Physiological, body composition, and body mass measures show that a developmental measure of weight suppression is more valid than the traditional measure.

OBJECTIVE: The traditional measure of weight suppression (TWS; the difference between an individual's highest past weight at adult height and current weight), has been associated with many psychological, behavioral and biological variables in those with eating disorders. A new measure of weight suppression, called developmental weight suppression (DWS), corrects two major problems in the original measure. Initial research indicates that DWS represents a superior operationalization of the construct weight suppression was originally designed to measure (Lowe [1993, Psychol Bull, 114: 100]). This study is the first to examine the relation between both WS measures and weight history, body composition and a variety of metabolic hormones. METHODS: Data were collected in 91 women with bulimia nervosa (BN) or BN-spectrum disorders. RESULTS: Both weight suppression indices were related to multiple hormones. However, multiple regression analyses showed that the independent effects of DWS differed from the independent effects of TWS in that only DWS was negatively related to: (1) current z-BMI, (2) body fat percentage, and (3) insulin, leptin, T3 free, and TSH. This differential pattern also occurred when results were corrected for multiple comparisons. DISCUSSION: Findings provide stronger biological support for the construct validity of DWS than TWS and suggest that: (1) from the perspective of individuals with BN, high DWS embodies success at food restriction and weight loss, (2) elevated DWS may trap individuals with BN in a powerful biobehavioral bind, and (3) DWS is the preferred measure of weight suppression in future research on eating disorders. PUBLIC SIGNIFICANCE: Most individuals with bulimia nervosa lose substantial weight in the process of developing their disorder. Such weight suppression is related to many characteristics of those with the eating disorder bulimia nervosa. This study shows why a new measure of weight suppression, based on an individual's growth during development, is more biologically valid than the traditional measure of weight suppression.

Weight History Correlates of Resting Energy Expenditure in Women With Bulimia Nervosa.

OBJECTIVE: Among those with bulimia nervosa, weight suppression has been associated with illness severity and treatment prognosis. Although significant weight loss is known to reduce metabolic rate, the relation between weight suppression and resting energy expenditure (REE) in bulimia nervosa has not been examined. This study tested the hypothesis of an inverse relation between weight suppression and REE in a sample of women with bulimia nervosa (N = 84). METHODS: In primary analyses, linear regressions were conducted between weight suppression and REE, corrected for fat-free mass. In follow-up, exploratory analyses, stepwise linear regressions were conducted to explore the main and interaction effects of weight history and weight suppression on REE. RESULTS: Neither traditional (TWS) nor developmental weight suppression (DWS) correlated with REE. Results from exploratory analyses, however, revealed a medium-to-large inverse relation between several weight history variables and REE (highest past weight, sr2 = 0.05; lowest postmorbid weight, sr2 = 0.07; current weight, sr2 = 0.05). Additionally, DWS interacted with current (sr2 = 0.08) and highest premorbid (sr2 = 0.05) z-BMI to influence REE with a medium-to-large effect. For individuals low in current and premorbid z-BMIs, higher DWS associated with lower REE levels. However, for individuals at higher premorbid z-BMIs, higher DWS unexpectedly associated with greater REE levels. DISCUSSION: In this sample of women with bulimia nervosa, reduced REE associated with higher weights across all timepoints. If the interaction effect between DWS and z-BMI history persists in future studies, this may indicate unique challenges faced by individuals low in z-BMI and high in DWS related to weight gain and normalization of eating.

Is there a basis for a weight cut-off point? A large-scale investigation of atypical anorexia and anorexia nervosa subtypes among patients at a residential treatment centre.

