Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment.

Self-weighing is consistently associated with more effective weight control. However, patterns show that participants disengage from their weight control behaviors following weight gain. Women with BMIs in the overweight/obese range (N = 50) enrolled in a long-term behavioral weight loss program completed ecological momentary assessment (EMA) surveys immediately after their daily weigh-ins. Nightly EMA surveys and self-monitoring data through Fitbit measured their weight control behavior that day. On days when participants gained weight (vs. lost or maintained), they reported more negative mood, more guilt/shame, and lower confidence in weight control. Motivation following daily weight gain depended on participants' overall satisfaction with their weight loss so far: more satisfied participants had marginally higher, but less satisfied participants had marginally lower motivation in response to daily weight gain. Greater guilt/shame and lower motivation after the weigh-in predicted less effective weight control behavior that day (e.g., lower likelihood of calorie tracking, fewer minutes of physical activity). Results demonstrate that even small weight gain is distressing and demoralizing for women in BWL programs, which can lead to goal disengagement. These findings have implications for future BWL interventions, including the potential utility of just-in-time adaptive interventions to promote more adaptive responses in the moments after weigh-ins.

Intraday relations between physical activity and energy intake among behavioral weight loss participants.

OBJECTIVE: Weight loss results from a negative energy balance, when energy intake (EI) is less than energy expended, e.g., from physical activity (PA). However, PA may impact energy balance beyond energy expenditure alone, through indirect effects on eating behavior. Yet, no research has examined if engaging in PA-a central component of most weight loss programs-is associated with same-day EI among individuals with overweight/obesity pursuing weight loss. METHOD: Adults (N = 101) with overweight/obesity in a weight loss program were prescribed a reduced-calorie diet and PA regimen (250 min of moderate-to-vigorous PA at midtreatment). For 3 weeks at midtreatment, PA and EI were measured via an accelerometer and self-monitoring app, respectively. Multilevel models examined within-person relations between PA and EI preceding PA ("pre-PA"), acutely following PA ("acute post-PA," the 2 hr following PA), in the time following the acute post-PA period ("remaining time in day"), and across entire PA days ("full-day"), relative to non-PA matched time periods. RESULTS: EI was higher in the pre-PA and acute post-PA periods. There were no reliable differences in EI during the remaining time in day nor across the full-day on PA days versus within-subject matched non-PA days. There also was insufficient evidence to suggest EI pre-PA, post-PA, or across entire PA days, relative to non-PA matched time periods, was associated with percent weight change. CONCLUSIONS: Findings suggest that engaging in PA was associated with different within-person EI patterns compared to non-PA days, though there was little evidence to support that these patterns relate to weight change. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

"Mindset Matters": Perseverance, a balanced approach and structured support as facilitators of whole foods plant-based adoption.

Whole foods plant-based diets (WFPBD) show potential for preventing and addressing chronic diseases. However, concerns exist about their acceptability and feasibility. Research on firsthand WFPBD adoption experiences is limited but crucial for promoting dietary change. In a 12-week remotely delivered lifestyle modification program using an ad libitum WFPBD, twenty weight-loss seeking adults (ages 18-75) with overweight or obesity completed self-report surveys and semi-structured interviews via Zoom. The study aimed to explore: (1) experiences with WFPBD adoption; (2) factors that helped or hindered adherence; and (3) perceived salient benefits. Interviews were analyzed inductively through a conventional content analysis, and associations between variables examined with correlational analyses. Participants overall reported WFPBD adoption being a positive, new experience, with an equal number (30%) finding it easy/easier than expected as challenging. Key cited challenges included overwhelm, different eating habits in the household, and meal preparation. Key cited facilitators included adopting an incremental approach to dietary change, persisting after setbacks, and having simple go-to meals. Greater self-compassion and family support, and less sabotage from friends and family corresponded to greater dietary change (rs > 0.45, ps < .05). Participants valued accountability, structure, human support, nutrition psychoeducation and recipes in the program. Three categories emerged regarding perceived benefits of following the WFPBD: physical health benefits, improvements to eating habits, and greater perceived control/agency over health. Results indicate that future interventions should include psychological strategies alongside nutrition education to enhance self-efficacy, address household barriers, and combat feelings of overwhelm through sufficient structure, support, and meal preparation guidance. Messaging around WFPBD may benefit from discussing prevailing positive experiences with adoption, common benefits experienced, and options for an incremental approach given that feasibility and acceptability concerns may deter efforts.

A Proof-of-Concept Pilot Test of a Behavioral Intervention to Improve Adherence to Dietary Recommendations for Cancer Prevention.

