Dori M. Steinberg

Objective: Treatment outcomes research for avoidant/restrictive food intake disorder (ARFID) has been limited to small, mixed‐age feasibility trials in face‐to‐face care settings. This study aims to examine clinical characteristics and treatment outcomes in a large sample of youth and adult patients receiving virtual multidisciplinary team treatment for ARFID.Method: The sample included N = 783 patients (532 youth and 251 adults) diagnosed with ARFID. Patients received cognitive behavioral therapy for ARFID (CBT‐AR) or family‐based treatment for ARFID (FBT‐ARFID) enhanced by specialized support from a multidisciplinary team. Patients (or caregivers) completed a number of measures assessing ARFID and mood‐related symptoms upon admission and throughout treatment.Results: Youth patients on weight restoration (56%) started treatment around 85% [84%, 86%] of their target weight, and increased to 94% [93%, 96%] by week 35. Adults on weight restoration (47%) started at 85% [84%, 87%] and reached 92% [90%, 94%]. Scores improved for both groups on all PARDI‐AR‐Q subscales: (sensory sensitivity: b = −0.25 [−0.33, −0.16]; lack of interest: b = −0.08 [−0.16, −0.00]; fear of aversive consequences: b = −0.12 [−0.19, −0.04]). Both youth and adults demonstrated reliable improvements in willingness to try new foods (b = −0.64 [−0.89, −0.37]), anxiety symptoms (b = −0.71 [−0.95, −0.48]), and depression symptoms (b = −0.86 [−1.07, −0.64]).Discussion: Youth and adult patients demonstrated reliable symptom improvements over the course of treatment across all measures, offering preliminary support for the effectiveness of FBT‐ARFID and CBT‐AR delivered virtually by a multidisciplinary care team.

Family-based treatment (FBT) is a first-line treatment for adolescents with eating disorders (ED's) for which weight gain early in treatment and caregiver empowerment are predictive of success. A variety of dietary interventions are used in practice, but little is known about their effectiveness. We compared clinical outcomes of patients (N = 100) undergoing eating disorder treatment, and user experience across two virtually delivered interventions: (1) Daily calorie target and (2) Plate-by-Plate™ approach. The calorie group gained more weight on average, though the difference was small (β = 1.62 [-0.02, 3.26]). Participants in both groups improve their eating disorder symptoms at roughly the same rate (β = 0.09 [-0.83, 1.04]). Caregivers in the Plate-by-Plate group increased confidence at a slower rate (β = 0.05 [-0.002, 0.09]). Caregivers rated the daily calorie target as more effective (β = 2.18 [0.94, 3.6]), and rated the two approaches equally for ease of use (β = -0.73 [-1.92, 0.48]). The daily calorie target approach was rated as more effective and was preferred overall by caregivers and dietitians. Findings challenge long-standing assumptions underlying FBT and suggest that clinicians should consider using a calorie framework with caregivers to guide renourishment efforts.

