Understanding heterogeneity, comorbidity, and variability in depression: Idiographic models and depression outcomes.

This study uses time-intensive, item-level assessment to examine individual depressive and co-occurring symptom dynamics. Participants experiencing moderate-severe depression (N = 31) completed ecological momentary assessment (EMA) four times per day for 20 days (total observations = 2480). We estimated idiographic networks using MDD, anxiety, and ED items. ED items were most frequently included in individual networks relative to depression and anxiety items. We built ridge and logistic regression ensembles to explore how idiographic network centrality metrics performed at predicting between-subject depression outcomes (PHQ-9 change score and clinical deterioration, respectively) at 6-months follow-up. For predicting PHQ-9 change score, R2 ranged between 0.13 and 0.28. Models predicting clinical deterioration ranged from no better than chance to 80 % accuracy. This pilot study shows how co-occurring anxiety and ED symptoms may contribute to the maintenance of depressive symptoms. Future work should assess the predictive utility of psychological networks to develop understanding of how idiographic models may inform clinical decisions.

Momentary physiological indices related to eating disorders: A systematic and methodological review.

Eating disorders (ED) are serious psychiatric illnesses, with no everyday support to intervene on the high rates of relapse. Understanding physiological indices that can be measured by wearable sensor technologies may provide new momentary interventions for individuals with ED. This systematic review, searching large databases, synthesises studies investigating peripheral physiological (PP) indices commonly included in wearable wristbands (heart rate [HR], heart rate variability [HRV], electrodermal activity [EDA], peripheral skin temperature [PST], and acceleration) in ED. Inclusion criteria included: (a) full peer-reviewed empirical articles in English; (b) human participants with active ED; and (c) containing one of five wearable physiological measures. Kmet risk of bias was assessed. Ninety-four studies were included (Anorexia nervosa [AN; N = 4418], bulimia nervosa [BN; N = 916], binge eating disorder [BED; N = 1604], other specified feeding and eating disorders [OSFED; N = 424], and transdiagnostic [N = 47]). Participants with AN displayed lower HR and EDA and higher HRV compared to healthy individuals. Those with BN showed higher HRV, and lower EDA and PST compared to healthy individuals. Other ED and Transdiagnostic samples showed mixed results. PP differences are indicated through various assessments in ED, which may suggest diagnostic associations, although more studies are needed to validate observed patterns. Results suggest important therapeutic potential for PP in ED, and larger studies including diverse participants and diagnostic groups are needed to fully uncover their role in ED.

Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning.

OBJECTIVE: Body mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) and atypical anorexia nervosa despite prior literature indicating few differences between disorders. Machine learning (ML) classification provides us an efficient means of accurately distinguishing between two meaningful classes given any number of features. The aim of the present study was to determine if ML algorithms can accurately distinguish AN and atypical AN given an ensemble of features excluding BMI, and if not, if the inclusion of BMI enables ML to accurately classify between the two. METHODS: Using an aggregate sample from seven studies consisting of individuals with AN and atypical AN who completed baseline questionnaires (N = 448), we used logistic regression, decision tree, and random forest ML classification models each trained on two datasets, one containing demographic, eating disorder, and comorbid features without BMI, and one retaining all features and BMI. RESULTS: Model performance for all algorithms trained with BMI as a feature was deemed acceptable (mean accuracy = 74.98%, mean area under the receiving operating characteristics curve [AUC] = 74.75%), whereas model performance diminished without BMI (mean accuracy = 59.37%, mean AUC = 59.98%). DISCUSSION: Model performance was acceptable, but not strong, if BMI was included as a feature; no other features meaningfully improved classification. When BMI was excluded, ML algorithms performed poorly at classifying cases of AN and atypical AN when considering other demographic and clinical characteristics. Results suggest a reconceptualization of atypical AN should be considered. PUBLIC SIGNIFICANCE: There is a growing debate about the differences between anorexia nervosa and atypical anorexia nervosa as their diagnostic differentiation relies on BMI despite being similar otherwise. We aimed to see if machine learning could distinguish between the two disorders and found accurate classification only if BMI was used as a feature. This finding calls into question the need to differentiate between the two disorders.

