberball game (Eisenberger, Jarcho, Lieberman, & Naliboff, 2006). It has also been found that social support reduces people’s risk of developing back pain (Hoogendoorn, van Poppel, Bongers, Koes, & Bouter, 2000) and holding a partner’s hand reduces self-reported distress during physically painful experiences; for example, placing one’s arm in ice water (Brown, Sheffield, Leary, & Robinson, 2003; Coan, Schaefer, & Davidson, 2006). In light of these findings, we must acknowledge that the relationship between psychological and physiological pain may be more than symbolic, having a very tangible neural basis.  There are many other experiences that lead to activation in this neural pathway, besides physical pain and social exclusion. The ACC is implicated in cognitive experiences like error detection (Carter, 1998) and conflict monitoring (Botvinick, Cohen, & Carter, 2004; Kerns, 2004). It is also involved in the processing of various “high-level” behavioural and attitudinal inconsistencies, such as cognitive dissonance (Izuma et al., 2010; van Veen, Krug, Schooler, & Carter, 2009). Though the ventral region of the ACC has been assumed to manage affect and the dorsal region has been assumed to manage cognition (see Steele & Lawrie, 2004), recent evidence suggests that both regions play a role in affect (Etkin, Egner, & Kalisch, 2011) as well 3  as cognition (Shackman et al., 2011). Due to the variety of experiences that activate the ACC, it has been called the brain’s “alarm system”, alerting us to the fact that something in our environment is amiss (Eisenberger & Lieberman, 2004). Based on the many functions that the ACC performs, we might expect that there are many good candidates for psychologically painful experiences besides social exclusion. One particularly good candidate is the arousal response associated with uncertainty (McGregor et al., 2010; Proulx & Heine, 2010). Not only is uncertainty theoretically related to error detection and conflict monitoring; it has consistently been shown to produce ACC activation across a variety of paradigms and measures. In animal learning tasks, uncertainty about whether a behaviour will produce a reward leads to ACC activation (Rushworth & Behrens, 2008). In studies with humans, the ACC has been shown to increase as the reward environment becomes more unpredictable (Behrens et al., 2007). There is also evidence to suggest that the ACC activation is especially responsive to prediction errors made during behavioural learning tasks (Matsumoto, 2003; Matsumoto, Matsumoto et al., 2007). Moreover, Jessup, Busemeyer and Brown (2010) found that rather than responding to any negative outcome, the ACC responds specifically to how unexpected an outcome is—regardless of whether it is negative or positive. For these reasons, there is a case to be made for uncertainty as a strong elicitor of psychological pain. In fact, there is some evidence that beliefs and behaviours that help us deal with uncertainty also decrease activation in the ACC. For example, studies have shown that having greater religious predicts less ACC activity as well as less uncertainty (Inzlicht, McGregor, Hirsh & Nash, 2009; Kay, Gaucher, McGregor & Nash, 2010). Theorists have proposed that any behaviours that allows us to compensate for uncertainty are successful because they diminish activity in the ACC (Proulx, Inzlicht, & Harmon-Jones, 2012). For example, the misattribution of 4  arousal paradigm; a commonly-used method of reducing arousal; has been demonstrated to attenuate ACC activation (Inzlicht & Al-Khindi, 2012). This study showed that when participants made an error on a go/no-go task, those who misattributed their arousal to a placebo showed less error-related negativity (ERN; a known indicator of ACC activity). Lastly, the desire to avoid uncertainty has many protective benefits given that human beings need stable relationships in order to engage in any kind of meaningful behaviour (Heine, Proulx & Vohs, 2006). Therefore, from an evolutionary standpoint, it is reasonable to assume that shared neural circuitry between uncertainty and physical pain may have evolved for many of the same reasons that it evolved between for social exclusion and physical pain; these all signal events that need to be attended to. For all of these reasons, we propose that there is a general association between psychological pain and uncertainty. 1.1 The Meaning Maintenance Model The Meaning Maintenance Model (MMM) provides a framework through which we can understand the motivation to avoid uncertainty. Here, uncertainty is defined as any experience that threatens meaning or violates expectations, also referred to as a meaning threat. The MMM states that when we experience a meaning threat, we experience negative arousal (Heine et al., 2006). The common experience that bridges related experiences of uncertainty such as the anxious arousal that accompanies goal frustration (McGregor et al., 2010) with existential terror (Greenberg, Pyszczynski, & Solomon, 1986) with older concepts like Piaget’s (1937/1954) notion of disequilibrium and Bruner and Postman’s (1949) notion of schema violation, is “the vague sense that something is not quite right in our environment ” (Proulx & Inzlicht, 2012a, p. 322). In the MMM literature, uncertain experiences are sometimes referred to as disanxiousuncertlibrium, a feeling that is associated with discomfort and negative arousal 5  (Proulx & Inzlicht, 2012a, 2012b). When we feel disanxiousuncertlibrium, we are motivated to engage in meaning-making efforts, regardless of the content of the specific meaning-threatening stimuli (Proulx & Inzlicht, 2012a). The MMM posits that anything that undermines our experience of meaningful relationships, whether it is a low-level perceptual inconsistency or a high-level attitudinal inconsistency, produces negative arousal and disanxiousuncertlibrium. As evidence for this common understanding of all threat-inducing experiences, people can have remarkably similar responses to different kinds of anomalies. For example, an early finding from terror management theory is that reminders of one’s mortality lead people to set higher bail for a woman who is arrested for prostitution (Rosenblatt et al., 1989). In fact, this effect has been replicated using many other threats to meaning such as an absurd joke (Proulx et al., 2010, study 2) an implicit change-detection paradigm (Proulx & Heine, 2008) and exposure to subliminally-presented incongruous word pairs (Randles, Proulx, & Heine, 2011). Though it is remarkable that all of these events lead people to engage in the same behaviour, this does not suggest that all anomalous experiences are the same. Being reminded that everyone will die some someday is a very different experience from watching an experimenter turn into someone else before one’s eyes. However, the MMM posits that any threat to existing meaning frameworks will produce a similar sense of unease, and it has even been suggested that they may rely on similar neural mechanisms during early-stage processing (Randles, 2013). As a result, people engage in many of the same strategies to address the arousal associated with different uncertainty-evoking experiences. Two common strategies for alleviating the anxiety associated with encountering an anomaly are assimilating the anomaly into an existing meaning framework, or revising a meaning framework so that it can accommodate the anomaly (Heine et al., 2006; see also Piaget, 6  1960). However, in the short term, neither of these strategies can completely account for the anomaly. Assimilation is rarely complete, and accommodation requires significant cognitive resources and time (Proulx & Heine, 2010). Hence, the strategy that is most relevant to the studies outlined above is fluid compensation. Fluid compensation involves affirming an unrelated meaning framework when presented with something unexpected (Heine et al., 2006; Proulx & Inzlicht, 2012). Engaging in fluid compensation allows us to reduce the negative arousal associated with uncertainty without addressing the source of our uncertainty directly (see Heine et al., 2006; Proulx & Inzlicht, 2012). Punishing lawbreakers is an example of fluid compensation because although witnessing an anomaly may be distressing, and although an absurd joke might produce an uncomfortable feeling of uncanniness (Proulx et al., 2010), there is ultimately no reason why it should make people more likely to punish lawbreakers besides that it allows them to restore a general rather than specific sense of certainty. Fluid compensation can also take the form of affirming one’s cultural identity (Proulx et al., 2010, study 1) and holding stronger opinions about social issues (McGregor et al., 2001).  Though the MMM maintains that efforts to address the source of our unease directly are the most effective (Heine et al., 2006) indirect strategies like fluid compensation are appropriate when we cannot face a threat head-on. For example, the knowledge that we will die some day poses a threat that cannot be overcome by any traditional methods—death being something that can neither be escaped nor comprehended (Heine et al., 2006). Similarly, a threat that is not consciously processed; for example, an implicit change detection paradigm; cannot be resolved because people are not aware that it has happened (Proulx & Heine, 2008). In these cases, we must rely on forms of threat compensation that reduce the discomfort associated with uncertainty rather than resolving the source of our uncertainty directly. This includes fluid compensation, 7  and another strategy called abstraction which involves searching for patterns in the environment when a meaning framework is not readily available to affirm (Proulx et al., 2012). The value of these forms of threat compensation is that we learn something of people’s motives to overcome uncertainty. That is, these strategies can be understood as palliative, or “pain-relieving”, because they serve the sole purpose of alleviating our discomfort (Proulx, Inzlicht, & Harmon-Jones, 2012). It becomes evident that the motivation to maintain meaningful relationships is associated with avoiding the “hurt” of uncertainty.  Critically, the aversive negative arousal associated with threats to meaning is theorized to originate in the dACC (Proulx & Inzlicht, 2012). This is based on the knowledge that all meaning threats produce uncomfortable arousal, and that this uncomfortable arousal is not unlike that associated with uncertainty, cognitive dissonance, or experiencing interpersonal rejection (Heine et al., 2006). Indeed, there is much conceptual overlap between the breakdown in expected relationships outlined by the MMM and the kind of uncertainty that leads to ACC activation. Specifically, they both are characterized by a nonspecific mechanism for managing responses to something that is “not quite right” (Heine et al., 2006). One benefit of taking an MMM approach is that it also provides some context for why the ACC is responsive to both low- and high-level sources of conflict (i.e., perceptual anomalies and reminders of one’s mortality both produce activation in the ACC, and both be understood as threats to meaning). For these reasons, it is sensible to conclude that the negative arousal associated with expectancy violations outlined in the MMM can be attributed to neural firing in the dACC. In fact, there is evidence that violated expectations produces activation in the ACC (Oliveira, McDonald, & Goodman, 2007) and further evidence that the ACC is implicated in the compensatory response that 8  accompanies the processing of meaning threats. This evidence comes from studies using acetaminophen, a painkiller drug that is active in the dACC (DeWall et al., 2010). 