Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: Eat Behav. 2021 Sep 4;43:101561. doi: 10.1016/j.eatbeh.2021.101561

Ability to Tolerate Distress Moderates the Indirect Relationship between Emotion Regulation Difficulties and Loss-of-Control Over Eating via Affective Lability

Emily K Burr 1, Robert D Dvorak 2, Brittany L Stevenson 3, Lauren M Schaefer 4, Stephen A Wonderlich 5
PMCID: PMC8629940  NIHMSID: NIHMS1739895  PMID: 34517279

Abstract

Introduction:

Loss-of-control eating (LOCE), inability to refrain from or cease eating, may contribute to significant distress and dysfunction, yet research is lacking specificity on vulnerabilities contributing to LOCE as an independent construct. Preliminary evidence indicates potential roles of distress tolerance, emotion regulation, and affective lability, but the relationship between these variables and LOCE has been under-assessed.

Material and Methods:

A sample (N = 3968) consisting of university students completed an assessment of pathological eating and affiliated affective vulnerabilities. A latent variable structural equation model (SEM) was generated to predict LOCE by way of affective lability and indirectly, emotion regulation difficulties and low distress tolerance, controlling for general eating pathology.

Results:

Findings indicated a significant direct effect of affective lability on LOCE, as well as significant indirect effects of emotion regulation difficulties and distress tolerance on LOCE, via affect lability. Additionally, distress tolerance moderated the relationship between emotion regulation difficulties and affective lability, such that lower ability to tolerate distress strengthened the relationship and higher distress tolerance capability attenuated it.

Discussion:

Findings suggest an influence of distress tolerance on the relationship between poor emotion regulation and affective lability, which in turn may affect LOCE. Clinical implications and suggestions for future research are discussed.

Keywords: eating behavior, binge eating, loss-of-control eating, affective lability, distress tolerance, emotion regulation

1.0. Introduction

Binge eating is a transdiagnostic symptom of binge-eating disorder (BED), bulimia nervosa (BN), and anorexia nervosa binge/purge subtype (American Psychiatric Association, 2013) and is common among individuals with obesity (Palavras et al., 2013). A binge eating episode is characterized by presence of overeating (i.e., eating an amount of food in a discrete period of time (e.g., two hours) that is larger than most would eat in that same period of time under similar circumstances), accompanied by a sense of loss of control over eating (American Psychiatric Association, 2013). An increasing literature base evinces the perception of loss-of-control eating (LOCE), even in the absence of overeating, may be the more clinically-relevant symptom (Latner et al., 2014). A large review concluded that individuals in both clinical and non-clinical samples are more likely to consider their own eating episodes to be a “binge” based on the degree of LOCE experienced, rather than objective amount of food eaten (Latner & Clyne, 2008). Further, LOCE demonstrates stronger associations with clinical impairment and comorbidity (Bloomquist et al., 2014; Colles et al., 2008) and may be a prodromal phase of disorders characterized by binge eating (Tanofsky-Kraff et al., 2020). Additionally, LOCE has been tied to other eating disorder pathology (Brownstone, 2017; Latner et al., 2007) and greater severity of emotional pathologies (e.g. anxiety, depression, distress; Latner et al., 2007). Thus, understanding the underlying characteristics that place individuals at risk for LOCE is an important avenue for public health research.

Research examining predictors of binge eating highlights a number of constructs that are likely to have relevance to LOCE. Affective lability (i.e., the tendency to experience intense and highly fluctuating emotions over time; Oliver & Simons, 2004) appears to be related to binge eating (Anestis et al., 2009). Ecological momentary assessment (EMA) protocols, which are able to examine real-time temporal associations between experiences in the natural environment (e.g., heightened negative affect preceding LOCE; Stevenson et al., 2018) have shown that greater affective lability is associated with a higher number of binge-eating episodes (Anestis et al., 2010; Yu & Selby, 2013) and on days when individuals engage in an LOCE episode, they tend to exhibit greater emotion instability (Selby et al., 2012). Additionally, there may be greater fluctuations in negative emotions on days when one loses control over eating, even though global trajectory of affect may not differ between LOCE and non-LOCE days (Stevenson et al., 2018). Findings from cross-sectional research has also revealed a strong association between fluctuations in negative affect and LOCE. For example, in one meta-analysis, Haedt-Matt and Keel (2011) found that across multiple cross-sectional studies, 60 – 100% of individuals who met criteria for BN or BED reported negative affect preceded their binge eating episodes. Affect regulation models of binge eating may help to explain this association. Broadly, these models posit that individuals binge eat in response to distressing emotions to regulate those emotions (Polivy & Herman, 1993). Support for affect regulation models is mixed. Findings robustly suggest negative affect increases before binge eating (Alpers & Tuschen-Caffier, 2001; Berg et al., 2013; Smyth et al., 2007), although evidence for post-binge decreases in negative affect are inconsistent (Crosby et al., 2009; Goldschmidt et al., 2012; Selby et al., 2012; Stevenson et al., 2018) and may be significantly influenced by statistical methods (Berg et al., 2017). Deficits in emotion regulation may give rise to affective lability, and ultimately contribute to eating disturbances (Contardi et al., 2018; Lavender et al., 2015). Therefore, it is theoretically possible that emotion regulation difficulties are associated more strongly with eating disturbances through the vulnerability of greater affective lability. Emotion regulation is defined as recognition, comprehension, and control over ones emotions (Gratz & Roemer, 2004), as well as use of strategies to influence/control their responses (Gross, 2002). Emotion regulation deficits are associated with the use of maladaptive coping strategies, including binge eating. For example, in women who binge eat, LOCE is correlated with greater emotion regulation difficulties compared to women who overeat without a sense of loss of control (Racine & Horvath, 2018). An EMA study among young women found that difficulties regulating ones emotions interacted with fluctuations in negative affect to predict binge eating (Kukk & Akkermann, 2017). Furthermore, a recent review of BED and obesity literature not only identified negative emotions are a robust trigger for binge eating, but studies that isolated the construct of LOCE reported greater loss of control after induction of negative emotions (Leehr et al., 2015), suggesting poor ability to regulate such emotions may be particularly salient to LOCE. However, emotion regulation difficulty does not generally occur in isolation. An often co-occurring vulnerability is inability to tolerate distress (Linehan, 2014).

