A longstanding problem in the field is that there are almost as many different definitions of recovery in eating disorders as there are studies on the topic. Yet, there has been a general shift to accepting that psychological/cognitive symptoms are important to recovery in addition to physical and behavioral indices. Further, several operationalizations of recovery have been proposed over the past two decades, and some efforts to validate operationalizations exist. However, this work has had limited impact and uptake, such that the field is suffering from "broken record syndrome," where calls are made for universal definitions time and time again. It is critical that proposed operationalizations be compared empirically to help arrive at a consensus definition and that institutional/organizational support help facilitate this. Themes in recent recovery research include identifying predictors, examining biological/neuropsychological factors, and considering severe and enduring anorexia nervosa. From qualitative research, those who have experienced eating disorders highlight recovery as a journey, as well as factors such as hope, self-acceptance, and benefiting from support from others as integral to the process of recovery. The field urgently needs to implement a universal definition of recovery that is backed by evidence, that can parsimoniously be implemented in clinical practice, and that will lead to greater harmonization of scientific findings.

Background Eating disorders (EDs) are severe mental illnesses, with high morbidity, mortality, and societal burden. EDs are extremely heterogenous, and only 50% of patients currently respond to first-line treatments. Personalized and effective treatments for EDs are drastically needed. Methods The current study (N = 34 participants with an ED diagnosis collected throughout the United States) aimed to investigate best methods informing how to select personalized treatment targets utilizing idiographic network analysis, which could then be used for evidence based personalized treatment development. We present initial data collected via experience sampling (i.e., ecological momentary assessment) over the course of 15 days, 5 times a day (75 total measurement points) that were used to select treatment targets for a personalized treatment for EDs. Results Overall, we found that treatment targets were highly variable, with less than 50% of individuals endorsing central symptoms related to weight and shape, consistent with current treatment response rates for treatments designed to target those symptoms. We also found that different aspects of selection methods (e.g., number of items, type of centrality measure) impacted treatment target selection. Conclusions We discuss implications of these data, how to use idiographic network analysis to personalize treatment, and identify areas that need future research. Trial registration: Clinicaltrials.gov, NCT04183894. Registered 3 December 2019—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04183894. NCT04183894 (ClinicalTrials.gov identifier).

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.

Background In the past decade, network analysis (NA) has been applied to psychopathology to quantify complex symptom relationships. This statistical technique has demonstrated much promise, as it provides researchers the ability to identify relationships across many symptoms in one model and can identify central symptoms that may predict important clinical outcomes. However, network models are highly influenced by node selection, which could limit the generalizability of findings. The current study (N = 6850) tests a comprehensive, cognitive–behavioral model of eating-disorder symptoms using items from two, widely used measures (Eating Disorder Examination Questionnaire and Eating Pathology Symptoms Inventory). Methods We used NA to identify central symptoms and compared networks across the duration of illness (DOI), as chronicity is one of the only known predictors of poor outcome in eating disorders (EDs). Results Our results suggest that eating when not hungry and feeling fat were the most central symptoms across groups. There were no significant differences in network structure across DOI, meaning the connections between symptoms remained relatively consistent. However, differences emerged in central symptoms, such that cognitive symptoms related to overvaluation of weight/shape were central in individuals with shorter DOI, and behavioral central symptoms emerged more in medium and long DOI. Conclusions Our results have important implications for the treatment of individuals with enduring EDs, as they may have a different core, maintaining symptoms. Additionally, our findings highlight the importance of using comprehensive, theoretically- or empirically-derived models for NA.

Objective Growing literature suggests that emotions influence the maintenance of eating disorder (ED) symptoms. However, most research has studied the relationship between ED symptoms and affect broadly (i.e., negative affect [NA], positive affect [PA]), rather than examining models comprised of multiple specific affective states (e.g., upset, proud). Method The current study (N = 196 individuals with EDs) used network analysis to examine the most interconnected (i.e., central) NA and PA states in EDs and test the complex associations between specific NA, PA, and ED symptoms. We estimated two networks: one with affective states only and another with affective states and ED symptoms. Results Feeling distressed, afraid, attentive, and determined were the most central symptoms in the affect‐only network. ED symptoms related to overvaluation of weight and shape, including affect‐based ED symptoms (i.e., guilt about eating), were central in the network of affect and ED symptoms. Guilt about eating and shame were central bridge symptoms across affect and ED symptom clusters, meaning that they were each strongly connected across clusters, and may represent important pathways among affect and ED symptoms. Discussion Limitations include the cross‐sectional and between‐person nature of these analyses, from which we cannot derive causal or within‐persons processes. Clinical interventions that target central and bridge symptoms (e.g., fear, shame) may disrupt the reinforcing cycle of NA in EDs that may contribute to ED behaviors. Future research should examine relationships among affective states and ED symptoms in longitudinal and intraindividual network models to develop more effective treatments for EDs.