1.2 Studies with Acetaminophen Acetaminophen is a common over-the-counter pain drug, and the active ingredient in Tylenol. It has also been used in many studies to test the relationship between dACC activation and various sources of psychological pain. Not only do these studies help establish a common neural basis for a variety of psychologically distressing experiences; they also speak to the many cognitive and affective consequences of consuming painkillers regularly. For instance, in a study by DeWall et al. (2010) it was found that when people consumed acetaminophen regularly over a 3-week period, they reported fewer daily experiences of hurt feelings (study 1). They also found that consuming acetaminophen over a 3-week period leads to less activity in the dACC and anterior insula during a social exclusion task (study 2). Thus, they demonstrated that acetaminophen both reduces people’s experiences of social pain, and attenuates the neural activity most associated with social pain. Studies have shown that acetaminophen also attenuates people’s empathy for pain. Mischkowski, Crocker and Way (2016) found that acetaminophen reduces empathy for the pain of others. In this study, participants who consumed acetaminophen experienced less empathic concern for someone receiving a physically painful noise blast (study 2). In the same study, they showed that acetaminophen reduces empathy for social pain. Participants who consumed acetaminophen experienced less empathic concern for people who were ostracized during a Cyberball game (study 2). It has also been found that acetaminophen more generally reduces peoples’ responses to emotionally-evocative stimuli. Durso et al. (2015) showed that a single, one-time dose of acetaminophen attenuates affective responses to both pleasant and unpleasant 9  photographs. These studies with acetaminophen serve as further evidence for the shared neural underpinnings between physical, social, and emotional pain. Acetaminophen has been found to affect a variety of experiences that involve cognitive processes. Randles et al. (2016) showed that acetaminophen attenuates people’s responses to mistakes made on a go/no-go task. Participants who consumed acetaminophen showed less error-related positivity (Pe) when they made a mistake, but did not show less error-related negativity (ERN). Consistent with what might be expected given the role of the ACC in error detection (see Carter, 1998) this finding suggests that acetaminophen affects people’s conscious processing of errors.  Acetaminophen has also been shown to attenuate people’s experience of more high-level conflict; for example, the conflict that accompanies dissonance between behaviours and attitudes. DeWall et al. (2015) found that acetaminophen reduces the dissonance response that follows making a difficult decision. In this study, participants exhibited less spreading-of-alternatives after they made a choice between tasks that were comparable in terms of desirability (study 1). They also showed that acetaminophen makes people less loss-averse (DeWall et al., 2015, study 2). Participants who consumed acetaminophen set a lower selling price for a mug they were given during a manipulation of the endowment effect. Again, this is not unexpected given our knowledge of the ACC’s role in processing cognitive dissonance (see Izuma et al., 2010; van Veen, Krug, Schooler, & Carter, 2009). Most critical to the current line of research, Randles et al. (2013) showed that acetaminophen attenuates the compensatory affirmation response associated with uncertainty. In study 1, participants who consumed acetaminophen were less likely to affirm a moral schema after experiencing a threat to meaning than those who consumed a placebo. Participants were 10  shown clips from an absurd David Lynch film called “Rabbits”. Afterwards, they were asked to set bail for a prostitute. As is outlined in the section on the MMM, this is a commonly-used measure of compensatory affirmation (see Rosenblatt et al., 1989; see also Proulx & Heine, 2008; Proulx et al., 2010, Randles, Proulx, & Heine, 2011). Participants who consumed acetaminophen set a lower bail than participants who consumed a placebo, suggesting that they were not compensating for uncertainty. In study 2, participants were given a mortality salience prime in which they were asked to write about what will physically happen to them after they die. Again, those who consumed acetaminophen set a lower bail than those who consumed a placebo.   Studies with acetaminophen provide compelling evidence for the relationship between negative arousal produced by threats to meaning and dACC activation. Furthermore, they allow us to make certain conclusions about the nature of threats to meaning. Specifically, the fact that consuming acetaminophen attenuates people’s responses to meaning threats, as well as a variety of other affective and cognitive experiences, lends support to the MMM’s proposition that cognitive dissonance, low-level error detection, and even social rejection can all be understood as arousal-inducing events that produce the sensation that something is not quite right in the environment (see Proulx & Inzlicht, 2012). However, in terms of the current research question, the most valued contribution of these studies is that they provide some initial direction for investigating the relationship between events that produce negative arousal and events that produce physical pain.  1.3 Pain and uncertainty Thus far, we have determined that there are shared neural underpinnings between various sources of psychological pain and physical pain; studies with acetaminophen can be used to 11  establish this shared neural circuitry; and that the discomfort associated with uncertainty is among the experiences that rely on the same neural systems as physical pain. Though acetaminophen is traditionally used to treat physical pain, all we can conclude based on the evidence reviewed above is that drugs that attenuate neural structures associated with physical pain also reduce responding to uncertain experiences. There is not yet evidence that uncertainty increases the experience of, or sensitivity to, physical pain. However, it has been found that lacking control makes people more sensitive to social pain (Lu, Hamamura, & Chan, 2017) and there is also compelling evidence that social pain is associated with physical pain (Eisenberger, 2003; Eisenberger et al., 2006). On this basis, we propose that rather than simply relying on the same neural pathways as physical pain, uncertainty can be understood as a source of psychological pain that interacts in complex ways with physiological pain. In the present research, we test the hypothesis that uncertainty leads to increased pain sensitivity. 1.4 Regret Another candidate for a psychologically painful experience is regret. Regret has been an area of academic interest since decision-theorists first began discussing the consequences of making a risky gamble (Kahneman & Tversky, 1982). The word “regret” passes our linguistic test for a psychologically painful experience, as it has at least a symbolic relationship with physical pain. A commonly-used definition of regret is “a more or less painful cognitive and emotional state of feeling sorry for misfortunes, limitations, losses, transgressions, shortcomings, or mistakes” (Landman, 1993, p. 36). As can be seen, the word “pain” appears in the definition of the word. And indeed, it takes no great leap of the imagination to understand what someone is trying to say when they talk about the pain of regret. Furthermore, a Google trends analysis reveal that searches on the word “regret” correlate r = .94 with searches on the phrase “pain in 12  lower right” and r = 0.94 with the phrase “how many Tylenol” (Google, 2017)1. These correlations indicate that at times when people are searching for information relating to regret, they are also searching for information about physical pain symptoms. This provides some initial support for the claim that the experience of regret is related to the experience of physical pain.  For all of these reasons, we suggest that regret is among the experiences that can be understood as psychologically painful. Regret also meets the qualification of shared neural circuitry with physical pain. Coricelli et al. ( 2005) revealed that the regret associated with making the wrong choice in a gambling paradigm leads to activation in three main areas: the dACC, medial orbitofrontal cortex, and anterior hippocampus. Furthermore, the ACC is particularly active when people compare the outcome of a gamble with the outcome of a foregone alternative (Coricelli et al., 2005). This may be attributed to the ACC’s role in reward processing, outcome evaluation, and performance monitoring (Amiez, 2005; Boksem, Tops, Wester, Meijman, & Lorist, 2006; Oliveira et al., 2007) which are all conceptually related to the learning processes associated with avoiding regretted outcomes (Coricelli, Dolan, & Sirigu, 2007). Therefore, it is evident that activity in the ACC is associated with the experience of regret.  It is important to distinguish between the kind of regret that accompanies losing a gamble and the reflective form of regret that accompanies life-long regrets, (Leach & Plaks, 2009). These two experiences have been called hot and cold regret (Leach & Plaks, 2009; Kahneman, 1995) and may have different neural underpinnings. Thus, we may speculate that drugs that                                                 1 This result was obtained when we conducted a monthly time series analysis on Google search terms used in the US, spanning the years between 2004 and 2017. 13  attenuate ACC activity may also attenuate people’s responses to hot regret, or regret for mistakes made in the short-term.  There are also many conceptual similarities between regret and other high-level conflicts that are attenuated by acetaminophen. In DeWall (2015), they observed that people displayed less post-decision dissonance when they consumed acetaminophen. In fact, regrettable actions lead people to engage in dissonance reduction (i.e., declaring that “I learned so much from the experience”; Gilovich & Medvec, 1995), and are even theorized to produce more cognitive dissonance than actions that are not associated with feeling personally responsible for the outcome (Gilovich & Medvec, 1995).  