OBJECTIVE: There is debate surrounding how to differentiate between anorexia nervosa (AN) and atypical AN (atypAN) as diagnostic entities, and whether a distinction based on BMI is warranted. Better understanding eating disorder (ED) and emotional symptoms across atypAN and AN subtypes [AN-restricting (AN-R), AN-binge/purge (AN-BP)], with and without controlling for BMI, can elucidate how atypAN differs from AN subtypes and whether there is a basis for a BMI cut-off. METHODS: 1810 female patients at an ED treatment centre completed intake surveys. ANCOVAs assessed differences across AN-R (n = 853), AN-BP (n = 726), and atypAN (n = 231) groups on ED, depressive, and anxiety symptoms, anxiety sensitivity, experiential avoidance, and mindfulness, with and without controlling for BMI. RESULTS: Relative to AN-R, atypAN and AN-BP groups endorsed significantly higher ED and depressive symptoms, anxiety sensitivity, experiential avoidance, and significantly lower mindfulness (all p < 0.001), but atypAN and AN-BP groups did not differ from one another. When controlling for BMI, all previously significant differences between atypAN and AN-R did not remain significant. CONCLUSION: Individuals with atypAN who have a higher BMI experience more pronounced ED and emotional symptoms, suggesting that relying solely on BMI as a marker of illness severity may be problematic.

Altered prefrontal activation during the inhibition of eating responses in women with bulimia nervosa.

BACKGROUND: The sense of 'loss of control' (LOC), or a feeling of being unable to stop eating or control what or how much one is eating, is the most salient aspect of binge eating. However, the neural alterations that may contribute to this experience and eating behavior remain poorly understood. METHODS: We used functional near-infrared spectroscopy (fNIRS) to measure activation in the prefrontal cortices of 23 women with bulimia nervosa (BN) and 23 healthy controls (HC) during two tasks: a novel go/no-go task requiring inhibition of eating responses, and a standard go/no-go task requiring inhibition of button-pressing responses. RESULTS: Women with BN made more commission errors on both tasks. BN subgroups with the most severe LOC eating (n = 12) and those who felt most strongly that they binge ate during the task (n = 12) showed abnormally reduced bilateral ventromedial prefrontal cortex (vmPFC) and right ventrolateral prefrontal cortex (vlPFC) activation associated with eating-response inhibition. In the entire BN sample, lower eating-task activation in right vlPFC was related to more frequent and severe LOC eating, but no group differences in activation were detected on either task when this full sample was compared with HC. BN severity was unrelated to standard-task activation. CONCLUSIONS: Results provide initial evidence that diminished PFC activation may directly contribute to more severe eating-specific control deficits in BN. Our findings support vmPFC and vlPFC dysfunction as promising treatment targets, and indicate that eating-specific tasks and fNIRS may be useful tools for identifying neural mechanisms underlying dysregulated eating.

A comparison of traditional and developmental measures of weight suppression in residential patients with bulimia nervosa.

OBJECTIVE: Weight suppression (WS) is associated with many eating disorder (ED)-related symptoms. However, traditional calculations of WS do not consider the age or height at which one's highest past weight was reached. Lowe et al. (2022) found that developmental WS (DWS) was associated with a wider variety of ED-related symptoms compared with traditional WS (TWS). This study replicated and extended these findings in a larger sample of individuals with bulimia nervosa (BN) at a residential ED treatment center. METHODS: Participants were 1051 female patients with BN. We examined the relations between each WS measure and ED symptoms, emotional symptoms, and weight history variables. RESULTS: TWS and DWS showed a similar number of relations with ED-related symptoms. DWS was positively related to behavioral symptoms (e.g., vomiting), and negatively related to cognitive symptoms (e.g., weight/eating concern). TWS was positively related to highest premorbid, highest postmorbid, and lowest postmorbid weights. DWS was also positively related to highest premorbid z-scored body mass index (zBMI), but negatively related to lowest and highest postmorbid zBMI. CONCLUSIONS: DWS, relative to TWS, may better capture the psychobiological impact of the weight discrepancy that a measure of WS is meant to reflect. PUBLIC SIGNIFICANCE: Weight suppression, the difference between an individual's past highest weight and current weight, is significantly related to many ED-related symptoms. This study found that a new weight suppression measure, based on expected weight-for-height during physical development, relates to ED characteristics in a different manner from the traditional measure of weight suppression, showing positive associations with behavioral symptoms and negative associations with cognitive symptoms.

