Emotion regulation in autism: Reappraisal and suppression interactions

Abstract

Emotion regulation has been proposed to be a transdiagnostic factor in the development and maintenance of psychopathology in the general population, yet the nature of the relationships between emotion regulation strategy use and psychological well-being has not been comprehensively explored in individuals with autism spectrum disorder (ASD). The aim of this study was to assess how the individual differences in self-reported emotion regulation strategy use relate to levels of both positive and negative psychological well-being. In total, 56 individuals with ASD aged 14–24 years (M_age = 18.15; SD_age = 2.30) completed Emotion Regulation Questionnaire, Diagnostic and Statistical Manual of Mental Disorders-5 Generalized Anxiety Disorder Dimensional Scale, Patient Health Questionnaire-9, Warwick-Edinburgh Mental Well-being Scale and Autism-Spectrum Quotient – Short. Individuals were grouped into four clusters based on their Emotion Regulation Questionnaire subscale scores. Individuals in the high suppression and low reappraisal group expressed higher depressive symptoms and lower positive well-being when compared with the low suppression and high reappraisal group. Interestingly, individuals who self-reported using both high suppression and reappraisal expressed relatively high positive well-being and low depression symptoms. We suggest that the maladaptive effect of habitual suppression usage may be buffered by the habitual use of reappraisal, and this interaction between adaptive and maladaptive emotion regulation strategy use has clinical implications.

Keywords

anxiety autism spectrum disorder depression emotion regulation positive well-being

Introduction

Autism spectrum disorder (ASD) is a cluster of neurodevelopmental conditions marked by social and communicative difficulties and the presence of restricted and repetitive behaviours (American Psychiatric Association (APA), 2013). In addition to these core symptoms, the majority of individuals with ASD have at least one comorbid mental health condition (APA, 2013; Croen et al., 2015; Simonoff et al., 2008; Totsika et al., 2011), the most common being anxiety and depression (Hofvander et al., 2009; Lainhart, 1999; Lugnegård et al., 2011; Mazzone et al., 2012).

An impaired ability to regulate emotions has been suggested as one of the key factors in the development and maintenance of affective and behavioural problems in ASD (Mazefsky et al., 2013; Weiss et al., 2014; White et al., 2014). Furthermore, it has been proposed that targeting emotion regulation (ER) impairments through the use of a transdiagnostic ER framework may be an effective approach in treating anxiety and depression in this population (Weiss et al., 2014). However, more empirical work is needed in order to provide a better understanding of the relationship between ER processes and psychological well-being in ASD.

Psychological well-being

Psychological well-being is a complex construct and a number of conceptualizations have been put forward. Historically, two principal approaches to defining well-being are (1) hedonic, where well-being is equated with the attainment of positive emotions and the absence of negative ones (Kahneman, 1999), and (2) eudaimonic, which considers well-being as the realization of individual’s true potential (Waterman, 1993). It has been suggested that eudaimonic well-being includes self-acceptance, personal growth, positive relationships and autonomy (Ryff and Keyes, 1995). An alternative way to categorize psychological well-being is to distinguish the positive aspects of well-being, which include positive mood and energy, and the negative aspects which include negative mood and distress (Karademas, 2007). Signs of negative psychological well-being, such as the presence of anxiety and depression symptomology, have been shown to be negatively associated with positive well-being (Winefield et al., 2012), leading to the suggestion that positive and negative aspects of well-being lie at opposite ends of a continuum. However, as the correlates of negative and positive psychological well-being have been shown to be largely distinct across the life span (Karademas, 2007; Patalay and Fitzsimons, 2016), it is generally agreed that, rather than being on a continuum, positive and negative aspects of psychological well-being are distinct constructs. It is therefore important to consider them separately. With this in mind, we consider the positive as well as negative aspects of psychological well-being in this article, incorporating both the hedonic and eudaimonic approaches.

In ASD research, studies have almost exclusively focused on the negative aspects of well-being, showing that both anxiety and depression are highly prevalent across the life span, with reported frequency of anxiety ranging from 14% to 84% and depression between 17% and 70% (Croen et al., 2015; Hofvander et al., 2009; Kim et al., 2000; Lainhart, 1999; Lugnegård et al., 2011; Mazzone et al., 2012; Murris et al., 1998; Uljarević et al., 2018). Both anxiety and depression can have significant negative impact on individuals with ASD. For example, anxiety symptoms are associated with greater loneliness (White and Roberson-Nay, 2009) and negative automatic thoughts and behavioural problems (Farrugia and Hudson, 2006), which interfere with individual’s quality of life. Depression equally has negative consequences for quality of life, including loss of interest in activities, increased maladaptive behaviours, decrease in adaptive functioning, and appetite and sleep problems (for review, see Stewart et al., 2006).