Investigating the Theory of Clinical Perfectionism in a Transdiagnostic Eating Disorder Sample Using Network Analysis.

Eating disorders are deadly psychiatric illnesses, with treatments working for less than half of individuals who seek treatment. The transdiagnostic theory of eating disorders proposes that eating disorders share similar maintaining symptoms, such as what this theory calls clinical perfectionism (i.e., high levels of concern over mistakes and personal standards). However, it has been difficult to examine the interrelationship of specific aspects of perfectionism, beyond assessing moderation effects, which have generally not found support for the theory of clinical perfectionism in eating disorders. Thus, we used network analysis to test the theory of perfectionism by testing the interrelationships between maladaptive perfectionism facets (concern over mistakes, personal standards, parental criticism, parental expectations, and personal standards) and eating disorder symptoms in 397 individuals diagnosed with an eating disorder. Concern over mistakes was a central symptom and demonstrated the strongest interrelationships with eating disorder symptoms compared to the other aspects of perfectionism, connecting to eating concerns and cognitive restraint. Objective binge eating had a strong negative connection to personal standards. We identified specific central symptoms and illness pathways of perfectionism, which partially supports the theory of clinical perfectionism. Results, if replicated, may suggest that concern over mistakes might be best reconceptualized as part of eating disorder pathology and be targeted to improve treatment outcomes for eating disorders.

Dynamic relationships among feeling fat, fear of weight gain, and eating disorder symptoms in an eating disorder sample.

Feeling fat and fear of weight gain are key cognitive-affective symptoms that are theorized to maintain eating disorders (EDs). Little research has examined the dynamic relationships among feeling fat, fear of weight gain, emotions, cognitions, and ED behaviors. Furthermore, it is unknown if these relations vary by ED diagnosis (e.g., anorexia nervosa (AN) vs other ED). The current study (N = 94 ED participants; AN n = 64) utilized ecological momentary assessments collected four times a day for 18 days (72 timepoints) asking about feeling fat, fear of weight gain, emotions (i.e., anxiety, guilt), cognitions (i.e., feelings of having overeaten, thoughts about dieting), and ED behaviors (i.e., vomiting, diuretic/laxative use, excessive exercise, body checking, self-weighing, binge-eating, restriction) at stressful timepoints (contemporaneous [mealtime], and prospective/temporal [next-meal]). Multilevel modeling was used to test for between and within-person associations. Higher feeling fat and fear of weight gain independently predicted higher next-meal emotions (i.e., anxiety, guilt), cognitions (i.e., feelings of having overeaten, thoughts about dieting, fear of weight gain, feeling fat), and ED behaviors (i.e., body checking, self-weighing [feeling fat]). There were relationships in the opposite direction, such that some emotions, cognitions, and ED behaviors prospectively predicted feeling fat and fear of weight gain, suggesting existence of a reciprocal cycle. Some differences were found via diagnosis. Findings pinpoint specific dynamic and cyclical relationships among feeling fat, fear of weight gain, and specific ED symptoms, and suggest the need for more research on how feeling fat, fear of weight gain and cognitive-affective-behavioral aspects of ED operate. Future research can test if treatment interventions targeted at feeling fat and fear of weight gain may disrupt these cycles.

Evidence-Based Assessments for Transdiagnostic Eating Disorder Symptoms: Guidelines for Current Use and Future Directions.

