Can someone help me better understand the article below more…

QuestionAnswered step-by-stepCan someone help me better understand the article below more…Can someone help me better understand the article below more clearly? Here are some of the things I am struggling with-Explain the research methodology that was used in the study.Discuss social factors that influence people or groups to conform to the actions of others.Indicate how behaviors and motivation are impacted by the presence of others. (How does this apply to COVID-19?)Indicate the structures of the brain that are involved in emotion and motivation. (How could a person’s emotions related to fear drive their behaviors during this pandemic?)Examine the article’s generalizability to various areas of psychology.Why would some people choose to follow the orders to avoid social contact and others allow desire for human interaction to be their driving force? clearly identify the article’s premise and present an insightful and thorough analysis with strong arguments and evidence. present informed and substantiated opinion on the article’s content and its relation to social psychology during the COVID-19 pandemic. By: Catherine N. M. OrtnerDepartment of Psychology, Thompson Rivers University;Leah ChadwickDepartment of Psychology, Thompson Rivers UniversityPia PennekampDepartment of Psychology, Thompson Rivers UniversityAcknowledgement: Materials and data for Studies 1 and 2 are available at: https://osf.io/mwruh/.The research was supported by a Social Sciences and Humanities Research Council of Canada Grant to Catherine N. M. Ortner [430-2014-00626]. We thank Alexis M. Wilson for her assistance with data collection and Haytham El Miligi, Steven Lyall, and Eric Petrysyhn for their work on development of the mobile application and Steffi LaZerte and Eva Rubinova for their assistance with data analyses in R.People regulate their emotions in a variety of different ways (Heiy & Cheavens, 2014) and effective emotion regulation is fundamental to long-term psychological well-being and mental health (Aldao & Nolen-Hoeksema, 2012b; Nelis et al., 2011). Therefore, the extent to which people consider the long-term effects of their regulatory choices on well-being may impact how they choose to regulate their emotions. For example, people who report prioritizing future over immediate consequences of their actions in general are more likely to use reappraisal (changing how one thinks about a negative situation to change one’s feelings) than those who place less emphasis on future consequences (Ortner, Chadwick, & Wilson, 2018). Reappraisal, in turn, leads to enduring, long-term reductions in negative feelings to a stimulus (Kross & Ayduk, 2008; Thiruchselvam et al., 2011). On the other hand, when people are instructed to focus on their feelings in the short-term—when asked to pick a strategy that will help them feel less negative in the current moment—they prefer to use distraction (shifting their attention to an unrelated, neutral stimulus; Sheppes et al., 2014). Distraction is effective in the short-term but risks the negative emotion resurfacing in the future (Kross & Ayduk, 2008). Thus, variation in the valuation of (hereafter referred to as motives for) short- and long-term outcomes of emotion regulation—reducing negative feelings in the present versus experiencing feelings of well-being in the long-term—may be important for emotion regulation choice and consequent well-being. However, little is known about how variation in short- and long-term motives within and between individuals predicts their selection of a variety of emotion regulation strategies in response to negative events in everyday life. In the current studies, we examined how such motives predicted emotion regulation strategy use in daily life using both daily diary and ecological momentary assessment methodologies.Short- and Long-Term Motives in Emotion RegulationThe capacity to consider the future is critical to many human behaviors, including planning, decision-making, and a range of activities that depend on effective self-regulation, such as healthy eating and academic performance (Atance & O’Neill, 2001; Benoit et al., 2011; Daniel et al., 2013; Joireman & King, 2016; Kaplan et al., 2016; Schacter et al., 2017). Consideration of future outcomes also predicts well-being—greater life satisfaction, happiness, positive affect, and lower negative affect (Azizli et al., 2015; Stolarski & Matthews, 2016). People try to predict how they will feel in the future (Loewenstein, 2007; Loewenstein & Schkade, 1999) and their simulation of worrisome future events is connected to effective emotion regulation for those events (Jing et al., 2016). Thus, future-oriented cognitions underlie many aspects of human behavior, including emotion regulation.Emotion regulation strategies vary in the extent to which they provide immediate or long-term relief of unpleasant feelings. For example, some strategies, like distraction, avoidance, or rumination, may or may not rapidly reduce unpleasant emotions, and have the potential cost of the negative emotion resurfacing in the future (Kross & Ayduk, 2008; Sheppes & Gross, 2011) or of psychopathology in the long term (Aldao et al., 2010). Other strategies, such as reappraisal, lead to more enduring changes in the emotional response to a stimulus (Kross & Ayduk, 2008; Thiruchselvam et al., 2011). Individuals have some knowledge about the differential short- and long-term consequences of strategies and appear to use this knowledge to guide the selection of specific regulatory strategies (Ortner, Chadwick, & Wilson, 2018). The more people consider the future consequences of their behaviors, the more likely they are to prefer to use strategies with beneficial long-term outcomes (such as reappraisal) and the less likely they are to prefer to use strategies leading to poor outcomes (such as learned helplessness; Ortner, Chadwick, & Wilson, 2018). In addition, when viewing negative emotional images in the laboratory, people show a stronger preference for reappraisal over distraction when given a longer-term motive (i.e., when informed they will view the images again later, without the opportunity to regulate), than when given a short-term motive (i.e., when asked to pick the strategy that will help them feel immediately less negative; Sheppes et al., 2014). Furthermore, how we regulate our emotions has consequences for mental health and well-being. Flexible use of different emotion regulation strategies is beneficial (Aldao et al., 2015; Bonanno & Burton, 2013) and several strategies are predictive of psychopathology (e.g., Aldao et al., 2010.In sum, there is preliminary evidence that interindividual and intraindividual variation in the valuation of short- and long-term outcomes, which we shall refer to as short- and long-term motives, predict strategy preference or selection (cf. Sheppes & Gross, 2011; Tamir, 2016; Tamir et al., 