Background: Eating disorders (EDs) affect 9% of the United States population, and anorexia nervosa (AN), specifically, has the second highest mortality rate of all psychiatric disorders. Yet, only 20% are able to access treatment. Access to care issues include long waitlists, lack of trained specialists, financial, and geographic barriers, all of which highlight the need for effective telehealth interventions. Family-based therapy (FBT) is a first-line treatment for adolescents and young adults with EDs, and weight gain early in treatment is considered a primary predictor of success with FBT. However, nutrition requirements for patients with EDs are uniquely complex. A variety of dietary interventions for guiding the renourishment process are used in practice, but empirical data on the effectiveness and acceptability of the various interventions are sparse. The significance of nutritional restoration and issues with access to first-line treatments underscore the need for further research exploring virtually delivered dietary interventions. Objective: Our objective is to compare the effectiveness and acceptability of 2 digitally delivered dietary interventions frequently used in eating disorder treatment settings: (1) calorie-based meal plans and (2) the Plate-by-Plate approach. Specifically, we will explore any potential differences in weight restoration achieved over 8 weeks of treatment as a primary measure of effectiveness, as well as additional treatment outcomes (ED symptoms, anxiety, depression, caregiver burden, and perceived effectiveness and acceptability for both caregivers and clinicians). Methods: Patients (N=100) with either AN or avoidant restrictive food intake disorders (ARFID) aged 6-24 years seeking treatment at a nationwide virtual eating disorder treatment program, were enrolled between May and August 2022. Upon admission, patients were randomly assigned to receive either the calorie-based intervention or Plate-by-Plate approach from their registered dietitian, all of whom have received training as study interventionists. While we were primarily interested in responses during the first 8 weeks of treatment, patients will be followed for up to 12 months. Descriptive statistics were used to describe patient characteristics and demographics. Weight changes and other treatment outcomes between groups will be compared using generalized linear models. Semistructured caregiver and clinician interview transcripts will undergo qualitative analysis. Results: Enrollment ran from March to August 2022, and we anticipate completion of data collection by November 2022. Analyses will be completed in January 2023. Conclusions: This study contributes to existing FBT literature by thoroughly exploring the acceptability of dietary interventions and their influence on weight restoration, an area in which research is sparse. International Registered Report Identifier (IRRID): DERR1-10.2196/41837

BACKGROUND Eating disorders (EDs) affect 9% of the United States population, and anorexia nervosa (AN), specifically, has the second highest mortality rate of all psychiatric disorders. The COVID-19 pandemic has resulted in rising prevalence estimates and exacerbation of ED behaviors and comorbid psychiatric issues. Pre-pandemic access to care issues were thus compounded by long wait lists, lack of trained specialists, financial and geographic barriers, all of which highlight the need for effective telehealth interventions. Family-based therapy (FBT) is a first-line treatment for adolescents and young adults with ED's, though geographic barriers and dearth of trained specialists contribute to challenges with access. Further, weight gain early in treatment is considered a primary predictor of success with FBT, and is predictive of best prognosis. However, nutrition requirements for patients with ED’s are uniquely complex. A variety of dietary interventions for guiding the renourishment process are used in practice, but empirical data on the effectiveness of the various interventions is sparse. The significance of nutritional restoration and issues with access to first-line treatments underscore the need for further research comparing virtually delivered dietary interventions. OBJECTIVE Our objective is to compare effectiveness and acceptability of two virtually-delivered dietary interventions frequently used in eating disorder treatment settings: 1) Calorie-based meal plans and 2) Plate-by-PlateTM (PBP) approach. Specifically, we will explore any potential differences in the rate of weight restoration achieved over 8 weeks of treatment, as well as additional treatment outcomes (e.g., ED symptoms, anxiety, depression), caregiver burden, and perceived ease of use and efficacy for both caregivers and clinicians. METHODS Patients with either anorexia nervosa (AN) or avoidant restrictive food intake disorders (ARFID) ages 6-24 seeking treatment at Equip Health, a nationwide virtual eating disorder treatment program, were enrolled beginning in May 2022. We will continue rolling enrollment until we reach a minimum N=80. Upon admission, patients are randomly assigned to receive either the calorie-based intervention or Plate-by-Plate™ approach from their registered dietitian, all of whom have received training as telehealth study interventionists. Primary outcomes of interest will be collected during the first 8 weeks of treatment, though patients will be followed for up to 12-months. Descriptive statistics will be used to describe patient characteristics and demographics. Rate of weight change and other treatment outcomes between groups will be compared using generalized linear models in R version 4.1.1. Semi-structured interview transcripts will undergo qualitative analysis. RESULTS Data collection for this study began in May 2022, and we anticipate completion of data collection in November of 2022. We plan to complete analysis in December 2022. CONCLUSIONS To our knowledge, this will be the first RCT comparing virtually-delivered dietary interventions for treatment of ED’s. Upon study completion, we hope to add to the growing body of evidence supporting FBT by identifying any potential differences between interventions in effectiveness, acceptability, and ease of use.