Considering the equivalent importance of positive and negative aspects of psychological health, it is surprising that positive aspects remain largely ignored in ASD research. Humour is one of the few aspects of positive well-being which has been explicitly addressed in ASD literature (Baron-Cohen, 1997; Emerich et al., 2003; Lyons and Fitzgerald, 2004; Ozonoff and Miller, 1996; Reddy et al., 2002; Samson and Antonelli, 2013). Other research has examined positive psychological well-being through the wider ‘quality-of-life’ construct (e.g. Jennes-Coussens et al., 2006; Kamp-Becker et al., 2010); however, most quality-of-life studies did not use measures that encompassed psychological well-being and, importantly, no research has explicitly examined positive psychological well-being.

Since anxiety and depression are both frequent and have a significant negative impact on individuals with ASD, it is important to reduce their associated symptoms through interventions that target their predictors. However, factors related to the occurrence of internalizing symptoms are currently not well understood in ASD (Uljarević et al., 2016), limiting the development of effective and individually tailored interventions. It has recently been argued that non-ASD-specific traits can serve as risk factors for the development and maintenance of anxiety and depression (Cuthbert and Insel, 2013). One such domain that has been shown to serve as a transdiagnostic risk factor for a range of poor mental health outcomes, particularly anxiety and depression, is emotion dysregulation (Gross and Jazaieri, 2014; McLaughlin et al., 2011). Effective regulation of emotions has been associated with a wide range of other positive outcomes such as physical health, school achievement, employment, social interactions and relationships (see review by Crowell et al., 2015).

ER strategy use and psychological well-being

The conceptual model of ER (Sheppes et al., 2015), which extends the original process model (see Gross, 1998), describes the stages of ER and outlines points along this process where emotion dysregulation can lead to mental health issues. Two prominent strategies for regulating emotions that fit within this model and have been studied extensively in the ER literature are cognitive reappraisal, which involves re-interpreting a situation to change the way one feels about it (Lazarus and Alfert, 1964), and expressive suppression, which involves inhibiting the expression of emotions (Gross and Levenson, 1993). A large body of empirical work has assessed the cognitive, experiential, behavioural and physiological consequences of reappraisal and suppression in non-ASD populations, and shown that suppression is associated with poorer memory for verbally coded information (Richards et al., 2003; Richards and Gross, 2000) and greater sympathetic activation (Gross, 1998).

The habitual use of reappraisal and suppression has been shown to be related to both positive and negative aspects of well-being. Using a questionnaire design, Gross and John (2003) conducted a series of studies that found reappraisers expressed greater positive emotions, had better self-esteem and life satisfaction, were more optimistic and had better interpersonal functioning and eudaimonic well-being, that is, higher levels of environmental mastery, personal growth, self-acceptance and a clearer purpose in life. Furthermore, it was found that at high levels of stress, individuals with high reappraisal ability show fewer depressive symptoms than those with low reappraisal ability (Troy et al., 2010).

Research on the negative aspects of psychological well-being has consistently demonstrated the adverse effects of suppression. Research shows that high suppression use is associated with increased negative emotions (Campbell-Sills et al., 2006; Gross and John, 2003), and in research involving clinical groups, individuals with high levels of anxiety and depression self-report using positive reappraisal less often than non-clinical individuals (Garnefski et al., 2002). Other studies have also provided evidence for the connection between suppression and affective issues (Butler et al., 2003; Ehring et al., 2010; Wenzlaff and Luxton, 2003). Thus, it seems clear that the habitual use of reappraisal for ER to regulate emotions is more conducive to better psychological well-being than using suppression.

Cognitive reappraisal and expressive suppression in ASD

Emotion dysregulation has been suggested to be inherent in ASD (Mazefsky et al., 2013; Mazefsky and White, 2014). Indeed, there appears to be a maladaptive pattern of ER strategy use in ASD, as majority of research has shown that individuals with ASD less frequently use adaptive ER strategies relative to non-ASD individuals (Bruggink et al., 2016; Jahromi et al., 2012; Konstantareas and Stewart, 2006; Rieffe et al., 2011, 2014; Samson et al., 2012, 2015a, 2015b, 2015c). Findings regarding the use of maladaptive ER strategy have been more varied with research showing more (Bruggink et al., 2016; Jahromi et al., 2012; Mazefsky et al., 2014; Samson et al., 2012, 2015b, 2015c), similar (Pouw et al., 2013; Rieffe et al., 2011, 2014; Samson et al., 2015a, 2015b, 2015c) and less frequent (Samson et al., 2015a, 2015c) use in ASD.