2013) and emotion regulation, in turn, is associated with well-being.However, little is known about how momentary short- and long-term motives influence the choice of strategies other than between reappraisal and distraction, outside of the laboratory environment, and across multiple events in everyday life. Individuals’ short- and long-term motives for regulation may vary from one event to another and these motives may predict strategy selection at the level of the event. Furthermore, the aforementioned studies did not control for hedonic and instrumental motives for emotion regulation.Hedonic and Instrumental Motives in Emotion RegulationAccording to Tamir’s (2016) taxonomy, motives driving emotion regulation can be hedonic (usually to increase pleasant feelings and decrease unpleasant feelings—prohedonic, but sometimes to feel pain—contra-hedonic) or instrumental (to achieve another goal, such as performing well on a cognitive task or optimizing a social relationship). A substantial body of research shows that these varied motives shape people’s attempts to up- and down-regulate or maintain their emotions across a variety of contexts (Tamir, 2016). People will even endure unpleasant feelings (e.g., anger or sadness) in order to achieve another goal (Hackenbracht & Tamir, 2010; Tamir et al., 2008). Situational motives predict not only the direction of regulation but also the specific strategies used to achieve regulation. For example, people are more likely to suppress their expressions of emotion in response to social motives, and reappraise in response to performance motives, in everyday life (English et al., 2017). At the trait level, the tendency to pursue eudaimonic outcomes in life is positively associated with the use of strategies that effectively down-regulate negative emotions (Ortner, Corno, Fung, & Rapinda, 2018). In sum, hedonic and instrumental motives predict both what people want to feel when they regulate their emotions and also the strategies they use to achieve those aims.Hedonic and instrumental motives and short- and long-term motives may represent partially overlapping constructs (cf. Sheppes & Gross, 2011; Tamir, 2016; Tamir et al., 2013). Tamir (2016) suggests that whereas hedonic motives aim to change the immediate emotional state (e.g., experiencing pleasure), instrumental motives may be aimed toward either immediate, nonemotional outcomes (e.g., experiencing anger during a confrontation in order to succeed in that confrontation) or future, nonemotional outcomes (e.g., experiencing unpleasant feelings while studying now in order to perform well on an exam in the future). On the other hand, in the way we conceptualize both short- and long-term motives, the desired outcome is emotional (hedonic—to increase pleasure and reduce pain). The emotional outcome is posited to be either immediate (short-term motives) or delayed to a future time point (long-term motives; cf. Higgins, 2014). Certainly, the nonemotional outcomes of instrumental motives may result in a future change in hedonic state, but the instrumental motives themselves are about nonemotional outcomes. For example, one may choose to remain angry in the short-term to facilitate success in a confrontation (instrumental motive; Tamir & Ford, 2012), in the hopes of experiencing pleasant feelings in the longer-term (long-term motive), upon succeeding in the confrontation. Thus, instrumental motives may work in the service of long-term emotional motives but are not equivalent to them. Therefore, we sought to control for hedonic and instrumental motives in the current studies.The Present StudiesIn the current investigation, we aimed to determine the extent to which momentary short- and long-term motives predict the use of a broad array of emotion regulation strategies across multiple events in daily life. We also assessed hedonic and instrumental regulatory motives in order to test whether short- and long-term motives uniquely predicted emotion regulation over and above any contribution of hedonic and instrumental motives. In two studies, we assessed the use of a large number of emotion regulation strategies (22 strategies in Study 1 and 15 strategies in Study 2). In Study 1, we employed daily diary methodology to assess short- and long-term motives, hedonic and instrumental motives, and the use of emotion regulation strategies in response to a single negative event each day across 7 days. In Study 2, we sought to replicate findings from Study 1 in an independent sample and with ecological momentary assessment to assess responses to negative events closer in time to the events themselves. For 7-10 days, participants were prompted six times a day to report on their experience of a recent negative event, their regulatory motives, and their use of emotion regulation strategies in response to that event.HypothesesWe assessed both interindividual and intraindividual variation in short- and long-term motives as predictors of several specific strategies. We made predictions for specific strategies that have previously been associated with consideration of future consequences in correlational studies or with short- and long-term motives in laboratory settings. Both trait consideration of future consequences and manipulation of long-term motives have been associated with increased use of reappraisal (Ortner, Chadwick, & Wilson, 2018; Sheppes et al., 2014). In the current studies, we assessed three cognitive change strategies—perspective taking, reappraisal, and benefit finding. These entail changing the appraisal of a situation (Gross, 2015) and have been considered antecedent-focused cognitive change strategies in the prior literature (Goldin et al., 2008; McRae et al., 2008; Ochsner et al., 2004, 2012). We predicted a positive association between long-term motives and use of cognitive change strategies both at the interindividual and intraindividual levels. Because short- and long-term motives should be at least partially separable from hedonic and instrumental motives (Tamir, 2016), we predicted that these effects would hold even when controlling for momentary hedonic and instrumental motives.Focusing on short-term regulatory motives has been associated with increased use of distraction, compared to focusing on long-term regulatory motives (Sheppes et al., 2014). Therefore, we expected that momentary and interindividual variation in short-term motives would predict the use of attention reorientation (assessed through two strategies—distraction and positive refocusing).Consideration of future consequences has also been positively associated with the use of situation modification (Ortner, Chadwick, & Wilson, 2018). In that study, examples of “situation modification” included getting help from a friend to prepare for a presentation or choosing a different place to park when someone has taken one’s parking spot. We considered these to be representative examples of what, in the