Think, look, change! :what’s your emotion regulation strategy?

Research Master’s Psychology

Internship Report

Think, look, change!

What’s your emotion regulation strategy?

Author: Ludovica Atticciati

Supervisor: Dr. Bram van Bockstaele

Collaborators: Anu Hiekkaranta

Word count: 5105

Date: July 8

, 2017

Abstract

This work aimed to present a paradigm to study situation modification as an emotion regulation (ER) strategy. A computer-based task was developed, where emotions were induced showing negative pictures, and then regulated by the participant, choosing situation modification, distraction, or reappraisal as the strategy to down-regulate their negative affect. Situation modification was selected to regulate mostly mild, rather than intense, negative emotions. When compared with distraction, the popularity of reappraisal decreased for intense negative emotions, thus replicating the effect found by Sheppes, Scheibe, Suri, and Gross (2011). Overall, all strategies proved effective in down-regulating affect. Personality traits were used as predictors of ER choice, replicating the negative relationship between neuroticism and reappraisal choice found by Gross and John (2003). Inhibitory control did not predict ER effectiveness. In conclusion, we proposed a new paradigm to study ER and showed that while all three strategies can be successfully used to decrease affect, the intensity of the emotional stimuli influences people’s ER strategy choice.

Think, look, change! What’s your emotion regulation strategy?

When we watch a sad movie and tell ourselves “it’s just fiction”, when we hide our disappointment when he or she does not call, when we hang out with friends to not think about it: in all these occasions, we are regulating our emotions. Emotion regulation (ER) refers to the processes that people use to control the rise, experience, or expression of

emotions (Gross, 1998). Impaired emotional processing has been consistently associated with psychopathology (e.g., Cloitre, Miranda, Stovall-McClough, & Han, 2005; Etkin & Wager, 2007; Alink, Cicchetti, Kim, & Rogosch, 2009; Glenn & Klonsky, 2009; Horan, Hajcak, Wynn, & Green, 2013). Understanding how to improve emotion regulation is therefore a priority in the development of treatments for mental disorders.

One of the most widely used theoretical frameworks to study ER is the process model of emotion regulation by Gross (1998; see also Gross, 2002). According to this model, emotion generation depends on the exposure to emotional cues, the elaboration of their inputs, the development of certain cognitions, and the observable expression of the emotion. As such, people can regulate their emotions by selecting which contexts to expose themselves to (situation selection), by actively changing some elements of the context (situation

modification), by attending to specific stimuli within the context (attention deployment), by reappraising either the stimulus itself or the emotional response to such stimulus (change of cognitions), or by directly influencing the expression of the emotional response (response modulation).

Webb and colleagues (2012) tested Gross’ process model of ER in a quantitative meta-analysis and compared the effectiveness of different ER strategies. Overall, evidence for effectiveness of the strategies was found. Cognitive change had small-to-medium effect sizes, while small effect sizes were found for response modulation; attention deployment showed no effect. However, for attention deployment, within-strategy comparisons clarified

that distraction is effective, despite a small effect size. The meta-analysis focused on cognitive change, attention deployment, and suppression, which are only three out of five families of ER strategies in the process model. Webb and colleagues argued explicitly that “experiments have rarely been used to test how people regulate their own emotions using situation selection or modification” (p. 776). Hence, there is a clear lack of knowledge on how situation selection and situation modification impact emotional responses.

Two more recent studies did investigate situation modification to regulate emotions. Vujovic, Opitz, Birk and Urry (2014) looked at what motivates people to avoid emotional stimuli. They presented negative and neutral pictures to their participants. If participants opted to press a key, the picture was replaced by a black screen. Vujovic and colleagues argued that the amount of key presses to make a picture disappear could be interpreted as a measure of emotion regulation through situation modification, and they found that people tended to use this strategy in 60% of trials with high-arousal negative pictures and low-arousal neutral pictures.

In another study, Livingstone and Isaacowitz (2015) compared the use of situation selection and situation modification in younger and older adults. In the situation selection condition, participants chose which of 3 computers screen they wanted to watch: One screen showed positive materials, the second screen showed negative materials, and the third screen showed neutral materials. In the situation modification condition, participants were randomly presented with positive, negative, and neutral material, and could skip the stimuli they did not wish to view by pressing a key. They found that older adults were more likely to avoid

negative stimuli, using both situation selection and modification, as compared to younger adults.