Background: Weight bias internalization, also known as weight self-stigma, is a serious health concern for individuals with higher body weight. Weight bias internalization is associated with the greater avoidance of health care and health-promoting activities, disordered eating, social isolation, and weight gain. Elevated weight bias internalization has been associated with low self-compassion, yet few investigations have explored self-compassion as a potential mechanism for reducing internalized weight bias. Objective: Ruby is a 2-arm randomized controlled trial that was designed to test the efficacy of a 4-week digital self-compassion intervention to reduce internalized weight bias compared with a wait-list control. Methods: Adults with elevated internalized weight bias and a BMI of >30 kg/m(2) (N=80) were recruited. Ruby is a standalone digital trial that will be delivered entirely via a smartphone and will involve web based data collection and text messages. The intervention content will include psychoeducation and daily mindfulness practices with a focus on self-compassion and body concerns. We will use intent-to-treat analyses to examine changes in weight bias internalization throughout time by treatment arm. The analyses will be conducted by using one-way analysis of covariance models and linear mixed models. Results: The protocol was designed in May 2020 and approved in December 2020. Data collection is currently underway. Conclusions: Ruby will be the first digital standalone, self-compassion-based intervention designed to reduce internalized weight bias. Owing to its standalone digital delivery, Ruby may be a highly scalable treatment for internalized weight bias that can be delivered on its own or combined with other treatments. We expect Ruby to be accessible to many, as participants can access the digital intervention at times of the day that are the most convenient in their schedule and are not burdened by in-person time commitments, which can be a barrier for participants with competing demands on their time and resources. If efficacious, Ruby will be poised to expand a burgeoning body of literature related to psychological intervention in this area.

BACKGROUND Weight bias internalization, also known as weight self-stigma, is a serious health concern for individuals with higher body weight. Weight bias internalization is associated with the greater avoidance of health care and health-promoting activities, disordered eating, social isolation, and weight gain. Elevated weight bias internalization has been associated with low self-compassion, yet few investigations have explored self-compassion as a potential mechanism for reducing internalized weight bias. OBJECTIVE Ruby is a 2-arm randomized controlled trial that was designed to test the efficacy of a 4-week digital self-compassion intervention to reduce internalized weight bias compared with a wait-list control. METHODS Adults with elevated internalized weight bias and a BMI of >30 kg/m2 (N=80) were recruited. Ruby is a standalone digital trial that will be delivered entirely via a smartphone and will involve web-based data collection and text messages. The intervention content will include psychoeducation and daily mindfulness practices with a focus on self-compassion and body concerns. We will use intent-to-treat analyses to examine changes in weight bias internalization throughout time by treatment arm. The analyses will be conducted by using one-way analysis of covariance models and linear mixed models. RESULTS The protocol was designed in May 2020 and approved in December 2020. Data collection is currently underway. CONCLUSIONS Ruby will be the first digital standalone, self-compassion–based intervention designed to reduce internalized weight bias. Owing to its standalone digital delivery, Ruby may be a highly scalable treatment for internalized weight bias that can be delivered on its own or combined with other treatments. We expect Ruby to be accessible to many, as participants can access the digital intervention at times of the day that are the most convenient in their schedule and are not burdened by in-person time commitments, which can be a barrier for participants with competing demands on their time and resources. If efficacious, Ruby will be poised to expand a burgeoning body of literature related to psychological intervention in this area. CLINICALTRIAL ClinicalTrials.gov NCT04678973; https://clinicaltrials.gov/ct2/show/NCT04678973 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/31307