current study, was named problem-solving (operationalized in this and other studies such as Heiy & Cheavens, 2014 as “I made a plan to make the situation better”). We therefore predicted an association between long-term motives and use of problem-solving, both at the interindividual and the intraindividual levels.Previous work has shown that individuals who have more difficulty tolerating distress are more likely to use emotional suppression, rumination, and avoidance (Jeffries et al., 2016). Presumably, when distress tolerance is low, short-term regulation of emotions is prioritized (one wishes to avoid or reduce unpleasant feelings immediately). Also, as noted earlier, these strategies are not beneficial in the long-term (Aldao et al., 2010; Kross & Ayduk, 2008; Sheppes & Gross, 2011). Therefore, one possibility is that at the interindividual level, those who experience greater short-term motives on average would be more likely to use these strategies. It is also possible that, within individuals, when people experience stronger short-term motives, they are more likely to apply such strategies. Again, we expected to find these associations over and above any role of hedonic and instrumental motives. Finally, based on prior research showing that people who consider the future outcomes of their actions are less likely to engage in learned helplessness (Ortner, Chadwick, & Wilson, 2018), we expected to find a negative association between long-term motives and learned helplessness at the interindividual level.For the remaining strategies assessed, our analyses were exploratory in nature. Method Materials and data for Studies 1 and 2 are available at: https://osf.io/mwruh/.ParticipantsStudy 1One-hundred and twenty participants were recruited via Prolific Academic (https://prolific.ac), an online participant recruitment platform. Prior to starting data collection, we determined a target sample size based on those typical of daily diary studies of emotion regulation (Cameron & Overall, 2018; Kalokerinos et al., 2017; Troy et al., 2019). We hoped to have data for 100 participants and oversampled to allow for attrition. Participation requirements included a minimum age of 18 years, English as first language, and a 95% or higher approval rate on Prolific. The Thompson Rivers University Research Ethics Review Board provided ethical approval for the study.Only participants who completed the initial survey and passed the Conscientious Responders Scale in the initial survey were invited to complete the daily diaries (see Materials and Procedure). Of 122 participants who completed the initial survey, 107 participants were invited to complete the daily diaries.At the end of the study, participants were remunerated £1.25 sterling for completing the initial questionnaire and £0.50 sterling for each completed daily diary.Participants ranged in age from 19 to 85 (M = 38.05, SD = 12.33) and identified as predominantly female (68.2% female, 31.8% male). Participants were White (87.9%), East Asian (5%), Latino/Hispanic (1%), mixed ethnicity (4%), South Asian (1%), or other (2%).Study 2Participants were recruited from Thompson Rivers University, a small, urban university, and the surrounding community. Prior to starting data collection, we aimed for a total of 100 participants, oversampling to allow for attrition. The target sample size was based on those typical of mobile application studies of emotion regulation (Brans et al., 2013; Grosse Rueschkamp et al., 2020; Heiy & Cheavens, 2014; see Results for further discussion of sample size).Of the 142 participants that attended the initial sign-up session, 98 completed the study. Participants ranged in age from 17 to 56 (M = 26.12, SD = 8.59) and identified primarily as female (70% female, 28% male), and as White (86.7%), Asian (5.1%), First Nations (2%), Middle Eastern (2%), Black (1%), Indian (1%), Hispanic (1%), or other (1%). Participants who completed the study were compensated $30 CAD.Materials and ProcedureStudy 1All measures were completed online via FluidSurveys. Participants gave informed consent and completed an initial questionnaire before the 7 days of daily diaries. Individuals were recruited via Prolific to complete each daily diary before they went to bed each night.Data were collected as part of a larger study on predictors of emotion regulation in everyday life (an article on emotion control beliefs and event importance and intensity as predictors of emotion regulation has been published). Below, we describe only a subset of the measures from the daily diaries that were relevant to the current research questions.Initial SurveyThe Conscientious Responders Scale (CRS; Marjanovic et al., 2014) included five instructional items dispersed among all other items in the initial survey (e.g., “To answer this question correctly select option number one”). Following Marjanovic et al. (2014), participants responding incorrectly to three or more of these items were considered nonconscientious and were not invited to complete the daily diaries.Daily DiariesFor each daily diary, participants were asked to “Think of the most notable negative emotional event that has happened to you today. An event could be a situation that actually happened, or it could be something that was on your mind, like thinking about a past event or a future event.” Participants first noted the type of event they had experienced (whether it involved family, friends or partner, employment, thinking about a future event, thinking about a past event, or other) and the primary emotion experienced (anger/annoyance, anxiety, sadness, regret, loneliness, fear, embarrassment/shame, guilt, and disgust).Emotion Regulation Strategy UseParticipants rated the extent to which they had engaged in each of 22 emotion regulation strategies for regulating emotions in response to the negative event on a 6-point scale (0 = not at all, 5 = very much). Items were primarily adapted from Heiy and Cheavens (2014): “I accepted the situation and/or my emotions” (acceptance); “I reminded myself that things could be worse” (perspective-taking); “I thought about how I could become stronger or learn from this situation” (benefit-finding); “I thought about the situation in a different way” (reappraisal); “I found an activity or thought of something else to keep myself busy and distracted” (distraction); “I thought of something pleasant instead of what happened” (positive refocusing); “I tried not to show my emotions” (expression suppression); “I made a plan to make the situation better” (problem-solving); “I talked about my feelings with someone else” (social sharing); “I went to sleep” (sleep); “I exercised” (exercise); “I thought over and over again about the situation or my feelings” (rumination); “I thought about all the different things in my life that this situation would impact” (consequences); “I thought about how this situation was my fault” (self-blame); “I thought about