For all of these reasons, I speculate that consuming acetaminophen may reduce the evaluative processes associated with regret, and thus reduce the sting of regret. In the present research, I test the hypothesis that acetaminophen attenuates people’s experience of regret. Ultimately, I seek to determine if regret, as well as uncertainty, are psychologically painful experiences that may have downstream consequences for how people experience physical pain. 14  Chapter 2: The present research  In study 1, I used the Nielsen Consumer Panel data to determine if uncertainty leads people to consume more painkillers. Specifically, I determined if various national indicators of uncertainty predict purchases of OTC painkiller drugs. In study 2, I determined if uncertainty increases sensitivity to physical pain by having participants place their arms in a cold pressor; a task that is commonly used to produce acute physical pain. In study 3, I explored another potential source of psychological pain: the experience of regret. Participants were administered acetaminophen, and I evaluated the impact of consuming this painkiller on self-reported regret. 2.1 Study 1: Uncertainty and painkiller purchases This study explored the hypothesis that various national indicators of uncertainty predict purchases of pain-related products. A recent study showed that economic insecurity, operationalized as state-level unemployment, predicts purchases of OTC painkillers in the US (Chou, Parmar, & Galinsky, 2016, study 1). Based on this finding, I predicted that uncertainty experienced on a national level would also increase sensitivity to pain, resulting in more painkiller purchases.   To investigate sales of OTC painkillers, I used the Nielsen Consumer Panel Data (Kilts Center for Marketing, 2016). This is a dataset that tracks purchases of consumer goods in America. I was specifically interested in products that I hypothesized would serve palliative (pain-relieving) functions. This would allow me to determine if uncertainty experienced on a national level would predict purchases of pain-related products. 2.1.1 Method The Nielsen Consumer Panel Data includes approximately 3.2 million unique products. I focused on two different product categories: over-the-counter (OTC) painkillers, and alcohol. I 15  was able to obtain monthly purchases data. The analyses I conducted were based on observations of the monthly uncertainty indices, and monthly purchases, for the months ranging from January 2004 to December 2013. This yielded 120 data points.  2.1.1.1 Panelists A total of 150,153 unique panelists were surveyed in the Nielsen Consumer Panel data. The number of panelists per year ranged from 39,577 to 63,350. These panelists were households living in 48 US States (Hawaii and Alaska were not included in the consumer panel data). We conducted a Chi square goodness of fit test to determine if the Nielsen dataset is geographically representative of the US population, finding that the sample is distributed roughly the same as the most recent U.S. Census data (2016), 𝜒" 47 = 0.04, 𝑝 = 1.00. Most households in the dataset had between 2 and 3 members (M = 2.53, SD = 1.37). Households were 83% white, 10% black, and 7% other. In terms of income, 36% households earned below $40,000 a year, 31.0 % earned between $40,000 and $70,000 a year, 32.0 % earned $70,000 to $100,000 a year, and 1% earned above $100,000.  2.1.1.2 Uncertainty Measures 2.1.1.2.1 Economic Policy Uncertainty  I used the monthly US Economic Policy Uncertainty (EPU) Index as a proxy for uncertainty. The EPU index is a measure of the frequency of newspaper articles relating to economic policy uncertainty (Baker et al., 2016). It indexes stories published in 10 major news outlets: USA Today, Miami Herald, Chicago Tribune, Washington Post, Los Angeles Times, Boston Globe, San Francisco Chronicle, Dallas Morning News, New York Times, and the Wall Street Journal. In order to meet the criteria for an article about economic policy uncertainty, the story must contain at least one word relating to the economy (“economic” or “economy”), one 16  word relating to uncertainty (“uncertain” or “uncertainty”), and one word relating to policy (“congress”, “deficit”, “Federal Reserve”, “legislation”, “regulation” or “White House”). Finally, this index takes into account tax code expirations and disagreement among professional forecasters (Baker et al., 2012).  I propose that the EPU is a good indicator of felt uncertainty among the Americans. The index has been shown to reliably forecast, and respond to various sources of social, political, and economic uncertainty (Bloom, 2014; Pástor & Veronesi, 2012; Pástor & Veronesi, 2013). The index spikes during major US and world events such as the Gulf Wars, 9/11, close presidential elections, and various disputes about policy and investment (Baker et al., 2016). These times have been known to produce widespread uncertainty among the American public.  2.1.1.2.2 Newspaper-Based Economic Policy Uncertainty Like the EPU index, the newspaper-based economic policy uncertainty (news-based EPU) index makes use of various economic policy uncertainty terms in newspapers (e.g., “uncertain” and “economy”’; Baker et al., 2016). However, it does not make use of other indicators of policy uncertainty such as federal tax code provisions about to expire and disagreement among economic forecasters (Baker, 2016). The advantage of the news-based EPU over the EPU is that the method of indexing uncertainty can be more easily extended over time and across countries. However, for my purposes, I chose to investigate the news-based EPU in addition to the EPU index because I believed that the degree to which uncertainty is expressed in media outlets should be a sufficient predictor of felt uncertainty among consumers.  2.1.1.2.3 Unemployment I used the unemployment rate as a second predictor of painkiller and alcohol purchases. I chose to include it because Chou et al. (2016) identified a relationship between OTC painkiller 17  purchases and unemployment among household heads, as well as the unemployment rate on the state-level (Chou et al., studies 1 and 2). For this reason, I anticipated that the unemployment rate would predict OTC painkiller purchases over the 10-year period we investigated. Furthermore, there is much evidence that the EPU predicts lower investment (Baker et al., 2016), indicating that the two metrics would be highly correlated. Therefore, I was interested in determining both if unemployment on a national level predicted painkiller purchases, and if economic policy uncertainty predicted purchases of painkillers and alcohol separately from unemployment. 2.1.1.3 Products 2.1.1.3.1 OTC Painkillers  I chose to investigate sales of OTC painkillers because studies have shown that acetaminophen reduces the pain associated with dissonance and uncertainty (Durso, Luttrell, & Way, 2015; Randles et al., 2013). Additionally, purchases of painkillers have been shown to increase when people experience economic insecurity (Chou, Parmar, & Galinsky, 2016, study 1). Therefore, I hypothesized that people would buy more OTC painkillers when they experience uncertainty. I used the Nielsen product category for pain remedies; specifically, products categorized as treatments for headache pain. This yielded 349 unique products (generally all variants of aspirin, ibuprofen, acetaminophen, and naproxen sodium). I chose not to include painkillers that treat specific conditions, such as arthritis and premenstrual pain.  I explored two different control variables to assess whether the relation between painkiller purchases and uncertainty is different from that found with other products. The first variable was cold medicine, which is a broad category of products that are tailored towards treating cough and cold symptoms. This was also a control used in previous studies of this kind (e.g., Chou et al., 18  2016). Though this category does include some painkiller drugs (i.e., acetaminophen), products categorized as cold medicine are not specifically for reducing pain. To investigate cold medicine, I included products categorized as cough and cold remedies, yielding 598 unique products.  Second, I looked at an even more inclusive category, Health and Beauty Products, which includes both painkillers and cold medicine, as well as many other kinds of products. In my analysis, I included all products that were categorized as Health and Beauty Products, but not as painkillers. In this way, I was able to determine if the effect was limited to OTC painkillers or if it extended to all products that one might find at a pharmacy. 2.1.1.3.2 Alcohol I investigated alcohol purchases because I believed alcohol would serve a palliative function when people experience psychological pain. This is based on the previous finding that alcohol reduces cognitive dissonance (Steele et al., 1981). Given the theoretical link between uncertainty and dissonance (see Proulx & Heine, 2010), I hypothesized that the EPU would predict alcohol purchases. To investigate alcohol sales, I looked at products categorized as alcoholic beverages. This yielded 1383 unique products (beer, wine, and liquor).   19  2.1.2 Results 2.1.2.1 Painkillers  As expected, I found that the EPU index was a strong predictor of painkiller purchases, 𝛽 = .37, t(118) = 4.35, p < .0001 (figure 2.1). I also found that unemployment independently predicted painkiller purchases, 𝛽 = .26, t(118) = 2.98, p = .004. Given the recent finding that economic insecurity leads to increased painkiller purchases (Chou et al., 2016), I wanted to assess the possibility that my results were simply the product of unemployment, which may covary with the EPU. To achieve this, I obtained the residuals of the EPU index on unemployment and used this variable to predict painkiller purchases. I found that the EPU index with unemployment partialled out positively predicted painkiller purchases, 𝛽 = .30, t(118) = 3.42, p < .001. Furthermore, when unemployment and EPU were entered into a linear model, unemployment did not predict painkiller purchases, 𝛽 = .06, t(117) = -0.46, p = .65, but the EPU index remained a strong predictor, 𝛽 = . 42, t(117) = 3.08, p = .003.  20  Figure 2.1. Painkiller purchases and EPU    Painkiller purchases were predicted by economic policy uncertainty, 𝛽 = .37, t(118) = 4.35, p < .0001.  I also looked specifically at the news-based EPU index. I found that the news-based EPU index also predicted painkiller purchases, 𝛽 = .37, t(118) = 4.35, p < .001 (figure 1.2). Next, I obtained the residuals of the news-based EPU index on unemployment, finding that news-based EPU with unemployment partialled out predicted painkiller purchases, 𝛽 =.22, t(118) = 2.01, p = .046.  Furthermore, when unemployment and news-based EPU were entered into a linear model, unemployment did not predict painkiller purchases, 𝛽 = .14, t(117) = 1.30, p = .20, but news-based EPU did, 𝛽 = . 22, t(117) = 2.01, p = .04. This suggests that the effect of EPU on painkiller 21  purchases is not driven by an increase in the unemployment rate when the news-based EPU index is higher.  Figure 2.2. Painkiller purchases and news-based EPU   Painkiller purchases were predicted by news-based economic policy uncertainty, 𝛽 = .37, t(118) = 4.35, p < .001.  