Research findings also show a connection between ER strategy use and mental health issues in ASD; across all studies showing higher symptoms of internalizing and externalizing problems in ASD (i.e. Bruggink et al., 2016; Mazefsky et al., 2014; Pouw et al., 2013; Rieffe et al., 2011, 2014; Samson et al., 2015a), the ASD groups reported either more use of maladaptive strategies and/or less use of adaptive ones, with only one exception (see Pouw et al., 2013).

Studies that have specifically examined reappraisal and suppression use in ASD have compared the frequency of strategy use between individuals with and without ASD. Individuals with ASD tend to habitually use less reappraisal (Samson et al., 2012, 2015a, 2015b) and more suppression (Samson et al., 2012, 2015b) although one study did find less and the same amount of suppression used based on self-report and parent report, respectively (Samson et al., 2015a).

Thus far, four studies have examined the relationships between reappraisal and suppression use and psychopathology in ASD (see Bruggink et al., 2016; Cai et al., 2018a, 2018b; Samson et al., 2015a). Samson et al. (2015a) showed that reappraisal, measured by both self- and parent-report using the Emotion Regulation Questionnaire (ERQ; Gross and John, 2003), predicted maladaptive behaviour in a sample of 8- to 20-year-olds. Surprisingly, suppression did not predict maladaptive behaviour. Other studies that have also used the ERQ found that both reappraisal and suppression predicted variance in depression symptoms in adolescents and adults (Cai et al., 2018b), and using a ratio calculated from self-reported ERQ subscales, the ratio was associated with both anxiety and depression symptoms (Cai et al., 2018a). In contrast, using the Cognitive Emotion Regulation Questionnaire (Garnefski and Kraaij, 2001) to measure ER, Bruggink et al. (2016) found that positive reappraisal predicted anxiety but was not associated with depression, a finding that does not align with most previous research in non-ASD populations. These inconsistent findings may be due to the use of different measures and age ranges in these studies. Importantly, no research to date has looked at the relationship between ER and eudaimonic or positive well-being.

ER strategy interactions

The capacity to regulate emotions in a context-specific manner is critical for healthy adaptation. Research has shown that people use multiple ER strategies in a given situation (Aldao and Nolen-Hoeksema, 2013), which requires a repertoire of strategies that the individual can choose from, and the ability to employ them in a flexible way (Bonanno and Burton, 2013). Some individuals may have a repertoire containing more adaptive ER strategies, while others may have more maladaptive ones, but most individuals would have access to a combination of both types of strategies. It is thus likely that the use of maladaptive strategies interacts with adaptive strategy use to have a joint impact on psychological well-being. Indeed, Aldao and Nolen-Hoeksema (2012) found that adaptive strategies had a negative association with a range of psychopathological symptoms, including anxiety, depression and alcohol problems, only when the levels of maladaptive strategies were elevated. Therefore, the effects of adaptive strategy use on mental health can be influenced by maladaptive strategy use.

Only recently have researchers began to examine the interactions between adaptive and maladaptive strategy use in ASD. When ERQ subscales were correlated with symptoms of anxiety and depression individually, only reappraisal correlated with depression symptoms (Cai et al., 2018a). However, when an ER ratio was used instead (suppression scores divided by reappraisal scores), the ratio was strongly associated with depression symptoms and moderately associated with anxiety symptoms. In addition, Cai et al. (2018b) found that individuals who self-reported low habitual use of reappraisal and high use of suppression expressed significantly more depressive symptoms than individuals who reported high use of both strategies. This latter finding demonstrated that the use of an adaptive strategy might be a protective factor for psychological well being in individuals who also use a maladaptive strategy.

Current study

Although researchers have began to examine the relationships between reappraisal, suppression and negative aspects of psychological well-being in individuals with ASD, not much work has assessed the interactions between adaptive and maladaptive ER strategy use in ASD. Furthermore, the relationships between reappraisal, suppression and positive aspects of psychological well-being remain unknown. The first aim in this study was to explore individual differences in patterns of self-reported reappraisal and suppression strategy among older adolescents and young adults with ASD using cluster analytical approach. An additional aim was to examine how individual differences in ER strategy use relate to self-reported levels of positive (encompassing both hedonic and eudaimonic) and negative psychological well-being. Although it was difficult to provide specific hypothesis due to the noted lack of similar research in ASD, based on the findings from non-ASD populations, it was hypothesized that individuals characterized by high reappraisal and low suppression would have better psychological well-being than the ones with low reappraisal and high suppression.