Low distress tolerance is common among individuals with emotion regulation difficulties (Jeffries et al., 2016; Van Eck et al., 2017) and is associated with the use of maladaptive emotion regulation strategies (Jeffries et al., 2016). Although the potential influence of distress tolerance on emotion regulation difficulties is underrepresented in literature to-date, improving distress tolerance is associated with concurrent improvements in emotion regulation and emotional eating (Juarascio et al., 2020). This suggests a potential interactive effect between these variables, particularly, a protective effect of improving distress tolerance. Distress tolerance (i.e. ones perceived ability to withstand negative emotional or other aversive states, and the degree to which one is impacted by and responsive to negative emotions in an uncontrolled way; Simons & Gaher, 2005) may play a role in LOCE. Poor distress tolerance is characteristic of multiple forms of maladaptive behaviors associated with heightened negative affect (Leyro et al., 2010). The role of poor distress tolerance in LOCE as an isolated construct is currently under-represented, although low distress tolerance is implicated in problematic eating behavior. For example, emotional eating is associated with low distress tolerance (Kozak & Fought, 2011), as are bulimic symptoms including binge eating (Anestis et al., 2007; Corstorphine et al., 2007). Moreover, among gay and bisexual women LOCE is correlated with low distress tolerance both within and outside the context of binge eating (Bayer, 2014). Low distress tolerance may be particularly influential when individuals have high affective lability, suggesting an influence of distress tolerance ability on other established vulnerabilities related to LOCE. For example, in women diagnosed with bulimia nervosa, low ability to tolerate distress correlated with greater fluctuations in negative affect, which can result in LOCE (Anestis et al., 2007).

Altogether, preliminary evidence suggests a potential relationship between affective lability, emotion regulation, distress tolerance, and LOCE. As described above, individuals with an impaired ability to regulate highly variable affect may be more likely to engage in LOCE as an emotion regulation strategy. Therefore, it was hypothesized there will be an indirect relationship between emotion regulation difficulties and LOCE by way of affective lability in this cross-sectional study. Given the strong relationship between emotion regulation difficulties and ability to tolerate distress, it was additionally hypothesized that distress tolerance ability moderates the association between emotion regulation difficulties and affective lability. In the present study, we investigate these hypotheses via a large cross-sectional sample.

2.0. Material and Methods

2.1. Participants and Procedure

University students (n = 3968, Mage = 19.93, 65.09% female) completed an online survey of eating pathology and associated psychological vulnerabilities, as a screener for a project on LOCE in real time via an EMA protocol. Participants were recruited from a large Southeast United States university and considered ineligible if they were 1) under 18 years of age or 2) not fluent in English.

2.2. Measures

Demographic Variables including age, sex, and race/ethnicity were self-reported.

General Eating Pathology was assessed using the 28-item version of the Eating Disorder Examination Questionnaire (EDE-Q) (Fairburn & Beglin, 2008). Participants indicate how many days in the past 28 days they have engaged in eating-disordered behavior and cognitions (e.g. “on how many of the past 28 days have you had a definite fear that you might gain weight?”) on a Likert-type scale ranging from 0 (“no days) to 6 (“every day”). The EDE-Q is categorized into 4 subscales and has a global score obtained by taking the mean of each of the subscales’ mean scores. Only the global score was utilized to assess for overall eating pathology. The possible range of the global score is 0 to 6. Scale reliability for this sample was high (Cronbach’s α = .91). A latent variable was comprised of the four EDEQ subscales.