However, in both these experiments, the situation modification procedure implied the complete avoidance of the emotional stimulus rather than regulation of the intensity and/or

exposure duration. As such, it is unclear whether these paradigms are examples of situation modification or examples of situation selection. In Livingstone and Isaacowitz (2015), both conditions allowed participants to avoid the unwanted stimuli: in situation selection,

participants attended to the 3 types of stimuli in order to select a monitor; in situation modification, participants briefly attended to the 3 types of stimuli before (potentially) skipping them. Thus, their paradigm appears to study avoidance, and not situation

modification. Likewise, Vujovic and colleagues (2014) had the emotional stimuli completely disappear after the key presses. Moreover, neither one of the studies compared the use of situation modification to other strategies, or investigated situation modification’s differential effectiveness across contexts. For instance, Vujovic and colleagues only noted that people tend to avoid negative stimuli more than neutral stimuli. As such, a number of questions remained unanswered with regard to when situation modification is the preferred strategy, when it is more likely to be successful, how does successfulness affect choice, what factors moderate choice and effectiveness, and so on.

While reappraisal (i.e. change of cognitions) is generally considered a functional ER strategy (Gross & John, 2003), recent evidence shows that flexibility in strategy use is key (e.g., Haines et al., 2016). As such, choosing the most appropriate ER strategy for any given context is fundamental to achieving optimal regulation. Sheppes, Scheibe, Suri, and Gross (2011) pioneered the study of ER strategy choice. On each trial, they asked participants to pick either distraction or reappraisal to regulate either mildly or highly intense negative emotions. Sheppes and colleagues found that people preferred reappraisal for mildly negative pictures and distraction for highly negative pictures. They did not collect information about the effectiveness of these strategies, so it remains unknown which strategy is more effective in a given context.

In sum, the main goal of our experiment was to develop a more valid paradigm to assess the use and effectiveness of situation modification as an ER strategy, as compared to those currently available. We compared this strategy with two more established strategies, namely distraction and reappraisal. Given the importance of choosing the best ER strategy, we developed an ER choice paradigm similar to the one used by Sheppes and colleagues (2011). In our study, we investigated participants’ choices for the three strategies (situation modification, distraction, and reappraisal), as well as their effectiveness. Furthermore, the use of different ER strategies has been linked to different personality traits. For instance, Gross and John (2003) found an association between neuroticism and poor reappraisal skills. Wang, Shi and Li (2009) even argued that limited use of reappraisal mediates the link between neuroticism and negative affect. We therefore collected data about personality traits and investigated their relation with ER choice. Another area of research concerns the relationship between ER and cognitive abilities. Neuroimaging evidence suggests a link between

inhibitory control and effectiveness of reappraisal (Goldin, McRae, Ramel, & Gross, 2008; Joormann & Gotlib, 2010). Moreover, cognitive control and ER ability might be developed at the same pace, even though findings are mixed (Carlson & Wang, 2007). The relationship between cognitive control and ER is still unclear; we therefore linked effectiveness of ER strategies also to a basic measure of inhibitory control.

Research questions and hypotheses

When do people choose to regulate emotions with situation modification?

Hypothesis 1: situation modification will be chosen more often to regulate highly negative emotions, as compared to mildly negative emotions.

Does the intensity of the negative stimuli moderate effectiveness of situation modification and reappraisal?

Hypothesis 2: situation modification is more effective than reappraisal to regulate intense negative emotions, but less than reappraisal to regulate mild negative emotions.

Does neuroticism predict choice of reappraisal?

Hypothesis 3: Overall, highly neurotic participants will pick reappraisal less frequently than participants with low neuroticism (based on Gross & John, 2003).

Is there a relation between inhibitory control and effectiveness of ER strategies? Hypothesis 4: based on the evidence reported above, we hypothesize that inhibitory control predicts the effectiveness of ER strategies and expect higher scores on inhibitory control to be associated with higher scores of effectiveness.

To investigate our hypotheses, we adopted a within-subjects design. Subjects went through a negative emotion induction, after which they picked an ER strategy to down-regulate their negative emotions. Negative emotions were self-reported twice: once before and once after the down-regulation phase. The strategy choice percentages and effectiveness measures were then related to personality traits, inhibitory control, and self-reported

psychological well-being.