Methods

Participants

The sample consisted of 56 adolescents and young adults with ASD aged 14.42–24.66 years (M_age = 18.15, SD_age = 2.30; 30% females), comprising 19 ASD, 2 autistic disorder, 25 Asperger syndrome, 9 high-functioning autism and 1 pervasive developmental disorder – not otherwise specified. Only individuals who both self-reported having received clinical ASD diagnosis and scored above the suggested autism spectrum quotient (AQ) cut off score of 65 were included. The individuals who self-reported a comorbid diagnosis of intellectual disability and neurological conditions were excluded. No missing data were allowed.

About 87.5% of participants were Caucasian, 5.4% Asian and 5.4% aboriginal. Living arrangements included being with one or both parents (85.7%), another relative (5.4%), housemates (3.6%), partner (1.8%) and on campus (1.8%). With regard to education, 37.5% had completed some high school (of which 76.2% were currently enrolled in either high school or a certificate course), 37.5% had finished high school, 17.9% had completed a certificate course and 5.4% had finished undergraduate studies. A quarter of the participants were employed, primarily part-time.

Procedure

Participants were part of the Longitudinal Study of Australian School Leavers with Autism that forms part of a programme of work funded by the Cooperative Research Centre for Living with Autism (Autism CRC). Ethics approval was obtained from La Trobe University’s Human Ethics Committee, and participants were recruited from state-based autism organizations (e.g. Aspergers Victoria), clinicians and participant databases of autism research organizations. Participants read an information statement about the study, what participation involved, and provided informed consent in writing. Parental consent, in addition to individual consent, was also obtained for individuals younger than 18 years. Once written consent was received via post or email, participants were sent an online survey link using the Qualtrics system through which they completed the survey.

Measures

Autism symptoms

The AQ-Short (Hoekstra et al., 2011) is a 28-item, abbreviated version of the full 50-item screening questionnaire (Baron-Cohen et al., 2001) relating to behaviours associated with ASD. Each item is rated on a 4-point scale from definitely agree to definitely disagree. Correlation with the 50-item AQ has been shown to be very high, with r ranging from 0.93 to 0.95; importantly, a score above 65 had a sensitivity of 0.97 and a specificity of 0.82 for ASD, which is comparable to the full AQ (50 items).

ER strategy use

The Emotion Regulation Questionnaire (ERQ) (Gross and John, 2003) is a 10-item self-report measure designed to assess the frequency of reappraisal (six items, e.g. ‘When I’m faced with a stressful situation, I make myself think about it in a way that helps me stay calm’) and suppression (four items, e.g. ‘I keep my emotions to myself’) use. The questionnaire has previously been used in ASD studies (e.g. Cai et al., 2018a; Samson et al., 2012). Each item is rated on a 7-point scale ranging from strongly disagree to strongly agree. A two-factor structure originally reported by Gross and John (2003) has subsequently been replicated in both exploratory and confirmatory factor analytic studies, with both factors showing adequate internal consistency (Cronbach’s alpha = 0.73–0.76 for the suppression and 0.79–0.82 for the reappraisal subscales; Melka et al., 2011; Moore et al., 2008).

Anxiety symptoms

The Diagnostic and Statistical Manual of Mental Disorders-5 Generalized Anxiety Disorder Dimensional Scale (DSM-5 GAD-D; Knappe et al., 2013) is a norm-referenced, 10-item self-report questionnaire, designed to assess the presence of anxiety symptoms. Each item is rated on a 5-point scale ranging from never to all of the time. The cut off score for clinically significant anxiety is 14 (Beesdo-Baum et al., 2012), with both sensitivity and specificity being 0.73.

Depression symptoms

The Patient Health Questionnaire-9 (PHQ-9; Kroenke et al., 2001) is a 9-item, norm-referenced questionnaire designed to screen for the presence of depression in general and clinical populations. Each item is rated on a 4-point scale ranging from not at all to nearly every day. Scores of 20, 15, 10 and 5 represent severe, moderately severe, moderate and mild depression, respectively. A score of 10 or above had both a sensitivity and a specificity of 0.88 for major depression (Kroenke et al., 2001).

Positive psychological well-being

The Warwick-Edinburgh Mental Well-being Scale (WEMWBS; Tennant et al., 2007) is a 14-item scale of psychological well-being covering both hedonic and eudaimonic aspects of positive well-being including positive affect (feelings of optimism, cheerfulness, relaxation), positive functioning (energy, clear thinking, self-acceptance, personal development, competence and autonomy) and satisfying interpersonal relationships. Each item is rated on a 5-point scale ranging from none of the time to all of the time and all items are worded positively.