Loss-of-Control Eating was measured using the Loss of Control over Eating Scale (LOCES) (Latner et al., 2014), a 24-item assessment of losing control over one’s eating (e.g. “I continued to eat past the point where I wanted to stop”) across three domains and as an overall construct. The three factors include behavioral aspects (e.g., “I kept eating although I was no longer hungry”), cognitive/dissociative aspects (e.g., “I could not concentrate on anything other than eating”) and positive/euphoric aspects (e.g., “While eating, I felt a sense of relief or release”). Items are statements rated using a Likert-type scale ranging from 1 (“never”) to 5 (“always”) based on past 28-day frequency and the mean score constitutes the full-scale score, with a possible range of 1 – 5. The LOCES has good internal consistency and convergent validity, and has been validated in undergraduate samples (Latner et al., 2014; Stefano et al., 2016). Scale reliability for this sample was high (Cronbach’s α = .97). Unlike the other measures utilized in this study, the LOCES does not have clear subscales that encapsulate all items, and thus 4 parcels of six randomly selected items were formed in order to construct the latent LOCES variable.

Distress Tolerance was assessed via the Distress Tolerance Scale (DTS) (Simons & Gaher, 2005), a 15-item self-report assessment of perceived distress intolerance (e.g. ”I can’t handle feeling distressed or upset”). DTS items are rated on a 5-point Likert scale ranging from 1 (“strongly agree”) to 5 (“strongly disagree”) in terms of ability to tolerate distressing affect, cognitions, and situations. Higher mean scores on the DTS indicate greater distress tolerance, with a possible range of 1–5. The DTS has good internal consistency and construct validity, and has been validated in undergraduate samples (Simons & Gaher, 2005). Scale reliability for this sample was high (Cronbach’s α = .94). A latent variable was comprised of the four DTS subscales.

Emotion Regulation was evaluated via the Difficulties in Emotion Regulation Scale (DERS) (Gratz & Roemer, 2004). The DERS is a 36-item self-report assessment of emotion regulation difficulties across 6 domains (lack of emotional awareness, lack of emotional clarity, non-acceptance, impulsivity when distressed, lack of access to functional coping strategies, and difficulty accomplishing goals when distressed) and yields a total score and subscale scores. Statements (e.g. “When I’m upset, I have difficulty controlling my behaviors”) are rated based on frequency on a 5-point Likert-type scale ranging from 1 (“almost never, 0–10%”) to 5 (“almost always, 91–100%”), and higher scores indicate greater difficulty regulating emotions globally and across the 6 domains. The possible range of total scores is 36 – 180. DERS total score scale reliability for this sample was high (Cronbach’s α = .94). A latent variable was comprised of the six DERS subscales.

Affective Lability was assessed using the 18-item version of the Affective Lability Scale (ALS) (Oliver & Simons, 2004), an assessment of emotional instability with 3 subscales tapping domains anxiety/depression, depression/elation, and anger. ALS items (e.g., “one minute I can be feeling Ok, and then the next minute I’m tense, jittery, and nervous”) are rated on a 4-point Likert-type scale ranging from 1 (“very undescriptive of me”) to 4 (“very descriptive of me”), with higher scores indicating greater affective lability. The ALS full scale score is the mean of all item responses, with a possible range of 1– 4. The ALS has good internal consistency and convergent validity, and has been validated in undergraduate samples (Oliver & Simons, 2004). ALS full scale score scale reliability for this sample was high (Cronbach’s α = .95). A latent variable was comprised of the three ALS subscales.

2.3. Data Cleaning and Preparation

This dataset had observations from n = 4,367 participants. However, n = 195 provided no data across any survey items, and were thus removed. The survey had four validity check items. Individuals that failed on 3 or more validity items were also excluded (n = 68). Finally, there were n = 149 non-students in the dataset. These observations were removed to ensure a more homogenous sample. This resulted in a final analysis sample of n = 3968. All items were examined for skewness and kurtosis, residuals were examined for heteroskedasticity. Standardized residuals and Cook’s d indicated no influential observations and no observations exerting excessive leverage. Among those who completed the measures, missing data was low, ranging from 0–1.17%. For data missing within a measure, multiple imputation was used to impute missing values. As long as there was a minimum of one response in a scale, we used all available data to impute responses to the remainder of the scale using the mean response across 10 pooled imputed datasets. Within scales, with at least one response, missing data ranged from 7.07% (DERS) to 5.20% (ALS). Greater than 50% of the scale was present for 99.55% (DERS) to 99.74% (ALS). A number of individuals were missing entire measures. This ranged from 6.23% (n = 251; EDEQ) to 20.82% (n = 839; LOCES). These missing observations were handled via full information maximum likelihood with robust standard errors in Mplus 8.5 (Muthén & Muthén, 2020). Age predicted missingness on the loss of control eating measure (b = −0.17, p < .001) indicating that older individuals were less likely to be missing data on the outcome variable. No other variables predicted missingness.

2.4. Analysis Overview

We first specified our measurement model to test the measurement of our latent constructs. To test our hypotheses, we specified a latent variable structural equation model. For each latent variable, the subscales were specified as observed variable indicators. Loss of control over eating (LOCES) was specified as the primary outcome variable. To isolate the model in the context of loss of control eating, general eating pathology (measured via the EDEQ) was included as a model covariate on the LOCES outcome. Difficulties in emotion regulation and distress tolerance were the primary predictor variables. Affect lability served as the mediator between the two exogenous predictors (difficulties in emotion regulation and distress tolerance) and the outcome (loss of control eating). Age was added as a covariate given its association with missingness on LOCE.

