Discussion: Psychoanalytic and Trait Theory

Personality and Individual Differences 110 (2017) 23–26

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Personality and Individual Differences

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Short Communication

Growth mindset of anxiety buffers the link between stressful life events and psychological distress and coping strategies

Hans S. Schroder a,⁎, Matthew M. Yalch a,b, Sindes Dawood c, Courtney P. Callahan a, M. Brent Donnellan d, Jason S. Moser a

a Michigan State University, United States b San Francisco Veterans Affairs Health Care System, United States c The Pennsylvania State University, United States d Texas A&M University, United States

⁎ Corresponding author at: 316 Physics Rd, Room 69 Michigan State University, East Lansing, MI 48823, United

E-mail address: [email protected] (H.S.

http://dx.doi.org/10.1016/j.paid.2017.01.016 0191-8869/© 2017 Elsevier Ltd. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history: Received 19 July 2016 Received in revised form 17 November 2016 Accepted 11 January 2017 Available online 18 January 2017

Beliefs about the malleability of global attributes like personality and intelligence – known as mindsets – are well-established predictors of resilience to challenges in educational contexts. Recent research further suggests that mindsets about anxiety may act in a similar fashion with mental health resilience. In this study we examined whether anxiety mindset would moderate relations between history of stressful life events and psychological distress and coping. Consistent with predictions, relations between number of stressful life events and posttrau- matic stress symptoms, depression, substance use, and motivations for non-suicidal self-injury were weaker among those with more of a growth mindset relative to those with more of a fixed mindset. These initial results suggest that anxiety mindsets function in a similar way for mental health resilience as how mindsets of intelli- gence function for academic outcomes.

© 2017 Elsevier Ltd. All rights reserved.

Keywords: Growth mindset Anxiety mindset Stressful life events Potentially traumatic events Coping Resilience

1. Introduction

Mindsets refer to implicit beliefs about the malleability of personal attributes (Dweck, 1999). The growth mindset is the belief that an attri- bute like intelligence or personality is changeable; the fixed mindset is the belief that such attributes are immutable. Research in social and ed- ucational psychology indicates that mindsets shape meaning-making processes and give rise to different goals, motivations, and behaviors (Dweck, Chiu, & Hong, 1995). Mindsets often determine responses to challenges and setbacks: students with a growth mindset of intelligence tend to adjust more adaptively after failure, whereas those with a fixed mindset of intelligence tend to disengage and feel helpless (Dweck & Leggett, 1988). Moreover, students with a growth mindset are better able to adjust to difficult academic transitions compared to those with a fixed mindset (Yeager et al., 2014). In fact, mindsets are more relevant during contexts that are challenging and have a less noticeable impact on behavior when tasks are easier (Dweck & Leggett, 1988). In this way, mindsets can be said to moderate the link between challenge level and subsequent performance/adjustment: among individuals with fixed mindsets, higher difficulty corresponds with poorer

E, Department of Psychology, States. Schroder).

performance and adjustment, whereas this association is weaker among growth-minded individuals.

The general finding that a growth mindset buffers the negative con- sequences of challenging and demanding environments has implica- tions for clinical psychology, given that stressful life circumstances are risk factors for developing psychological distress (Abramson, Seligman, & Teasdale, 1978; Infurna & Luthar, 2016). Although the ap- plication of mindsets to clinical science is in its infancy (Kneeland, Dovidio, Joormann, & Clark, 2016), three promising findings have emerged. First, connections between mindsets and mental health symp- toms are somewhat domain-specific, such that correlations with symp- toms are stronger for mindsets of emotion and anxiety, compared to mindsets of personality and intelligence (Schroder, Dawood, Yalch, Donnellan, & Moser, 2015, 2016). Second, growth mindsets of emotions and anxiety are associated with adaptive emotion-regulation strategies such as cognitive reappraisal (De Castella et al., 2013; Kneeland et al., 2016). Third, the growth mindset of anxiety is associated with greater motivation to engage and succeed in psychological therapy (De Castella et al., 2015; Schroder et al., 2015; Valentiner, Jencius, Jarek, Gier-Lonsway, & McGrath, 2013).

Although such findings are suggestive, it remains unclear whether the anxiety mindset moderates the association between life challenges and adjustment. The current study was designed to test this hypothesis, using history of stressful life events (SLEs) as a proxy for challenge, and a

Table 1 Frequency of stressful life events endorsed on the Life Events Checklist-5.