Statistical analyses

The k-means cluster analysis was used to classify participants according to their pattern of reappraisal and suppression subscale scores on the ERQ. As the measurement units for the two ERQ subscales did not differ, the two variables were not standardized. The first step was to determine the optimal number of clusters by plotting the within-group sum of squares for each cluster by applying the k-means procedure using R version 3.3.0 and identify the elbow in the resulting scree plot (see Everitt and Hothorn, 2006: 251 for the R code used). The k-means cluster analysis was then conducted in SPSS version 21 for Mac with the default 10 iterations, and participants were grouped into clusters.

Further analyses were conducted to assess the differences between cluster groups in terms of age, gender, ASD traits, symptoms of anxiety and depression, and positive well-being. As the age, ASD traits and depression scores across clusters were not normally distributed, the Kruskal–Wallis tests were used for cluster comparisons for these variables, Mann–Whitney U tests were used to further compare the highest depression group with the lowest depression group (extreme groups), and r was calculated as a measure of effect size. A chi-square test for independence was used to assess the association between gender and cluster membership. Anxiety and positive well-being scores across clusters were normally distributed; hence, one-way between-group analysis of variance was conducted, effect size calculated using eta squared, and post hoc comparison of extreme groups completed via Tukey’s honestly significant difference (HSD) test. Assumptions of homogeneity of variance were accounted for using the Welch test as a robust test of equality of means.

Results

Descriptive statistics and Cronbach’s alpha for the AQ-Short, ERQ-S, ERQ-R, DSM-5 GAD-D, PHQ-9 and WEMWBS can be found in Table 1.

Table 1.

Descriptive statistics of measures.

	Mean (SD)	Range	Cronbach’s alpha
AQ-Short	77.02 (9.35)	65–104	0.76
ERQ-S	15.79 (5.61)	5–28	0.84
ERQ-R	23.23 (6.40)	6–37	0.83
DSM-5 GAD-D	13.89 (9.03)	0–35	0.92
PHQ-9	7.68 (6.38)	0–26	0.88
WEMWBS	43.48 (8.90)	14–56	0.90

SD: standard deviation; AQ-Short: Autism-Spectrum Quotient – Short; ERQ-S: Emotion Regulation Questionnaire – Suppression; ERQ-R: Emotion Regulation Questionnaire – Reappraisal; DSM-5 GAD-D: Diagnostic and Statistical Manual of Mental Disorders-5 Generalized Anxiety Disorder Dimensional Scale; PHQ-9: Patient Health Questionnaire-9; WEMWBS: Warwick-Edinburgh Mental Well-being Scale.

The severity of depressive symptoms based on PHQ-9 scores ranged from minimal (37.5%), mild (26.8%), moderate (21.4%), moderately severe (8.9%), to severe (5.4%). A third of our sample (35.7%) reached the PHQ-9 criterion (score of 10) for major depression and 41.7% reached the cut-off criterion (score of 14) for anxiety on the DSM-5 GAD-D.

The scree plot was used for the elbow test to determine the number of clusters based on the reappraisal and suppression subscale scores. Based on the scree plot (shown in Figure 1), four clusters were chosen for the k-means analysis.

Figure 1.

Scree plot based on cognitive reappraisal and expressive suppression subscale scores.

Figure 2 displays the scatterplot of participants based on reappraisal and suppression scores, grouped into their clusters.

Figure 2.

Scatter plot of individual scores on cognitive reappraisal and expressive suppression subscale scores by cluster.

Based on the distribution of reappraisal and suppression scores, the four participant clusters were classified as (1) high suppressors and high reappraisers (HSHR), (2) high suppressors and low reappraisers (HSLR), (3) low suppressors and high reappraisers (LSHR) and (4) low suppressors and low reappraisers (LSLR). Descriptive information on suppression and reappraisal scores for each cluster is shown in Table 2.

Table 2.

Suppression and reappraisal subscale scores by cluster.

Cluster groups, mean (SD)
	HSHR (n = 24)	HSLR (n = 9)	LSHR (n = 15)	LSLR (n = 8)
Suppression	19.46 (3.75)	19.89 (2.67)	11.00 (2.72)	9.13 (3.40)
Reappraisal	25.29 (2.76)	14.89 (4.23)	28.80 (3.43)	16.00 (4.78)

SD: standard deviation; HSHR: high suppressors and high reappraisers; HSLR: high suppressors and low reappraisers; LSHR: low suppressors and high reappraisers; LSLR: low suppressors and low reappraisers.