Method Participants

We recruited a total of 38 healthy individuals (29 females, age range: 19-60; Mage =

Materials

Emotional pictures: We selected pictures from the International Affective Picture System (IAPS; Lang, Bradley & Cuthbert, 2008), following previous studies (Sheppes et al., 2014; Bradley et al., 2001; Weinberg & Hajcak, 2010). We created 26 pairs of low-intensity pictures (mean arousal = 3.34, mean valence = 5.15) and 26 pairs of high-intensity pictures (mean arousal = 6.39, mean valence = 1.77), for a total of 52 pairs. Arousal and valence intensity were derived from the IAPS normative ratings. Pictures were matched on content (e.g., mutilation-related pictures were coupled together) and intensity of negative valence.

Situation modification cue: situation modification was implemented by gradually overlaying five white, increasingly more opaque layers on top of one of the pictures (opacity: 25%, 40%, 60%, 80%, 90%). The other picture remained visible, so participants could not completely avoid the emotional context. The opaquest layer was set to 90% (and not 100%), so that it did not cover the picture completely (Figure 1). This was done because, by covering one picture completely, we would risk making the other picture more salient, thus making down-regulation of negative affect even harder to accomplish.

Figure 1. Example of situation modification cue. The picture on the left remains visible, while the picture on

the right is overlaid by an increasingly opaque, white layer.

Reappraisal cues: Reappraisal cues were based on the ones used by Sheppes and colleagues (2014; e.g. “She is alive and medics are on the scene to help her”). We developed additional reappraisal sentences as needed, following their examples. Reappraisal sentences were placed below the picture pairs (Figure 2).

Distraction cues: for distraction, cues consisted of emphasizing an emotionally neutral area of the pictures by laying a white, semi-transparent layer on the rest of the image (Figure 3), creating a spotlight similar to the procedure used by Urry (2010). Importantly, this layer did not prevent the visualization of the details of the image, but guided attention to an emotionally neutral part of the picture pairs.

Figure 3. Example of distraction cue.

Questionnaires

Big Five Inventory-10 (BFI-10; Rammstedt & John, 2007): participants indicated how much they agreed with 10 statements using a 5-point Likert-type scale (where 1 = fully agree, 5 = fully disagree). The test-retest reliability of the BFI-10 is .75. Convergent validity

correlations between self-report and peer-report are .44, which indicate a modest external validity.

COPE-Inventory (Carver, Scheier, & Weintraub, 1989): This 20-item scale was included to assess (1) habitual use of ER strategies, using the sub-scales Active coping, Positive interpretation, Acceptance and Mental disengagement, and (2) problem-focused

coping, using the scale Problem-focused. Responses were given on 4-point Likert scales. Cronbach alpha of the scale is .71; test-retest reliability is .61.

World Health Organisation quality of life assessment (WHOQOL-BREF; Whoqol Group, 1998): Participants were administered the 6-item Psychological well-being and the 3-item Social relationships sub-scales. Responses were given on a 5-point Likert scale. The Cronbach’s alpha for this scale is .78.

Eriksen Flanker task

The classical Eriksen flanker task (Eriksen & Eriksen, 1974) was used as a measure of inhibitory control. In this task, a central target arrow was presented together with 4 distractors (flanker arrows). Participants were instructed to respond to the direction of the target arrow and ignore the flankers. In congruent trials, the flankers pointed in the same direction as the target arrow; in incongruent trials, flankers pointed in the opposite direction of the target arrow. Outcome measures were accuracy, i.e. the proportion of correct responses, and

reaction times, i.e. the time elapsed from the presentation of the stimuli until the participant’s response. By subtracting the mean reaction time for congruent trials to the mean reaction time for incongruent trials, we obtained an index of inhibitory control per participant. The larger the difference, the lower the inhibitory control. Overall split-half reliability of this task is modest, but high for incongruent and congruent reaction times (Stins, Polderman, Boomsma, & de Geus, 2005). However, in our sample split-half reliability was very poor even when computed within trial type (i.e., for congruent and incongruent trials), as correlations were small for both congruent trials (r(662) = .05, p = .21) and incongruent trials (r(615) = -.02, p = .61).