After specifying the primary model, modification indices were examined to determine additional, non-hypothesized, associations that may correlate. Only associations with sound theoretical rationale were added. After fitting the initial model, we added a latent variable interaction between difficulties in emotion regulation and distress tolerance to test our final hypothesis. Latent variable interactions require numerical integration, and thus do not provide fit indices. To ensure that the addition of this interaction improves the overall model, we utilize a Clark’s distribution free test of the model loglikelihoods to compare the individual loglikelihoods from the model without the interaction to the model with the interaction. Next, we calculate the simple slopes of difficulties of emotion regulation at high (+1SD) and low (−1SD) levels of distress tolerance. Finally, we examine direct, indirect, and conditional associations between difficulties in emotion regulation and loss of control eating, via affect lability, at mean, low, and high levels of distress tolerance.

3.0. Results

3.1. Descriptive and Bivariate Statistics

The final sample consisted of 3968 participants. Approximately 34.89% of the sample reported their sex as male (n = 1384), 65.09% identified as female (n = 2582), and .03% of participants identified as other/ unreported (n = 2). Regarding gender identity, 35.27% of the sample identified as a man (n = 1399), 63.83% identified as a woman (n = 2532), 0.40% identified as gender fluid (n = 16), and 0.50% identified as other (n = 20). Regarding race, the sample was predominantly White, 74.40% (n = 3968), followed by 13.46% Black (n = 534), 11.32% Asian (n = 449), 1.31% Native American (n = 52), 0.60% Pacific Islander (n = 24), and 4.18% Other (n = 166). In regard to ethnicity, 28.29% of the sample identified as Hispanic (n = 1222), 71.67% identified as non-Hispanic (n = 2844), and 0.05% did not report ethnicity (n = 2). See Table 1 for additional descriptive statistics and bivariate correlations.

Table 1.

Descriptive Statistics and Bivariate Correlations

Descriptive Statistics Bivariate Correlations
% Mean SD 1. 2. 3. 4. 5. 6.
Demographic Variables
 1. Age -- 19.931 4.000 --
 2. Sex (female) 65.090 -- -- .020 --
Eating Pathology Covariate
 3. EDEQ -- 1.605 1.439 .125** .266** --
Psychological Vulnerabilities
 4. DERS -- 87.130 27.123 −.056** .060** .370** --
 5. DTS -- 3.285 0.951 −.0036 −.107** −.260** −.530** --
 6. ALS -- 2.011 0.731 .021 .192** .493** .574** −.393** --
Outcome Variable
 7. LOCES -- 1.99 0.821 .092** .164** .666** .399** −.259** .537**
Open in a new tab
*

indicates significance at the p < .05 level

**

indicates significance at p < .001

EDEQ: Eating Disorder Examination Questionnaire; DERS: Difficulties in Emotion Regulation Scale; DTS: Distress Tolerance Scale; ALS: Affect Lability Scale; LOCES: Loss-of-Control Over Eating Scale

3.2. Measurement Model

We first specified a measurement model. The initial measurement model showed relatively poor fit to the data: χ2 (179) = 4859.42, p < .001, Confirmatory Fit Index (CFI) = .91, root mean square error of approximation (RMSEA) = .08, standardized root mean square residual (SRMR) = .05. Examination of modification indices indicated correlated errors within a number of latent constructs. Modification indices >100 were iteratively freed. In total, 5 correlated errors were freed (weight concern with shape concern; shape concern with eating concern; DERS awareness with DERS clarity; DTS regulation with DTS tolerance; and two of the LOCES parcels). This resulted in significantly better fit, Satorra-Bentler Δχ2 (5) = 1665.31 p < .001. The final measurement model showed adequate latent measurement: χ2 (174) = 2946.11, p < .001, CFI = .95, RMSEA = .06, SRMR = .04.

3.3. Structural Model

Next, we specified the structural model. Loss of control eating was specified as the outcome. Difficulties with emotion regulation and distress tolerance were specified as the primary exogenous variables. Affect lability was specified as the mediator. To test for full mediation, difficulties in emotion regulation had both direct and indirect correlational paths to LOCE. The model showed poor fit to the data, χ2 (195) = 4249.14, p < .001, CFI = .93, RMSEA = .07, SRMR = .16. Examination of modification indices indicated a significant association between affect lability to general eating pathology (EDEQ). As this association has both empirical and theoretical support in the literature, it was added, and the model was re-estimated. The revised model showed good fit to the data, χ2 (194) = 3037.83, p < .001, CFI = .95, RMSEA = .06, SRMR = .04, Satorra-Bentler Δχ2 (1) = 1183.20 p < .001. Only one model parameter, the association between difficulties in emotion regulation to LOCE, was not statistically significant indicating full mediation. Difficulties in emotion regulation was positively, and distress tolerance was negatively, associated with affect lability. Affect lability was associated with LOCE. There was a strong positive association between LOCE and the measure of global eating pathology (EDEQ) added as a covariate to isolate the LOCE construct.