The cluster groups did not differ significantly in age (χ²(3, 55) = 0.71, p = 0.871), gender (χ²(3, 56) = 1.49, p = 0.685), AQ-Short score (χ²(3, 56) = 7.32, p = 0.062) or DSM-5 GAD-D score (F(3, 52) = 1.95, p = 0.133). The groups differed significantly in PHQ-9 score (χ²(3, 56) = 10.45, p = 0.015) and WEMWBS score (F(3, 17.95) = 14.19, p < 0.001; large effect size: 0.37).

Distributions of PHQ-9, DSM-5 GAD-D, WEMWBS and AQ-Short scores by clusters are presented in Figure 3(a), (b), (c) and (d), respectively. As can be seen from the violin graphs, the participants in LSHR had the lowest symptoms of anxiety and depression, and the highest levels of positive well-being. On the other hand, the participants in HSLR had the highest symptoms of anxiety and depression, and the lowest levels of positive well-being. The mean levels of anxiety and depression symptoms, and positive well-being are similar for HSHR and LSLR, and are situated between the means for the other two clusters. The distribution of scores on the AQ-Short by clusters (see Figure 3(d)) shows a similar pattern to anxiety scores and the group comparisons using Kruskal–Wallis test approached significance. The AQ-Short mean for the HSLR cluster was the highest compared to the other three clusters.

Figure 3.

(a) PHQ-9, (b) DSM-5 GAD-D, (c) WEMWBS and (d) AQ-Short scores by clusters.

Post hoc tests using the Mann–Whitney U test for PHQ-9 found that the HSLR group had significantly higher levels of self-reported depression (U = 31, z = –2.20, p = 0.028, r = 0.45) and significantly lower levels of positive well-being (mean difference via the Tukey’s HSD test = 16.11, p < 0.0001) than individuals in the LSHR group.

Discussion

This study examined the relationship between anxiety, depression and psychological well-being, and patterns of ER strategy use in a sample of older adolescents and young adults diagnosed with ASD. A substantial number of participants in this study had high levels of anxiety and depression, with 36% meeting the clinical cut-off for major depression and 42% meeting the cut-off for clinically significant anxiety. These frequencies for anxiety and depression are around the mid-point of rates reported in previous studies with individuals with ASD, which vary from 13.6% to 84% for anxiety (Uljarević et al., 2016; Van Steensel et al., 2011; White et al., 2009) and 15% to 70% for depression (Hofvander et al., 2009; Lainhart, 1999; Lugnegård et al., 2011; Mazzone et al., 2012; Sterling et al., 2008; Uljarević et al., 2018).

Based on the distribution of the reappraisal and suppression scores, the four identified cluster groups were classified as (1) high suppressors and high reappraisers (HSHR), (2) high suppressors and low reappraisers (HSLR), (3) low suppressors and high reappraisers (LSHR), (4) low suppressors and low reappraisers (LSLR). The clusters did not differ significantly in age, gender or ASD traits.

ER and negative psychological well-being

The main aim of this study was to explore how individual differences in the pattern of reappraisal and suppression relate to the variability in the self-reported levels of negative and positive psychological well-being. In terms of negative aspects of well-being, the identified groups differed in levels of depression and, as hypothesized, the HSLR group had higher levels of depression when compared with the LSHR group.

Our results align with research findings in non-ASD populations showing that individuals with higher levels of depressive symptoms self-report greater use of suppression and lower use of reappraisal (Garnefski et al., 2002; Joormann and Gotlib, 2010). Our results also support Samson et al.’s (2015a) work that showed the low use of reappraisal predicted maladaptive behaviour, as well as Cai et al’s (2018b) findings that the use of suppression and reappraisal predicted variance in depression symptoms.

However, our findings were not consistent with Bruggink et al.’s (2016) results, which found no association between reappraisal and depression in a sample of ASD adults. This inconsistency may be due to the different measures of reappraisal used; the 4-item positive reappraisal subscale of the Cognitive Emotion Regulation Questionnaire (Garnefski and Kraaij, 2001), used by Buggink and colleagues is less emotion focused (example item: ‘I think that the situation also has its positive sides’), and, as a result, it is worded quite differently to the 6-item reappraisal subscale of the ERQ ( ‘When I want to feel more positive emotion, I change the way I’m thinking about the situation’). In addition, as the focus of research is ER, it is imperative that the measures used contain items that explicitly tap into both the emotion and the regulation strategy. Even though the reappraisal strategy is cognitively based, the purpose of implementing the strategy is to modify the emotion; hence, the missing emotion-related wording in the items used in the Cognitive Emotion Regulation Questionnaire, along with the primary focus on negative or unpleasant events in the study by Garnefski and Kraaij (2001), may have resulted in their lack of significant findings.