Emotion Regulation task

The trials started with a preview of the pictures pair (4000 msec). In this phase, participants were instructed to look at the pictures. Then participants rated how intensely they felt disgust, threat, sadness and anger (pre-regulation emotional impact evaluation) on 9-point Likert scales (1 = not at all; 9 = a great deal). Three buttons then appeared on the screen, asking participants to pick a strategy to down-regulate affect: Distraction, reappraisal, or situation modification. Participants picked a strategy by clicking on the corresponding button with the mouse. Participants were instructed to look at the negative pictures on the screen and to reduce the intensity of negative emotions by focusing on non-arousing, emotionally neutral areas of the pictures (distraction), or by thinking about the pictures in a way that reduces their negative meaning (reappraisal; Sheppes et al., 2011); or by changing the scene by making one of the pictures less visible (situation modification). No time limit was set for this phase and directions remained on the screen until the choice was made. During the choice period, the pictures were not shown, in order to avoid habituation and participants’ trying out multiple strategies before picking one. After a strategy was chosen, the pictures reappeared on the screen together with the helping cue (10,000 msec; down-regulation phase). After picture offset, participants rated again how intensely they had experienced disgust, threat, sadness and anger on 9-point scales (post-regulation emotional impact evaluation).

The emotion regulation task included 52 trials (26 with mildly negative pictures, 26 with intense negative pictures), preceded by 6 practice trials. During these practice trials, all the three strategies were explained in the instructions, and the trial procedure was carried out twice per strategy, to make sure that participants knew what to expect from any given choice.

The data collection was carried out in sound-proof cubicles at the University of Amsterdam. After signing the consent forms, participants started the procedure. First, subjects filled out questionnaires and completed the flanker task; then they did the emotion regulation task. Overall, the procedure lasted 1 hour. Participation was compensated with either 10 € or 1 research credit.

Results Data Reduction and Outlier Analysis

Eriksen Flanker task: Reaction times were excluded when either <= 150 msec or more than 2.5 standard deviations above the participant’s mean. Each participant’s flanker score was calculated by subtracting the average reaction time for congruent trials from the average reaction time for incongruent trials.

Emotion Regulation task: Each strategy was associated with a choice percentage (i.e., how often did a participant choose each of the three strategies) and an effectiveness score. The choice percentage was computed out of the total number of trials, as well as for different trial types (mild and intense). Effectiveness scores were obtained by subtracting the average of the pre-regulation emotional impact evaluation from the average of the post-regulation emotional impact evaluation.

Confirmatory Analyses

Hypothesis 1: We carried out a multilevel binomial logistic regression to compare the use of situation modification with mildly negative stimuli and intense negative stimuli. To carry out the analysis, reappraisal and distraction choices were pooled together. For each stimulus intensity we therefore had 2 percentages: One for situation modification and one for other strategies. As expected, the analysis reported a statistically significant difference (B =

-.352, p = .005). However, the direction of the difference was opposite to our prediction (see Figure 4), with situation modification being chosen more often to regulate mild negative emotions (19.43%) than intense negative emotions (14.88%).

Figure 4. Situation modification choice proportions for intense and mildly negative stimuli.

Hypothesis 2: First, a paired t-test comparing pre- and post-regulation emotional impact ratings confirmed an effect of emotion regulation (t(209) = 2.557, p = .011). Then, a 2 (Time: pre-regulation, post-regulation) x 2 (Intensity: high, low) x 3 (Strategy: situation modification, distraction, reappraisal) repeated measures ANOVA was run, with

effectiveness scores as dependent variable. We were interested in the 3-way interaction between time, intensity and strategy, but no effect was found (F(2, 396) = .140, p = .869), indicating no differences in strategy effectiveness across different levels of picture intensity. The analysis did not report other relevant statistically significant results.

Hypothesis 3: Dirichlet’s regression was applied to see if neuroticism predicted strategy choice. We decided to use this test, because it takes into account the unit-sum constraint of compositional data (Hijazi & Jernigan, 2007). Results showed that neuroticism

does predict reappraisal choice (B = .166, p = .032). Neuroticism also predicted reappraisal choice after taking age and sex into account (B = .167, p = .035). People with higher levels of neuroticism were less likely to pick reappraisal as a strategy to down-regulate their negative affect (Figure 5).

Figure 5. Neuroticism as a predictor for reappraisal choice.