EEEventD description N %

Natural disaster 215 17.23 Fire or explosion 70 5.61 Transportation accident 557 44.63 Serious accident at work, home, or during recreational activity 178 14.26 Exposure to toxic substance 60 4.81 Physical assault 245 19.63 Assault with weapon 30 2.40 Sexual assault 107 8.57 Other unwanted or uncomfortable sexual experience 309 24.76 Combat or exposure to a war-zone 11 0.88 Captivity 7 0.56 Life-threatening illness or injury 85 6.81 Severe human suffering 34 2.72 Sudden, violent death 42 3.37 Sudden, unexpected death of someone close to you 381 30.53 Serious injury, harm, or death you caused to someone else 37 2.96 Any other very stressful event or experience 553 44.31

Note. Values represent the number of “Happened to me” responses participants endorsed on the LEC-5. Participants were allowed to endorse multiple events.

24 H.S. Schroder et al. / Personality and Individual Differences 110 (2017) 23–26

set of psychological symptoms (posttraumatic stress disorder and de- pression symptoms) and maladaptive coping strategies (alcohol abuse, drug use, and motivations for non-suicidal self-injury) as indica- tors of adjustment. Although most people directly experience at least one SLE (Norris, 1992), repeated exposure to SLEs is associated with these and other adverse outcomes (Infurna & Luthar, 2016; Kendler, Karkowski, & Prescott, 1999; Nock, 2010). The primary hypothesis was that the relation between SLEs and distress/adjustment would be stronger among individuals with more of a fixed mindset of anxiety compared to those with more of a growth mindset of anxiety.

2. Method

2.1. Participants

Undergraduates (N = 1682) from a large Midwestern university participated for partial course credit1, and 1254 were retained after screening for inattention (Mage = 19.83 years, range 18–33; 69.5% fe- male, 73.4% Caucasian). The university's Institutional Review Board ap- proved all procedures and all participants provided consent.

3. Measures

3.1. Anxiety mindset

The Implicit Theories of Anxiety Scale (TOA; Schroder et al., 2015) assessed mindset of anxiety. Four fixed-minded items (“You have a cer- tain amount of anxiety and you really cannot do much to change it”, “Your anxiety is something about you that you cannot change very much”, “To be honest, you cannot really change how anxious you are”, and “No matter how hard you try, you can't really change the level of anxiety that you have”) are rated on a scale of 1 (Strongly Disagree) to 6 (Strongly Agree). The TOA has been shown to have acceptable reliabil- ity and validity in previous research (Schroder et al., 2015, 2016). Items are reverse-scored and then averaged such that higher scores reflect greater endorsement of the growth mindset of anxiety.

3.2. Stressful life events

The Life Events Checklist-5 (LEC-5; Gray, Litz, Hsu, & Lombardo, 2004) is a widely used checklist of SLEs across the lifespan. The LEC-5 consists of 17 items and participants indicate their experience of each of the events using the following response options: “Happened to me”, “Witnessed”, “Learned About”, “Not Sure”, and “Not Applicable”. For this study, only the “Happened to me” responses were summed to cre- ate an index of history of SLEs.

3.3. Psychological distress

The Posttraumatic Checklist for DSM-5 (PCL-5; Blevins, Weathers, Davis, Witte, & Domino, 2015) is a 20-item self-report measure of DSM-5 symptoms of PTSD experienced during the past month. The Pa- tient Health Questionnaire – 9 (PHQ-9; Kroenke, Spitzer, & Williams, 2001) is a 9-item measure of depression.

3.4. Maladaptive coping

Alcohol abuse in the past 30 days was measured with items from the Patient Reported Outcome Measurement System Alcohol Use Short Form (PROMIS-Alc; Pilkonis et al., 2013), and data were available from 794 re- spondents who had a drink during this time frame. The Drug Abuse

1 Data from some of these participants are reported in other published and in prepara- tion papers (citations available in unmasked copy). However, these other papers exam- ined different research questions with different variables and thus all of the analyses reported here are novel.

Screening Test-10 (DAST-10; Skinner, 1982) is a 10-item (Yes/No) self- report measure used to screen for drug abuse problems. The 39-item In- ventory of Statements About Self-Injury (ISAS; Klonsky & Glenn, 2009) as- sesses 13 functions for engaging in non-suicidal self-injury (e.g., affect regulation, self-punishment, sensation seeking).

3.5. Control variable – negative temperament

As research consistently underscores the influence of trait negative affectivity on mental health outcomes (Lahey, 2009), we controlled for negative temperament using the Negative Temperament subscale of the Schedule for Nonadaptive and Adaptive Personality (SNAP-NT; Clark, 1993) in additional analyses.