Background: Effective weight loss interventions exist, yet few can be scaled up for wide dissemination. Further, none has been fully delivered via text message. We used the multiphase optimization strategy (MOST) to develop multicomponent interventions that consist only of active components, those that have been experimentally determined to impact the chosen outcome. Objective: The goal of this study is to optimize a standalone text messaging obesity intervention, Charge, using the MOST framework to experimentally determine which text messaging components produce a meaningful contribution to weight change at 6 months. Methods: We designed a 6-month, weight loss texting intervention based on our interactive obesity treatment approach (iOTA). Participants are randomized to one of 32 experimental conditions to test which standalone text messaging intervention components produce a meaningful contribution to weight change at 6 months. Results: The project was funded in February 2017; enrollment began in January 2018 and data collection was completed in June 2019. Data analysis is in progress and first results are expected to be submitted for publication in 2021. Conclusions: Full factorial trials are particularly efficient in terms of cost and logistics when leveraged for standalone digital treatments. Accordingly, MOST has the potential to promote the rapid advancement of digital health treatments. Subject to positive findings, the intervention will be low cost, immediately scalable, and ready for dissemination. This will be of great potential use to the millions of Americans with obesity and the providers who treat them. Trial Registration: ClinicalTrials.gov NCT03254940; https://clinicaltrials.gov/ct2/show/NCT03254940 International Registered Report Identifier (IRRID): RR1-10.2196/19506

Background: Over 100 million individuals have high blood pressure, and more than half of them are women. The Dietary Approaches to Stop Hypertension (DASH) dietary pattern is a proven lifestyle approach to lower blood pressure, yet population-level adherence is poor. Innovative strategies that promote DASH are needed. Objective: This paper aims to improve adherence to the DASH diet among women with hypertension or prehypertension. Methods: We conducted a 3-month randomized controlled feasibility trial comparing app-based diet tracking (active comparator) to app-based diet tracking plus feedback on DASH adherence via text message (intervention). The intervention platform extracted nutrient data from the app, compared it to DASH recommendations, and sent tailored feedback text messages. Outcomes included the number of days participants tracked their diet, changes in their DASH adherence score, and blood pressure. Results: The women (N=59) had a mean age of 49.9 (SD 11.9) years and were primarily non-Hispanic White (41/59, 69%) and college educated (49/59, 83%). The mean baseline DASH score was 2.3 (SD 1.3). At 3 months, the intervention and active comparator participants had similar mean days tracked per week (4.2, SD 2.1 days vs 4.6, SD 2.7 days; P=.54) and mean changes in their DASH score (0.8, 95% CI 0.2-1.5 vs 0.8, 95% CI 0.4-1.2; P=.75). Intervention participants had lower systolic (mean difference: –2.8 mmHg, 95% CI –1.8 to 7.4; P=.23) and diastolic (mean difference: –3.6 mmHg, 95% CI –0.2 to 7.3; P=.07) blood pressure compared with active comparator participants. Most intervention participants (23/29, 79%) said they would recommend the DASH Cloud intervention to a friend or family member. However, only 34% (10/59) indicated that the feedback text messages helped them reach their diet goals. Conclusions: A digital health intervention to improve DASH adherence is feasible and produces moderately high engagement among women with elevated blood pressure. The intervention did not enhance DASH adherence over diet tracking alone but resulted in greater reductions in blood pressure. Larger studies are needed to determine how digital health interventions can improve population-level adherence to DASH. Trial Registration: ClinicalTrials.gov NCT03215472; https://clinicaltrials.gov/ct2/show/study/NCT03215472

Objective: This study aimed to compare weight collected at clinics and recorded in the electronic health record (EHR) with primary study‐collected trial weights to assess the validity of using EHR data in future pragmatic weight loss or weight gain prevention trials.Methods: For both the Track and Shape obesity intervention randomized trials, clinic EHR weight data were compared with primary trial weight data over the same time period. In analyzing the EHR weights, intervention effects were estimated on the primary outcome of weight (in kilograms) with EHR data, using linear mixed effects models.Results: EHR weight measurements were higher on average and more variable than trial weight measurements. The mean difference and 95% CI were similar at all time points between the estimates using EHR and study‐collected weights.Conclusions: The results of this study can be used to help guide the planning of future pragmatic weight‐related trials. This study provides evidence that body weight measurements abstracted from the EHR can provide valid, efficient, and cost‐effective data to estimate treatment effects from randomized clinical weight loss and weight management trials. However, care should be taken to properly understand the data‐generating process and any mechanisms that may affect the validity of these estimates.