Hypothesis 4: A linear simple regression was used to test whether inhibitory control predicted ER effectiveness. This relation was translated into the following equation:

yeffectiveness = B0 + B1*xinhibitory control + ε

We associated individual inhibitory control scores to the effectiveness scores of each trial. However, inhibitory control did not predict effectiveness of ER strategies (p = .206), and, if anything, the pattern shown by the data was opposite to our prediction (Figure 6).

Figure 6. Non-significant relation between inhibitory control and ER effectiveness.

Exploratory Analyses

Do choice preferences change across mild and intense negative emotions?

A series of multilevel binomial logistic regressions was carried out to see if stimulus intensity predicted choice percentages. We compared strategies in pairs. The number of the observations varied across stimulus intensity, because we excluded observations where the third (non-considered) strategy was chosen, leading to different N’s for mild and intense trials. With the exception of the comparison between situation modification and reappraisal, all comparisons were statistically significant, suggesting that the likelihood of choosing one strategy over the other changed accordingly to the stimulus type (mild, intense). The results are reported in Table B2. Overall, participants preferred reappraisal over distraction for both mild and intense stimuli, but more strongly for the former (Reappraisalmild = 78.52%,

Reappraisalintense = 65.4%; odds ratio = .508, p < .000). These results replicate what Sheppes

and colleagues (2011) found, i.e. that participants are more likely to use reappraisal with mild stimuli, as compared to intense stimuli, while with the latter distraction becomes more

Modificationmild = 52.89%), but the trend was reversed for intense stimuli (Situation

Modificationintense = 33.56%; odds ratio = 2.419, p < .000).

We also looked at reappraisal’s and distraction’s choice percentages across stimulus type, using the same procedure used to test hypothesis 1 (i.e., by collapsing the other 2 strategies on one; e.g., reappraisal vs others). The choice percentages of all strategies

changed across stimulus type. Like situation modification, reappraisal was more popular with mild stimuli (63.26%), as compared to intense stimuli (55.67%; odds ratio = 1.454, p < .000), while distraction’s choice steeply increased with intense stimuli (Distractionmild: 17.31%;

Distractionintense: 29.45%; odds ratio = .473, p < .000). Detailed results are reported in Table

B2.

Do other personality traits predict reappraisal choice?

We used Dirichlet’s regression to see if other personality traits than neuroticism

predicted reappraisal choice above and beyond age and sex. Only openness had a statistically significant relation with reappraisal choice (B = -.246, p = .042), even though the negative relation was very weak (Figure 7); detailed results can be found in Table A1.

Do other questionnaire scores predict ER strategy choice?

Data from the WHOQOL questionnaire were analyzed using Dirichlet’s regression. The test suggested that psychological well-being predicts the use of all strategies (situation modification: B = -.179, p = .009; distraction: B = -.236, p < .000; reappraisal: B = -.259, p < .000). Detailed results are reported in Table C3.

Dirichlet’s regressions reported that scores on the BDI predict the use of all three strategies (situation modification: B = .039, p = .024; distraction: B = .047, p = .006; reappraisal: B = .052, p = .008). Figure 8 reports scatterplots with slopes.

Figure 8. Relationships between BDI scores and situation modification, distraction and reappraisal choices.

Scores on STAI were analyzed with Dirichlet’s regression and showed no association between trait-anxiety and ER strategy choice, while state-anxiety predicted distraction choice (B = .047, p = .007), but not situation modification or reappraisal.

For the COPE-inventory, the subscale acceptance did predict the use of reappraisal (B = -.167, p = .028), and positive reinterpretation predicted both reappraisal (B = -.226, p = .006) and distraction (B = -.197, p = .040). The other subscales did not predict the use of any of the three strategies. Table C3 shows the results in more detail.

For the CERQ, as reported in Table C3, all strategies were predicted by the subscale positive refocus (situation modification: B = -.147, p = .002; distraction: B = -.193, p < .000; reappraisal: B = -.190, p < .000), rumination (situation modification: B = .115, p = .015; distraction: B = .153, p < .000; reappraisal: B = .162, p < .000), catastrophizing (situation modification: B = .188, p = .008; distraction: B = .233, p = .005; reappraisal: B = .267, p = .001), blame others (situation modification: B = .212, p < .000; distraction: B = .236, p < .000; reappraisal: B = .286, p < .000). Positive reappraisal led to significant predictions for distraction (B = -.102, p = .045) and reappraisal (B = -.112, p = .013), but not for situation modification. The subscale putting into perspective predicted the use of distraction (B = -.141, p = .006), but not of the other strategies.