An examination of frontal asymmetry in relation to eating in the absence of hunger and loss-of-control eating.

Loss-of-control (LOC) eating involves a subjective feeling that one cannot stop eating or control one's eating. Individuals with LOC eating may exhibit strong appetitive drives and weak inhibitory control, and these two opposing motivations have been related to EEG measurements of frontal asymmetry or lateralized frontal activation. The present study investigated whether frontal asymmetry is related to hedonic hunger, LOC eating severity and frequency, and eating in the absence of hunger (EAH) in the laboratory. Fifty-nine individuals participated in an ostensible taste study after resting-state electroencephalogram (EEG) recordings. After the EEGs, they were provided a meal to eat until fullness, followed by an array of snacks and instructions to eat as much as they would like. The results indicated that several measures of right-frontal asymmetry were related to greater EAH and greater self-reported LOC eating severity. Although right-frontal asymmetry has been theorized to reflect avoidance motivation, recent evidence suggests it may indicate effortful control during approach-avoidance conflicts. Because individuals with LOC eating presumably experience heightened conflict between drives to eat beyond energy needs and to minimize such eating, those experiencing greater LOC may exert greater effort to manage these conflicting motivations. An integration of these neurobiological correlates of LOC eating may help provide a more comprehensive understanding of LOC eating and inform treatments.

Overlapping and distinct relationships between hedonic hunger, uncontrolled eating, food craving, and the obesogenic home food environment during and after a 12-month behavioral weight loss program.

Hedonic hunger, reward-driven eating outside of biological need, is a newer construct in eating behavior research. During behavioral weight loss (BWL), greater improvements in hedonic hunger are associated with higher weight loss, but it remains unclear if hedonic hunger predicts weight loss independent of more well-established, similar constructs (uncontrolled eating and food craving). Research also is needed to understand how hedonic hunger interacts with contextual factors (e.g., obesogenic food environment) during weight loss. Adults (N = 283) in a 12-month randomized controlled trial of BWL were weighed at 0, 12, and 24 months, and completed questionnaires assessing hedonic hunger, food craving, uncontrolled eating, and the home food environment. All variables improved at 12 and 24 months. Decreases in hedonic hunger at 12 months were associated with higher concurrent weight loss, but not when accounting for improvements in craving and uncontrolled eating. At 24 months, reduction in craving was a stronger predictor of weight loss than hedonic hunger, but improvement in hedonic hunger was a stronger predictor of weight loss than change in uncontrolled eating. Changes to the obesogenic home food environment failed to predict weight loss, regardless of levels of hedonic hunger. This study adds novel information on the individual and contextual factors associated with short- and long-term weight control, which can help refine conceptual models and treatment strategies.

Prefrontal cortex activation by binge-eating status in individuals with obesity while attempting to reappraise responses to food using functional near infrared spectroscopy.

PURPOSE: Difficulty reappraising drives to consume palatable foods may promote poorer inhibition and binge eating (BE) in adults with obesity, but neural underpinnings of food-related reappraisal are underexamined. METHODS: To examine neural correlates of food-related reappraisal, adults with obesity with and without BE wore a portable neuroimaging tool, functional near-infrared spectroscopy (fNIRS). fNIRS measured activity in the prefrontal cortex while participants watched videos of food and attempt to "resist" the food stimuli (i.e., "consider the negative consequences of eating the food"). RESULTS: Participants (N = 32, 62.5% female; BMI 38.6 [Formula: see text] 7.1; 43.5 [Formula: see text] 13.4 y) had a BMI > 30 kg/m2. Eighteen adults (67.0% female; BMI 38.2 [Formula: see text] 7.6) reported BE (≥ 12 BE-episodes in preceding 3 months). The control group comprised 14 adults who denied BE (64.0% female; BMI 39.2 [Formula: see text] 6.6). Among the entire sample, mixed models showed significant, small hyperactivation during crave and resist compared to watch (relax) condition bilaterally in the medial superior frontal gyrus, dorsolateral areas, and middle frontal gyrus (optodes 5, 7, 9, 10, 11, and 12) in the total sample. No statistically significant differences in neural activation were observed between the BE and control group. Moreover, there were no significant group by condition interactions on neural activation. CONCLUSION: Among adults with obesity, BE status was not linked to differential activation in inhibitory prefrontal cortex areas during a food-related reappraisal task. Future research is needed with larger samples, adults without obesity, and inhibition paradigms with both behavioral and cognitive components. LEVEL OF EVIDENCE: Level III: Evidence obtained from well-designed cohort or case-control analytic studies. TRIAL REGISTRATION: # NCT03113669, date April 13, 2017.