Next, we added a latent variable interaction between distress tolerance and difficulties in emotion regulation. This requires numerical integration, and thus fit statistics are not available. This interaction was statistically significant (B = −0.061, SE = 0.015, Cohen’s f = 0.07, p = .001). As these are non-nested models, and there are no fit indices, we used a Vuong test of the model loglikelihoods to compare overall fit. The Vuong test indicated that the model with the interaction was a better fit to the data than the model without, V = 13.64, p < .001. In the final model, difficulties in emotion regulation was positively (B = 0.519, SE = 0.023, Cohen’s f = 0.79, p < .001), and distress tolerance was negatively (B = −0.143, SE = 0.021, Cohen’s f = 0.18, p < .001), associated with affect lability. Affect lability was positively associated with LOCE (B = 0.209, SE = 0.022, Cohen’s f = 0.19, p < .001). Global eating pathology was robustly associated with LOCE (B = 0.466, SE = 0.015, Cohen’s f = 0.81, p < .001). The final model, depicted in Figure 1, accounted for 58% of the variance in LOCE.

Figure 1. Hypothesized Structural Model and Simple Slopes Analysis.

Figure 1.

Open in a new tab

*All paths were statistically significant at p ≤ .001

Finally, we probed the simple slopes of affect lability on difficulties in emotion regulation at high (+1SD) and low (−1SD) levels of distress tolerance (see Figure 1 callout box). At high distress tolerance, the association between difficulties in emotion regulation and LOCE was attenuated, although it remained statistically significant (b = 0.444, SE = 0.036, Cohen’s f = 0.74, p < .001). In contrast, at low levels of distress tolerance, the association between difficulties in emotion regulation and LOCE was potentiated (b = 0.594, SE = 0.020, Cohen’s f = 0.83, p < .001). There was a significant total indirect association between difficulties in emotion regulation and LOCE (IND = 0.310, SE = 0.017, p < .001) that was stronger at low distress tolerance (IND = 0.355, SE = 0.016, p < .001) and weaker at high distress tolerance (IND = 0.265, SE = 0.023, p < .001). Therefore, distress tolerance had a significant but small moderating effect on the direct relationship between affect lability and emotion regulation difficulties and the indirect relationship between emotion regulation difficulties and LOCE.

4.0. Discussion

Present findings suggest a pathway that is associated with the presence and severity of LOCE. Difficulty regulating one’s emotions and low distress tolerance were associated with greater affective lability, which in turn was associated with greater LOCE, controlling for general eating pathology. This finding is consistent with prior research identifying affective lability as a risk factor for LOCE (Anestis et al., 2010; Yu & Selby, 2013; Selby et a., 2012, Stevenson et al., 2018). Additionally, present findings support the relationship between difficulty regulating one’s emotions and affective lability (Contardi et al., 2018), which is of critical relevance given established findings linking difficulties with emotion regulation to LOCE (Racine & Horvath, 2018; Kukk & Akkermann, 2017; Anestis et al., 2009). In addition, greater ability to tolerate distress was linked to a weaker association between difficulty regulating one’s emotions and affective lability, whereas at low levels of distress tolerance this association was more robust. These findings have clinical relevance, as low distress tolerance often co-occurs with poor emotion regulation (Linehan, 2014), is heavily implicated in binge pathology (Bayer, 2014; Kozak & Fought, 2011), and, alongside high affective lability, may contribute to LOCE (Anestis et al., 2007).

It should be noted that there is some overlap between distress tolerance and difficulties in emotion regulation that could affect the interpretation of these results. An argument could be made that distress tolerance is simply another aspect of difficulties in emotion regulation. Distress tolerance is associated with a passive ability to withstand aversive emotional experiences (Leyro et al., 2010), rather than active strategies to combat the experience of negative affect. In contrast, difficulties in emotion regulation represents deficits in one’s ability to regulate more aversive emotional responses. Thus, individuals with more distress tolerance may not require the same level of emotion regulation abilities, and hence deficits in emotion regulation may be less impactful. This could explain why the association between emotion regulation difficulties and affect lability is lower at high levels of distress tolerance. However, if it were simply the case that high distress tolerance requires less emotion regulation skills, we would expect to see a consistent separation in the simple slopes of difficulties in emotion regulation across all levels of distress tolerance, which we do not. Instead, we see that distress tolerance only matters as difficulties in emotion regulation increase, indicating a distinct protective effect among those with the greatest difficulties in “regulating” not “tolerating” their emotions.

These findings, although limited in directional interpretability due to the cross-sectional design, suggest multiple potential treatment targets for reducing LOCE and identify vulnerabilities to assess for in patients presenting with high affective lability. For example, targeting low distress tolerance may be effective. However, it should be noted that the effect sizes of distress tolerance, both the main association with affect lability and the moderating effect on difficulties in emotion regulation, were quite modest. Even at the highest levels of distress tolerance, there remained a robust indirect association between difficulties in emotion regulation and LOCE. This highlights the limits of distress tolerance as a single protective factor. Though the associations suggest distress tolerance ability is related to lower LOCE through two different mechanisms, these data prove the moderation to be insufficient to nullify the link between emotion regulation difficulties and LOCE.