2.1.2.2 Controls First, looking at cold medicine, I found that the EPU index had marginal negative relationship with purchases in this category, 𝛽 = -.18, t(118) = -1.98, p = .05. This was not surprising because it has been noted in previous literature that the EPU index negatively predicts 22  investment in the economy (Baker et al., 2016); thus, I interpret this finding to mean that cold medicine can be understood as somewhat of a luxury product that is not purchased when the economy is uncertain. The news-based EPU index also had a marginal negative relationship with cold medicine purchases, 𝛽 = -.16, t(118) = -1.80, p = .07. Again, I interpret this finding to mean that cold medicine is among the products that are invested in less when the economy is uncertain.  Consistent with this these findings, unemployment negatively predicted cold medicine purchases, 𝛽 = -.26, t(118) = 2.90, p = .004.  Next, turning to the health and beauty product category, I found that this category was negatively predicted by the EPU index, 𝛽 = -.23, t(118) = -2.57, p = .01. Likewise, I found that the news-based EPU index also negatively predicted purchases in the Health and Beauty category, 𝛽	 = 	−.23, t(118) 	= 	−2.60, p	 = 	 .01. Health and beauty purchases were also negatively predicted by unemployment, 𝛽 = -.25, t(118) = -2.81, p = .006. In sum, whereas painkiller purchases are positively predicted by uncertainty, cold medicine and the more inclusive category of health and beauty products both negatively predict painkiller purchases.  2.1.2.3 Alcohol The second product category that I hypothesized would be related to uncertainty was alcohol, given that I expect people might self-medicate when feeling uncertain. I found that the EPU index positively predicted alcohol purchases, 𝛽 = 0.24, t(118) = 2.68, p = .008 (figure 2.3). Unemployment also predicted alcohol purchases, 𝛽 = 0.22, t(118) = 2.50, p = .01. However, the residuals of EPU on unemployment did not predict alcohol purchases, 𝛽 = .09, t(118) = 0.69, p = .49. 23  Figure 2.3. Alcohol purchases and EPU    Alcohol purchases were predicted by economic policy uncertainty, 𝜷 = 0.24, t(118) = 2.68, p = .008.  I then investigated the news-based EPU index, finding that it marginally predicted alcohol purchases, 𝛽 = 0.17, t(118) = 1.96, p = .053 (figure 2.4). However, the residuals of the news-based EPU index on unemployment did not predict alcohol purchases, 𝛽 = .07, t(118) = 0.67, p = .51. Taken together, these results suggest that the relationships between the two EPU indices and alcohol purchases were driven by the increased unemployment rate. My interpretation of this finding is that although policy uncertainty does appear to have a relationship with alcohol purchases, it is more difficult to conclude that the driving factor is a sense of uncertainty that 24  leads people to seek out palliative products. Rather, I propose that other psychological messages that might accompany unemployment; for example, boredom and free time; may be driving the relationship between EPU and alcohol purchases. Taken together, these findings lead me to conclude that there is a unique relationship between the experience of uncertainty on a national scale and painkiller consumption.  25  Figure 2.4. Alcohol purchases and news-based EPU    Alcohol purchases were marginally predicted by news-based economic policy uncertainty, 𝛽 = 0.17, t(118) = 1.96, p = .053.  2.1.3 Discussion I found that the EPU index and the news-based EPU index predicted purchases of OTC painkillers. Although unemployment also predicted painkiller purchases, the relationship between painkiller purchases and the EPU index, as well as painkiller purchases and the news-based EPU index, was stronger. Furthermore, uncertainty predicted painkiller purchases even after accounting for the influence of unemployment on uncertainty. Though all indices also predicted liquor purchases, the relationship between uncertainty and painkiller purchases was 26  best accounted for by unemployment. Therefore, study 1 suggests that people seek out palliative, or pain-killing products, during uncertain times. Though it is possible that stress is driving the effect of uncertainty and painkiller consumption, I would expect that other product categories that are associated with stress and illness (e.g., cold medicine) would show a similar pattern to OTC painkillers. Given that this was not the case, we are reasonably confident that panelists were experiencing increased physical pain sensitivity, and the effect was not entirely attributable to stress. Though these findings serve as preliminary evidence that uncertainty affects painkiller purchases, there are many limitations to the present study. Namely, the analysis I conducted did not allow me to investigate any psychological or demographic variables associated with the panelists. Namely, I would be interested in determining if gender interacts with pain-related uncertainty, given that unemployment is more stressful for men than women (Artazcoz et al., 2004). Therefore, it is plausible that uncertainty in the economy leads to increased pain sensitivity among men, but not women. Furthermore, according to the MMM, engaging in fluid compensation strategies would allow panelists to experience less anxious uncertainty after a meaning-threating experience. Therefore, it is possible that the effect of uncertainty on physical pain is less pronounced among people who compensate for uncertainty; for example, by participating in a religion. For these reasons, a controlled, and in-depth analysis of the mechanisms driving the effect of uncertainty on painkiller consumption is needed. 2.2 Study 2: Uncertainty and pain sensitivity In study 1, I found that indicators of national uncertainty predict painkiller purchases. In study 2, I wanted to find support for the link between pain and uncertainty in a controlled experimental setting. I manipulated uncertainty and then measured sensitivity to physical pain 27  using a cold pressor task (CPT). This task involves placing one’s arm in ice water up to the elbow and leaving it there until the experience becomes painful, or uncomfortable (Wolf & Hardy, 1941). This method has been used to measure physical pain sensitivity following events that are believed to increase, or decrease, psychological pain (see Brown et al., 2003; see also Chou et al., 2016; Feldner & Hekmat, 2001).  2.2.1 Methods 2.2.1.1 Participants I recruited a total of 197 participants. This sample size was determined from effect size estimates from previous studies of uncertainty and compensatory affirmation (Randles et al., 2013). Of these initial 197 participants, 23 of which were discarded from our analysis because of various procedural and instructional errors2. There were 175 participants (52 male, 123 female) included in this study. Participants were primarily of East Asian (56%), and European (28%) descent. As their first language, participants primarily spoke English (50.3%) and Chinese (28.6%). The mean age was 21.38 (SD = 5.11).  2.2.1.2 Procedure The study was described as a measure of pain sensitivity. Participants were offered either course credit, or $10.00 for their participation. The cold pressor task consisted in a large basin filled with water, a compartment with ice packs contained kept separate from the participant’s                                                 2 Seven participants were removed because the water during the CPT was either too cold and participants did not complete both trials, or not cold enough, and participants left their arm in for the full 3 minutes during the first trial. Two participants placed their arm in the cold water early or multiple times during the first trial, and two participants completed the task with a second person in the room. One participant was accidentally read the debrief before the study began.   28  arm, and a fish pump to circulate the water. The temperature of the water was kept at 4 degrees Celsius. This temperature is safe but capable of quickly producing discomfort. Though we tried to keep the task consistent between trials, we allowed the temperature of the water to vary by 2 degrees Celsius in either direction. We excluded trials where the temperature exceeded 7 degrees Celsius, or went below 2 degrees Celsius.  Participants were first instructed to fill out a brief demographics survey. Afterwards, they were brought into the room with the cold pressor. Participants were told to place their dominant arm in the ice water until the task became painful, or uncomfortable (12 participants were left-handed). They were explicitly told that we were not measuring pain tolerance, but sensitivity to pain. When participants would describe the situation as painful, or when it was uncomfortable to leave their arm in the water, they should remove it. During the task, the researcher was instructed to stand about a meter behind the participant and look in a different direction. This ensured that participants all had roughly the same experience of social evaluation. The researcher began recording participants’ time in the water when they had their arms immersed up to their elbow. For safety reasons, the researcher did not allow participants to leave their arms in the cold pressor for more than 180 seconds.   Participants completed the cold pressor task twice. The first measurement provided me with a measure of participants’ baseline sensitivity to pain. Before the second trial, they were reminded again that the experiment was measuring sensitivity to pain rather than pain tolerance, and that participants should remove their arms from the ice water when it became uncomfortable or painful to leave it in.  Next, participants completed the uncertainty manipulation. In this task, participants were subliminally presented with word pairs that were either coherent (control) or incoherent 29  (experimental). The coherent word pairs were meaningful and sensible to participants (e.g., turn-left, bull-frog) whereas the incoherent word pairs were meaningless and nonsensical (e.g., turn-frog, bull-left). The full list of word pairs used in this study is attached in Appendix A. This task has been used in previous studies to produce uncertainty, and has been shown to lead to compensatory affirmation and abstraction responses (Randles et al., 2011). Participants saw a fixation cross for 1000 ms, after which they were shown a series of words for 356 ms each. They were tasked with sorting these words into “pleasant” or “unpleasant” categories. In fact, this was a filler task meant to disguise the true purpose of the manipulation. It was between trials of the sorting task that participants viewed the word pairs. Each pair was displayed for 42 ms. Given that I was not expecting participants to detect the manipulation, I did not explicitly ask participants if they felt uncertain after exposure to the word pairs. After being exposed to the word pairs, participants completed the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). This is a measure of people’s transient mood states. Scales like the PANAS are often used to create a delay period between the uncertainty prime and the presentation of the dependent variable in studies of this kind (e.g., Randles, Heine & Santos, 2013).  Lastly, participants completed a second trial of the cold pressor task. My primary dependent variable for this study was the degree of change in participants’ willingness to leave their arms submerged in the ice water after exposure to the meaningless word pairs.  