With the Compliments of Springer Publishing Company, LLC

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1 With the Compliments of Springer Publishing Company, LLC

2 Journal of Cognitive Psychotherapy: An International Quarterly Volume 31, Number The Interactive Effect of Attention to Emotions and Emotional Distress Intolerance on Anxiety and Depression Natasha Benfer, BS Joseph R. Bardeen, PhD Department of Psychology, Auburn University, Auburn, Alabama Thomas A. Fergus, PhD Department of Psychology and Neuroscience, Baylor University, Waco, Texas Emotional distress intolerance (EDI) has been identified as a risk factor for mood and anxiety disorders. One factor that may influence the association between EDI and psychopathology is attention to emotions (AE). Recent evidence suggests that AE may encompass two dissociable components: voluntary and involuntary AE. This study aimed to examine the moderating role of both voluntary and involuntary AE in the association between EDI and psychological symptoms (i.e., anxiety, depression) in a sample of 955 community adults. We hypothesized that voluntary AE would buffer, and involuntary AE would enhance, the association between EDI and psychological symptoms. In partial support of our hypotheses, involuntary, but not voluntary, AE moderated the relationship between EDI and both symptom outcomes such that the positive associations between EDI and psychological symptoms were significantly stronger at higher, versus lower, levels of involuntary AE. Thus, individuals with relatively higher EDI and involuntary AE may be at particularly high risk for experiencing anxiety and depression. Clinical implications are discussed. Keywords: emotional distress intolerance; distress tolerance; anxiety; depression; emotion; attention to emotions Recently, there has been a groundswell of support for identifying transdiagnostic risk and resiliency factors that cut across emotional disorders (Barlow, Allen, & Choate, 2004; Mansell, Harvey, Watkins, & Shafran, 2008). This transdiagnostic approach helps to clarify the extensive comorbidity that has been observed among disorders and aids in the identification of treatment techniques that can be applied across a wide range of presenting problems (Brown, Campbell, Lehman, Grisham, & Mancill, 2001). For example, emotional distress intolerance (EDI), defined as an individual s perceived ability to endure negative emotional states (Simons & Gaher, 2005), has been identified as a potential risk factor for a wide range of psychopathology, including those presentations for which the prevalence rates, and degree of comorbidity, are particularly high (i.e., anxiety and mood disorders; Bernstein, Marshall, & Zvolensky, 2011; Keough, Riccardi, Timpano, Mitchell, & Schmidt, 2010; Leyro, Zvolensky, & Bernstein, 2010). More specifically, 2017 Springer Publishing Company 91

3 92 Benfer et al. Bernstein et al. (2011) found that EDI predicted number of lifetime mood and anxiety disorders above and beyond other related, but distinct, facets of distress tolerance (e.g., discomfort intolerance). In addition, EDI prospectively predicts greater worry and obsessions, the cardinal features of generalized anxiety disorder (GAD) and obsessive-compulsive disorder, respectively (Cougle, Timpano, Fitch, & Hawkins, 2011; Macatee, Capron, Guthrie, Schmidt, & Cougle, 2015), as well as depressive symptoms (O Cleirigh, Ironson, & Smits, 2007). It may be that individuals who perceive themselves as having a relatively low threshold for emotional distress are more likely to use maladaptive emotion regulation strategies (e.g., physical avoidance, suppression) to alleviate their emotional suffering. These behaviors typically reduce suffering in the short term but do not allow the individual to naturally habituate to the emotional experience and the contexts that are associated with it, thus increasing the likelihood that these emotions, associated contexts, stimulus triggers, and so forth will be avoided in the future and one s emotional distress will be maintained over time (Bardeen, 2015; Kashdan, Morina, & Priebe, 2009). Indeed, a low perceived capacity to endure negative emotional states shares medium to large associations with depressive symptoms (r ; Bernstein et al., 2011; Timpano, Buckner, Richey, Murphy, & Schmidt, 