Design of the PACIFIC study: A randomized controlled trial evaluating a novel treatment for adults with overweight and obesity.

The majority of adults in the United States have overweight or obesity which is associated with significant health and psychological consequences. Behavioral Weight Loss (BWL) is the current gold-standard weight-loss program for adults but recidivism rates continue to be disturbingly high. Given the health consequences of excess weight and the lack of long-term effectiveness of BWL, it is important to identify novel weight-loss programs. We developed the ROC (Regulation of Cues) program to reduce overeating through improvement in sensitivity to appetitive cues and decreased responsivity to external food cues. This study is a 4-arm randomized control trial designed to evaluate the efficacy of ROC, ROC combined with BWL, BWL alone and an active comparator over 24 months. Study recruitment completed in November 2017. Two hundred and seventy-one participants were randomized (mean age = 46.97 years; 82% female, mean BMI = 34.59; 20% Hispanic) and assessments were conducted at baseline, mid-treatment (6 months) and post-treatment (12 months). At this time, participants are completing 6- (18 months) and 12-month (24 months) follow-ups. Targeting novel mechanisms is critically important to improve weight-loss programs. Through this trial, we hope to identify treatments for adults with overweight and obesity to facilitate long-term weight loss and improved health

Evaluating psychometric properties of the Emotional Eating Scale Adapted for Children and Adolescents (EES-C) in a clinical sample of children seeking treatment for obesity: a case for the unidimensional model.

BackgroundThe Emotional Eating Scale - Adapted for Children and Adolescents (EES-C) assesses children's urge to eat in response to experiences of negative affect. Prior psychometric studies have demonstrated the high reliability, concurrent validity, and test-retest reliability of theoretically defined subconstructs among non-clinical samples of children and adolescents who were primarily healthy weight; however, no psychometric studies exist investigating the EES-C among clinical samples of children with overweight/obesity (OW/OB). Furthermore, studies conducted in different contexts have suggested a discordant number of subconstructs of emotions related to eating. The purpose of this study was to evaluate the validity of the EES-C in a clinical sample of children seeking weight-loss treatment.MethodUsing a hierarchical bi-factor approach, we evaluated the validity of the EES-C to measure a single general construct, a set of two separate correlated subconstructs, or a hierarchical arrangement of two constructs, and determined reliability in a clinical sample of treatment-seeking children with OW/OB aged 8-12 years (N = 147, mean age = 10.4 years.; mean BMI z = 2.0; female = 66%; Hispanic = 32%, White and other = 68%).ResultsComparison of factor-extraction methods suggested a single primary construct underlying EES-C in this clinical sample. The bi-factor indices provided clear evidence that most of the reliable variance in the total score (90.8 for bi-factor model with three grouping factors and 95.2 for bi-factor model with five grouping factors) was attributed to the general construct. After adjusting for relationships with the primary construct, remaining correlations among sets of items did not suggest additional reliable constructs.ConclusionResults suggest that the primary interpretive emphasis of the EES-C among treatment-seeking children with overweight or obesity should be placed on a single general construct, not on the 3- or 5- subconstructs as was previously suggested

A framework for applying natural language processing in digital health interventions

BACKGROUND: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. OBJECTIVE: This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. METHODS: We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopathology (including binge eating and purging behaviors) and improving body image. These users generated 37,228 intervention text snippets and exchanged 4285 user-coach messages, which were analyzed using the proposed model. RESULTS: We applied the framework to predict binge eating behavior, resulting in an area under the curve between 0.57 (when applied to new users) and 0.72 (when applied to new symptom reports of known users). In addition, initial evidence indicated that specific text features predicted the therapeutic outcome of reducing ED symptoms. CONCLUSIONS: The case study demonstrates the usefulness of a structured approach to text data analytics. NLP techniques improve the prediction of symptom changes in DHIs. We present a technical framework that can be easily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts

Effectiveness of a digital cognitive behavior therapy-guided self-help intervention for eating disorders in college women: A cluster randomized clinical trial