OBJECTIVES: Prevention programs that can help adults improve the quality of their diets to reduce cancer risk are needed. This Phase IIa study prospectively tested a mHealth intervention designed to improve adherence to dietary quality guidelines for cancer prevention. METHODS: All participants (N = 62) received nutrition education and a self-regulation skills curriculum, with a primary target of changing grocery shopping behavior. Using a randomized, factorial design, the study varied whether each of the following 4 components were added to the 20-week intervention: (1) location-triggered app messaging, delivered when individuals arrived at grocery stores, (2) reflections on benefits of change, delivered with extra coaching time and tailored app messages, (3) coach monitoring, in which food purchases were digitally monitored by a coach, and (4) involvement of a household member in the intervention. RESULTS: Benchmarks were successfully met for recruitment, retention, and treatment acceptability. Across conditions, there were significant reductions in highly processed food intake (P < .001, η2 = .48), red and processed meat intake (P < .001, η2 = .20), and sugar-sweetened beverage intake (P = .008, η2 = .13) from pre-to post-treatment. Analyses examining whether each intervention component influenced change across time found that participants who received coach monitoring increased their intake of fruits, vegetables, and fiber, whereas those with no coach monitoring had less improvement (P = .01, η2 = .14). The improvement in red and processed meat was stronger among participants with household support ON, at a marginally significant level, than those with household support OFF (P = .056, η2 = .07). CONCLUSION: This study showed feasibility, acceptability, and preliminary signals of efficacy of a remotely delivered intervention to facilitate adherence to dietary guidelines for cancer prevention and that coach monitoring and household support may be especially effective strategies. A fully powered clinical trial is warranted to test an optimized version of the intervention that includes nutrition education, self-regulation skills training, coach monitoring, and household member involvement. TRIAL REGISTRATION: ClinicalTrials.gov NCT04947150.

The role of self-compassion and its individual components in adaptive responses to dietary lapses.

Dietary lapses (i.e., instances of dietary non-adherence) are common during weight loss attempts, and compromise success in two ways: increasing caloric intake and demoralizing the participant, sometimes leading them to abandon their weight control goals altogether. Efforts to understand and prevent demoralization have received almost no research attention. Self-compassion has high potential to promote adaptive responses to these setbacks because it reframes "failure" and promotes self-improvement. Past research shows that when participants experience a lapse, those practicing higher self-compassion report higher self-efficacy and intentions to continue dieting. The current study extended this literature to examine whether self-compassion in response to a lapse would predict lower likelihood of a subsequent same-day lapse and greater reports of perceived control over weight management behaviors. We also examined whether the individual facets of self-compassion, including self-kindness (treating oneself the way one would a friend); common humanity (the understanding that everyone has struggles); and mindfulness (non-judgmental awareness of thoughts and feelings) are associated with these outcomes. Participants (N = 140) enrolled in a behavioral weight loss trial completed 6 ecological momentary assessment (EMA) surveys a day for seven days. Total self-compassion and each facet of self-compassion individually were all associated with less negative affect after a lapse. None of the self-compassion variables predicted the likelihood of participants reporting a lapse again that day. However, higher total self-compassion and higher self-kindness after a lapse were both associated with greater perceived self-control over weight management behaviors in the hours following. Common humanity and mindfulness, respectively, were not associated with reports of perceived control. Results suggest that self-compassion following dieting setbacks may prevent goal disengagement, and that self-kindness is the facet most strongly associated with adaptive responses to these setbacks.

Using Wearable Passive Sensing to Predict Binge Eating in Response to Negative Affect Among Individuals With Transdiagnostic Binge Eating: Protocol for an Observational Study.

BACKGROUND: Binge eating (BE), characterized by eating a large amount of food accompanied by a sense of loss of control over eating, is a public health crisis. Negative affect is a well-established antecedent for BE. The affect regulation model of BE posits that elevated negative affect increases momentary risk for BE, as engaging in BE alleviates negative affect and reinforces the behavior. The eating disorder field's capacity to identify moments of elevated negative affect, and thus BE risk, has exclusively relied on ecological momentary assessment (EMA). EMA involves the completion of surveys in real time on one's smartphone to report behavioral, cognitive, and emotional symptoms throughout the day. Although EMA provides ecologically valid information, EMA surveys are often delivered only 5-6 times per day, involve self-report of affect intensity only, and are unable to assess affect-related physiological arousal. Wearable, psychophysiological sensors that measure markers of affect arousal including heart rate, heart rate variability, and electrodermal activity may augment EMA surveys to improve accurate real-time prediction of BE. These sensors can objectively and continuously measure biomarkers of nervous system arousal that coincide with affect, thus allowing them to measure affective trajectories on a continuous timescale, detect changes in negative affect before the individual is consciously aware of them, and reduce user burden to improve data completeness. However, it is unknown whether sensor features can distinguish between positive and negative affect states, given that physiological arousal may occur during both negative and positive affect states. OBJECTIVE: The aims of this study are (1) to test the hypothesis that sensor features will distinguish positive and negative affect states in individuals with BE with >60% accuracy and (2) test the hypothesis that a machine learning algorithm using sensor data and EMA-reported negative affect to predict the occurrence of BE will predict BE with greater accuracy than an algorithm using EMA-reported negative affect alone. METHODS: This study will recruit 30 individuals with BE who will wear Fitbit Sense 2 wristbands to passively measure heart rate and electrodermal activity and report affect and BE on EMA surveys for 4 weeks. Machine learning algorithms will be developed using sensor data to distinguish instances of high positive and high negative affect (aim 1) and to predict engagement in BE (aim 2). RESULTS: This project will be funded from November 2022 to October 2024. Recruitment efforts will be conducted from January 2023 through March 2024. Data collection is anticipated to be completed in May 2024. CONCLUSIONS: This study is anticipated to provide new insight into the relationship between negative affect and BE by integrating wearable sensor data to measure affective arousal. The findings from this study may set the stage for future development of more effective digital ecological momentary interventions for BE. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47098.