Eating disorders are severe and often chronic mental illnesses that are associated with high impairment and mortality rates. Recent estimates suggest that eating disorder prevalence rates are on the rise, indicating an increased need for accurate assessment and detection. The current review provides an overview of transdiagnostic eating disorder assessments, including interview, self-report, health and primary care screeners, and technology-based and objective assessments. We focused on assessments that are transdiagnostic in nature and exhibit high impact in the field. We provide recommendations for how these assessments should be used in research and clinical settings. We also discuss considerations that are crucial for assessment, including the use of a categorical versus dimensional diagnostic framework, assessment of eating disorders in related fields (i.e., anxiety and depression), and measurement-based care for eating disorders. Finally, we provide suggestions for future research, including the need for more research on short transdiagnostic screeners for use in health care settings, standardized assessments for ecological momentary assessment, development of state-based assessment of eating disorder symptoms, and consideration of assessment across multiple timescales.

A Pilot, Time-Series Investigation of Depression, Anxiety, and Eating Disorder Symptoms in Adults Experiencing Major Depressive Symptoms: The Need for Eating Disorder Assessment and Research in Depression.

Major Depressive Disorder (MDD) is a prevalent psychiatric disorder impacting 10-16% of Americans in their lifetime. Approximately 60% of individuals with MDD have comorbid anxiety disorders. Additionally, although scarce research has examined eating disorders (EDs) in depression, a bidirectional association exists between ED and MDD symptoms. The current pilot study (N = 31 individuals with moderate to severe depression) modeled networks of depressive, anxiety, and ED symptoms using intensive time-series data. This study also tested if temporal central symptoms predicted six-month clinical outcomes. The most central symptoms were guilt, self-dislike, lack of energy, and difficulty concentrating. Several anxiety and ED symptoms were also central, including physical anxiety, social anxiety, body dissatisfaction, and desire for thinness. The central symptom crying predicted six-month depression with a medium effect size. These findings suggest anxiety and ED symptoms may influence the day-to-day course of depression in some individuals with comorbid diagnoses, but predictors of symptoms across hours may differ from predictors across longer time scales (i.e., months). Time scale should be considered when conducting and interpreting research on MDD. Research, assessment, and treatment for MDD should continue to explore transdiagnostic approaches including anxiety and ED symptoms to optimize care for individuals with complex presentations.

Personalizing eating disorder treatment using idiographic models: An open series trial.

OBJECTIVE: Treatments for adults with eating disorders (EDs) only work in about 50% of individuals, and for some diagnoses (e.g., anorexia nervosa; atypical anorexia nervosa), there are no existing evidence-based treatments. Part of the reason that treatments may only work in a subset of individuals is because of the high heterogeneity present in the EDs, even within diagnoses. Manualized treatments delivered in a standard format may not always address the most relevant symptoms for a specific individual. METHOD: The current open series trial recruited participants with transdiagnostic ED diagnoses (N = 79) to investigate the feasibility, acceptability, and initial clinical efficacy of a 10-session network-informed personalized treatment for eating disorders. This treatment uses idiographic (i.e., one-person) network models of ecological momentary assessment symptom data to match participants to evidence-based modules of treatment. RESULTS: We found that network-informed personalized treatment was highly feasible with low dropout rates, was rated as highly acceptable, and had strong initial clinical efficacy. ED severity decreased from pre- to posttreatment and at 1-year follow-up with a large effect size. ED cognitions, behaviors, clinical impairment, worry, and depression also decreased from pre- to posttreatment. CONCLUSIONS: These data suggest that network-informed personalized treatment has high acceptability and feasibility and can decrease ED and related pathology, possibly serving as a feasible alternative to existing treatments. Future randomized controlled trials comparing network-informed personalized treatment for ED to existing gold standard treatments are needed. Additionally, more research is needed on this type of personalized treatment both in the EDs, as well as in additional forms of psychopathology, such as depression. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Integrating clinician and patient case conceptualization with momentary assessment data to construct idiographic networks: Moving toward personalized treatment for eating disorders.