Importance: Eating disorders (EDs) are common, serious psychiatric disorders on college campuses, yet most affected individuals do not receive treatment. Digital interventions have the potential to bridge this gap. Objective: To determine whether a coached, digital, cognitive behavior therapy (CBT) intervention improves outcomes for college women with EDs compared with referral to usual care. Design, Setting, and Participants: This cluster randomized trial was conducted from 2014 to 2018 at 27 US universities. Women with binge-purge EDs (with both threshold and subthreshold presentations) were recruited from enrolled universities. The 690 participants were followed up for up to 2 years after the intervention. Data analysis was performed from February to September 2019. Interventions: Universities were randomized to the intervention, Student Bodies-Eating Disorders, a digital CBT-guided self-help program, or to referral to usual care. Main Outcomes and Measures: The main outcome was change in overall ED psychopathology. Secondary outcomes were abstinence from binge eating and compensatory behaviors, as well as ED behavior frequencies, depression, anxiety, clinical impairment, academic impairment, and realized treatment access. Results: A total of 690 women with EDs (mean [SD] age, 22.12 [4.85] years; 414 [60.0%] White; 120 [17.4%] Hispanic; 512 [74.2%] undergraduates) were included in the analyses. For ED psychopathology, there was a significantly greater reduction in the intervention group compared with the control group at the postintervention assessment (β [SE], -0.44 [0.10]; d = -0.40; t1387 = -4.23; P \u3c .001), as well as over the follow-up period (β [SE], -0.39 [0.12]; d = -0.35; t1387 = -3.30; P \u3c .001). There was not a significant difference in abstinence from any ED behaviors at the postintervention assessment (odds ratio, 1.48; 95% CI, 0.48-4.62; P = .50) or at follow-up (odds ratio, 1.51; 95% CI, 0.63-3.58; P = .36). Compared with the control group, the intervention group had significantly greater reductions in binge eating (rate ratio, 0.82; 95% CI, 0.70-0.96; P = .02), compensatory behaviors (rate ratio, 0.68; 95% CI, 0.54-0.86; P \u3c .001), depression (β [SE], -1.34 [0.53]; d = -0.22; t1387 = -2.52; P = .01), and clinical impairment (β [SE], -2.33 [0.94]; d = -0.21; t1387 = -2.49; P = .01) at the postintervention assessment, with these gains sustained through follow-up for all outcomes except binge eating. Groups did not differ in terms of academic impairment. The majority of intervention participants (318 of 385 participants [83%]) began the intervention, whereas only 28% of control participants (76 of 271 participants with follow-up data available) sought treatment for their ED (odds ratio, 12.36; 95% CI, 8.73-17.51; P \u3c .001). Conclusions and Relevance: In this cluster randomized clinical trial comparing a coached, digital CBT intervention with referral to usual care, the intervention was effective in reducing ED psychopathology, compensatory behaviors, depression, and clinical impairment through long-term follow-up, as well as realizing treatment access. No difference was found between the intervention and control groups for abstinence for all ED behaviors or academic impairment. Given its scalability, a coached, digital, CBT intervention for college women with EDs has the potential to address the wide treatment gap for these disorders. Trial Registration: ClinicalTrials.gov Identifier: NCT02076464

Eating disorders in weight-related therapy (EDIT): protocol for a systematic review with individual participant data meta-analysis of eating disorder risk in behavioural weight management

The Eating Disorders In weight-related Therapy (EDIT) Collaboration brings together data from randomised controlled trials of behavioural weight management interventions to identify individual participant risk factors and intervention strategies that contribute to eating disorder risk. We present a protocol for a systematic review and individual participant data (IPD) meta-analysis which aims to identify participants at risk of developing eating disorders, or related symptoms, during or after weight management interventions conducted in adolescents or adults with overweight or obesity. We systematically searched four databases up to March 2022 and clinical trials registries to May 2022 to identify randomised controlled trials of weight management interventions conducted in adolescents or adults with overweight or obesity that measured eating disorder risk at pre- and post-intervention or follow-up. Authors from eligible trials have been invited to share their deidentified IPD. Two IPD meta-analyses will be conducted. The first IPD meta-analysis aims to examine participant level factors associated with a change in eating disorder scores during and following a weight management intervention. To do this we will examine baseline variables that predict change in eating disorder risk within intervention arms. The second IPD meta-analysis aims to assess whether there are participant level factors that predict whether participation in an intervention is more or less likely than no intervention to lead to a change in eating disorder risk. To do this, we will examine if there are differences in predictors of eating disorder risk between intervention and no-treatment control arms. The primary outcome will be a standardised mean difference in global eating disorder score from baseline to immediately post-intervention and at 6- and 12- months follow-up. Identifying participant level risk factors predicting eating disorder risk will inform screening and monitoring protocols to allow early identification and intervention for those at risk