Commentary on: "What is restrained eating and how do we identify it?": Unveiling the elephant in the room.

This paper is a commentary on Polivy, Herman and Mills' (2020) article, entitled "What is restrained eating and how do we identify it?". Polivy et al.'s paper makes a useful contribution by providing guidelines to researchers for choosing the most appropriate measure of restraint for their research questions. However, the authors assume that restrained eating can be appropriately conceptualized as a trait, an assumption I question. They also assume that restrained eating has a causal influence on the outcomes (e.g., counterregulatory eating, negative affect eating, binge eating) with which it has been associated, which I also question. Finally, they ignored a second prominent model for conceptualizing dieting behavior, the Three-Factor Model of Dieting. The Three-Factor Model decomposes the construct of restrained eating into two types of dieting (current weight loss dieting and weight suppression) that do appear to be causally related to eating control and one type (restrained eating to avoid excessive consumption) that modulates likelihood of overeating but does not cause it. I conclude by noting that scientific progress is best served by promoting, not avoiding, discussion and debate about a multiplicity of perspectives on topics of interest, especially when incompatible hypotheses and data exist on such topics.

The effect of weight suppression on eating behavior: Does the intentionality of weight loss matter?

Weight suppression (WS) has been consistently related to eating pathology. The weight loss that produces weight suppression has always been assumed to be intentional, but no study has tested whether unintentional weight loss would also be associated with eating pathology. The current study examined whether the association between WS and eating pathology may be moderated by intentionality of weight loss in a community-based sample of 520 adults. Participants were categorized into low WS (<5% weight loss from highest past weight), intentional, high WS (>5% intentional weight loss), and unintentional, high WS (>5% unintentional weight loss) groups. The intentional WS group reported greater restraint than the unintentional WS and low WS groups, and the low WS group reported greater restraint and more frequent loss-of-control (LOC) eating than those with unintentional WS. Further, WS was positively related to loss-of-control eating frequency only in the intentional WS group, and negatively associated with LOC eating frequency in the low WS group. Additionally, BMI was positively associated with LOC and binge eating frequency and restraint only in the low WS group. Given the relatively high prevalence of substantial but unintended weight loss found in this study, researchers studying weight suppression should consider asking about intentionality of weight loss and analyzing their data with and without unintentional weight suppressors included in the sample.

Within-subject weight variability in bulimia nervosa: Correlates and consequences.

OBJECTIVE: The oscillations between binge eating, purging, and dieting in bulimia nervosa (BN) may produce substantial within-subject weight variability. Although weight variability has been predictive of eating- and weight-related variables in community samples, it has not been empirically examined in eating disorders. The current study examined cross-sectional and prospective associations between weight variability and BN pathology. METHOD: Four weights were collected over an average of 42.02 days, and weight variability was calculated as the root mean square error around each individual's weight trajectory regression line. Linear regressions were performed to examine the association between weight variability and eating disorder psychopathology, cross-sectionally at baseline and prospectively at 6-month follow-up, adjusting for baseline BMI. RESULTS: Weight variability was cross-sectionally associated with eating pathology, but these relationships became non-significant after adjusting for BMI. However, at 6-month follow-up, greater baseline weight variability predicted increases in body dissatisfaction, shape and weight concerns, and global eating pathology, even after adjusting for baseline BMI. DISCUSSION: These findings demonstrate, for the first time, that within-subject weight variability predicts greater eating disorder pathology over time in BN. The results add to evidence that weight history variables contribute to BN psychopathology above and beyond well-documented psychological dysfunction in BN.

Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to generate personalized predictions of symptom trajectories among patients receiving treatment for EDs, and compared model performance to a simpler logistic regression prediction model. METHOD: Participants were adolescent girls and adult women (N = 333) presenting for residential ED treatment. Self-report progress assessments were completed at admission, discharge, and weekly throughout treatment. Latent growth mixture modeling previously identified three latent treatment response trajectories (Rapid Response, Gradual Response, and Low-Symptom Static Response) and assigned a trajectory type to each patient. Machine learning models (support vector, k-nearest neighbors) and logistic regression were applied to these data to predict a patient's response trajectory using data from the first 2 weeks of treatment. RESULTS: The best-performing machine learning model (evaluated via area under the receiver operating characteristics curve [AUC]) was the radial-kernel support vector machine (AUCRADIAL = 0.94). However, the more computationally-intensive machine learning models did not improve predictive power beyond that achieved by logistic regression (AUCLOGIT = 0.93). Logistic regression significantly improved upon chance prediction (MAUC[NULL] = 0.50, SD = .01; p <.001). DISCUSSION: Prediction of ED treatment response trajectories is feasible and achieves excellent performance, however, machine learning added little benefit. We discuss the need to explore how advance knowledge of expected trajectories may be used to plan treatment and deliver individualized interventions to maximize treatment effects.

A new, developmentally-sensitive measure of weight suppression.

OBJECTIVE: Weight suppression (WS) has demonstrated associations with numerous indices of eating behavior, psychopathology and eating disorder prognosis. However, because WS has traditionally been measured as a simple subtraction of current weight from highest past weight at adult height, this calculation is problematic for most individuals with disordered eating, who usually reach their highest past weight during adolescence. Here we propose a new method for computing WS to address this shortcoming, termed "developmental weight suppression" (DWS), and provide a web-based tool for ease of calculation. METHOD: DWS is calculated as the difference between one's highest premorbid z-BMI (i.e., BMI z-score), and current z-BMI. z-BMIs were calculated using Cole's lambda-mu-sigma (LMS) approach, in accordance with LMS parameters publicly available from the Center for Disease Control (2010). A web-based user interface is available at https://niuxin.shinyapps.io/devws/, making its computation easier and its adoption by researchers simpler. DISCUSSION: By using z-BMIs in place of weights, DWS is more sensitive to the developmentally-relevant factors of age, height, and sex. Preliminary findings suggest that DWS is more strongly related to measures of eating pathology and biological reactions to weight loss than traditionally-computed WS, although more research is needed to test this hypothesis.

Weight variability during self-monitored weight loss predicts future weight loss outcome.

BACKGROUND: Obesity treatments often do not produce long-term results. It is therefore critical to better understand biological and behavioral correlates or predictors of future weight change. OBJECTIVE: We tested the hypothesis that greater weight variability, independent of total body weight change, during early weight loss would predict degree of long-term success. SUBJECTS/METHODS: We included 24,009 American users of the Withings smart scale with over a year's worth of self-monitored weight data. Multilevel modeling was used to calculate weight variability as the root mean square error around participants' weight trajectory regression line, using weekly average weights from the first 12 weeks of weight loss. Linear regressions were then used to examine whether weight variability predicted weight change from week 12 to week 48, 72, and 96. RESULTS: Greater weight variability predicted less weight loss/more weight regain at week 48 (b ± SE: 1.18 ± 0.17, p < 0.001), week 72 (b ± SE: 1.45 ± 0.21, p < 0.001), and week 96 (b ± SE: 1.45 ± 0.23, p < 0.001), controlling for baseline BMI and overall weight change during the first 12 weeks. An interaction effect was found between weight variability and baseline BMI such that the relationship between weight variability and later weight change was stronger in individuals with lower baseline BMI. CONCLUSIONS: This study found that in a large population sample, weight variability early on during weight loss significantly predicted longer term weight loss outcomes. The results provide further support that weight variability be considered an important predictor of future weight change. Research is needed to understand the mechanisms underlying this effect.