Eating disorders are serious psychiatric illnesses with treatments ineffective for about 50% of individuals due to high heterogeneity of symptom presentation even within the same diagnoses, a lack of personalized treatments to address this heterogeneity, and the fact that clinicians are left to rely upon their own judgment to decide how to personalize treatment. Idiographic (personalized) networks can be estimated from ecological momentary assessment data, and have been used to investigate central symptoms, which are theorized to be fruitful treatment targets. However, both efficacy of treatment target selection and implementation with 'real world' clinicians could be maximized if clinician input is integrated into such networks. An emerging line of research is therefore proposing to integrate case conceptualizations and statistical routines, tying together the benefits from clinical expertise as well as patient experience and idiographic networks. The current pilot compares personalized treatment implications from different approaches to constructing idiographic networks. For two patients with a diagnosis of anorexia nervosa, we compared idiographic networks 1) based on the case conceptualization from clinician and patient, 2) estimated from patient EMA data (the current default in the literature), and 3) based on a combination of case conceptualization and patient EMA data networks, drawing on informative priors in Bayesian inference. Centrality-based treatment recommendations differed to varying extent between these approaches for patients. We discuss implications from these findings, as well as how these models may inform clinical practice by pairing evidence-based treatments with identified treatment targets.

Longitudinal group and individual networks of eating disorder symptoms in individuals diagnosed with an eating disorder.

Eating disorders (EDs) are serious psychiatric illnesses with high mortality and societal cost. Despite their severity, there are few evidence-based treatments, and only 50% of individuals respond to existing treatments. This low response rate may be due to the fact that EDs are highly heterogeneous disorders. Precision treatments are needed that can intervene on individual maintenance factors. The first step in such treatment development is identification of central treatment targets, both at the group (i.e., on average) and individual level. The current study (N = 102 individuals with an ED) utilized intensive longitudinal data to model several types of group-level and individual network models. Overall, we identified several group-level central symptoms, with the most common central symptoms of fear of weight gain, desire for thinness, feeling like one is overeating, thinking about dieting, and feeling guilty. We also found that these symptoms, specifically fear of weight gain, a desire to be thinner, thinking about dieting, feeling like one is overeating, and feeling guilty, predicted ED severity at a 1- and 6-month follow-up. We modeled 97 individual networks and found that central symptoms were highly heterogeneous, regardless of ED diagnosis. This work adds to the growing literature using intensive longitudinal data to model ED pathology and implicates fear of weight gain, thinking about dieting, and feelings of guilt as symptoms needing further treatment development work. Additionally, this work contributes essential knowledge on how group and individual network modeling can be used to conceptualize the maintenance of EDs on average and at the individual level. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

An eye-tracking study examining the relationship between males' eating disorder symptomatology, body mass index, and expectations about character behaviour in text.

Eating disorder prevalence is increasing in males, perhaps more rapidly than in females. Theorists have proposed that cognitive biases are important factors underpinning disordered eating, especially those related to food, body, and perfectionism. We investigated these factors in relation to males' eating disorder symptomatology in the general population by using eye-tracking during reading as a novel and implicit measure. 180 males' eye movements were monitored while they read scenarios (third-person in Experiment 1 (n = 90, 18-38(Mage = 21.50, SD = 3.65)); second-person in Experiment 2 (n = 90, 18-35(Mage = 20.50, SD = 2.22))) describing characters' emotional responses (e.g. upset) to food-, body image-, and perfectionism-related events. Participants' eating disorder symptomatology was then assessed, and body mass index (BMI) was calculated. Results showed processing of characters' emotional responses (detected via eye-tracking) to body- and perfectionism-related events for third-person scenarios was related to eating disorder symptomatology. Processing of characters' emotional responses to body-related events for second-person scenarios was related to males' BMI. The moment-to-moment processing of characters' emotional responses to food-related scenarios was not related to eating disorder symptomatology or BMI. Findings support theories that include body- and perfectionism-related cognitive biases as underlying mechanisms of eating disorder symptomatology and the use of implicit measures of cognitive processes underlying males' eating disorder symptomatology.