30  2.2.2 Results Approximately 39% of participants indicated that they had seen the subliminally-presented words3. Though this indicates that our procedure did not lead to true subliminal presentation, this is not different from what has been observed in previous studies of this kind (see Randles et al., 2011).  To determine if uncertainty increased participants’ sensitivity to pain, I obtained the standardized residuals of performance at time 2 on time 1. This allowed me to account for individual differences in pain sensitivity, controlling for performance on the task at time 1. Using this approach, I found that there was no difference in performance change at time 2, F(1, 173) = .023, p = .880. Contrary to my predictions, participants in the meaning threat condition (M = .012, SD = 1.19) did not experience a greater decrease in performance than participants in the no-threat control group (M = -.011, SD = 0.78). Overall, there was no effect of threat on performance in the cold pressor task at time 2 (see figure 2.5).                                                  3 When we excluded participants who correctly identified at least one word pair, our sample was severely depleted and our findings did not reach significance, F(1, 57) = 0.13, p = .72.  31  Figure 2.5. Uncertainty condition and cold pressor time  There was no difference between conditions in terms of cold pressor performance at time 1 and time 2 and condition, F(1, 173) =  .079, p = .78. 2.2.3 Discussion In this study, I did not observe a difference between my uncertainty and control conditions. Therefore, it is possible that uncertainty does not increase people’s sensitivity to physical pain. On the other hand, studies have shown that there is shared sensitivity between physical and social pain (Eisenberger et al., 2006) and that experiences like lacking control increase pain sensitivity (Chou et al., 2016). Given the evidence supporting that various arousing or distressing experiences increase sensitivity to physical pain, I speculate that the current study suffered from various theoretical and methodological shortcomings that prevented me from detecting a relationship between pain and uncertainty. 05101520253035404550Control ThreatTime in Cold Pressor (seconds)ConditionTime 1 Time 232  Firstly, it is possible that my subliminally-presented word pairs were too easy to identify, and this prevented our manipulation from producing uncertainty. Proulx and Heine (2008) found that for subliminally-presented meaning threats, misattributing one’s arousal to a saline solution leads people to engage in less affirmation. Therefore, I may speculate that the manipulation failed to produce uncertainty because participants were able to identify the source of their arousal; specifically, the word pairs being flashed across the screen.  Another possibility is that the cold pressor task failed to accurately measure pain sensitivity. My task was different from previous studies involving cold pressor for various reasons. Firstly, due to procedural limitations4, I was unable to keep the cold pressor cooler that 3 degrees Celsius, and the temperature of the water averaged 4 degrees Celsius. This is one degree warmer than the water that is traditionally used in cold pressor tasks (see Chou et al., 2016; see also Wolf & Hardy, 1941). Finally, I instructed participants to leave their arms in the water until it became uncomfortable or painful for them. It is possible that each participant had a different interpretation of what was uncomfortable or painful, leading to variance in participants’ performance that obscured any systematic differences between my two conditions.   Lastly, I speculate that one acute experience of uncertainty is not enough to affect people’s sensitivity to physically painful stimuli. Given that in study 1, the threats were more pervasive and self-relevant, I speculate that more chronic forms of uncertainty produce a change in pain sensitivity whereas single isolated incidents do not.  Though past research has shown that reminders of economic insecurity can lead to changes in performance on the cold pressor task                                                 4 Due to the volume of participants who completed the study each day, we were unable to maintain the temperature at 1 degree Celsius. Additionally, we used ice packs to maintain the water temperature and only supplemented with ice, which makes it much more difficult for water to reach near zero temperatures.   33  (Chou et al., 2016), subliminally-presented word primes may not be impactful enough to produce changes in pain sensitivity. For these reasons, I will continue to pursue this research question using a wider range of uncertain paradigms and pain sensitivity measures.   2.3 Study 3: Acetaminophen and regret  Studies 1 and 2 were concerned with the relationship between uncertainty and physical pain. In study 3, I investigated whether regret, a concept related to dissonance and decision error (Coricelli et al., 2005; Thomas Gilovich & Medvec, 1995) is related to physical pain processing. Specifically, I was interested in whether consuming acetaminophen attenuates people’s responding to regretful experiences. This study represents a first attempt to establish regret as one of the experiences that are psychologically painful. 2.3.1 Methods 2.3.1.1 Participants I recruited 316 undergraduate students from the University of British Columbia Human Subjects Pool. This sample size, though somewhat conservative, was based on effect size estimates from previous studies of acetaminophen on compensatory affirmation (Randles et al., 2013). One participant was discarded because they did not consume the capsule, and 3 were discarded because the experimenter did not record their anonymous ID properly and was unable to determine which condition they were assigned to. Of the remaining 312 participants. 76% were female, and the average age was 20.07 (SD = 3.53). In terms of ethnicity, the largest portion of our sample (42.63%) identified as East Asian (Chinese, Taiwanese, or Korean), 29.50% identified as White (British or European descent), and the next largest group (9.94%) identified as South Asian (India, Pakistan, Bangladesh). The largest portion of participants spoke English 34  as their first language (53.21%) and the second largest spoke Chinese (Mandarin or Cantonese) as a first language (24.36%). All participants were compensated with 2 credits towards their psychology courses. 2.3.1.2 Procedure Acetaminophen reaches peak concentration at 45 to 60 minutes (Bertolini et al., 2006; Mallet et al., 2008) and therefore participants waited in the room for 45 minutes before receiving any experimental materials. This is consistent with what has been done in other psychological studies of acetaminophen (e.g., Durso, Luttrell, & Way, 2015; Randles, Heine, & Santos, 2013). I was also very cautious about which participants were given acetaminophen due to the risks associated with exceeding the maximum dosage, and the various health conditions that can make acetaminophen dangerous (Graham, Davies, Day, Mohamudally, & Scott, 2013; James, 2003). Before I administered the pill, participants were told that they should not participate if they were on any medication, if they had been diagnosed with alcoholism, if they had consumed more than 2 alcoholic drinks within the last 24 hours, if they had taken Tylenol within the last 24 hours, if they had a history of liver concerns, or if they had any allergies to Tylenol. If participants did not meet my specifications, they were granted credit for the study but did not receive any of the experimental materials. When I was confident that it was safe for them to consume acetaminophen, participants were randomly assigned to one of our experimental (Tylenol) or control (placebo) conditions. Those in the experimental condition were given 1000mg of extra-strength Tylenol (the active ingredient in Tylenol is acetaminophen), and those in the control condition were given 1000mg of sugar (placebo). One thousand milligrams of acetaminophen is the maximum recommended dose for adults, and it is also the peak effectiveness (Gibb & Anderson, 2008). Both the experimenter and the participant were blind to the pill condition. 35  After the 45-minute waiting period, participants completed a number of filler tasks. First, they were given 10 minutes to complete as many Sudoku puzzles as possible. Next, they filled out a demographics survey, the 10-item personality inventory (TIPI; Gosling, Rentfrow, & Swann, 2003), and the Personal Need for Structure scale (PNS; Neuberg & Newsom, 1993). These questions were included to ensure that the acetaminophen had reached peak absorption for all participants. Next, they filled out the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). The PANAS was included to investigate whether any findings were mediated by changes in affect.  Before completing the manipulation, participants engaged in a task for a separate study. They played a competitive reaction time game intended to elicit reactive aggression. They then filled out a series of surveys measuring their propensity to engage in aggressive behaviours when provoked. Afterwards, participants were shown a number of regret-eliciting stimuli. Their responses to these stimuli served as our primary dependent variables. 2.3.1.2.1 Regret vignettes Participants were shown two regret-inducing vignettes: one in which they were told that they had been assigned to a low-paying summer job, and another in which they were told that they had been assigned to an undesirable course section. For both, participants were told to imagine that the scenario happened to them personally. They were instructed to picture the situation in vivid detail, and to think about exactly what the experience would feel like. The job vignette was adapted from Leach and Plaks (2009; See Appendix B). Participants were asked to select between job 1 and job 2, knowing that one of them would turn out to be a more desirable job than the other. Participants were unaware of which one would be the more desirable job until after they made a selection. No matter what participants chose, they were informed that they 36  were assigned to the low-ranking, low-paying position. They were also informed that if they had accepted the other job, they would have been given the high-ranking, high-paying position. The experience of regret requires that people feel responsibility for the outcome (Zeelenberg & Pieters, 2007). For this reason, participants were prompted to choose between the two jobs, and were made aware that they had made the wrong choice. Participants also read a vignette in which they were asked to choose between two course sections, one of which was desirable and one of which was undesirable. Participants did not know which one would be the desirable section until after they had chosen. The vignette was adapted from Connolly et al. (1997; see Appendix B). As in the job vignette, participants made a selection between two course sections. No matter what they chose, participants were told that they ended up in the undesirable course section. After being presented with each vignette, participants filled out a four-item measure of how much regret they experienced (see Appendix B). Example items are “how much do you regret your decision” and “how happy are you with your decision”, reverse-coded. Participants gave their responses on a scale ranging from 1(Not at All) to 7(Extremely). The order of the vignettes was randomized. 