Stephanie P. Goldstein

Background: Over 70% of US adults are overweight or have obesity. Internet-delivered weight loss (IDWL) treatment overcomes many common barriers to in-person weight loss (WL) programs; yet, IDWLs underperform compared to in-person treatment. Yoga is a novel intervention that targets physical and psychological health and can be delivered virtually, increasing translation potential. Yoga has been understudied as an intervention to address barriers to WL despite favorable effects in other health disciplines. Preliminary studies suggest yoga to improve self-regulation and reduce lapses from dietary recommendations, 2 factors integral to long-term WL success. Objective: The aim of the study is to conduct the first fully powered randomized controlled trial to test the added effect of yoga to IDWL treatment on weight (primary outcome), dietary lapses, potential lapse triggers, and self-regulation mediator variables (secondary outcomes). Methods: Adults that are overweight or have obesity will be recruited to participate in a 12-month IDWL program. Following a 3-month assessment, eligible participants will be randomized to (1) a yoga intervention, including 14 weeks of group-based, virtual Iyengar yoga delivered twice weekly, followed by 22 weeks of yoga delivered once per week, and then 6 months of no contact, or (2) a contact-matched wellness comparison condition. Assessments will take place at baseline, 3 months, 6 months, 12 months, and 18 months. Several questionnaires, ecological momentary assessments, and objectively measured weight and accelerometry data will be collected. This trial is registered on ClinicalTrials.gov (NCT06166225). Results: This randomized trial was funded with an original project period of July 2023-June 2028. Enrollment began in February 2024 and is ongoing with the expectation of closing enrollment in June 2026. Conclusions: This trial will examine the combined effect of yoga and WL treatment among individuals with overweight or obesity and will be the first fully powered trial to assess the combination of virtually delivered yoga and WL beyond 6 months. Findings will inform whether yoga could be considered a valuable intervention component for improving IDWL treatment.

Objective: Dysregulated eating is common among youth and is associated with trait‐level negative affect and emotion regulation difficulties. Despite the transient nature of affect, momentary associations among affect and eating behavior are unclear, which limits development of more impactful treatment tools, such as “just‐in‐time” intervention approaches (JITAI). The current study (N = 62) drew from two ecological momentary assessment (EMA) studies involving children and adolescents who endorsed loss of control (LOC) eating symptoms during a two‐week assessment period.Method: Intensive time series network analysis tested concurrent and prospective relationships across six specific affective states (i.e., upset, guilty, scared, tired, excited, attentive) and four eating‐related experiences (e.g., LOC, overeating, hunger, craving) in real time. Additionally, we repeated these models within demographic subgroups of the sample based on age, race, and sex.Results: In the full‐sample models, contemporaneously assessed guilt was associated with craving and LOC eating, and tiredness was associated with LOC eating. In the prospective analysis, tiredness was negatively predicted by LOC eating and positively predicted by overeating at the previous timepoint, and attentiveness positively predicted craving. Differences in affect‐eating relationships were identified across teens and preteens as well as male and female participants.Discussion: These results suggest that specific affective states are associated with dysregulated eating‐related experiences in real time among youth, and associations may differ depending on demographic characteristics. Findings may be used to inform the development and tailoring of momentary interventions.

Self-monitoring technology (e.g., smartphone applications) aids weight loss, but its role in weight maintenance remains under studied. To evaluate use and perceptions of self-monitoring technologies in National Weight Control Registry (NWCR) participants (adults who have maintained a ≥30lbs loss for ≥1 year) who maintained versus regained weight. NWCR participants completed an online survey about self-monitoring technology use and perceptions. Of 1,000 invited participants, 794 completed the survey. Those who reported gaining ≥2.3kg (5lbs) in the past year were categorized as the "regain" group (40.8%); those reporting p<.01) and diet (p<.01) but not exercise (p=.23) than "maintain". There were no differences in wearable trackers interest, most valued features, or use barriers, but the "regain" group was more likely to report guilt, discouragement, body image concerns, and anxiety about weight loss when using behavior-tracking technologies (p<.001); rates of discontinuation from these feelings or unhealthy weight control practices were not different between groups. This appears to be the first study investigating naturalistic use of self-monitoring technology in a demographically homogenous sample maintaining significant weight loss. The "regain" group was more likely to use self-monitoring technology but reported more tracking-associated negative feelings. Future research must determine how to support individuals emotionally and with weight maintenance when self-monitoring contributes to negative byproducts. Other work should identify the optimal elements of self-monitoring technology for weight loss maintenance.