2009) and a broad array of anxiety symptom types (magnitude of rs ranging from.32 to.56; Brandt, Zvolensky, & Bonn-Miller, 2013; Fergus, Bardeen, & Orcutt, 2015; Keough et al., 2010; Macatee et al., 2015). Some evidence suggests that protective factors may attenuate the impact of pathology-related risk factors, such as EDI, on maladaptive outcomes (Bardeen, Tull, Dixon-Gordon, Stevens, & Gratz, 2015; Fergus, Bardeen, & Orcutt, 2013). Pursuant to this study, how much a person takes notice, contemplates, values, and monitors their own feelings (i.e., attention to emotions [AE]; Huang, Berenbaum, & Chow, 2013) may be important in understanding how EDI relates to emotional distress. Huang et al. (2013) found that AE consists of two distinct facets: involuntary (e.g., I tend to pay attention to my emotions even when I don t want to ) and voluntary AE (e.g., I think about and try to understand my emotional reactions ). These dissociable components are differentially related to levels of worry (the cardinal symptom of GAD) and depressive symptoms, such that involuntary AE is positively associated with worry and depressive symptoms, but voluntary AE is only associated with depressive symptoms, not worry, when simultaneously accounting for involuntary AE. In addition, voluntary AE is positively associated, and involuntary AE is negatively associated, with emotional clarity (Huang et al., 2013). Thus, the willingness to attend to emotions is linked to emotional clarity, whereas the tendency to involuntarily attend to emotions is associated with maladaptive outcomes and difficulty identifying discrete emotions. As described, individuals with greater EDI may be more likely to use maladaptive emotion regulation strategies to alleviate emotional distress in the short term, which maintains and exacerbates such distress in the long run. However, the volitional component of emotional responding (i.e., being willing to engage with, and choose when to flexibly disengage from, emotionally distressing internal states) may be important in understanding how EDI relates to anxiety. Specifically, those who are able to exert volitional control over attending to their emotions may experience greater emotional clarity and understanding and the eventual alleviation of the distress associated with emotions such as fear, sadness, and so forth. Voluntary AE, in other words, may be an important psychological process that combats experiential avoidance among those with high levels of EDI (Hayes, Wilson, Gifford, Follette, & Strosahl, 1996). In contrast, emotional distress may be amplified for those who unintentionally attend to their emotions and have relatively high EDI. These individuals may be more likely to use maladaptive regulatory strategies to alleviate their distress, thus decreasing emotional understanding and habituation to negative emotions and associated contexts. EDI may be a particularly potent risk factor for the development of emotional disorders among those who involuntarily attend to emotionally distressing internal states. To date, the roles of voluntary and involuntary AE have not been examined in the relationship between EDI and psychological

4 Distress Intolerance, Attention to Emotions, and Distress 93 distress. As such, the purpose of this study was to examine the interplay between EDI and AE on common symptoms presentations (e.g., anxiety and depression). We predicted that the strength of the positive association between EDI and both anxiety and depression would depend on levels of both voluntary and involuntary AE. More precisely, at higher levels of voluntary AE, the EDIpsychological distress (i.e., anxiety and depression) relationship would be weaker. Alternatively, at higher levels of involuntary AE, the EDI-psychological distress relationship would be stronger. Participants and Procedure Method A total of 996 participants from the United States were recruited for this study using Amazon Mechanical Turk (MTurk). MTurk is an online crowd sourcing website where researchers can recruit general population adults to participate in paid survey research. Previous research has supported use of MTurk for such purposes, citing its reliability and relatively diverse sample demographics (Behrend, Sharek, Meade, & Wiebe, 2011; Buhrmester, Kwang, & Gosling, 2011). Consistent