Latent trajectories of eating disorder treatment response among female patients in residential care.

OBJECTIVE: Eating disorder (ED) treatment outcomes are highly variable from beginning to end of treatment; however, little is known about differential trajectories during the course of treatment. This study sought to characterize heterogeneous patterns of ED treatment response during residential care. METHOD: Participants were adolescent girls and adult women (N = 360) receiving residential ED treatment for anorexia nervosa, bulimia nervosa, binge-eating disorder, other specified feeding or eating disorder, unspecified feeding or eating disorder, or avoidant/restrictive food intake disorder. Self-report symptom assessments were completed at admission, discharge, and approximately weekly throughout the residential stay to assess curvilinear patterns of change. Latent growth mixture modeling was applied to identify subgroups of patients with similar treatment response trajectories. RESULTS: Three latent groups emerged, including gradual response (58.3%; steady improvements from admission to discharge), rapid response (23.9%; steep early improvements that were maintained through discharge), and low-symptom static response (17.8%; nearly nonclinical self-reported symptoms at admission that remained static through discharge). Groups differed on important clinical characteristics, such as body mass index, endorsement of compensatory behaviors, severity of global ED psychopathology at admission, and degree of symptom improvement by end of treatment. DISCUSSION: Patients follow heterogeneous response patterns in residential ED treatment, and these patterns are associated with differential treatment outcome. Future work should explore whether these trajectories are associated with differential outcomes at follow-up and whether tailoring clinical intervention to a patient's trajectory type can improve treatment response.

Development and validation of a progress monitoring tool tailored for use in intensive eating disorder treatment.

OBJECTIVE: Despite calls for routine use of progress and outcome monitoring in private and intensive treatment centres for eating disorders (EDs), existing measures have limited relevance to these supervised treatment settings. This study sought to develop and validate the progress monitoring tool for eating disorders, a multidimensional measure for progress monitoring in the context of intensive ED treatment. METHOD: Thirty-seven items were generated by a team of content experts, clinicians, and administrative staff from the target treatment setting. Adolescent and adult females (N = 531) seeking residential ED treatment completed the items at admission as part of the clinic's routine assessment battery; 83% were retained for repeat assessment at discharge. Exploratory factor analysis was conducted for preliminary measure development. RESULTS: Results yielded a five-factor, 26-item structure explaining 50% of total variance. Final construct domains included weight and shape concern, ED behaviours and urges, emotion avoidance, adaptive coping, and relational connection. The measure demonstrated adequate internal consistency, sensitivity to change during treatment, and convergence with validated assessment measures. CONCLUSIONS: Preliminary data support the progress monitoring tool for eating disorders as a novel and valid multidimensional measure of treatment-relevant constructs. This measure may have utility in measuring treatment progress for patients receiving intensive treatment for EDs.

Why is premorbid BMI consistently elevated in clinical samples, but not in risk factor samples, of individuals with eating disorders?

Body image disturbance is widely viewed as contributing to the development and maintenance of disordered eating. Yet this perspective is not inconsistent with the possibility that elevated premorbid BMIs also increase the risk of developing eating disorders. Research examining whether actual body size may play a role in eating disorder development reveals a curious pattern of findings. Few prospective risk factor studies conducted with community-based samples found a relationship between premorbid BMI and subsequent eating disorder pathology whereas retrospective research conducted with clinical samples indicates a consistent pattern of elevated premorbid BMIs relative to population norms or control groups. This study documents these disparate findings, considers potential explanations for them and proposes further study of premorbid BMI as a factor contributing to the psychopathology of eating disorders, particularly among those who come to the attention of treatment providers.