A pilot randomized control trial of online exposure for eating disorders and mechanisms of change delivered after discharge from intensive eating disorder care: A registered report.

More than 50% of individuals with an eating disorder (ED) will readmit to treatment within 6 months of treatment discharge and often due to persistent cognitive ED pathology. Interventions addressing unremitted cognitive ED pathology following discharge from intensive treatment are crucial to prevent readmission. Imaginal exposure therapy facilitates the approach of feared stimuli not accessible in everyday life (e.g., rapidly gaining weight). In the current pilot randomized control trial (RCT), participants will be randomly assigned to a five-session online imaginal exposure condition (n = 65) or a control online writing and thinking intervention (n = 65) within a month of discharge from intensive treatment. Exposure participants write about and imagine an ED fear and control participants will write about their ED generally. We will examine the feasibility and acceptability of the treatment conditions and whether imaginal exposure is more effective in preventing readmission than the control condition. We will test the efficacy of the imaginal exposure treatment in reducing ED symptoms and fears of food and weight gain, and whether fear learning is a mechanism of change related to ED pathology. Ultimately, this research will lead to the development of an easily deployable readmission prevention treatment based on fear conditioning targets.

Pinpointing core and pathway symptoms among sleep disturbance, anxiety, worry, and eating disorder symptoms in anorexia nervosa and atypical anorexia nervosa.

BACKGROUND: Sleep, anxiety, and worry are strongly related to psychiatric illness and in particular to eating disorder (ED) symptoms. However, it is unclear how these specific sleep and anxiety symptoms are interrelated with anorexia nervosa (AN) pathology. METHODS: We utilized network analysis to test our theoretically-based conceptual model, by identifying core features and illness (i.e., bridge) pathways among sleep disturbance, anxiety, worry, and ED symptoms in 267 participants with a diagnosis of AN or atypical AN. RESULTS: The following core symptoms were identified: shape judgement, restriction, and feeling tired. The strongest bridge symptoms included worry, feeling tired, loss of energy, and physical anxiety. Worry was connected positively to fasting, fear of gaining weight or becoming fat, loss of energy, and feeling tired, and negatively to changes in sleeping patterns. Feeling tired was connected to restriction, fasting, binge eating, and worry. Loss of energy was connected to loss of control over eating and worry. Physical anxiety was negatively connected to restriction. CONCLUSIONS: We identified specific core symptoms and illness pathways supporting our theoretical conceptual model of how ED symptoms, anxiety, worry, and sleep disturbances inter-relate in AN and atypical AN. In particular we found that symptoms associated with sleep and anxiety were central and had strong connections with AN symptoms. In addition to targeting AN symptoms, these data suggest that targeting sleep disturbance, anxiety, and worry could improve treatment for AN.

Visual mapping of body image disturbance in anorexia nervosa reveals objective markers of illness severity.

Body image disturbance (BID) is a core feature of eating disorders, for which there are few objective markers. We examined the feasibility of a novel digital tool, "Somatomap", to index BID related to anorexia nervosa (AN) severity. Fifty-five AN inpatients and 55 healthy comparisons (HC) outlined their body concerns on a 2-Dimensional avatar. Next, they indicated sizes/shapes of body parts for their current and ideal body using sliders on a 3-Dimensional avatar. Physical measurements of corresponding body parts, in cm, were collected for reference. We evaluated regional differences in BID using proportional z-scores to generate statistical body maps, and multivariate analysis of covariance to assess perceptual discrepancies for current body, ideal body, and body dissatisfaction. The AN group demonstrated greater regional perceptual inaccuracy for their current body than HC, greater discrepancies between their current and ideal body, and higher body dissatisfaction than HCs. AN body concerns localized disproportionately to the chest and lower abdomen. The number of body concerns and perceptual inaccuracy for individual body parts was strongly associated with Eating Disorder Examination Questionnaire (Global EDE-Q) scores across both groups. Somatomap demonstrated feasibility to capture multidimensional aspects of BID. Several implicit measures were significantly associated with illness severity, suggesting potential utility for identifying objective BID markers.