with similar survey studies, participants were paid $1.50 for their participation (Buhrmester et al., 2011). To eliminate random responders, three catch questions were included (e.g., Please click the circle at the bottom of the screen. Do not click on the scale items that are labeled from 1 to 9 ; Oppenheimer, Meyvis, & Davidenko, 2009; Paolacci, Chandler, & Ipeirotis, 2010). Participants needed to answer at least two of the three catch questions correctly to be included in the current sample. The resulting final sample consisted of 955 participants. The sample was primarily composed of White (82.4%) females (68.5%), with an average age of 36 years (SD , range ). Participants completed informed consent and a random ordered battery of questionnaires via a secure online platform. Measures Attention to Emotions Scale. The Attention to Emotions Scale (AES; Huang et al., 2013) measures voluntary (8 items) and involuntary (7 items) AE with a 5-point scale ranging from strongly agree to strongly disagree. Higher scores on voluntary and involuntary scales indicate greater respective AE. Voluntary and involuntary AE represent two distinct but related constructs. In support of concurrent validity, compared to those lower in voluntary AE, those with higher levels of voluntary AE paid greater attention to emotional face stimuli on a behavioral task (Huang et al., 2013). In addition, higher levels of involuntary AE are associated with lower levels of clarity of emotions, whereas higher levels of voluntary AE are associated with higher levels of clarity of emotions, after accounting for involuntary AE. Both scales have exhibited adequate internal consistency in previous research (Huang et al., 2013). Internal consistency in the current sample was a 5.90 for voluntary and a 5.86 for involuntary AE. Distress Tolerance Scale. The Distress Tolerance Scale (DTS; Simons & Gaher, 2005) assesses one s perceived ability to withstand negative emotional states. The scale consists of 15 items, with a 5-point scale ranging from strongly agree to strongly disagree. For this study, the DTS total score was recoded so that higher scores indicated greater EDI. DTS scores are concurrently related to depressive symptoms and a range of anxiety symptom types (e.g., GAD, social anxiety disorder [SAD], panic symptoms; Bernstein et al., 2011). The DTS has demonstrated excellent internal consistency (a 5.93 and.94; Fergus & Bardeen, 2016; Keough et al., 2010). Internal consistency in the current sample was a The Depression Anxiety Stress Scales-21 Item Version. The Depression Anxiety Stress Scales-21 (DASS-21; Lovibond & Lovibond, 1995) is a 21-item measure with scales that assess past week symptoms of depression, anxiety, and stress. Each subscale contains 7 items rated on a

5 94 Benfer et al. 4-point scale ranging from did not apply to me at all to applied to me very much, or most of the time. Higher scores indicate higher symptom levels. The DASS-21 have exhibited adequate psychometrics properties in several studies (Henry & Crawford, 2005; Lovibond & Lovibond, 1995), including evidence of strong convergent validity between DASS-21 Anxiety and other measures of anxiety, as well as between DASS-21 Depression and measures of depressive symptoms (Antony, Bieling, Cox, Enns, & Swinson, 1998). In addition, DASS-21 Anxiety and Depression have demonstrated strong internal consistency (Bardeen, Fergus, & Orcutt, 2014; Osman et al., 2012) and discriminant validity (Henry & Crawford, 2005). Internal consistency in the current sample was a 5.85 for DASS-21 Anxiety and a 5.93 for DASS-21 Depression. Data Analytic Strategy Using the procedure recommended by Allison (2002) and Enders (2010), missing values were estimated using multiple imputation via the Missing Values add-on in IBM SPSS (Version 19). Five datasets were imputed to compute five estimates for all missing values, which accounted for 1.22% of total data points. Estimated values were created from parameter estimates and standard errors from each data set. In addition, bivariate correlations were calculated to determine whether demographic variables (i.e., sex, age, and race/ethnicity) were significantly associated with outcome variables (DASS- 21 Depression and Anxiety), thus warranting inclusion as covariates in our primary analytic models (Tabachnick & Fidell, 2007). Race and ethnicity were collapsed into a single dummy coded variable (coded as Hispanic and/or non-white [n 5 168, 17.6%] versus non-hispanic White [n 5 787, 82.4%]). Next, two sets of regression analyses were conducted: DASS-21 Anxiety served as the outcome variable in the first set, and DASS-21 Depression served as the outcome variable in the second set. Each set of regressions was conducted with voluntary AE serving as the moderator in the first set, and involuntary AE serving as the moderator in the other resulting in a total of four regression models. For all models, EDI served as the predictor variable. Predictor variables and covariates were mean-centered and entered into the first step of each model (Aiken & West, 1991). The interaction term, computed as the product of the predictor and moderator variable, was entered into the second step of each model. Significant interactions were examined using simple slopes analysis (Aiken & West, 1991). Specifically, for each significant interaction, two simple regression equations were constructed in which the relation between the predictor and outcome variable was tested at both high (11 SD) and low (21 SD) levels of the moderating variable. Results Descriptive Statistics and Potential Covariates Among potential covariates (i.e., age, sex, race/ethnicity), only age was significantly associated with either of the outcome variables. Specifically, younger participants reported relatively higher levels of both anxiety (r , p,.001) and depression (r , p,.001). As such, age was included as a covariate in all four regression models, whereas sex and race/ethnicity were dropped from further multivariate analyses. Consistent with previous research (Huang et al., 2013), voluntary and involuntary AE shared an association that was positive and large in magnitude (r 5.47, p,.001). In support of the distinct nature of these constructs, voluntary and involuntary AE were differentially associated with variables of interest. Specifically, voluntary AE was negatively correlated with both anxiety (r , p 5.048) and depressive (r , p 5.002) symptoms, but was not significantly correlated with EDI (r , p 5.43). Involuntary AE was positively correlated with EDI (r 5.30, p,.001) and both anxiety (r 5.22, p,.001) and depressive (r 5.23, p,.001) symptoms.

6 Distress Intolerance, Attention to Emotions, and Distress 95 Anxiety Regressions Voluntary Attention to Emotions. In the first step of the regression model, age and EDI significantly predicted DASS-21 Anxiety (age: b , p,.001; EDI: b 5.35, p,.001), but voluntary AE did not (b , p 5.08). Contrary to our prediction, the interaction term (voluntary AE by EDI) did not significantly predict DASS-21 Anxiety in the second step of the model ( R ; b 5.04, p 5.19). Involuntary Attention to Emotions. In the first step of the regression model, age, EDI, and involuntary AE significantly predicted DASS-21 Anxiety (age: b , p,.001; EDI: b 5.33, p,.001; involuntary AE: b 5.11, p,.001). As predicted, the interaction term (involuntary AE by EDI) significantly predicted DASS-21 Anxiety in the second step of the model ( R ; b 5.07, p 5.01). Results of the simple slopes analysis indicated that the positive association between EDI and DASS-21 Anxiety was significantly stronger at higher (b 5.39, p,.001) versus lower (b 5.24, p,.001) levels of involuntary AE (Figure 1). Those with higher levels of involuntary AE and EDI appear to be at greater risk for experiencing anxiety symptoms. Depression Regressions Voluntary Attention to Emotions. In the first step of the regression model, EDI and voluntary AE significantly predicted DASS-21 Depression (EDI: b 5.43, p,.001; voluntary AE: b , p 5.003), but age did not (b , p 5.09). Contrary to our prediction, the interaction term (voluntary AE by EDI) did not significantly predict DASS-21 Depression in the second step of the model ( R ; b 5.02, p 5.49). Involuntary Attention to Emotions. In the first step of the regression model, EDI and voluntary AE significantly predicted DASS-21 Depression (EDI: b 5.40, p,.001; involuntary Anxiety Low Involuntary AE High Involuntary AE 0 Low EDI High EDI Figure 1. Moderating effect of involuntary attention to emotions (AE) on the relationship between emotional distress intolerance (EDI) and anxiety.