2.3.1.2.2 Cognitive reflection task Counterbalanced with these vignettes was the cognitive reflection task (CRT; Frederick, 2005). This task is a three-item measure designed to test the degree to which people are engaged in system 1 and system 2 processing. An example item is “a ball and a bat cost $1.10 together. The ball costs $1.00 more than the bat. How much does the bat cost?”. The answer to this question is 5 cents, because 1 dollar more than 5 cents is $1.05. However, the intuitive answer is 10 cents because it comes more easily to mind. The CRT measures the degree to which people provide the accurate response (system 2) rather than the intuitive response (system 1). I included 37  this measure because the ACC has been theorized to play a role in conflict monitoring during dual process tasks (see Alter, Oppenheimer, Epley, & Eyre, 2007; see also De Neys & Glumicic, 2008) though I was not aware of any specific studies that test this claim. I predicted that participants who consumed acetaminophen would engage in system 1 processing rather than system 2 processing because they would be less able to detect the conflict between possible responses, which is essential to overriding the “intuitive” system 1 response (De Neys & Glumicic, 2008). I also included this measure to determine if changes in cognitive processing mediate the relationship between acetaminophen and regret sensitivity. 2.3.1.2.3 Personality measure of regret I used the Regret Scale, a 5-item measure of people’s tendency to experience regret (Schwartz et al., 2002). This scale has been reliably used to measure regret proneness, and to predict various related constructs such as maximization and indecisiveness (see Spunt, Rassin, & Epstein, 2009; see also Zeelenberg & Pieters, 2007). I included this measure to determine if my regret vignettes were more successful in eliciting regret among people who are prone to experiencing it.  2.3.2 Results After completing the study, participants indicated which of the two pills they believed they had taken. Consistent with what has been found in previous studies of this kind (e.g., Randles et al., 2013) only 52.6% of participants correctly guessed which pill they had taken, which is not different from chance5 (p =.35).                                                   5 Excluding participants who correctly guessed their condition did affect any of the findings.  38  2.3.2.1 PANAS The results of the PANAS showed that there was a marginal relationship between negative affect and pill condition, where the acetaminophen group (M = 20.66, SD = 6.39) experienced slightly less negative affect than participants in the control group (M = 21.64, SD = 6.09), t(311) = -1.37, p = .17. This direction is consistent with previous research, which shows that affect is dampened by acetaminophen (Durso et al., 2015). However, I did not find a relationship with positive affect, as there was no difference between the acetaminophen group (M = 18.03, SD = 5.38) and the placebo group (M = 17.94, SD = 6.09). t(311) = 0.15, p = .88, which is different from what I would have predicted given that Durso et al. (2015) observed attenuated positive and negative affect after participants consumed acetaminophen. Though they did not use the PANAS as their dependent variable, it is noteworthy that I did not replicate this finding in the current study. Taken together, this is not compelling evidence that acetaminophen led to a change in affect. 2.3.2.2 Personality measure of regret Our measure of trait-level regret sensitivity had acceptable reliability (α = .76). As predicted, I did not observe a difference in people’s sensitivity to regret after consuming acetaminophen (M = 21.57, SD = 6.07) and after consuming a placebo (M = 21.24, SD = 6.07), t(309) = -.477, p = .63.  2.3.2.3 Job regret My four-item regret scale did not have acceptable reliability (α = .62) which suggests that I may have been unable to detect a change in regret using this dependent variable. Using this scale, I found no relationship between the acetaminophen condition (M = 20.64, SD = 4.46) and control condition (M = 20.39, SD = 4.68), t(266) = -0.45, p = .65 (figure 2.6). Therefore, I 39  assessed regret as a single-item measure, using the question “how much do you regret your decision”. Again, I found no difference between the acetaminophen (M = 4.30, SD = 1.91) and control (M = 4.10, SD = 2.00) conditions, t(264) = -0.83, p = .41. Due to an error in the script randomization, only 266 of 312 participants responded to the vignette6.  Figure 2.6. Pill condition and job regret   There was no difference between the acetaminophen and placebo conditions on my measure of regret after participants read the job vignette, t(266) = -0.45, p = .65.  These results suggest that I did not elicit regret, that my dependent variables failed to measure regret, or that acetaminophen did not have an impact on regret as it was operationalized in my study. Though it is difficult to decide which scenario I am facing, the personality measure of regret did predict more regret from the job vignette, ß = .18, t(264) = 3.04 p = .003, and was                                                 6 Some participants were not presented with both regret vignettes, due to an error in the randomization of the Qualtrics script. We were not made aware of this error until later in our data collection. The results were not different when we excluded participants who did not see all of the stimuli, t(184) = -.44, p = .66. 1919.52020.52121.522Placebo Acetaminophen40  marginally predictive of my single-item measure of regret, , ß = .10, t(264) = 1.57p = .12. This suggests that I did elicit regret with our job vignette, though I am hesitant to declare that I elicited the specific form of regret that might be attenuated by acetaminophen.  2.3.2.4 Course regret  Again, due to an error in the script randomization, some participants did not see the course regret vignette7. As was the case with my job regret measure, my four-item regret scale did not have acceptable reliability (α = .54). Using this scale, I found no relationship between the acetaminophen condition (M = 21.25, SD = 4.39) and control condition (M = 20.48, SD = 4.23), t(265) = -1.44, p = .15 (see figure 2.7). I also assessed regret as a single-item measure, and found no difference between the acetaminophen (M = 4.30, SD = 2.01) and control (M = 4.09, SD = 1.87) conditions, t(265) = -0.87, p = .39. This either suggests that I did not elicit regret, or that acetaminophen did not have an impact on regret. The personality measure of regret did predict more regret following the course vignette, ß = .16, t(265) = 3.00, p = .01, but did not predict regret in our single-item measure of regret, ß = .02, t(265) = 1.15, p = .25. This serves as mixed evidence that I successfully elicited regret with our course vignette.                                                  7 When I excluded participants who did not see all of the stimuli, the results were not different, t(184) = -1.38, p = .17. 41  Figure 2.7. Pill condition and course regret   There was no difference between the acetaminophen (M = 21.25, SD = 4.39) and placebo (M = 20.49, SD = 4.23) conditions on my measure of regret after participants read the course vignette, t(265) = -1.44, p = .15. Overall, I am unable to demonstrate that regret was affected by consuming acetaminophen. Though I did not find any differences between my pill conditions in terms of regret, I did find a difference in performance on the CRT task. Participants assigned to the control condition (M = 1.16, SD = 1.15) scored lower on the CRT than those assigned to the experimental condition (M = 1.45, SD = 1.18), t(273) = 2.13, p = .034. In fact, this finding is in the opposite direction of what I was anticipating. That is, I expected system 2 processing would decrease after participants consumed acetaminophen given that the ACC is responsible for conflict detection, and detecting conflict is necessary for suppressing system 1 processing. Given the unexpectedness of this result, I am hesitant to make any claims about what it means. To my knowledge, this is the first study to demonstrate a relationship between acetaminophen and 1919.52020.52121.522Placebo Acetaminophen42  performance on dual processing tasks. Lastly, the CRT did not serve as a moderator for any of my other findings. 2.3.3 Discussion In the present study, I did not determine that acetaminophen attenuates people’s experience of regret. This suggests either that there is no relationship between regret and activation in the neural regions associated with acetaminophen; that various methodological and procedural errors prevented me from finding an effect; or that there is a relationship between regret and acetaminophen, but I did not elicit the kind of regret that is attenuated by consuming acetaminophen. In terms of the first possibility, though it is conceivable that my hypothesis is incorrect, studies have shown that regret leads to activation in the ACC (Coricelli et al., 2005), especially when people are comparing their selection with more desirable alternatives. Moreover, there is much evidence that related constructs such as cognitive dissonance and decision errors lead to activation in this area (Carter, 1998; van Veen et al., 2009). Therefore, I suspect that the results I obtained reflect one of the other two possibilities; namely, that methodological errors prevented us from detecting an effect, or that there is an effect of acetaminophen on regret, but not the kind of regret that was elicited in the present study. Firstly, there are many reasons why I may have failed to measure regret. Our four-item measure of regret had low reliability for both the job vignette and the course vignette, which affects the degree to which my dependent variable is able to detect differences between the two conditions. Furthermore, the wording of our regret scale was such that I was asking participants how much regret they were feeling, rather than how much regret they might feel if they had actually experienced the situations outlined in the vignettes. This may have led to some confusion or misunderstanding among some of our participants. That is, they may have answered 43  that they were experiencing no regret because they were not actually participating in the scenario outlined in the vignettes.  