Limitations of this study must be noted. The first is the cross-sectional design, which prohibits interpretations regarding a directional nature of the relationship between variables. When misapplied, mediation analyses on cross-sectional research may bias interpretation of findings towards directionality (Maxwell & Cole, 2007). However, there are a few instances where mediation in cross-sectional research may be defensible (Maxwell & Cole, 2007). Prior EMA research establishing a temporal precedence between emotion regulation difficulties and LOCE (Kukk & Akkermann, 2017) as well as affective lability and LOCE (Anestis et al., 2010; Yu & Selby, 2013), lend credence to applicability of a path model, although authors acknowledge findings in this study cannot be concluded to provide greater evidence of a causal relationship. Additionally, although there is no published data on the convergent validity of the ALS specifically with EMA measures, there is evidence that retrospective self-report affective lability and ecologically measured lability in negative affect are significantly related (r = .38) (Anestis et al., 2010). However, there is some EMA evidence suggesting emotion regulation difficulties may actually increase post-LOCE episodes (Stevenson et al., 2019). Therefore, although EMA evidence suggests high affective lability around LOCE episodes (Anestis et al., 2010; Yu & Selby, 2013), and particularly greater fluctuations in negative emotions (Stevenson et al., 2018), the cross-sectional nature of this research limits interpretability regarding trajectory of affect or variability in affect at time points when LOCE is salient. Additionally, self-report relies on retrospective recall, which may introduce error or bias. A limitation to the generalizability of these findings is the use of a predominantly university sample, although the sample is arguably appropriate, as university students exhibit high rates of LOCE (Hopwood et al., 2018; Kukk & Akkermann, 2017). Finally, the lack of body mass index (BMI) assessment is a limitation, as BMI, a correlate of LOCE (Latner et al., 2014), cannot be accounted for in the model.

5.0. Conclusions

This study provides novel insight into how three affective mechanisms that commonly contribute to LOCE interact with one another. Future research is necessary to solidify the understanding of how increased distress tolerance moderates the relationship between difficulties with emotion regulation and affective lability, as well as the influence of these mechanisms on LOCE specifically (with or without objective overeating). Follow up studies implementing longitudinal and ecological assessments may provide greater nuance in measurement of momentary affect and reveal directionality of the relationship of the path model. In sum, this study provides preliminary evidence to support the necessity of pursuing the interplay of psychological vulnerabilities that contribute to LOCE and the protective role of elevated distress tolerance.

Highlights.

  • Emotion regulation difficulties are associated with loss-of-control eating

  • This association is by way of affective lability

  • Distress tolerance moderates a relationship of emotion regulation and affect lability

  • High distress tolerance may protect against loss-of-control eating

Footnotes

Conflict of Interest

The authors declare no conflict of interest.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Emily K. Burr, Department of Psychology, University of Central Florida

Robert D. Dvorak, Department of Psychology, University of Central Florida

Brittany L. Stevenson, University of Minnesota, Department of Psychiatry

Lauren M. Schaefer, Sanford Center for Bio-behavioral Research; Department of Psychiatry and Behavioral Science, University of North Dakota School of Medicine and Health Sciences