7 96 Benfer et al Depression Low Involuntary AE High Involuntary AE 0 Low EDI High EDI Figure 2. Moderating effect of involuntary attention to emotions (AE) on the relationship between emotional distress intolerance (EDI) and depression. AE: b 5.11, p,.001), but age did not (b , p 5.12). As predicted, the interaction term (involuntary AE by EDI) significantly predicted DASS-21 Depression in the second step of the model ( R ; b , p,.001). Results of the simple slopes analysis indicated that the positive association between EDI and DASS-21 Depression was significantly stronger at higher (b 5.49, p,.001), versus lower (b 5.30, p,.001), levels of involuntary AE (Figure 2). Those with higher levels of involuntary AE and EDI appear to be at greater risk of experiencing depressive symptoms. Discussion In this study we sought to examine the moderating effects of both voluntary and involuntary AE in the relationship between EDI and two symptom outcomes (anxiety, depression). We hypothesized that the association between EDI and both outcomes would be weaker at higher levels of voluntary AE and stronger at higher levels of involuntary AE. We found partial support for our hypotheses, such that involuntary AE significantly moderated the association between EDI and both anxiety and depression in the proposed direction, but voluntary AE did not. Voluntary AE was associated with both anxiety and depression at the bivariate level. These small magnitude associations were no longer significant after accounting for EDI. This finding is consistent with research in which voluntary AE was significantly associated with maladaptive outcomes (e.g., worry) but not after accounting for its shared variance with other predictors (Huang et al., 2013). Moreover, voluntary AE did not moderate the relationship between EDI and either of our outcome measures (anxiety, depression). One explanation consistent with previous research is that adaptive, compared to maladaptive, self-regulatory processes are generally less strongly

8 Distress Intolerance, Attention to Emotions, and Distress 97 associated with maladaptive outcomes (Aldao, Nolen-Hoeksema, & Schweizer, 2010; Seligowski, Lee, Bardeen, & Orcutt, 2015). Involuntary AE shared correlations with anxiety and depression that were small to medium in size (r 5.22, p,.001 and r 5.23, p,.001, respectively), whereas the correlations between voluntary AE and anxiety and depression were small in size (r , p,.05 and r , p,.01, respectively). The medium large magnitude associations between EDI and our outcome variables may be too large for voluntary AE, with its relatively small associations with anxiety and depression, to mitigate the deleterious effects of EDI on anxiety and depressive symptoms. The main effects of EDI and involuntary AE in predicting anxiety and depression were qualified by significant interaction effects, such that the EDI-psychological distress (i.e., anxiety and depression) relationship was significantly stronger at higher, versus lower, levels of involuntary AE. Previous research has shown that lower involuntary AE is related to greater nonjudgmental acceptance of emotions, whereas higher involuntary AE is related to nonacceptance of emotions (Boden & Thompson, 2015). Therefore, it may be that those high in involuntary AE, who are less willing to stay in contact with and more likely to negatively evaluate emotions, are utilizing avoidance strategies to escape the discomfort associated with internal experiences in the short term, which paradoxically maintains distress over longer time (Bardeen, 2015). This study contributes to the limited literature examining voluntary and involuntary AE as distinct constructs. Consistent with previous research, we found that these two constructs had differential roles in psychological dysfunction (Boden & Thompson, 2015; Huang et al., 2013). In addition, findings from this study illuminate how involuntary AE interacts with EDI, a wellestablished transdiagnostic factor, to predict anxiety and depressive symptoms. Thus, it may be important to assess and target involuntary AE in the treatment of mood and anxiety pathology. Interventions that seek to reduce automatic threat- and emotion-related processing (e.g., attention modification; Amir, Beard, Burns, & Bomyea, 2009) and increase conscious willingness to stay in contact with uncomfortable emotions (e.g., acceptance and commitment therapy; Hayes, Luoma, Bond, Masuda, & Lillis, 2006) may be helpful in decreasing the likelihood that individuals with higher levels of EDI will develop emotional disorders. Study limitations must be acknowledged. Despite use of a large community sample of adults, considerable variability in DASS-21 Anxiety and Depression scores was observed, with 41.4% of the sample reporting anxiety symptoms and 42.4% reporting depressive symptoms that were not in the normal range. For anxiety symptoms, 12.6% of the sample were in the mild range, 10.2% were in the moderate range, 5.9% were in the severe range, and 12.7% were in the extremely severe range. For depressive symptoms, 11.2% were in the mild range, 14.8% were in the moderate range, 9.8% were in the severe range, and 6.9% were in the extremely severe range. 