Secondly, it is possible that I did not elicit the particular kind of regret that is affected by consuming acetaminophen. In my design, participants were asked to imagine that they were experiencing regret. In contrast, previous studies involve gambling tasks in which participants were told that they would receive whatever money or prizes they won during the study (e.g., Coricelli et al., 2005; Gilovich, Medvec, & Chen, 1995) and for this reason, participants were truly regretful when they made a mistake. This suggests that the present study suffered from a lack of realism. Though my personality measure of regret predicted how much participants reported experiencing regret after reading the vignettes, it is possible that my procedure did not elicit real regret. Alternatively, there are various reasons why acetaminophen may have made the act of imagining regret more challenging. Mischkowski et al. (2016) found that people are less able to empathize with the social pain experienced by others after consuming acetaminophen. Thus, it is possible that acetaminophen interrupts people’s ability to imagine psychologically painful experiences, leading them to respond differently to our vignettes for reasons that are unrelated to regret. Indeed, the only difference I observed between my two pill conditions was in their performance on a cognitive task (i.e., the CRT) suggesting that the act of imagining regret produced confounds in my design such that participants’ cognitive evaluation of the vignettes differed between conditions. Finally, it is possible that participants were unconvinced by my manipulation because the job and course vignettes were structurally quite similar, and as a result, their purpose was not well-disguised. For all of these reasons, I suggest that future studies elicit real rather than imagined regret, and make use of more reliable measures of regret.   44  Chapter 3: General Discussion Studies 1 and 2 tested the hypothesis that uncertainty, like other forms of psychological pain (i.e., social rejection), increases sensitivity to physical pain. I found partial evidence that people are more likely to experience physical pain when they are uncertain. Specifically, in study 1, various US national indicators of uncertainty predicted purchases of OTC painkillers among American consumers. In study 2, I did not find evidence that uncertainty makes people more sensitive to physical pain. Although I do not yet have laboratory evidence to support a relationship between pain sensitivity and uncertainty, I believe that studies 1 and 2 represent important first steps in uncovering the relationship between meaning-threatening experiences, psychological pain, and physical pain. In study 3, I tested the hypothesis that regret may be among the experiences that are attenuated by acetaminophen. I did not find any evidence that acetaminophen reduces sensitivity to regret. I speculate that my study was not successful in eliciting the specific kind of regret that might be affected by acetaminophen. Therefore, I hope to explore new approaches to the study of regret, beginning with situations that elicit real rather than imagined regret.  I believe that these three studies represent promising new directions in the study of pain, psychological threat and uncertainty. There is much research supporting that social rejection increases sensitivity to physical pain (DeWall et al., 2010; Eisenberger, 2003; Eisenberger, Jarcho, Lieberman, & Naliboff, 2006; Eisenberger & Lieberman, 2004) but there is little evidence that experiences like uncertainty and regret increase sensitivity to physical pain. However, there are various theoretical limitations that must be addressed before I draw conclusions about the contributions of the present set of studies.  45  3.1 Limitations  3.1.1 A unifying definition of uncertainty One theoretical limitation is the degree to which I can assume that uncertainty, as it is captured by the threat defense literature, is conceptually similar to what I am measuring in the present program of research. For example, the news-based EPU index is an economic tool for assessing policy uncertainty, and though it spikes during times that are experienced as uncertain by Americans (Baker et al., 2016), it was not developed for the purpose of predicting “meaning threats”, as outlined by the MMM. Scholars have pointed out that uncertainty can be defined in many different ways. Van den Bos and Lind (2001) make a distinction between hot uncertainty and cold uncertainty, where hot uncertainty is the kind of uncertainty that threatens people’s identity and cold uncertainty is the kind of uncertainty that is experienced when people are evaluating probabilities. These are also referred to as personal uncertainty and informational uncertainty, respectively (see van den Bos, 2009). It is argued that cold uncertainty is not personally threatening, and that only hot uncertainty is associated with “a subjective sense of doubt or instability in self-views, worldviews, or the interrelation between the two” (van den Bos, 2009, p. 198). Though the MMM does not explicitly make a distinction between different forms of uncertainty (see Heine et al., 2006), it becomes evident that informational uncertainty as it is defined here may not meet our definition of a meaning-threatening experience. This calls into question whether indices like the news-based EPU index are evaluating the same construct as other meaning maintenance studies, or other studies from the threat defense literature. This is an important limitation of the present research. However, there is much evidence that outcome uncertainty produces activation in the ACC (see Shackman et al., 2011, for a review) and so it is reasonable to speculate that informational uncertainty is not so distinct from 46  more existential forms of uncertainty. Furthermore, studies have shown that information uncertainty does lead to compensatory affirmation behaviours (bolstering one’s worldview) that are similar to those observed after meaning-threatening experiences (e.g., Grieve & Hogg, 1999; Hogg, 2003). Most relevant to the current research, there is some preliminary evidence that uncertainty in politics predicts painkiller consumption. In one study, it was found that the degree to which people reported experiencing worldview threat after the 2016 US national election predicted how many painkillers they took in the following week (Benjamin & Heine, unpublished data).  Despite this evidence, it is still possible that the results obtained in the present set of studies are driven by a mechanism besides pain and ACC activation. For example, stress may lead people to experience more pain, which might motivate the purchase of more painkiller drugs. It should be noted that if stress were the mechanism driving painkiller purchases, I would also expect an increase in purchases of other pharmaceuticals (e.g., cold medicine) which I did not observe. Nevertheless, I must acknowledge that I am not certain that the news-based EPU index actually tracked meaning-threatening experiences, and I am therefore unsure about the meaning of my findings. I suggest that future researchers resolve this ambiguity by conducting controlled laboratory studies of different forms of uncertainty. Specifically, future studies should determine if different forms of uncertainty can lead to increased pain sensitivity. 3.1.2 Acetaminophen in the brain Acetaminophen has been theorized to attenuate activity in the ACC, specifically the dorsal area (DeWall et al., 2010). There is fMRI evidence that activity in the dACC in reaction to an interpersonal rejection is attenuated by consuming acetaminophen (DeWall et al., 2010, study 1) and that unlike some other painkiller drugs, acetaminophen is most active in the central 47  nervous system rather than the peripheral nervous system (Anderson, 2008). However, the precise mechanism by which acetaminophen attenuates physical pain is largely unknown (DeWall et al., 2010; Toussaint et al., 2010). For this reason, I cannot be confident that the mechanism through which acetaminophen attenuates people’s responses to psychologically painful events is via the dACC. This raises certain questions about the efficacy of acetaminophen studies in determining the relationship between psychological pain and activation in the dACC. Acetaminophen has been shown to affect a variety of other neural regions besides the dACC; for example, it attenuates responding in areas associated with affective processing (DeWall et al., 2010). Randles (2013) noted that acetaminophen might affect various cognitive processes or attentional systems, creating some ambiguity about the causal mechanisms involved in studies with acetaminophen. Indeed, many theorists acknowledge that studies using acetaminophen suffer from our limited knowledge of which neural mechanisms acetaminophen is acting upon (see DeWall et al., 2010; Durso, Luttrell, & Way, 2015; Mischkowski, Crocker, & Way, 2016; Randles et al., 2013). In fact, acetaminophen has also been found to affect the cannabinoid 1 (CB1) receptor (Ottani, Leone, Sandrini, Ferrari, & Bertolini, 2006) which has been shown have a relationship with physical pain (for a review, see Pertwee, 2001). This makes activity on CB1 receptors a good candidate for an alternate explanation for acetaminophen’s many palliative properties. Indeed, Deckman et al. (2014) found that another drug that produces CB1 receptor activation, marijuana, attenuates social pain as well as physical pain. Though it is likely that acetaminophen does attenuate activity in the ACC, it is not clear that this is its primary function in reducing physical and psychological pain. Therefore, I am unsure if the mechanism I propose (specifically in study 3) is supported by the literature. Given the many limitations of the 48  present research, I suggest a variety of future directions that will allow me to address these theoretical shortcomings. 3.2 Future Directions  3.2.1 Neural evidence  One way to overcome the uncertainty associated with acetaminophen’s activity in the brain is by obtaining neural evidence. The studies I conducted are premised upon the assumption that the signal that manages experiences like regret and uncertainty originates in the dACC. In study 3, I claim that acetaminophen should interrupt people’s responding to regret, which originates in the dACC. Though there is fMRI evidence that the ACC is active during experiences that are theoretically related to conflict and uncertainty, there is no neural evidence that the stimuli used in these studies are associated with activation in the ACC.  There are many reasons why this research would benefit from obtaining neural evidence that the specific experience that the MMM outlines (i.e., disanxiousuncertlibrium) relies on activity in the ACC. The point has been raised that efforts to maintain meaning may involve other systems besides simple conflict detection, such as the behavioural inhibition system (BIS) and norepinephrine system (Proulx & Inzlicht, 2012b). Therefore, it is possible that the experiences I used to elicit uncertainty are distinct enough from the low-level cognitive conflicts used to produce ACC activation in previous studies (e.g., the Flanker task and the Stroop task) that my proposed mechanism may not be correct. The uncertainty associated with living in an unstable social and political climate (see study 1) and the uncertainty associated with perceiving mismatched word pairs (see study 2) may not rely on the same mechanisms as those that govern low-level contradictions (see Shackman et al., 2011) or even distinct forms of high-level contradiction (e.g., cognitive dissonance; see Izuma et al., 2010). For these reasons, future 49  research should focus on obtaining direct neural evidence that the ACC is involved in uncertainty management of the kind outlined in the MMM.  