The remainder subscales did not lead to significant predictions of the ER strategies.

Discussion

The main goal of the present work was to develop a paradigm to allow the study of situation modification as an emotion regulation (ER) strategy. To achieve it, we created a computer-based task where negative emotions were induced using mild and intense negative pictures, and then regulated using distraction, reappraisal, or situation modification. For each picture type, we looked at how often strategies were chosen and how effective they were. Situation modification was chosen to regulate intense and mild negative emotions, but, unexpectedly, more often the latter than the former. We expected situation modification to be more popular to reduce highly negative emotions than mildly negative emotions, because it allows to partially block out the emotional stimuli. According to the conceptual framework by Sheppes and colleagues (2011), this should make situation modification more appealing when the emotion to be regulated is strong. We suggest two potential explanations for our finding. On one hand, the increased popularity of distraction with intense stimuli might

account for the reduced situation modification choices. In fact, both distraction and situation modification allow to reduce elaboration of negative stimuli. A study comparing situation modification and reappraisal only would exclude this potential issue. On the other hand, we need to consider that situation modification typically requires integration with other

strategies. After blocking out a portion of the stimuli by means of the opaque layers, one needs to handle those negative parts that remain uncovered. One can either block them out using distraction, or allow them to be further elaborated and re-interpreted by using

reappraisal. However, we did not check what strategies participants used after situation modification was complete. It is possible that they used reappraisal. In this case, the decreased preference for situation modification might reflect the decreased preference for post-modification reappraisal. Using our paradigm, this can be investigated by either asking participants to report how they regulated emotions after using situation modification, or, preferably, by manipulating the follow-up strategy (instructing half of the subjects to use reappraisal, and the second half to use distraction) and then looking at how situation modification choices vary.

We hypothesized that situation modification would be more effective than reappraisal to regulate intense negative emotions, but not to regulate mild negative emotions. This hypothesis was not supported. Our failing to find empirical support for it might be explained in a similar way as for the first hypothesis. In fact, situation modification’s effectiveness depends on the effectiveness of the follow-up strategy (because we have one effectiveness score per trial). Therefore, whenever participants used reappraisal alongside with situation modification, comparing the effectiveness of these 2 strategies was pointless, because the two scores are highly correlated. Another possible explanation is that strategies were equally effective, as a consequence of participants choosing the strategies on their own. Thus,

participants were more likely to choose the more effective strategies, leading to equally high effectiveness score.

Our third hypothesis was that reappraisal choice would be negatively associated with neuroticism. This hypothesis was confirmed, thus replicating the finding of Gross and John (2003). Lower levels of neuroticism were linked to higher rates of reappraisal choice. Given the apparent robustness of this relationship, future studies could investigate whether training participants with high scores on neuroticism to use reappraisal can reduce their levels of neuroticism.

Finally, it was hypothesized that inhibitory control would predict ER effectiveness. However, we failed to support our hypothesis. One reason for this could be that we used facilitated strategies, which are supposed to require less inhibitory control. Future

investigations of this relation could therefore use uncued strategies. Moreover, inhibitory control might be linked to some strategies only (e.g., distraction), hence the associations between inhibitory control and effectiveness of individual strategies, rather than all strategies pooled together, should be explored.

We also used other questionnaire data to predict strategy use. A subset of these scales were indeed significant; however, given the exploratory nature of this analyses and the pattern of results found, we suggest to interpret these findings with caution. We used many predictors and did not adopt particular measures against the inflation of type I error. Overall, an unclear pattern of predictions arose; for instance, STAI-state, but not STAI-trait predicted strategy choice. Given the correlation between these scales, findings like ours are hard to explain. Moreover, the scales addressing reappraisal were negatively, if at all, associated to this strategy; or predicting distraction positively. At the present moment, we cannot state whether the problem lies within the questionnaires, which might not capture the construct they aim to, or within the operationalization of the strategies within the experiment, which

might induce a gap between the strategies people tend to use in real life and those they use in the laboratory. Finally, it might be the case that our sample was not big enough in relation to the effect size of some of the relations in study.