all the other things that have happened to me in addition to this situation” (generalizing); “I thought about how the situation was someone else’s fault” (other-blame); “I ignored my feelings” (emotional suppression); “I smoked a cigarette, drank alcohol, and/or got high” (substance use); “I acted like the situation had never happened at all” (denial); “I hurt (pinched, cut, burned, and/or hit) myself” (nonsuicidal self-injury); “I avoided focusing on my thoughts or feelings about the situation” (avoidance); and “I can never do anything about my problems so I felt unable to deal with the situation” (learned helplessness).Short- and Long-Term MotivesParticipants rated their agreement with two items assessing regulatory short- and long-term motives in relation to the negative event on a 6-point scale from 0 = not at all to 5 = very much (“When choosing how to react, I was motivated by how I wanted to feel in the short-term”; “When choosing how to react, I was motivated by how I wanted to feel in the long-term.” See online supplemental materials for detailed instructions for these items).Emotion Regulation Instrumental and Hedonic Motives (Adapted From Tamir et al., 2008)Participants rated their agreement to two items assessing instrumental and hedonic emotion regulation motives in relation to the negative event on a 6-point scale from 0 (not at all) to 5 (very much; Instrumental: “In dealing with my emotions about this event, I wanted to control my feelings so that I could achieve some other goal (e.g., avoid conflict, keep up appearances, get work done, make others feel better, etc.)”; Hedonic: “In dealing with my emotions about this event, I wanted to control my feelings so that I could change my mood”).Study 2Participants completed up to six assessments per day over 7-10 days either on a mobile application designed for Android devices (app) or through SurveySignal (a text-messaging based data collection platform). We switched to SurveySignal part way through the study because several participants who had signed up to use the app (approximately 24%) experienced technical difficulties with the app (e.g., not receiving notifications for assessments). We required participants to complete at least 14 assessments to remain in the study because we wished to ensure that we would obtain more datapoints than in Study 1 (which included one negative event per day) and to motivate participants to take the time to complete assessments. If they had not completed 14 assessments within the first 7 days, further days were added up to a maximum of 10 days, to allow for the completion of 14 assessments in total. For both the app and SurveySignal, notifications to complete an assessment were sent quasi-randomly within six two-hour segments within a 12-hr time period (9 a.m. to 9 p.m.) each day, such that participants would receive six notifications per day with the constraint that no two notifications would occur closer than 45 minutes apart. If participants did not respond immediately, they received a reminder after 10 minutes. After 30 minutes that assessment timed out and participants could no longer respond. In the app, clicking on the notification took participants to the assessment items. In the app, participants also had the option to complete self-initiated assessments, whereby they could open the app to fill out an assessment at any time. Unfortunately, technical errors in the app design meant that we were unable to reliably distinguish between app-initiated and self-initiated assessments (participants reported that some app-initiated assessments were being labeled as self-initiated assessments). In SurveySignal, clicking on the text message notification took participants to the assessment items in SurveyMonkey.Data were collected as part of a larger study on predictors of emotion regulation in everyday life (other data from the study have not yet been analyzed). Below, we describe only a subset of the measures from the assessments that were relevant to the current research questions.For the assessment items, participants were first asked “Have you experienced any negative or unpleasant events since the last assessment? An event could be a situation that actually happened or it could be something that was on your mind, like thinking about a past event or a future event. If yes, select yes and continue. If no, ignore this assessment.”Participants then completed most of the same emotion regulation items as in Study 1. Because participants would be completing up to six assessments each day, we streamlined completion of the assessment by eliminating sleep, exercise, self-blame, other-blame, nonsuicidal self-injury, and emotional suppression. Participants also responded to the same instrumental and hedonic motives and short- and long-term regulation motives items as in Study 1.Data AnalysesFor each strategy, we conducted mixed models analyses with the lme4 package (Version 1.1-23, Bates et al., 2015) in R Version 4.0 (R Core Team, 2020), with response (Level 1) nested within participants (Level 2). The data structure in Study 2 was, strictly speaking, a three-level model (with events—Level 1—nested within days—Level 2, nested within persons—Level 3). However, because of the small number of clusters (7-10 days) we treated this as a two-level model (Kerkhoff & Nussbeck, 2019; Snijders & Bosker, 1993).We were interested in examining the association between our predictors (short- and long-term motives) and emotion regulation at both Level 1 (does state-like variation in motives within the individual—within clusters—predict emotion regulation) and Level 2 (does trait-like variation in motives between individuals predict emotion regulation). When both cluster means (i.e., participants’ mean motives across response days/responses) and grand-mean centered values (i.e., participants’ motives on each measurement occasion, centered around the grand mean) are entered as predictors, the fixed effects estimates can be interpreted as follows: the fixed effect estimates for the cluster means represents the association between motives and emotion regulation at Level 2 (interindividual) and the fixed effect estimate for the grand-mean centered values represents the association between motives and emotion regulation at Level 1 (momentary, intraindividual; see Enders & Tofighi, 2007 for details on this approach). Therefore, we entered into the models cluster means (i.e., individuals’ mean short- and long-term motives across all days) and grand-mean centered short- and long-term motives to test the differential effects of interindividual (Level 2) and intraindividual (Level 1) variation in short- and long-term motives, respectively. To control for interindividual (Level 2) and intraindividual (Level 1) hedonic and instrumental motives, we entered person means and grand-mean centered values of hedonic and instrumental motives as predictors in the model. We did not expect an effect of