Purpose Anorexia nervosa (AN) is a severe psychiatric disorder, and shape and weight concerns are often chronic despite weight normalization. No specific treatments exist for those preoccupations that interfere with recovery and trigger relapse. A case study using a ketogenic diet followed by ketamine infusions led to sustained remission in one patient with chronic AN. Here we conducted an open-label trial to test whether this response could be replicated. Methods Five adults weight recovered from AN but with persistent eating disorder thoughts and behaviors adopted a therapeutic ketogenic diet (TKD) aimed at maintaining weight. After sustaining nutritional ketosis, participants received six ketamine infusions and were followed over 6 months. Results All participants completed the study protocol without significant adverse effects. Two participants maintained TKD for 8 weeks prior to ketamine infusions due to good behavioral response and remained on TKD. Three participants received TKD for 4 weeks prior to and during ketamine, then tapered off after the final infusion. The group showed significant improvements on the Clinical Impairment Assessment (p = 0.008), Eating Disorder Examination Questionnaire (EDEQ) Global score (p = 0.006), EDEQ-Eating Concerns (p = 0.005), EDEQ-Shape Concerns (p = 0.016), EDEQ-Weight Concerns (p = 0.032), Eating Disorders Recovery Questionnaire (EDRQ) Acceptance of Self and Body (0.027) and EDRQ-Social and Emotional Connection (p = 0.001). Weight remained stable, except for one participant who relapsed 4 months after treatment and off TKD. Conclusion This novel treatment appears to be safe and effective for adults with chronic AN-related psychopathology. The results from this open trial support that there are specific neurobiological underpinnings of AN that can be normalized using TKD and ketamine. Level of evidence Level IV, multiple time series with intervention

Background Overweight and obesity are serious public health concerns. As the prevalence of excess weight among individuals continues to increase, there is a parallel need for inexpensive, highly accessible, and evidence-based weight loss programs. Objective This weight loss trial will aim to examine the efficacy of the Noom weight loss program in comparison to a digital control after a 6-month intervention phase and a 24-month maintenance phase, with assessments continuing for 2 years beyond the intervention (to 30 months—after the baseline). The secondary outcomes include quality of life, psychosocial functioning, sleep quality, physical activity, diet, and health status. This trial will also examine the severity of obesity-related functional impairment, weight loss history, and demographic moderators, along with adherence and self-efficacy as mediators of the outcome. Methods A total of 600 participants were randomized in a parallel-group, controlled trial to either Noom Healthy Weight Program (intervention) or Noom Healthy Weight Control (control) for a 6-month intervention. Both intervention and control groups include diet and exercise recommendations, educational content, daily logging capabilities, and daily weigh-in entries. The Noom Healthy Weight Program also includes a coach support for weight loss. Remote follow-up assessments of eating, physical activity, psychosocial factors, app use data, and weight will be conducted at 1, 4, 6, 12, 18, 24, and 30 months after baseline. Weight is measured at each follow-up point during a Zoom call using the participants’ scales. Results Enrollment began in March 2021 and the 6-month intervention phase ended in March 2022. Data collection for the final assessment will be completed in March 2024. Conclusions This study tests commercially available digital lifestyle interventions for individuals with overweight and obesity seeking weight loss support. Data obtained from the study will evaluate whether the Noom Healthy Weight Control Program can help individuals overcome weight loss, achieve long-term maintenance, adhere to lifestyle changes, and feature use barriers that are present in other traditional weight loss treatments. Trial Registration ClinicalTrials.gov NCT04797169; https://clinicaltrials.gov/ct2/show/NCT04797169 International Registered Report Identifier (IRRID) DERR1-10.2196/37541

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Objective: Incorporating open science practices has become a priority for submission criteria in the International Journal of Eating Disorders (IJED). In this systematic review, we used the rigor and reproducibility framework developed by Hildebrandt and Prenoveau (2020) to examine the implementation of statistically sound open science principles in IJED, determining whether the cost and effort of incorporating these practices ultimately make research more likely to be cited. Method: For this systematic review, six trained coders examined 1145 articles published from January 2011 to May 2021, including the 5 years prior to the 2016 introduction of the Open Science Foundation article preregistration. We coded for the presence or absence of 10 specific open science elements and calculated citation metrics for each article.Results: There was evidence of a significant positive relationship between time and total rigor and reproducibility (Total RR) criteria included in IJED articles following the implementation of preregistration in 2016. For every increase in year from 2011 to 2016, there was a .14 decrease in Total RR criteria. From 2016 to 2021, there was a .42 increase per volume in Total RR criteria. There was no statistically significant relationship between Total RR criteria and citation impact. Discussion: Although findings indicate that statistical rigor and reproducibility in this field has increased, the lack of direct relationship between open science methods and article visibility for scientists suggests that there is a limited incentive for researchers to participate in reporting guidelines. Public Significance: Statistical controversies within science threaten the rigor and reproducibility of published research. Open science practices, including the preregistration of study hypotheses, links to statistical code, and explicit data-sharing arguably generate reliable and valid inferences. This review illustrates the rigor and reproducibility of articles published in IJED between 2011 and 2021 and identifies whether open sciences practices have become increasingly prevalent in eating disorder research. ResumenObjetivo: La incorporación de prácticas de ciencia abierta se ha convertido en una prioridad para los criterios de envío en el International Journal of Eating Disorders

Several studies in clinical and non-clinical populations indicate differences between rationally and empirically derived subscales for the Eating Disorder Examination Questionnaire (EDE-Q), including samples of patients seeking bariatric surgery. This study aimed to use exploratory structural equation modelling (ESEM) to estimate the factor structure of the EDE-Q and assess for the additive value of alternative measurement of eating disorder symptoms. Adolescents and adults completed the EDE-Q and a psychiatric evaluation prior to bariatric surgery. Data from 330 participants were analysed using the original four-factor and modified three-factor structure of the EDE-Q using both confirmatory factor analysis (CFA) and exploratory structural equation modelling (ESEM). Age, ethnicity, and body mass index were examined as covariates in the best fitting model, and model subscales used to generate a predictive model of clinician screened DSM-5 eating disorder diagnoses for criterion validity. A CFA of the four-factor EDE-Q provided poor model fit for a pre-surgical bariatric population, but the three-factor EDE-Q and an ESEM of the four-factor EDE-Q provided excellent model fit. The Eating Concern subscale of the four-factor ESEM model significantly predicted eating disorder diagnosis and was positively correlated with age. Our results suggest the ESEM derived factors of the EDE-Q offered some improvements to the original empirically derived factor structure, as subscale scores based on the original items and cross-loading items yielded an adequate prediction of clinician diagnoses.