Objective: Lifestyle intervention can produce clinically significant weight loss and reduced disease risk/severity for many individuals with overweight/obesity. Dietary lapses, instances of non-adherence to the recommended dietary goal(s) in lifestyle intervention, are associated with less weight loss and higher energy intake. There are distinct “types” of dietary lapse (e.g., eating an off-plan food, eating a larger portion), and behavioral, psychosocial, and contextual mechanisms may differ across dietary lapse types. Some lapse types also appear to impact weight more than others. Elucidating clear lapse types thus has potential for understanding and improving adherence to lifestyle intervention. Methods: This 18-month observational cohort study will use real-time digital assessment tools within a multi-level factor analysis framework to uncover “lapse phenotypes” and understand their impact on clinical outcomes. Adults with overweight/obesity ( n = 150) will participate in a 12-month online lifestyle intervention and 6-month weight loss maintenance period. Participants will complete 14-day lapse phenotyping assessment periods at baseline, 3, 6, 12, and 18 months in which smartphone surveys, wearable devices, and geolocation will assess dietary lapses and relevant phenotyping characteristics. Energy intake (via 24-h dietary recall) and weight will be collected at each assessment period. Results: This trial is ongoing; data collection began on 31 October 2022 and is scheduled to complete by February 2027. Conclusion: Results will inform novel precision tools to improve dietary adherence in lifestyle intervention, and support updated theoretical models of adherence behavior. Additionally, these phenotyping methods can likely be leveraged to better understand non-adherence to other health behavior interventions. Trial Registration: This study was prospectively registered https://clinicaltrials.gov/study/NCT05562427

This paper presents new methods to detect eating from wrist motion. Our main novelty is that we analyze a full day of wrist motion data as a single sample so that the detection of eating occurrences can benefit from diurnal context. We develop a two-stage framework to facilitate a feasible full-day analysis. The first-stage model calculates local probabilities of eating $P(E_{w})$ within windows of data, and the second-stage model calculates enhanced probabilities of eating $P(E_{d})$ by treating all $P(E_{w})$ within a single day as one sample. The framework also incorporates an augmentation technique, which involves the iterative retraining of the first-stage model. This allows us to generate a sufficient number of day-length samples from datasets of limited size. We test our methods on the publicly available Clemson All-Day (CAD) dataset and FreeFIC dataset, and find that the inclusion of day-length analysis substantially improves accuracy in detecting eating episodes. We also benchmark our results against several state-of-the-art methods. Our approach achieved an eating episode true positive rate (TPR) of 89% with 1.4 false positives per true positive (FP/TP), and a time weighted accuracy of 84%, which are the highest accuracies reported on the CAD dataset. Our results show that the daily pattern classifier substantially improves meal detections and in particular reduces transient false detections that tend to occur when relying on shorter windows to look for individual ingestion or consumption events.

The ethical, legal, and social implications (ELSIs) of digital health are important when researchers and practitioners are using technology to collect, process, or store personal health data. Evidence underscores a strong need for digital health ELSI training, yet little is known about the specific ELSI topic areas that researchers and practitioners would most benefit from learning. To identify ELSI educational needs, a needs assessment survey was administered to the members of the Society of Behavioral Medicine (SBM). We sought to identify areas of ELSI proficiency and training need, and also evaluate interest and expertise in ELSI topics by career level and prior ELSI training history. The 14-item survey distributed to SBM members utilized the Digital Health Checklist tool (see recode.health/tools) and included items drawn from the four-domain framework: data management, access and usability, privacy and risk to benefit assessment. Respondents (N = 66) were majority faculty (74.2%) from psychology or public health. Only 39.4% reported receiving “formal” ELSI training. ELSI topics of greatest interest included practices that supported participant engagement, and dissemination and implementation of digital tools beyond the research setting. Respondents were least experienced in managing “bystander” data, having discussions about ELSIs, and reviewing terms of service agreements and privacy policies with participants and patients. There is opportunity for formalized ELSI training across career levels. Findings serve as an evidence base for continuous and ongoing evaluation of ELSI training needs to support scientists in conducting ethical and impactful digital health research. New technologies are increasingly used in research and practice, which introduce new ethical, legal, and social implications (ELSIs). While there are scholars who study ELSIs in research, it is important that behavioral scientists have ELSI training in order to identify and mitigate possible harms and maximize benefits among their patients/participants, particularly when using technologies that collect personal health information. ELSI training opportunities are limited and, because ELSI is a broad complicated field, we know very little about the specific topics that researchers/practitioners would benefit from learning. To understand ELSI training needs specific to the field of digital health, we asked the members of the Society of Behavioral Medicine, a multidisciplinary nonprofit organization, to tell us about which ELSI areas they are most interested in. We found that 39.4% of members received formal ELSI training. Members were most interested in using technology to help patients/participants stay engaged in their treatments, and developing technologies that can be used outside of research (in the “real world”). Members were least experienced in reviewing terms of service/privacy policies and handling information collected from non-patient/participants (people in the backgrounds of voice recordings/videos). Training interests differed by career level (faculty vs. students), and so future ELSI trainings could be more beneficial if they were mindful of prior experiences.