Our paradigm can potentially contribute to extend the knowledge about situation modification and ER; however, the paradigm itself can be improved. One relevant limitation concerns the lack of an active role of participants in implementing situation modification. The definition of this strategy largely depends on the active component of it, therefore

including it in the design would make for a better operationalization. Moreover, in real-world situations people have to manage their modifying situations themselves; therefore, ecological validity would strongly increase if participants would have to actively produce the

modification. One way this could be achieved is by having participants press a key to make the layers appear on one of the pictures. In general, it will be important to not have them do tasks that might induce distraction, making the distinction between strategies weakly delineated.

Reappraisal was extremely popular in all conditions. Even though this could be due to participants’ genuine preference for this strategy, it is also possible that our cues influenced this result, at least partially. In fact, as opposed to our distraction and situation cues,

reappraisal cues were entertaining. While this makes our results (especially the replication of Sheppes and colleagues (2011)) even more interesting (because, nevertheless, reappraisal showed a decrease with intense stimuli), it is a flaw that needs to be addressed. For this reason, we are running a second experiment, where distraction and reappraisal are not cued, while situation modification is implemented in the same way as in the present study. In this new study, reappraisal will not be entertaining anymore, and both this strategy and distraction will require a cognitive effort. It will be interesting to see whether this will make their

Another limitation of our study is the lack of a no-down-regulation control group. As such, data on effectiveness cannot rule out the alternative explanation that affect decreased post-regulation merely because of time. Where possible, future studies could include a

control condition where subjects are instructed not to decrease their affect. If in this condition negative emotions will remain stable across ratings, it will be possible to conclude that the decrease found in the active-ER conditions is actually due to successful ER.

In conclusion, we developed a paradigm to study situation modification as an ER strategy. As compared to the two paradigms available, the main strength of ours is that it does not allow for avoidance of the stimuli. Thus, it allows to distinguish between situation

modification and situation selection, a different ER strategy. Our paradigm allowed us to see that situation modification is a strategy that people may successfully use to regulate

emotions. While this strategy was used with both mild and intense negative emotions, it was more likely to be chosen to regulate the former than the latter. We also replicated the findings of two previous studies: The negative relation between neuroticism and reappraisal use (Gross & John, 2003), and the stronger preference for reappraisal over distraction with mild emotional stimuli, as compared to intense emotional stimuli (Sheppes et al., 2011). It is our hope that the availability of a new, effective paradigm will allow for an increase in the investigations of situation modification as an emotion regulation strategy.

References

Alink, L. R., Cicchetti, D., Kim, J., & Rogosch, F. A. (2009). Mediating and moderating processes in the relation between maltreatment and psychopathology: Mother-child relationship quality and emotion regulation. Journal of Abnormal Child

Psychology, 37(6), 831-843. doi:10.1007/s10802-009-9314-4

Bradley, M. M., Codispoti, M., Sabatinelli, D., & Lang, P. J. (2001). Emotion and motivation II: sex differences in picture processing. Emotion, 1(3), 300-319. doi:10.1037//1528-3542.1.3.300

Carlson, S. M., & Wang, T. S. (2007). Inhibitory control and emotion regulation in preschool children. Cognitive Development, 22(4), 489-510. doi:10.1016/j.cogdev.2007.08.002 Cloitre, M., Miranda, R., Stovall-McClough, K. C., & Han, H. (2005). Beyond PTSD:

Emotion regulation and interpersonal problems as predictors of functional impairment in survivors of childhood abuse. Behavior Therapy, 36(2), 119-124.

doi:005-7894/05/0119–0124$1.00/0

Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Attention, Perception, & Psychophysics, 16(1), 143-149.

Etkin, A., & Wager, T. D. (2007). Functional neuroimaging of anxiety: a meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. American Journal of Psychiatry, 164(10), 1476-1488. doi:10.1176/appi.ajp.2007.07030504

Glenn, C. R., & Klonsky, E. D. (2009). Emotion dysregulation as a core feature of borderline personality disorder. Journal of Personality Disorders, 23(1), 20-28.

https://doi.org/10.1521/pedi.2009.23.1.20

Goldin, P. R., McRae, K., Ramel, W., & Gross, J. J. (2008). The neural bases of emotion regulation: reappraisal and suppression of negative emotion. Biological Psychiatry, 63(6), 577-586. doi:10.1016/j.biopsych.2007.05.031