Gastric symptoms and low perceived maternal warmth are associated with eating disorder symptoms in young adolescent girls.

OBJECTIVE: This study sought to determine whether gastric symptoms are associated with later eating disorder (ED) symptoms during early adolescence, and whether this relationship is moderated by parental warmth/acceptance and/or the child's sex. METHOD: Longitudinal data from the Adolescent Brain Cognitive DevelopmentSM Study were utilized. Participants ages 9-10 years old (N = 4,950; 2,370 female) completed measures at baseline and 1 year later (Y1). At baseline, gastric symptoms were measured by parent-reported items from the Child Behavior Checklist (CBCL), and perceived parental acceptance was measured by youth report on the Children's Report of Parent Behavior Inventory (CRPBI) Acceptance subscale separately for mothers and fathers. ED symptoms at Y1 were assessed by parent report on a computerized version of the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS). Linear mixed-effects models were conducted separately for maternal and paternal acceptance to test relationships among variables. RESULTS: A three-way interaction between baseline gastric symptoms, sex, and maternal acceptance predicted Y1 ED symptoms (𝛽 = 0.08; p < .01). Post-hoc analyses revealed that the interaction between gastric symptoms and maternal acceptance was significant for girls only (𝛽 = -0.06, p < .01), such that low maternal acceptance was associated with a stronger relationship between baseline gastric symptoms and Y1 ED symptoms. No statistically significant main effects or interactions were found in the model for paternal acceptance. DISCUSSION: Gastric symptoms and low perceived maternal acceptance may interact to result in heightened risk for EDs in young adolescent girls.

Disturbed Eating and Body Dysmorphic Symptoms in a Young Adult Sample Are Separable Constructs That Each Show a Mixture of Distributions.

Eating disorder and body dysmorphic disorder symptoms overlap and frequently co-occur clinically, yet whether they represent one or more underlying constructs in the general population is unknown. We examined relationships between these symptoms on underlying factor structures and dimensional distributions in a young adult sample of 328 students using the Eating Disorder Examination-Questionnaire (EDE-Q 6.0) and the Dysmorphic Concern Questionnaire (DCQ). We performed factor and hierarchical cluster analyses on pooled items and Gaussian mixture modeling on score distributions. EDE-Q 6.0 and DCQ total scores were correlated (r = 0.53, p < .001). Pooled items demonstrated a three-factor solution; DCQ items separating from two EDE-Q 6.0 factors. Hierarchical clustering yielded a two-cluster solution that separated the two scales. Mixture modeling demonstrated that more than one underlying distribution best fit the data for each scale. These results suggest that the EDE-Q 6.0 and DCQ measure different sets of psychopathological features, despite their tendency to track together. Moreover, eating disorder and body dysmorphic phenotypes each show nonuniform variation from normal to abnormal. This argues against using linear dimensional applications of these scales to assess individuals ranging from mild to severe in symptom severity. Separate scales may be necessary to characterize lower and higher ranges of clinical severity.

What is the relationship between body mass index and eating disorder symptomatology in professional female fashion models?