response day (Study 1) or response (Study 2) but included response day/response as a fixed effect to account for the possibility that participant responses could change across time, due to participant reactivity.Using maximum likelihood estimation, we tested models using an autoregressive structure for the residuals, to allow responses occurring closer together in time to be more highly correlated than those further apart. In Study 1, the autoregressive structure improved model fit in only seven of the 18 models tested, as determined by a chi square difference test. In Study 2, the autoregressive structure improved model fit in only four of the 14 models tested. Therefore, for parsimony and consistency across models, we retained the default identity covariance matrix for the residuals. The pattern of results was the same in both cases.We conducted tests of model fit with and without random slopes for each model. In Study 1, the addition of random slopes improved model fit for only five out of 18 models (with nonconvergence in two models that included random slopes). In Study 2, the addition of random slopes improved fit for nine out of 14 models (with nonconvergence in one model that included random slopes). In all cases, the addition of random slopes did not change the results for the fixed effects. Therefore, given the goal of parsimony and consistency, we did not include random slopes in the final models. We ran all final models with restricted maximum likelihood estimation.In Study 1, residuals for sleep, exercise, substance use, and nonsuicidal self-injury were not normally distributed. Also, endorsement of these strategies was low, with a median score of zero for each. Therefore, we did not analyze those strategies further. For all other strategies, when checking for multicollinearity, correlations between short-term, long-term, hedonic, and instrumental motives ranged from r = .39 to r = .66 at the interindividual level and from r = −.04 to r = .27 at the event level (correlations among predictors are shown in the online supplemental materials); we found variance inflation factor (VIF) values well below 10 (all VIF’s ≤ 3.064) and tolerance statistics above .2 (all values ≥ .326), suggesting that multicollinearity was not a concern (Bowerman & O’Connell, 1990).In Study 2, residuals for substance use were not normally distributed. Also, endorsement of this strategy was low, with a median score of one. Therefore, we did not analyze substance use further. For all other strategies, when checking for multicollinearity, correlations between short-term, long-term, hedonic, and instrumental motives ranged from r = .47 to r = .66 at the interindividual level and from r = −.03 to r = .24 at the event level, suggesting some independence of constructs (correlations among predictors are shown in the online supplemental materials); we found VIF values well below 10 (all VIF’s ≤ 3.126) and tolerance statistics well above .2 (all values ≥ .320), suggesting that multicollinearity was not a concern (Bowerman & O’Connell, 1990).We applied the Bonferroni correction to reduce the family-wise error rate, adjusting for the number of confirmatory and exploratory analyses for each study (Study 1, confirmatory analyses: α = .05/10 = .005; Study 1, exploratory analyses: α = .05/8 = .00625; Study 2, confirmatory analyses: α = .05/9 = .0056; Study 2, exploratory analyses: α = .05/5 = .01).As yet, there is little consensus on local effect size measures for mixed models analyses (Nezlek, 2008). We computed standardized coefficients (β) to produce local effect size estimates that would be comparable across effects and studies. The standardized coefficients were determined by using the effectsize package in r, which standardizes Level 1 parameters according to variance within groups and Level 2 parameters according to variance between groups (Ben-Shachar et al., 2020).ResultsDescriptive StatisticsStudy 1Participants completed a total of 630 daily diaries (M = 5.89 per person; SD = 1.46). We ran empty, unconditional models for each outcome variable to estimate the variation between persons (interindividual variation) and between response days (intraindividual variation). The intraclass correlation (ICC) represents the proportion of the variance in the outcome variable that is accounted for by interindividual variability (as a proportion of the total variability, which is accounted for by both interindividual and intraindividual variability). ICCs for the outcome variables varied from .18 to .47 (see Table 1; note some ICCs were already reported elsewhere; Ortner & Pennekamp, 2020) indicating that both intraindividual and interindividual variation accounted for variations in emotion regulation strategy use, and supporting the use of multilevel models for the data analyses. Correlations among predictors are in the online supplementary materials (Tables S1 and S2).Descriptive Statistics for Emotion Regulation Strategies (Study 1)Study 2Ninety-eight participants completed a total of 1,705 assessments (M = 17.40 responses per participant). After completing data analyses, we conducted a power analysis using simr (Version 1.5, Green & Macleod, 2016), using the parameter estimates for benefit-finding from Study 1. With 100 participants (the target sample size) and 14 assessments per participant (the minimum required number of assessments requested of participants), we would have had approximately 95% and 83% power to detect effect of β = .16 and β = .35 for our primary effects of interest, momentary variation, and interindividual variation in long-term motives.Thirty participants completed at least 14 assessments on the mobile application and 68 participants completed at least 14 assessments on SurveySignal, as required to remain in the study. Due to a technical error that continued to invite participants to complete assessments on the mobile application after 7 days, even when they had already completed a sufficient number of assessments, some of those participants continued to complete extra assessments. Therefore, to ensure consistency in sampling across the two methods (SurveySignal and mobile application), we filtered out assessments completed from Days 8 through 10 if the participant had already completed 14 assessments in the first 7 days.ICCs for the outcome variables varied from .22 to .47 (see Table 2), indicating that both intraindividual and interindividual variation accounted for variations in emotion regulation strategy use, and supporting the use of multilevel models for the data analyses. Correlations among predictors are in the online supplementary materials (Tables S3 and S4).Descriptive Statistics for Emotion Regulation Strategies (Study 2)Confirmatory AnalysesResults from confirmatory analyses are presented in Table 3 (Study 1) and Table 4 (Study 2). We describe hypotheses as supported when the results were consistent across both studies (see Table 5 for a