Background: Children with loss of control (LOC) eating and overweight/obesity have relative deficiencies in trait‐level working memory (WM), which may limit adaptive responding to intra‐ and extra‐personal cues related to eating. Understanding of how WM performance relates to eating behavior in real‐time is currently limited.Methods: We studied 32 youth (ages 10–17 years) with LOC eating and overweight/obesity (LOC‐OW; n = 9), overweight/obesity only (OW; n = 16), and non‐overweight status (NW; n = 7). Youth completed spatial and numerical WM tasks requiring varying degrees of cognitive effort and reported on their eating behavior daily for 14 days via smartphone‐based ecological momentary assessment. Linear mixed effects models estimated group‐level differences in WM performance, as well as associations between contemporaneously completed measures of WM and dysregulated eating.Results: LOC‐OW were less accurate on numerical WM tasks compared to OW and NW (ps < .01); groups did not differ on spatial task accuracy (p = .41). Adjusting for between‐subject effects (reflecting differences between individuals in their mean WM performance and its association with eating behavior), within‐subject effects (reflecting variations in moment‐to‐moment associations) revealed that more accurate responding on the less demanding numerical WM task, compared to one's own average, was associated with greater overeating severity across the full sample (p = .013). There were no associations between WM performance and LOC eating severity (ps > .05).Conclusions: Youth with LOC eating and overweight/obesity demonstrated difficulties mentally retaining and manipulating numerical information in daily life, replicating prior laboratory‐based research. Overeating may be related to improved WM, regardless of LOC status, but temporality and causality should be further explored.Public significance statement: Our findings suggest that youth with loss of control eating and overweight/obesity may experience difficulties mentally retaining and manipulating numerical information in daily life relative to their peers with overweight/obesity and normal‐weight status, which may contribute to the maintenance of dysregulated eating and/or elevated body weight. However, it is unclear whether these individual differences are related to eating behavior on a moment‐to‐moment basis.

Weight and shape concern (WSC) is a facet of negative body image that is common among individuals with overweight/obesity seeking behavioral weight loss treatment (BWL), but remains understudied. This secondary analysis evaluates associations between WSC, weight change, and weight-related behaviors among individuals in a 24-week BWL. Adults (n = 32) with body mass index 25–50 kg/m² completed a baseline WSC questionnaire, measured weight at 12 and 24 weeks, measured physical activity via accelerometer, and completed 24-hour dietary recalls. Adherence to self-monitoring dietary intake and weight were assessed. A series of linear mixed models were used to evaluate associations between baseline WSC and weight change, as well as weight-related behaviors. Results revealed no significant effect of WSC on weight change. There were significant WSC x time interactions, such that those rating WSC “very important” decreased self-weighing and the “low importance” group decreased their caloric intake during treatment. The “pretty important” group had greater minutes of activity than the “low importance” group. Findings indicated that WSC may impact weight-related behaviors that contribute to BWL success. This trial was pre-registered on ClinicalTrials.gov (NCT03739151).

Background: Dietary lapses can hinder weight loss and yoga can improve self‐regulation, which may protect against lapses. This study examined the effect of yoga on dietary lapses, potential lapse triggers (e.g., affective states, cravings, dietary temptations), and reasons for initiating eating following weight loss treatment.Methods: Sixty women with overweight/obesity (34.3 ± 3.9 kg/m²) were randomized to a 12 week yoga intervention (2x/week; YOGA) or contact‐matched control (cooking/nutrition classes; CON) following a 12‐week behavioral weight loss program. Participants responded to smartphone surveys (5x/day) over a 10‐day period at baseline, 12, and 24 weeks to assess lapses and triggers.Results: At 24 weeks, YOGA and CON differed on several types of lapses (i.e., less eating past full, eating more than usual, loss of control when eating, self‐identified overeating, difficulty stopping eating in YOGA), and YOGA was less likely to eat to feel better or in response to stress (ps < 0.05). YOGA also reported less stress and anxiety and more positive affect (ps < 0.01); dietary temptations and cravings did not differ from CON.Conclusion: Yoga resulted in fewer dietary lapses and improved affect among women with overweight/obesity following weight loss. While preliminary, findings suggest that yoga should be considered as a potential component of weight loss treatment to target dietary lapses.