Low body mass index (BMI<18/18.5) is utilized as a mandated cutoff for professional fashion model employment, based on assumptions that low BMI indicates eating disorder pathology. No previous studies have examined the association between experimenter-measured BMI and eating disorder symptomatology in professional fashion models. We measured BMI and Eating Disorder Examination Questionnaire (EDE-Q) responses in United Kingdom (UK) professional fashion models, and nonmodels. Characteristics were compared using robust standardized mean difference (rSMD) obtained via probability of superiority. Associations between BMI and eating disorder symptomatology were examined using robust regression, controlling for age. Models exhibited lower BMI but higher fat-percentage and muscle mass. On the EDE-Q, models had higher Restraint, Global, Eating, and Weight Concerns, and similar Shape Concern scores compared to nonmodels. BMI was positively associated with eating disorder symptoms in both groups, and all but one of the eight models with clinically significant EDE-Q level had ≥18.5 measured BMI. Lower BMI was not indicative of worse eating disorder symptomatology in models or nonmodels. Thus, using a low BMI cutoff (<18.5) may not be an appropriate single index of health for detecting elevated eating disorder symptoms in models. Different policies to protect models' health should be considered.

Development and validation of new figural scales for female body dissatisfaction assessment on two dimensions: thin-ideal and muscularity-ideal.

BACKGROUND: Body dissatisfaction influences women's mental and physical health. To date, most research has focused on body dissatisfaction in relation to the 'thin-ideal'. Thus, the association between body dissatisfaction, eating disorder symptomatology and muscularity-ideal in women is less clear. Lack of understanding is underpinned by the lack of reliable and valid muscularity-related assessments for women. To address this need, we developed, tested and re-tested two new body dissatisfaction scales: The Female Body Scale (FBS; adiposity dimension) and Female Fit Body Scale (FFITBS; muscularity dimension). METHODS: One hundred and fifty-two women in the United Kingdom rated which body figure best represented their current and ideal body, completed the Eating Disorder Examination Questionnaire (EDE-Q 6.0), and their body composition was measured. During re-test, the EDE-Q 6.0 and Drive for Muscularity Scale (DMS) were completed. RESULTS: Both the FBS and the FFITBS were found to be valid and reliable, and distinct types of body dissatisfaction were identified. Higher EDE-Q scores corresponded with greater body dissatisfaction scores on both the FBS and FFITBS. Thin-ideal (FBS) and larger/muscularity-ideal (FFITBS) body dissatisfaction predicted higher scores on the DMS. The muscularity scale (FFITBS) uniquely revealed that 28% of participants indicated body dissatisfaction toward the larger-muscularity-ideal. CONCLUSIONS: Results reveal distinct dimensions of body dissatisfaction. These new, validated scales may be utilized to quickly identify eating disorder risk in women as a preventative assessment for clinicians and inform female-focused body-image and eating disorder research.

The role of negative urgency in risky alcohol drinking and binge-eating in United Kingdom male and female students.

Identifying students at risk of developing binge-eating and alcohol use disorders is a priority in the United Kingdom (UK). Although relationships between negative urgency (impulsive behavior during times of negative emotion), risky drinking, and binge-eating have been established in students from other countries, these links have yet to be replicated in male and female UK students. UK students aged 18-30 (n = 155) completed the: (1) the Urgency, Pre-meditation, Perseverance, Sensation Seeking (UPPS-P) negative urgency subscale; (2) Alcohol Use Disorders Identification Test (AUDIT); and (3) Binge-Eating Scale (BES). For categorical analysis, participants were assigned to one of four groups as a function of AUDIT and BES clinical cut-off scores: (1) no risk (28%); (2) risky drinkers (47%); (3) binge-eaters (6%); and (4) risky drinkers + binge-eaters (19%). For dimensional analysis, across students with non-zero AUDIT and BES scores (n = 141), BES, AUDIT, gender, and their interactions were entered as predictors in the same block of a regression. UPPS-P negative urgency was the dependent variable. Categorical results indicated that binge-eaters with and without risky drinking endorsed significantly higher negative urgency than students with no risk. Dimensional results showed that although higher BES and AUDIT scores were positively linked to higher negative urgency, but only the BES was significantly associated. Furthermore, BES shared substantially more variance with negative urgency than the AUDIT, and the BES-negative urgency relationship was stronger in male students than female students. High risk students may benefit the most from interventions that help regulate negative emotion.