summary).Confirmatory Analyses (Study 1): Estimates of Fixed Effects for Short- and Long-Term Motives as Predictors of Emotion RegulationConfirmatory Analyses (Study 2): Estimates of Fixed Effects for Short- and Long-Term Motives as Predictors of Emotion RegulationConfirmatory Analyses: Hypotheses Supported Across Both Studies Are Marked “Y” and Show the Direction of the AssociationHypothesis 1As predicted, momentary variation in long-term motives predicted the use of benefit-finding and reappraisal. As momentary long-term motives increased within individuals, they engaged in more use of these strategies, when controlling for momentary and intraindividual variation in hedonic and instrumental motives. However, this association did not hold for the third cognitive change strategy, perspective taking. Furthermore, the association was not significant at the interindividual level, although for benefit-finding the effect size (Study 1, β = .35; Study 2, β = .28) was larger than or comparable to the effect size for momentary long-term motives (Study 1, β = .16; Study 2, β = .27).Hypothesis 2Contrary to our prediction, short-term motives were not significantly associated with measures of attention reorientation (distraction and positive refocusing).Hypothesis 3As predicted, problem-solving was positively associated with momentary variation in long-term motives, but, contrary to our hypothesis, not with interindividual variation in long-term motives.Hypothesis 4Momentary variation in long-term motives was negatively associated with emotional suppression, but this was only measured in Study 1. There was no association between either momentary or interindividual variation in short-term motives and rumination, avoidance, and learned helplessness. Contrary to our prediction, we found a significant positive association between momentary long-term motives and rumination.Exploratory AnalysesResults from exploratory analyses are presented in Table 6 (Study 1) and Table 7 (Study 2). We describe significant results only if they were consistent across studies.Exploratory Analyses (Study 1): Estimates of Fixed Effects for Short- and Long-Term Motives as Predictors of Emotion RegulationExploratory Analyses (Study 2): Estimates of Fixed Effects for Short- and Long-Term Motives as Predictors of Emotion RegulationAmong the remaining strategies, there were few significant associations with short- and long-term motives. The only consistent finding was that social sharing and consequences were positively associated with momentary long-term motives.Hedonic and Instrumental MotivesAlthough hedonic and instrumental motives were not the primary focus of the current studies, we briefly summarize their associations with emotion regulation when they were consistent across both studies (see Table 8).Results for Hedonic and Instrumental Motives Showing Only Those Findings That Were Consistent Across Both Studies and the Direction of the AssociationSeveral strategies were positively associated with momentary changes in hedonic motives: distraction, positive refocusing, and avoidance. Perspective-taking and positive refocusing were also positively associated with interindividual variation in hedonic motives. Finally, both distraction and expressive suppression were positively associated with momentary variation in instrumental motives.Discussion We expected to find that interindividual and intraindividual variation in short- and long-term motives for emotion regulation would predict the use of several emotion regulation strategies in response to negative events, over and above the roles of hedonic and instrumental motives. We focus primarily on discussing the results where we found commonalities between the daily diary and mobile application studies.The pattern of results was partially consistent with our predictions. As expected, intraindividual variation in long-term motives was positively associated with the use of several strategies that support long-term change, like benefit-finding, reappraisal, and problem-solving. This finding is consistent with prior work showing that manipulating long-term motives increases the use of reappraisal (Sheppes et al., 2014) and that people believe reappraisal and problem-solving to be more effective for reducing negative feelings in the long- than the short-term (Ortner, Chadwick, & Wilson, 2018). Interindividual variation in long-term motives did not significantly predict cognitive change strategies and problem-solving. Study 1 results suggested we had adequate power in Study 2 to detect those associations and the sizes of the effects were comparable with or larger than the effect sizes than for momentary variation. However, power to detect the interindividual relationships was lower than power to detect the intraindividual relationships (see Results section). Furthermore, we used a stringent alpha to correct for the number of strategies tested, with consequent loss of power. The pattern of results suggests that more focused (e.g., studying only cognitive change strategies) and higher-powered studies are needed to ascertain the relative roles that intra- and interindividual variation in long-term motives play in predicting the use of cognitive change strategies. In addition, it may be that intraindividual variation in motives is a more important predictor of emotion regulation choices or that other individual differences (e.g., personality characteristics) play a more important role in predicting interindividual variation in emotion regulation choices.Contrary to our prediction, momentary short-term motives did not predict attention reorientation (distraction and positive refocusing) over and above momentary variation in hedonic motives, which predicted attention reorientation across both studies. Therefore, the finding of increased preference for distraction when focusing on short-term regulatory motives in previous work (Sheppes et al., 2014) may be attributable to hedonic motives rather than short-term motives per se. In addition, we found that people who experienced stronger hedonic motives overall used positive refocusing more. A novel finding across both studies was that use of distraction also increased with increasing momentary instrumental motives. Thus, distraction may serve two motives—reducing unpleasant feelings as well as subsequently achieving an instrumental goal. For example, after a bad argument with a friend, an individual may distract themselves by watching a TV show to feel better and so that they can then focus on studying for an exam. Presumably, the hedonic and instrumental motives could be experienced simultaneously, even if the outcomes are achieved sequentially.Our predictions for the other specific strategies received limited support. We expected that long-term motives would be negatively associated with strategies such as emotional suppression, avoidance, rumination, and learned helplessness. As expected, emotional suppression