I propose that future research makes use of fMRI to investigate the neural regions associated with the processing of uncertainty. Specifically, I am interested in determining if activation of ACC accompanies the experience of being reminded about uncertainties in the world, such as social and political events that produce uncertainty, as well as uncertainty associated with both explicit and implicitly-perceived meaninglessness like the “quickly-blueberry” paradigm outlined in study 2. Though the MMM maintains that all threats to meaning produce a similar defensive response in the ACC, there is not yet evidence supporting this claim. I also propose that future studies make use of electroencephalographic (EEG) paradigms to investigate the neural substrates associated with the stimuli used in MMM studies. Research with EEG allows us to draw conclusions about how experiences are processed in the brain. Specifically, events that produce error-related negativity (ERN) and error-related positivity (Pe), two components of the evoked-response potential (ERP), can be inferred to elicit activation in the anterior cingulate cortex (Dehaene, Posner, & Tucker, 1994; Herrmann et al., 2004; Stemmer et al., 2004). This makes EEG studies particularly useful for the present line of research. Thus far, studies have shown that errors made on the Flanker task, Stroop task, and go/no-go task reliably produce ERN and Pe signals (see Liotti et al., 2000; Nieuwenhuis et al., 2003; Scheffers & Coles, 2000). For this reason, the ERN and Pe signals have been associated with error processing and conflict detection (Herrmann et al., 2004; Yeung, Botvinick, & Cohen, 2004). However, these signals are also elicited by other cognitive experiences such as violated expectations during learning tasks (Holroyd & Coles, 2002). Trait sensitivity to punishment and rewards has also been shown to predict the size of the ERN response (Boksem et al., 2006) 50  where sensitivity to reward and punishment is associated with people’s likelihood of compensating for uncertainty (Jonas et al., 2014; McGregor, Nash, & Inzlicht, 2009). Given that the ERN and Pe are associated with ACC activation, and given that tasks which are associated with conflict elicit ERN and Pe responses, I propose that future studies use EEG to investigate the neural substrates associated with meaning-threatening experiences. I also propose that future studies use EEG to establish a relationship between acetaminophen and ACC activation. Randles et al. (2016) found that the Pe associated with errors made on a go/no-go task is reduced by acetaminophen. This was the first study using EEG to investigate the role of acetaminophen in attenuating activity in the ACC (Randles, 2016). I propose that future research use EEG to determine if the relationship between consuming acetaminophen and experiencing less sensitivity to affective and cognitive stimuli is mediated by activity in the ACC. In particular, I believe this would allow us to follow up study 3 by determining if activity in the ACC mediates the relationship between consuming acetaminophen and experiencing less regret. 3.2.2 Laboratory evidence The present research sought to answer the question of whether uncertainty leads to increased pain sensitivity. However, the broader question is whether there is shared sensitivity to physical pain and uncertainty. I propose that future studies determine if people who have dispositional sensitivity to pain also have sensitivity to uncertain experiences. Indeed, there is evidence from the social rejection literature people who report more discomfort while experiencing a painful stimulus also report greater distress after experiencing social rejection (e.g., Eisenberger, 2006). I suggest that future studies determine if physical pain sensitivity is 51  correlated with tolerance for uncertainty, using either the need for cognitive closure (NFCC; Webster & Kruglanski, 1994) or personal need for structure scale (PNS; Thompson et al., 2001).  Given our knowledge of the shared sensitivity between physical and psychological sources of pain, theorists have hypothesized that the experience of psychological pain should increase sensitivity to physical pain, and the experience of physical pain should increase sensitivity to psychological pain (e.g., Eisenberger & Lieberman, 2004). Furthermore, experiences that downregulate the sensitivity to psychological pain should also downregulate sensitivity to physical pain, and vice versa (Eisenberger & Lieberman, 2004). I share these predictions, and propose that future studies determine if physical pain leads people to experience greater sensitivity to uncertainty; if experiences that reduce uncertainty also reduce physical pain (e.g., self-affirmation, worldview defense); and if experiences that reduce physical pain lead people to report less distress during uncertain experiences. Lastly, I propose that future researchers determine whether pain makes people more regretful, and whether regret makes people more sensitive to physical pain.  Based on these predictions, a promising opportunity for future research is studies involving chronic pain patients. Chronic pain is defined as pain lasting more than 6 months, without any adaptive purpose (American Psychiatric Association, 2013). Therefore, studying chronic pain patients would allow me to determine how the presence of physical pain, in the absence of any other symptomology (i.e., life-threatening illnesses), affects people’s experience of psychological sources of pain. Research has shown that chronic pain patients have a higher rate of depression (Ciechanowski et al., 2003) anxious attachment style (Ciechanowski et al., 2003) and less extroversion (Phillips & Gatchel, 2000). They are also are more avoidant of potentially fearful social situations (Asmundson, Norton, & Jacobson, 1996). This has led 52  theorists to speculate that chronic pain patients are more sensitive to social pain because of the shared neural circuitry between social and physical pain processing (e.g., Eisenberger et al., 2006). I posit that chronic pain patients are also more sensitive to regret and perceived meaninglessness, and will therefore engage in greater efforts to avoid these distressing experiences.  3.3 Conclusion These studies investigate the relationship between physical and psychological pain, as well as the relationship between acetaminophen consumption and people’s sensitivity to psychologically painful events. I determined that during times of uncertainty, people are more likely to purchase palliative, or pain-killing products. Though I did not find that meaning threats make people more sensitive to physically painful stimuli, I will continue to investigate the relationship between physical pain and uncertainty. I am also searching for new approaches to investigating the relationship between the experience of regret and physical pain. This program of research represents an important first step in the investigation of how experiences like uncertainty and regret affect people’s sensitivity to, or experience of, physical pain. Though there has been much research on the relationship between physical pain sensitivity and social pain, no research has demonstrated a relationship between pain sensitivity and uncertainty or regret. This is surprising, given the wealth of studies supporting shared neural circuitry between pain and cognitive conflict, post-decision dissonance, regret, and uncertainty. I encourage future researchers to pursue the question of how uncertain or regretful events affect people’s experience of physical pain, and likewise, how physical pain affects people’s experiences of regret and uncertainty. 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Journal of Consumer Psychology, 17(1), 3–18. https://doi.org/10.1207/s15327663jcp1701_3 68  Appendices Appendix A   Both Conditions  Control Word Pairs Experimental Word Pairs Hot-lava Quickly-running Quickly-blueberry Snow-man Careful-sewing Careful-sweater Cheese-cake Juicy-blueberry Juicy-sewing Round-table Pink-sweater Pink-running Basket-ball Car-dent Car-throw Belly-dance Fighting-bravely Fighting-dent Tissue-box Clean-dish Clean-bravely Play-list Fast-throw Fast-dish Maple-leaf Belly-dance Belly-slowly Tool-box Ping-pong Ping-dance Young-puppy Jumping-high Jumping-pong Park-bench Crawling-slowly Crawling-high Down-hill Metal-fork Role-fork Fork-lift Magic-wand Magic-softly Bull-frog Weeping-softly Weeping-wand Ping-pong Role-playing Metal-playing Mad-cat Bull-frog Bull-left Air-plane Tool-box Tool-politely Power-chord Turn-left Turn-frog Ham-burger Smiling-politely Smiling-box    69  Appendix B   B.1 Job vignette You have applied for two summer jobs. You receive a call from your potential boss at one of the companies. He says that they want to hire you, but they haven’t decided which position to put you in: a high-ranking, high-paying position or a low-ranking, low-paying position. They will not tell you which position you were assigned to until next week. The only catch is you have to let him know by the end of today if you will accept or decline the offer. / A few minutes later, you get a call from the second company. The second boss says the same thing: They want to hire you, but they haven’t decided which position to put you in: a high-ranking, high-paying position or a low-ranking, low-paying position. They will not tell you which position you were assigned to until next week. / You are faced with a decision: Do you accept the first offer (Job 1) or the second offer (Job 2)? Because you need the money, you do not have the option of going without a job.  B.2 Course vignette Imagine it's time for you to do your course selection for your next year of University. There is a required course that you must take in order for you to graduate. This course has two possible sections - Section 006 or Section 007 - for you to register in. Each section has a different professor. / At this time it is not known which of the two possible professors will be teaching which section. However, you have had each of these professors for other courses in the past. When you had Professor A in the past, you found him engaging, organized and patient with students - and he had also given you a good mark. When you had Professor B in the past, you found him boring, disorganized and impatient with students - and he had given you a poor mark. 70  Since you like Professor A and dislike Professor B, you would like to choose the course that Professor A will be teaching. / It is really important for you to get a good mark as you are trying to raise your GPA. Getting a low mark would be detrimental to your transcript so you want to maximize your chances of success in this course. / You must register for a section even though you don't know which professor will be teaching which section. You do not have the option to switch sections later on. Which section do you choose, Section 006 or Section 007?  71  B.3 Scale to measure regret from course and job vignette  Not at All (1) 2 3 4 5 6 Extremely (7) How happy are you with your decision? m  m  m  m  m  m  m  How much do you regret your decision? m  m  m  m  m  m  m  How satisfied are you with the outcome? m  m  m  m  m  m  m  How disappointed are you with the outcome? m  m  m  m  m  m  m   

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