Finally, although the group differences in anxiety did not reach significance, the pattern nevertheless resembled that of depression scores, with the LSHR group showing lower scores overall.

ER and positive psychological well-being

In addition to exploring negative aspects as reported above, this study provides a significant contribution to the existing literature in ASD by focusing on positive aspects of psychological well-being (incorporating both hedonic and eudaimonic aspects). The identified groups differed in positive well-being and, as hypothesized, the LSHR group had significantly higher levels of positive psychological well-being when compared with the HSLR group. This finding is in line with ER research in the general population. For example, Gross and John (2003), also using ERQ, found that reappraisers reported higher positive well-being than suppressors, as assessed by levels of optimism, self-esteem and life satisfaction.

Our findings demonstrate, for the first time, that individuals with ASD who self-reported using both high suppression and reappraisal expressed relatively high positive well-being and relatively low levels of depression symptoms; these individuals expressed better well-being than high suppressors only and lower positive and higher negative aspects of well-being than high reappraisers only. This finding is contrary to most ER research in non-ASD populations, suggesting that suppression is a putatively maladaptive strategy for managing emotions. Our results suggest a possibility that the effect of maladaptive strategy use (suppression) on mental health may be buffered by the high use of adaptive strategy (reappraisal).

Research has traditionally examined the use of adaptive and maladaptive ER strategies separately. Our findings emphasize the need to go beyond the separate assessment of ER strategies and consider within-individual interactions. This approach is in line with more recent research in non-ASD populations (e.g. Aldao and Nolen-Hoeksema, 2013). Although the study design limits our ability to understand the participants’ capacity to implement ER strategies across specific contexts, the finding reported here aligns with the view that healthy adaptation involves the flexible use of strategies that are suitable for specific situational demands (Aldao et al., 2015; Bonanno and Burton, 2013; Sheppes et al., 2014).

ER flexibility and clinical implications

Evidence from recent research in non-ASD populations indicates that the inflexible reliance on particular ER strategies, even if they are generally thought to be adaptive, and the inability to select from a repertoire of strategies in a context-sensitive manner, has negative consequences. First, even though reappraisal has generally been shown to be associated with better mental health and well-being, this relationship occurs only in the context of stress that is uncontrollable (Troy et al., 2010). In controllable stressful situations, higher reappraisal was associated with poorer psychological health. As a side note, individuals with ASD may experience more stress that is uncontrollable due to the nature of the condition. Similarly, even though the majority of research shows suppression to be associated with poorer mental and physical well-being, suppression may be useful in certain situations. For example, Butler et al. (2003) suggested that the use of suppression may be unproblematic, and potentially even beneficial, in situations where it serves to disrupt negative emotion escalation and increases interpersonal distance when distance is desired. Thus, the key is implementing suppression flexibly and sparingly. Empirically, Bonanno et al. (2004) demonstrated the linkage between successful adaptation and the ability to flexibly enhance or suppress emotional expression. Using a sample of newly enrolled New York college students soon after the September 11th incident, participants who were better able to both enhance and suppress emotional expression, as indicated by their higher overall flexibility scores, self-reported less distress by the end of their second year.

A comprehensive review by Kashdan and Rottenberg (2010) suggested that the main feature of mood and anxiety disorders is a stereotyped way of responding to situations (i.e. psychological inflexibility). They further proposed that one of the key factors that impact psychological flexibility is executive functioning. Interestingly, empirical research has demonstrated that reappraisal is associated positively with aspects of executive function such as working memory capacity and set-shifting costs (McRae et al., 2012). One possible hypothesis is that more individuals with ASD have difficulties with executive function when compared to individuals without ASD, resulting in higher prevalence of emotion dysregulation and maladaptive pattern of ER strategy use in the ASD population. Indeed, studies have demonstrated executive dysfunction in ASD (see review by O’Hearn et al., 2008). Despite studies showing impairments across different aspects of executive function in ASD (Ozonoff and Jensen, 1999; Rinehart et al., 2001), no research to date has explicitly assessed mechanisms underlying the interplay between executive function and emotion dysregulation in ASD. Here we suggest that impairments in attention-shifting and working memory might be particularly important to be considered as factors impacting the ability of individuals with ASD to regulate their emotions in a flexible manner.