Stephen A. Wonderlich, Sanford Center for Bio-behavioral Research

References

  1. Alpers GW, & Tuschen-Caffier B (2001). Negative feelings and the desire to eat in bulimia nervosa. Eating Behaviors, 2(4), 339–352. 10.1016/S1471-0153(01)00040-X [DOI] [PubMed] [Google Scholar]
  2. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. [Google Scholar]
  3. Anestis MD, Peterson CB, Bardone-Cone AM, Klein MH, Mitchell JE, Crosby RD, Wonderlich SA, Crow SJ, Le Grange D, & Joiner TE (2009). Affective lability and impulsivity in a clinical sample of women with bulimia nervosa: The role of affect in severely dysregulated behavior. International Journal of Eating Disorders, 42(3), 259–266. 10.1002/eat.20606 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Anestis MD, Selby EA, Crosby RD, Wonderlich SA, Engel SG, & Joiner TE (2010). A comparison of retrospective self-report versus ecological momentary assessment measures of affective lability in the examination of its relationship with bulimic symptomatology. Behaviour Research and Therapy, 48(7), 607–613. 10.1016/j.brat.2010.03.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Anestis MD, Selby EA, Fink EL, & Joiner TE (2007). The multifaceted role of distress tolerance in dysregulated eating behaviors. International Journal of Eating Disorders, 40(8), 718–726. 10.1002/eat.20471 [DOI] [PubMed] [Google Scholar]
  6. Bayer V (2014). Eating disorders in lesbian and bisexual women: Relationship of binge eating to depressive symptoms, shame, distress tolerance, and internalized homophobia. [DOI] [PubMed] [Google Scholar]
  7. Berg KC, Cao L, Crosby RD, Engel SG, Peterson CB, Crow SJ, Le Grange D, Mitchell JE, Lavender JM, Durkin N, & Wonderlich SA (2017). Negative affect and binge eating: Reconciling differences between two analytic approaches in ecological momentary assessment research. International Journal of Eating Disorders, 50(10), 1222–1230. 10.1002/eat.22770 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Berg KC, Crosby RD, Cao L, Peterson CB, Engel SG, Mitchell JE, & Wonderlich SA (2013). Facets of negative affect prior to and following binge-only, purge-only, and binge/purge events in women with bulimia nervosa. Journal of Abnormal Psychology, 122(1), 111–118. 10.1037/a0029703 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bloomquist KK, Roberto CA, Barnes RD, White MA, Masheb RM, & Grilo CM (2014). Development and validation of the Eating Loss of Control Scale. Psychological Assessment, 1(77). 10.1037/a0034729 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Brownstone L (2017). Subjective binge eating: phenomenology, momentary emotions, and associated features. In Dissertation. 10.1017/CBO9781107415324.004 [DOI] [Google Scholar]
  11. Colles SL, Dixon JB, & Brien PEO (2008). Grazing and Loss of Control Related to Eating : Two High-risk Factors Following Bariatric Surgery. Obesity, 16(3), 615–622. 10.1038/oby.2007.101 [DOI] [PubMed] [Google Scholar]
  12. Contardi A, Imperatori C, Amati I, Balsamo M, & Innamorati M (2018). Assessment of affect lability: Psychometric properties of the ALS-18. Frontiers in Psychology, 9(March). 10.3389/fpsyg.2018.00427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Corstorphine E, Mountford V, Tomlinson S, Waller G, & Meyer C (2007). Distress tolerance in the eating disorders. Eating Behaviors, 8(1), 91–97. 10.1016/j.eatbeh.2006.02.003 [DOI] [PubMed] [Google Scholar]
  14. Crosby RD, Wonderlich SA, Engel SG, Simonich H, Smyth J, & Mitchell JE (2009). Daily mood patterns and bulimic behaviors in the natural environment. Behaviour Research and Therapy, 47(3), 181–188. 10.1016/j.brat.2008.11.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Fairburn CG, & Beglin S . (2008). Cognitive behavior therapy and eating disorders. Guilford Press. [Google Scholar]
  16. Goldschmidt AB, Engel SG, Wonderlich SA, Crosby RD, Peterson CB, Le Grange D, Tanofsky-Kraff M, Cao L, & Mitchell JE (2012). Momentary affect surrounding loss of control and overeating in obese adults with and without binge eating disorder. Obesity, 20(6), 1206–1211. 10.1038/oby.2011.286 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Gratz KL, & Roemer L (2004). Multidimensional Assessment of Emotion Regulation and Dysregulation: Development, Factor Structure, and Initial Validation of the Difficulties in Emotion Regulation Scale. Journal of Psychopathology and Behavioral Assessment, 26(1), 41–54. 10.1023/B:JOBA.0000007455.08539.94 [DOI] [Google Scholar]
  18. Gross JJ (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39(3), 281–291. 10.1017/S0048577201393198 [DOI] [PubMed] [Google Scholar]
  19. Hopwood CJ, Nye CD, Blomquist KK, & Grilo CM (2018). Confirmatory Validation and Measurement Equivalence of the Eating Loss of Control Scale in Binge Eating and Non-Clinical Samples. Journal of Psychopathology and Behavioral Assessment, 40(3), 476–483. 10.1007/s10862-018-9643-0 [DOI] [Google Scholar]
  20. Jeffries ER, McLeish AC, Kraemer KM, Avallone KM, & Fleming JB (2016). The Role of Distress Tolerance in the Use of Specific Emotion Regulation Strategies. Behavior Modification, 40(3), 439–451. 10.1177/0145445515619596 [DOI] [PubMed] [Google Scholar]
  21. Juarascio AS, Parker MN, Manasse SM, Barney JL, Wyckoff EP, & Dochat C (2020). An exploratory component analysis of emotion regulation strategies for improving emotion regulation and emotional eating. Appetite, 150(February). 10.1016/j.appet.2020.104634 [DOI] [PubMed] [Google Scholar]
  22. Kozak AT, & Fought A (2011). Beyond alcohol and drug addiction. Does the negative trait of low distress tolerance have an association with overeating? Appetite, 57(3), 578–581. 10.1016/j.appet.2011.07.008 [DOI] [PubMed] [Google Scholar]