3.6. Data collection and analysis

Data collection took place over two consecutive semesters (first se- mester N = 1026; second semester N = 229) using slightly different surveys. The PROMIS-Alc, DAST-10, ISAS, SNAP-NT were only collected during the first and larger survey and Ns differ across analyses. Correla- tions were computed to quantify relations between study variables. We next used the simple moderation model from the PROCESS macro for SPSS (Hayes, 2013) to test the primary moderation hypothesis2. In each of five models (one model per outcome variable), number of SLEs endorsed on the LEC-5 was specified as the predictor and TOA as the moderator variable. LEC-5 and TOA scores were mean-centered prior to analysis.

4. Results

Endorsement rates of SLEs are listed in Table 1. The average number of SLEs was 2.34 (SD = 1.97; range 0–11). Table 2 presents descriptive statistics and bivariate correlations. Number of SLEs was positively re- lated to all outcomes except for alcohol abuse. Consistent with previous studies (Schroder et al., 2015, 2016), the growth mindset of anxiety was negatively correlated with all other variables.

Results of the moderation analyses are presented in Table 3. The anxiety mindset predicted each of the five outcomes, over and above the number of SLEs. The interaction between LEC-5 and TOA was statis- tically significant for PTSD symptoms, depression symptoms, drug abuse, and non-suicidal self-injury functions, although it was not statis- tically significant for alcohol abuse. In each case, for individuals with

2 As noted by a reviewer, the PROCESS macro uses listwise deletion; results were iden- tical when regression models were computed using pairwise deletion.

Table 3 Results of the moderation analyses.

Overall model Simple slopes

N R2 ΔR2 β b SE Lower 95% CI Upper 95% CI 1 SD below TOA

1 SD above TOA

b SE b SE

PTSD Symptoms (PCL-5) 1246 0.24⁎⁎

LEC-5 0.27⁎⁎ 2.37⁎⁎ 0.22 1.94 2.80 2.98⁎⁎ 0.29 1.76⁎⁎ 0.31 TOA −0.34⁎⁎ −4.31⁎⁎ 0.32 −4.94 −3.69 LEC-5_x_TOA 0.01⁎⁎ −0.08⁎⁎ −0.45⁎⁎ 0.15 −0.74 −0.16

Depression Symptoms (PHQ-9) 1250 0.21⁎⁎

LEC-5 0.16⁎⁎ 0.45⁎⁎ 0.07 0.31 0.60 0.63⁎⁎ 0.09 0.28⁎⁎ 0.10 TOA −0.39⁎⁎ −1.60⁎⁎ 0.11 −1.81 −1.39 LEC-5_x_TOA 0.005⁎⁎ −0.07⁎⁎ −0.13⁎⁎ 0.05 −0.23 −0.03

Drug Abuse (DAST) 1022 0.06⁎⁎

LEC-5 0.14⁎⁎ 0.11⁎⁎ 0.02 0.06 0.15 0.19⁎⁎ 0.03 0.03 0.03 TOA −0.11⁎⁎ −0.12⁎⁎ 0.03 −0.19 −0.06 LEC-5_x_TOA 0.01⁎⁎ −0.12⁎⁎ −0.06⁎⁎ 0.02 −0.09 −0.03

Alcohol Abuse (PROMIS) 793 0.02⁎⁎

LEC-5 0.05 0.13 0.10 −0.06 0.33 0.26a 0.13 0.01 0.14 TOA −0.12⁎⁎ −0.50⁎⁎ 0.15 −0.80 −0.21 LEC-5_x_TOA 0.002 −0.05 −0.09 0.07 −0.23 0.04

Motivations for Self-Injury (ISAS) 999 0.05⁎⁎

LEC-5 0.10⁎⁎ 0.44⁎⁎ 0.14 0.16 0.72 0.74⁎⁎ 0.19 0.14 0.20 TOA −0.17⁎⁎ −1.13⁎⁎ 0.21 −1.55 −0.71 LEC-5_x_TOA 0.01⁎ −0.07⁎ −0.22⁎ 0.10 −0.41 −0.03

Note. Bolded names in the first column are outcomes; all others are predictors. a p = 0.05. ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

Table 2 Descriptive statistics and bivariate correlations between variables.