In addition to providing evidence for the relationship between patterns of ER strategy use and psychological well-being, the current findings have implications for the design of ER interventions in ASD that are tailored to specific profiles of individuals. Effective reappraisal appears to be a protective factor against poor psychological well-being in our sample of young ASD participants. Therefore, interventions targeting the up-skilling of reappraisal capacity could increase well-being in this population. Indeed, preliminary findings evaluating the effectiveness of an ER therapy that involves increasing the capacity of individuals to reframe their situation or emotion (Mennin and Fresco, 2014) showed symptom improvements in a sample of clinical patients with affective disorders (Mennin et al., 2015). In addition, emotional competence training has been shown to improve a range of outcomes beyond psychological well-being, including physical well-being, social relationships and employability (Nelis et al., 2011). Not everyone diagnosed with ASD has emotion dysregulation, and identifying individuals at risk of developing affective conditions is important. One of the benefits of the individual differences approach adopted here via the cluster analytic approach is the identification of groups that might be at risk of developing mental health conditions and may best benefit from targeted interventions (Clatworthy et al., 2005).

Limitations and future directions

While this study provides insight into how adaptive and maladaptive ER strategies may interact and into the relationships between this interaction and negative and positive psychological well-being, a few study limitations are important to note. Due to the online survey design, we were unable to assess the cognitive ability of participants, or to independently verify participant’s diagnostic status via established diagnostic instruments such as the Autism Diagnostic Interview – Revised or Autism Diagnostic Observation Schedule. However, it is important to point out that none of the participants included in this study reported a diagnosis of intellectual disability (ID), and the majority had either completed high school or were currently enrolled in a secondary education institution, making it unlikely that ID was present. In addition, all participants included in this research scored above the AQ-Short cut off score for ASD that has good sensitivity and specificity (see the section ‘Measures’).

The cross-sectional design of this study, although allowing us to explore the inter-relationships between ER and psychological well-being, does not allow to infer causal relationships. In the non-ASD population, findings have been inconsistent, with some studies showing that emotion dysregulation predicts depression (e.g. McLaughlin et al., 2011; Wenzlaff and Luxton, 2003), whereas others show that depressive symptoms precede the habitual use of suppression (e.g. Larsen et al., 2013). Future research should assess this relationship via longitudinal designs to determine the causality and identify potential risk factors for developing mental health disorders in these individuals. Such information will be important for the design of future interventions.

In this study, we specifically focused on two ER strategies, suppression and reappraisal, given the strong evidence base for their relationship with affective symptoms in general populations (e.g. Garnefski et al., 2002; Gross and John, 2003). However, strategies such as rumination have also been implicated in the maintenance of anxiety and depression symptoms in non-ASD populations (Yook et al., 2016). Therefore, it will be important to further characterize the interactions between adaptive and maladaptive ER strategies by the inclusion of a range of other strategies over and beyond what was studied here.

In using self-reported data, we were unable to capture contextual information when using ER, or the individuals’ capacity to flexibly implement the two ER strategies. Based on the summary of contemporary ER findings in the non-ASD populations, it is evident that psychological flexibility is critical for well-being, including ER flexibility. Leveraging research approaches such as observational methods or experience sampling methodology that capture contextual information in real time and allow researchers to derive a flexibility marker may help us gain more understanding of the role of ER flexibility in healthy psychological well-being.

Conclusion

This is the first study to explore the individual differences in patterns of adaptive ER strategy (reappraisal) and maladaptive strategy (suppression) use among youths with ASD via cluster analysis. Using a within-individual interactions approach to assess the relationships between ER strategy use and positive (hedonic and eudaimonic) and negative (anxiety and depression) psychological well-being, our results suggested that the use of reappraisal buffered the effect of suppression use on psychological well-being. Flexible use of ER strategies is important in maintaining and improving psychological health. This ability for ER flexibility may be limited in the ASD population due to executive function deficits; however, further research is necessary to unravel the mechanisms underlying the relationships between ER flexibility and psychological well-being in ASD. Nevertheless, these findings can inform the development of interventions for improving both positive and negative aspects of well-being in ASD.

Supplementary Material

Lay_Abstract, AUT774558_Lay_Abstract – Emotion regulation in autism: Reappraisal and suppression interactions

Lay_Abstract, AUT774558_Lay_Abstract for Emotion regulation in autism: Reappraisal and suppression interactions by Ru Ying Cai, Amanda L Richdale, Cheryl Dissanayake, Julian Trollor and Mirko Uljarević in Autism

Footnotes

Acknowledgements

The authors acknowledge the financial support of the Cooperative Research Centre for Living with Autism (Autism CRC), established and supported under the Australian Government’s Cooperative Research Centres programme. We would also like to thank all those who participated in the Longitudinal Study of Australian School Leavers with Autism from which these data are drawn.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study was supported by Cooperative Research Centre for Living with Autism (Autism CRC) under Grant Number 3.016 RC.

ORCID iD

Ru Ying Cai

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