The independent and interacting effects of weight suppression and admission body mass index on treatment weight change in patients with anorexia nervosa or bulimia nervosa.

OBJECTIVE: Weight suppression (WS) and body mass index (BMI) have predicted weight change in individuals with eating disorders, but the interaction between these variables is understudied. Furthermore, WS is usually measured as absolute WS-the numeric difference between current weight and highest past weight-overlooking the potentially important influence of how much a person weighed at their highest historical weight. METHOD: The current study investigated the independent and interacting effects of BMI and two measures of WS at admission on residential treatment weight change. WS measures included absolute WS and the relative WS index, the percentage of total body weight lost from highest past weight. Participants were women with anorexia nervosa (n = 357) or bulimia nervosa (n = 293) who provided complete data, 87% of the eligible treatment sample. RESULTS: In both diagnostic subsamples, BMI, absolute WS, and the relative WS index all significantly predicted weight change. The interaction between BMI and WS predicted weight change, but only when the relative WS index was used. DISCUSSION: Results highlight the potential importance of considering an individual's weight and weight history when predicting their treatment weight change and support the importance of utilizing both methods of calculating WS in future research.

The relationship of weight suppression to treatment outcomes during behavioral weight loss.

Many adults enter behavioral weight loss (BWL) programs at a weight below their highest lifetime weight. The discrepancy between highest lifetime weight and current weight is known as weight suppression (WS). Research has yet to characterize WS during BWL or investigate its relation to weight loss outcomes or treatment acceptability. Adults (N = 272) in a 12-month BWL program were assessed. WS was calculated by subtracting measured baseline weight from self-reported highest lifetime weight. Participants with higher WS lost significantly less weight than those with lower WS during treatment, although they still had clinically meaningful weight losses (e.g., participants with WS above the median: 7.8 kg; participants with WS below the median: 12.0 kg). WS was unrelated to weight losses at 24-month follow-up. Controlling for weight loss, treatment acceptability was unrelated to WS. BWL appears appropriate for those with high WS, but future research should aim to improve outcomes in this group.

Implementation of transdiagnostic treatment for emotional disorders in residential eating disorder programs: A preliminary pre-post evaluation.

Objective: Data are lacking from empirically supported therapies implemented in residential programs for eating disorders (EDs). Common elements treatments may be well-suited to address the complex implementation and treatment challenges that characterize these settings. This study assessed the preliminary effect of implementing a common elements therapy on clinician treatment delivery and patient (N = 616) symptom outcomes in two residential ED programs. Method: The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders was adapted to address ED and co-occurring psychopathology and implemented across sites. Therapists' treatment fidelity was rated independently to assess implementation success. Additionally, longitudinal (pre-post) design compared treatment outcomes among patients treated before and after implementation. Patient outcomes included ED and depressive symptoms, experiential avoidance, anxiety sensitivity, and mindfulness. Results: Following training and implementation, clinicians demonstrated adequate to good fidelity. Relative to pre-implementation, post-implementation patients showed significantly greater improvements in experiential avoidance, anxiety sensitivity, and mindfulness at discharge (ps ≤ .04) Relative to patients who were treated during the pre-implementation phase, patients in the post-implementation phase experienced more favorable outcomes on ED symptom severity, depression, mindfulness, and anxiety sensitivity at 6-month-follow-up (ps ≤ .001). A similar result was observed for experiential avoidance, yet this interaction effect was no longer statistically significant (p = .10) when the time x length of stay effect/covariate was added to the model. Conclusions: Preliminary pilot data support the feasibility of implementing transdiagnostic common elements therapy in residential ED treatment, and suggest that implementation may benefit transdiagnostic outcomes for patients. Clinical or methodological significance of this article: Limited data are available to guide evidence-based residential treatment for eating disorders. This study represents a unique effort to adapt, implement, and test an evidence-based therapy protocol across a large private network of intensive eating disorder treatment programs.