Variable M SD LEC-5 TOA PCL-5 PHQ-9 DAST-10 PROMIS ISAS SNAP-NT

LEC-5 2.34 1.97 – TOA 4.12 1.36 −0.16⁎⁎ (0.96) PCL-5 18.33 17.10 0.33⁎⁎ −0.40⁎⁎ (0.96) PHQ-9 6.68 5.58 0.23⁎⁎ −0.42⁎⁎ 0.58⁎⁎ (0.89) DAST-10 0.11 0.15 0.17⁎⁎ −0.15⁎⁎ 0.20⁎⁎ 0.23⁎⁎ (0.71) PROMIS 13.51 5.68 0.07 −0.13⁎⁎ 0.26⁎⁎ 0.24⁎⁎ 0.33⁎⁎ (0.91) ISAS 4.15 9.18 0.13⁎⁎ −0.19⁎⁎ 0.34⁎⁎ 0.40⁎⁎ 0.16⁎⁎ 0.16⁎⁎ (0.96) SNAP-NT 3.04 1.05 0.15⁎⁎ −0.42⁎⁎ 0.36⁎⁎ 0.43⁎⁎ 0.13⁎⁎ 0.09⁎ 0.22⁎⁎ (0.73)

Note. Cronbach's alpha is listed in parentheses along the diagonal. Ns for all correlations except PROMIS range from 965 to 1253; Ns for PROMIS range from 755 to 795. ⁎ p b 0.05. ⁎⁎ p b 0.01.

25H.S. Schroder et al. / Personality and Individual Differences 110 (2017) 23–26

more of a fixed mindset of anxiety, there was a stronger relationship be- tween history of SLEs and the indicators of symptoms and coping strat- egies, compared to those with more of a growth mindset.

When SNAP-NT was added as a covariate in the regression models, three of the four significant interaction terms remained significant; the interaction term predicting depression symptoms did not reach sta- tistical significance (b = −0.09, p = 0.10, ΔR2 = 0.002)3.

5. Discussion

The moderating role of mindsets in understanding the association be- tween challenges and adjustment outcomes has been well established for mindsets of intelligence and personality. Here we tested whether

3 In a final set of analyses, we tested whether mindsets of intelligence or personality also moderated the association between SLE and indicators of adjustment. None of these models yielded significant interaction terms, except for the ones in which drug abuse was the outcome (ps = 0.03 and 0.045 for the SLE × intelligence mindset and the SLE × personality mindset interaction terms, respectively). Thus, the moderating role of mindsets for more clinically relevant variables appears to be specific to the anxiety mindset domain.

mindsets about anxiety would function in a conceptually similar way by moderating associations between history of SLEs and clinical indica- tors of adjustment. Results supported this hypothesis, such that correla- tions were stronger for those with more of a fixed mindset of anxiety.

In addition to its negative connections with psychological symptoms (Schroder et al., 2015, 2016), the growth mindset of anxiety may also be protective against adverse correlates associated with SLEs, which has important implications. First, it suggests decades of theorizing in the mindset domains of intelligence and personality can be translated for clinical purposes to the anxiety domain. In the intelligence domain, growth- and fixed-minded individuals attribute failed performance to lack of effort or to a lack of ability, respectively (Dweck & Leggett, 1988). Future research will need to identify the corresponding attribu- tions relevant to the domain of anxiety. Perhaps anxious individuals with a fixed mindset of anxiety attribute their state anxiety – arising from an unpleasant interpersonal encounter for example - to their core disposition as an “anxious person” rather than the transient dynamics of the particular situation. It will also be important to under- stand how the anxiety mindset fits with other meta-cognitive con- structs such as anxiety sensitivity (Reiss & McNally, 1985) and meta- cognitive beliefs (Wells, 1995). A second implication is that interven- tions designed to promote the malleability of personality in academic

26 H.S. Schroder et al. / Personality and Individual Differences 110 (2017) 23–26

contexts (Yeager et al., 2014) may be adapted to promote a growth mindset of anxiety to specifically target psychological distress and cop- ing strategies. For instance, just as personality interventions consist of web-based tutorials that describe how personality “lives” in the brain and that the brain can change (so personality can change as well), an anxiety mindset intervention may describe how emotion regulation cir- cuits in the brain can be strengthened with practice and effort – resulting in a change in anxiety.

Limitations included the self-reported measurement of SLEs without subjective experience ratings and the cross-sectional design. Nonethe- less, findings provide initial evidence that the growth mindset of anxi- ety buffers relations between SLEs and psychological distress and coping strategies. These results add to those of previous studies that suggest fusing mindset theory with clinical psychology may prove valu- able. All told, understanding how people think about their attributes may provide insights into the processes of risk and resilience.

Acknowledgements

HSS was supported by a National Science Foundation Graduate Re- search Fellowship (NSF Award No. DGE-0802267). JSM was funded by National Institutes of Health K12 grant (HD065879). Any opinions, find- ings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of these funding agencies. The authors declare there are no competing financial interests. Portions of the data were reported at the 2016 Association for Psychological Science Convention in Chicago, IL.

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