was negatively associated with momentary long-term motives (though we only assessed emotional suppression in Study 1). Avoidance was negatively associated with momentary long-term motives, but only in Study 2—this association may be too small to detect reliably. Contrary to our predictions, across both studies, as individuals experienced stronger long-term motives across events, they were more likely to ruminate. We had expected that people would ruminate less when they experienced long-term motives, but this expectation rests on the assumption that people know that rumination has long-term negative consequences for well-being and are deliberate in their use of emotion regulation strategies to achieve immediate and/or future positive outcomes. The finding that rumination was positively associated with momentary long-term motives may be understandable in light of other research showing that when cued to think about an unresolved goal, people were more likely to ruminate (Roberts et al., 2013) and that people expect rumination to facilitate solving a problem (Matsumoto & Mochizuki, 2018). Thus, although rumination amplifies negative feelings in the short- and long-term (Kross & Ayduk, 2008), individuals might engage in it in an attempt to solve problems that will impact them in the long run.The results suggest that long-term motives are positively associated with the use of strategies that are effective in the longer-term (such as reappraisal; Kross & Ayduk, 2008) but not consistently negatively associated with strategies that are detrimental in the longer-term (such as rumination and emotional suppression; Aldao & Nolen-Hoeksema, 2010). Rather, within individuals, events associated with stronger long-term motives may be associated with more rumination, perhaps because people believe it to be beneficial.For the exploratory analyses, we found few consistent associations between long-term motives and emotion regulation strategy use. Social sharing and consequences (i.e., thinking about other things in one’s life that would be impacted by the negative event) were associated with momentary long-term motives. In other words, as long-term motives increased across events, individuals tended to engage in more social sharing and thought more about consequences of the event. Social sharing may facilitate engaging in other beneficial strategies, such as reappraisal (Larsen & Prizmic, 2004), and has been associated with achieving adaptive outcomes (e.g., resolving a problem or improving relations with others; Páez et al., 2013). As such, social sharing may fulfill long-term regulatory motives. For consequences, it is not surprising that people would consider other events in their lives that would be impacted when thinking about how to manage future feelings. None of the other strategies examined in an exploratory fashion were associated with short- or long-term regulatory motives. However, consistent with past research (English et al., 2017), momentary instrumental motives predicted expression suppression.In the current studies, we controlled for hedonic and instrumental motives because these are thought to overlap at least partially with short- and long-term motives, respectively (cf. Sheppes & Gross, 2011; Tamir, 2016; Tamir et al., 2013). In the extant literature, hedonic motives are typically framed in the short-term, whereby the individual aims to change or maintain their immediate hedonic state. Instrumental motives involve the desire to change emotions in order to achieve nonemotional outcomes, such as social or task performance. In such cases, the desired (nonemotional) outcome may occur at the same time as the emotional state is achieved, or after: the instrumental and emotional outcomes may be separable in time (Tamir, 2016). Thus, while the desired instrumental outcome may precipitate changes in the emotional state (e.g., maintaining anger to facilitate success in a confrontation (instrumental motive) may result in pleasant feelings upon success), it is not the same as it.Our proposed conceptualization of short- and long-term motives also builds on research showing that different regulatory strategies have differential consequences for emotions in the short- and long-term. For example, distraction results in immediate relief of unpleasant feelings, but reappraisal results in more enduring changes in unpleasant feelings (Denson et al., 2012; Kross & Ayduk, 2008; Ray et al., 2008). Presumably, these consequences hold regardless of any intervening instrumental motives. Indeed, we posit that long-term motives for emotion regulation can arise in the absence of particular instrumental motives: if I know that reappraising a negative event (e.g., being cut-off while driving) will help me feel better in the long-run, this may be a sufficient reason for me to choose to use this strategy. We also suggest that long-term motives are distinct from eudaimonic motives (a type of instrumental motive in Tamir’s (2016) framework), which focus on motives to achieve autonomy, mastery, and a sense of meaning in life.Our results support making a distinction between short- and long-term motives on the one hand and hedonic and instrumental motives on the other hand. First, we found that short- and long-term motives predicted emotion regulation even when controlling for hedonic and instrumental motives, suggesting that these constructs do make at least partially independent contributions to emotion regulation. Second, although we observed moderate to strong correlations between long-term and instrumental motives and between short-term and hedonic motives at the interindividual level (ranging from r = .49 to r = .57, see online supplemental materials, Table S2 and S4), correlations at the event-level were weak (ranging from r = .12 to r = .18, Tables S1 and S3). Notably, at the interindividual level, the correlations between short-term and instrumental motives and between long-term and hedonic motives were as strong as those between short-term and hedonic motives and between long-term and instrumental motives (Tables S2 and S4). In other words, the correlations among the predictors were driven primarily by associations at the interindividual level—some people were simply more motivated to regulate their emotions than others, overall. However, these motives were decoupled when looking at the association within individuals: For an individual who tended to endorse long-term and instrumental motives more strongly on average, these variables would not be highly correlated across occasions within the individual—again, suggesting that these constructs are at least partially separable.The associations at the interindividual level suggests some redundancy among predictors and might, in part, account for why we found limited associations between long-term motives and emotion regulation between persons, except when hedonic and instrumental motives were removed from the analyses (see online