1 Although research supports the conceptualization of anxiety and depression as continuous, rather than categorical, constructs (Kollman, Brown, Liverant, & Hofmann, 2006; Prisciandaro & Roberts, 2005; Shear, Bjelland, Beesdo, Gloster, & Wittchen, 2007), we are limited in our ability to generalize findings from this study to those with diagnosable anxiety and mood disorders. Outcomes from this study may also be limited by our use of an Internet sample. MTurk samples are more diverse than undergraduate samples (Behrend et al., 2011) but may not be fully representative of the general population, thus reducing the generalizability of study findings (Paolacci & Chandler, 2014). Finally, our study is restricted by its cross-sectional design. Because all data were gathered during one session, we cannot make inferences about the temporal nature of relations among AE, EDI, and anxiety and depression. Future research may benefit from the use of longitudinal or experimental designs to establish directional relations among these constructs. Despite these limitations, this study provides the first examination of the role of voluntary and involuntary AE in the relationship between EDI and psychological distress. In combination with previous research, our findings suggest that involuntary AE may be a transdiagnostic

9 98 Benfer et al. risk factor worthy of additional research. Evidence that involuntary AE enhances the effect of outcome-specific risk factors across a wide variety of maladaptive outcomes may indicate the need for interventions directly targeting this construct. Specifically, interventions that target more automatic, or bottom-up, AE may be beneficial in treating a wide variety of symptom presentations. Interestingly, recent evidence suggests that more automatic, or bottom-up, attention to negative content may be more accurately described as a pattern of monitoring in which one repeatedly shifts attention away from the negative content (i.e., avoidance) and then back again, thus resulting in greater engagement with this content over time (Bardeen, Tull, Daniel, Evenden, & Stevens, 2016; Zvielli, Bernstein, & Koster, 2015). To date, the majority of attention-retraining programs have been designed to train attention away from negative content. Given recent empirical research suggesting attention dysregulation in the form of attentional shifts between negative and other content, clients may be better served by retraining approaches designed to increase attentional flexibility and reduce attentional dyscontrol by balancing attention allocation instead of training clients to attend away from negative content (e.g., Badura-Brack et al., 2015). Notes 1. Although the DASS-21 was developed as a quantitative measure consistent with dimensional models of anxiety and depression, in which scores ranging from a complete absence of symptom expression to the highest level of severity are to be included (Lovibond & Lovibond, 1995), and research supports conceptualizing anxiety and depressive symptoms continuously (e.g., Prisciandaro & Roberts, 2005), we reexamined our regression models in a more restricted sample, in which only participants who endorsed at least one symptom on the DASS-21 Anxiety (n 5 772) and DASS-21 Depression (n 5 745) scales were included. Consistent with our original analysis, the voluntary AE 3 EDI interaction did not significantly predict DASS-21 Anxiety or Depression in either of the respective subsamples. Regarding the regression models with DASS-21 Depression as the outcome variable, statistically significant findings remained significant, and nonsignificant findings were unchanged when the models were reexamined in the reduced sample (n 5 745). One difference is of note. For the anxiety model, in which involuntary AE served as the moderator, the interaction term did not reach statistical significance at the p,.05 level in the reduced sample (n 5 772). Specifically, the magnitude of the interaction effect was slightly reduced (from b to b ; p 5.10). However, the pattern of effects was consistent with that which was described in the full sample. Consistent with the original analysis, follow-up simple slopes analysis indicated that the positive association between EDI and DASS-21 Anxiety was stronger at higher (b , p,.001), versus lower (b , p,.001), levels of involuntary AE. References Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage. Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30(2), Allison, P. D. (2002). Missing data. Thousand Oaks, CA: Sage. Amir, N., Beard, C., Burns, M., & Bomyea, J. (2009). Attention modification program in individuals with generalized anxiety disorder. Journal of Abnormal Psychology, 118, Antony, M. M., Bieling, P. J., Cox, B. J., Enns, M. W., & Swinson, R. P. (1998). Psychometric properties of the 42-item and 21-item versions of the Depression Anxiety Stress Scales in clinical groups and a community sample. Psychological Assessment, 10,

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