  23. Kukk K, & Akkermann K (2017). Fluctuations in negative emotions predict binge eating both in women and men: An experience sampling study. Eating Disorders, 25(1), 65–79. 10.1080/10640266.2016.1241058 [DOI] [PubMed] [Google Scholar]
  24. Latner JD, & Clyne C (2008). The diagnostic validity of the criteria for binge eating disorder. International Journal of Eating Disorders, 41(1), 1–14. 10.1002/eat [DOI] [PubMed] [Google Scholar]
  25. Latner JD, Hildebrandt T, Rosewall JK, Chisholm AM, & Hayashi K (2007). Loss of control over eating reflects eating disturbances and general psychopathology. Behaviour Research and Therapy, 45(9), 2203–2211. 10.1016/j.brat.2006.12.002 [DOI] [PubMed] [Google Scholar]
  26. Latner JD, Mond JM, Kelly MC, Haynes SN, & Hay PJ (2014). The loss of control over eating scale: Development and psychometric evaluation. International Journal of Eating Disorders, 47(6), 647–659. 10.1002/eat.22296 [DOI] [PubMed] [Google Scholar]
  27. Lavender JM, Wonderlich SA, Engel SG, Gordon KH, Kaye WH, & Mitchell JE (2015). Dimensions of emotion dysregulation in anorexia nervosa and bulimia nervosa: A conceptual review of the empirical literature. Clinical Psychology Review, 40, 111–122. 10.1016/j.cpr.2015.05.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Leehr EJ, Krohmer K, Schag K, Dresler T, Zipfel S, & Giel KE (2015). Emotion regulation model in binge eating disorder and obesity - a systematic review. Neuroscience and Biobehavioral Reviews, 49, 125–134. 10.1016/j.neubiorev.2014.12.008 [DOI] [PubMed] [Google Scholar]
  29. Leyro TM, Zvolensky MJ, & Bernstein A (2010). Distress Tolerance and Psychopathological Symptoms and Disorders: A Review of the Empirical Literature Among Adults. Psychological Bulletin, 136(4), 576–600. 10.1037/a0019712 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Linehan MM (2014). DBT Skills Training Manual (2nd ed.). Guilford Press. [Google Scholar]
  31. Maxwell SE, & Cole DA (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12(1), 23–44. 10.1037/1082-989X.12.1.23 [DOI] [PubMed] [Google Scholar]
  32. Muthén LK, & Muthén BO (2020). Mplus statistical modeling software: Release 8.4. Muthén & Muthén. [Google Scholar]
  33. Oliver MNI, & Simons JS (2004). The affective lability scales: Development of a short-form measure. Personality and Individual Differences, 37(6), 1279–1288. 10.1016/j.paid.2003.12.013 [DOI] [Google Scholar]
  34. Palavras MA, Morgan CM, Borges FMB, Claudino AM, & Hay PJ (2013). An investigation of objective and subjective types of binge eating episodes in a clinical sample of people with co-morbid obesity. Journal of Eating Disorders, 1(1), 1–7. 10.1186/2050-2974-1-26 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Polivy J, & Herman CP (1993). Etiology of binge eating: Psychological mechanisms. In Binge eating: Nature, assessment, and treatment (pp. 173–205). Guilford Press. [Google Scholar]
  36. Racine SE, & Horvath SA (2018). Emotion dysregulation across the spectrum of pathological eating: Comparisons among women with binge eating, overeating, and loss of control eating. Eating Disorders, 26(1), 13–25. 10.1080/10640266.2018.1418381 [DOI] [PubMed] [Google Scholar]
  37. Selby EA, Doyle P, Crosby RD, Wonderlich SA, Engel SG, Mitchell JD, & Le Grange D (2012). Momentary emotion surrounding bulimic behaviors in women with bulimia nervosa and borderline personality disorder. Journal of Psychiatric Research, 46(11), 1492–1500. 10.1016/j.jpsychires.2012.08.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Simons JS, & Gaher RM (2005). The distress tolerance scale: Development and validation of a self-report measure. Motivation and Emotion, 29(2), 83–102. 10.1007/s11031-005-7955-3 [DOI] [Google Scholar]
  39. Smyth JM, Wonderlich SA, Heron KE, Sliwinski MJ, Crosby RD, Mitchell JE, & Engel SG (2007). Daily and Momentary Mood and Stress Are Associated With Binge Eating and Vomiting in Bulimia Nervosa Patients in the Natural Environment. Journal of Consulting and Clinical Psychology, 75(4), 629–638. 10.1037/0022-006X.75.4.629 [DOI] [PubMed] [Google Scholar]
  40. Stefano EC, Wagner AF, Mond JM, Cicero DC, & Latner JD (2016). Loss of Control Over Eating Scale (LOCES): Validation in undergraduate men and women with and without eating disorder symptoms. Eating Behaviors, 23, 137–140. 10.1016/j.eatbeh.2016.09.005 [DOI] [PubMed] [Google Scholar]
  41. Stevenson BL, Dvorak RD, Wonderlich SA, Crosby RD, & Gordon KH (2018). Emotions before and after loss of control eating. Eating Disorders, 26(6), 505–522. 10.1080/10640266.2018.1453634 [DOI] [PubMed] [Google Scholar]
  42. Stevenson BL, Wilborn D, Kramer MP, & Dvorak RD (2019). Real-time changes in emotion regulation and loss of control eating. Journal of Health Psychology. 10.1177/1359105318823242 [DOI] [PubMed] [Google Scholar]
  43. Tanofsky-Kraff M, Schvey NA, & Grilo CM (2020). A developmental framework of binge-eating disorder based on pediatric loss of control eating. The American Psychologist, 75(2), 189–203. 10.1037/amp0000592 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Van Eck K, Warren P, & Flory K (2017). A Variable-Centered and Person-Centered Evaluation of Emotion Regulation and Distress Tolerance: Links to Emotional and Behavioral Concerns. Journal of Youth and Adolescence, 46(1), 136–150. 10.1007/s10964-016-0542-y [DOI] [PubMed] [Google Scholar]
  45. Yu J, & Selby EA (2013). The interaction between affective lability and interpersonal problems in binge eating. Journal of Social and Clinical Psychology, 32(5), 465–481. 10.1521/jscp.2013.32.5.465 [DOI] [Google Scholar]

RESOURCES