supplemental materials, Tables S5 and S6). For example, we obtained the expected associations between short-term and long-term motives and attention reorientation strategies (distraction and positive refocusing) only when hedonic motives were removed as a predictor. Similarly, associations between interindividual variation in long-term motives and benefit-finding, reappraisal, and perspective-taking were only significant when hedonic and instrumental motives were excluded from the models. Nonetheless, the results suggest that short-term and hedonic motives, and long-term and instrumental motives, make somewhat distinct contributions to emotion regulation, although further research is needed to delineate the roles of intra- versus interindividual variation in these constructs.Overall, our results highlight the need to consider contextual variation in long-term motives as predictors of emotion regulation within individuals. The pattern of results, whereby intraindividual variation in motives predicted cognitive change strategies, problem-solving, and social sharing, suggests that individuals are flexible in modulating their use of different strategies—strategies that are in turn associated with more positive mental health outcomes (Aldao & Nolen-Hoeksema, 2010, 2012a; Kross & Ayduk, 2008; Páez et al., 2013). Prior research has also shown that cross-situational variability in the use of certain strategies, like problem-solving, is associated with lower levels of psychopathology (Aldao & Nolen-Hoeksema, 2012a). Our results add to this line of research by highlighting long-term motives as a potentially relevant predictor of such cross-situational variability, though further research is required to establish a connection with mental health. We have noted some possible explanations for the lack of associations found at the interindividual level, including low power to detect those relationships, and so we suggest that further research is required to ascertain the strength of the relationship between motives and emotion regulation between individuals.Limitations and Future DirectionsOur studies provide a novel examination of the role of short- and long-term emotion regulation motives in emotion regulation strategy use in daily life. However, it is important to note several limitations. First, our daily diary and mobile application methods involve repeated sampling of behavior through self-report measures. The self-report nature of our measures assumes that participants are willing and able to accurately report their current levels of affect, as well as their choice and use of emotion regulation strategies. It is possible that even if participants respond honestly, they may lack the introspective ability or emotional awareness to provide accurate responses. In addition, repeated exposure to the same measures may have fatigued the participants and caused them to answer out of habit. However, as indicated by the intraclass correlations, we found considerable variability in strategy use within individuals, suggesting that participants were not simply responding habitually to the emotion regulation items. Second, we only examined emotion regulation in the context of the down-regulation of negative events. Further studies should examine the role of short- and long-term motives for regulating positive emotions and when maintaining or even upregulating negative emotions.Third, we cannot assume a causal relation between motives and emotion regulation strategy use from these studies. Future studies should assess how manipulation of short- and long-term motives predicts the use of varied emotion regulation strategies in ecologically valid contexts. Fourth, in Study 2, participants were instructed to respond to an assessment only if they had experienced a negative event and we retained participants only if they had completed at least 14 assessments. As such, we could not ascertain whether participants who did not complete the required number of assessments simply did not experience as many negative events or if they were less compliant with instructions as other participants. Our final sample may reflect only individuals who experience more frequent negative events and/or readily followed the instructions, which may limit generalizability. Finally, in both studies, our samples were predominantly White and English-speaking, so generalizability to different populations is not known.Despite these limitations, the present study advances our understanding of how short- and long-term motives for emotion regulation predict emotion regulation in daily life.ConclusionWe have added to the current literature on the role of motives in emotion regulation by showing that momentary variation in long-term motives plays a role in predicting the use of certain strategies (benefit-finding, reappraisal, problem-solving, rumination, social sharing, and thinking about consequences), over and above the role of hedonic and instrumental motives. These findings suggest that long-term motives are at least partially separable from hedonic and instrumental motives and that when examining contextual variables that predict strategy use, it is crucial to consider not just interindividual differences, but also intraindividual variation in those contextual variables. Future research should build on these findings to examine how different event characteristics might predict momentary variation in long-term motives and to develop tools to ameliorate emotion regulation in the service of enhancing mental health and well-being.Footnotes1 Other measures included in the full study are as follows. The initial questionnaire also included measures of Consideration of Future Consequences (CFC-14), typical use of emotion regulation strategies (the same strategies as were assessed in the daily diaries), well-being, eudaimonic, and hedonic motives for activities, and depression, anxiety, and stress. The daily diaries also included items assessing current mood, short- and long-term event implications, and intensity, valence, and importance of the event.2 Other measures included in the full study are as follows: an initial questionnaire included measures of Consideration of Future Consequences (CFC-14), typical use of emotion regulation strategies (the same strategies as were assessed in the daily diaries), well-being, eudaimonic, and hedonic motives for activities, and depression, anxiety, and stress. A final questionnaire included measures of well-being, depression, anxiety, and stress. The assessment items also included items assessing current mood, short- and long-term event implications, and intensity, valence, and importance of the event.ReferencesAldao, A., Nolen-Hoeksema, S., & Schweizer, S. 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Sep 13, 2021Accession Number: 2021-85095-001Digital Object Identifier: 10.1037/emo0000989                        Social SciencePsychologyPSYCHOLOGY PSY 1010Share Question