Gross, J. J. (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(3), 271-299. doi:1089-2680/98/$3.00

Gross, J. J. (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39(3), 281 291.

https://doi.org/10.1017/S0048577201393198

Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348-362. http://dx.doi.org/10.1037/0022-3514.85.2.348

Gross, J. J., & Thompson, R. A. (2007). Emotion regulation: Conceptual foundations. Handbook of emotion regulation (pp. 3-24). New York, NY, US: Guilford Press. Joormann, J., & Gotlib, I. H. (2010). Emotion regulation in depression: relation to cognitive

inhibition. Cognition and Emotion, 24(2), 281-298.

http://dx.doi.org/10.1080/02699930903407948

Haines, S. J., Gleeson, J., Kuppens, P., Hollenstein, T., Ciarrochi, J., Labuschagne, I., ... & Koval, P. (2016). The wisdom to know the difference: strategy-situation fit in emotion regulation in daily life is associated with well-being. Psychological Science, 27(12), 1651-1659. https://doi.org/10.1177/0956797616669086

Hijazi, R. H., & Jernigan, R. W. (2009). Modelling compositional data using Dirichlet regression models. Journal of Applied Probability & Statistics, 4(1), 77-91.

Horan, W. P., Hajcak, G., Wynn, J. K., & Green, M. F. (2013). Impaired emotion regulation in schizophrenia: evidence from event-related potentials. Psychological

Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1999). International affective picture system (IAPS): Technical manual and affective ratings. Gainesville, FL: The Center for Research in Psychophysiology, University of Florida, 2.

Li, C. S. R., & Sinha, R. (2008). Inhibitory control and emotional stress regulation:

Neuroimaging evidence for frontal–limbic dysfunction in psycho-stimulant addiction. Neuroscience & Biobehavioral Reviews, 32(3), 581-597.

https://doi.org/10.1016/j.neubiorev.2007.10.003

Livingstone, K. M., & Isaacowitz, D. M. (2015). Situation selection and modification for emotion regulation in younger and older adults. Social Psychological and Personality Science, 6(8), 904-910. https://doi.org/10.1177/1948550615593148

Rammstedt, B., & John, O. P. (2007). Measuring personality in one minute or less: A 10-item short version of the Big Five Inventory in English and German. Journal of Research in Personality, 41(1), 203-212. https://doi.org/10.1016/j.jrp.2006.02.001

Sheppes, G., Scheibe, S., Suri, G., & Gross, J. J. (2011). Emotion-regulation choice. Psychological Science, 22, 1391–1396. doi:10.1177/ 0956797611418350 Sheppes, G., Scheibe, S., Suri, G., Radu, P., Blechert, J., & Gross, J. J. (2014). Emotion

regulation choice: A conceptual framework and supporting evidence. Journal of Experimental Psychology: General, 143(1), 163-181.

http://dx.doi.org/10.1037/a0030831

Stins, J. F., Polderman, J. C., Boomsma, D. I., & de Geus, E. J. (2005). Response interference and working memory in 12-year-old children. Child Neuropsychology, 11(2), 191-201. http://dx.doi.org/10.1080/092970490911351

Urry, H. L. (2010). Seeing, thinking, and feeling: emotion-regulating effects of gaze-directed cognitive reappraisal. Emotion, 10(1), 125-135. http://dx.doi.org/10.1037/a0017434

Vujovic, L., Opitz, P. C., Birk, J. L., & Urry, H. L. (2014). Cut! That’s a wrap: regulating negative emotion by ending emotion-eliciting situations. Frontiers in Psychology, 5, 165. doi:10.3389/fpsyg.2014.00165

Wang, L., Shi, Z., & Li, H. (2009). Neuroticism, extraversion, emotion regulation, negative affect and positive affect: The mediating roles of reappraisal and suppression. Social Behavior and Personality, 37(2), 193-194. doi:10.2224/sbp.2009.37.2.193

Weinberg, A., & Hajcak, G. (2010). Beyond good and evil: The time course of neural activity elicited by specific picture content. Emotion, 10, 767–782. doi:10.1037/a0020242

APPENDIX A Table 1

APPENDIX B Table 2

Note. *** p < .001, ** p < .01, * p < .05. SM = Situation Modification; D = Distraction, R = Reappraisal, O = Others, N = sample size of the comparison.

APPENDIX C Table 3