Behavioral weight loss outcomes in individuals with binge-eating disorder: A meta-analysis.

OBJECTIVE: Binge-eating disorder (BED) is highly comorbid with obesity. Weight loss may benefit individuals with BED; however, these individuals are often excluded from behavioral weight loss interventions (BWLIs), and findings from BWLIs including participants with and without BED are mixed. To the authors' knowledge, this study represents the first meta-analysis of weight loss outcomes of individuals with and without BED in BWLIs, while adjusting for weight-influencing variables. Treatment dropout rates were also examined. METHODS: Electronic search engines and grey literature search methods were used to identify manuscripts published through December 2022 related to BWLIs and BED. Thirty manuscripts (BED n = 1519; 25 non-BED n = 6345) were included. RESULTS: A meta-regression found that individuals with BED lost less weight compared with individuals without BED (~1.4 kg; ~2.9 kg among studies without meal replacements), but they still lost ~8.1 kg at post-treatment. A random-effects model showed that BED diagnosis increased odds of treatment dropout by 50%. CONCLUSIONS: BWLIs produced robust weight loss in those with BED, but those with BED lost less weight and had higher risk of dropout compared with those without. Future research should aim to close the gap in weight loss outcomes and retention between those with and without BED.

Does virtual reality enhance the effects of inhibitory control training for loss-of-control eating? A pilot factorial experiment.

Inhibitory control, one's ability to inhibit automatic responses to desirable stimuli, may be inadequately targeted in interventions for loss-of-control eating (LOC). Promising evidence has identified inhibitory control trainings (ICTs) as an avenue to target inhibitory control directly; however, effects of ICTs on real-world behavior are limited. Compared to typical computerized trainings, virtual reality (VR) presents several potential advantages that may address key shortcomings of traditional ICTs, i.e. poor approximation to everyday life. The present study utilized a 2 × 2 factorial design of treatment type (ICT vs sham) by treatment modality (VR vs standard computer), which allows for increased statistical power by collapsing across conditions. Our primary aim was to examine the feasibility and acceptability of six weeks of daily training among groups. A secondary aim was to preliminarily assess main and interactive effects of treatment type and modality on target engagement and efficacy (i.e., training compliance, change in LOC episodes, inhibitory control, and implicit liking of foods). Participants (N = 35) with ≥1×/weekly LOC were assigned to one of four conditions and completed ICTs daily for six weeks. The trainings were feasible and acceptable, evinced by high retention and compliance across time and condition. Although completing daily trainings across treatment types and modalities was associated with large decreases in LOC, there were no meaningful effects of either treatment type or modality, nor a significant interaction effect, on LOC or mechanistic variables. Future research should aim to increase the efficacy of ICT (both standard and VR-based) and test in fully-powered clinical trials.

Sharing digital self-monitoring data with others to enhance long-term weight loss: A randomized controlled trial.

BACKGROUND: Participants in behavioral weight loss (BWL) programs increasingly use digital tools to self-monitor weight, physical activity, and dietary intake. Data collected with these tools can be systematically shared with other parties in ways that might support behavior change. METHODS: Adults age 18 to 70 with overweight/obesity (BMI 27-50 kg/m2) will enroll in a remotely delivered, 24-month BWL program designed to produce and maintain a 10% weight loss. Participants will be asked to use a wireless body weight scale, wearable activity sensor, and dietary intake app daily. All participants will receive individual and group counseling, engage in text messaging with members of their group, and appoint a friend or family member to serve in a support role. A 2x2x2 factorial design will test the effects of three types of data sharing partnerships: 1) Coach Share: The behavioral coach will regularly view digital self-monitoring data and address data observations. 2) Group Share: Participants will view each other's self-monitoring data in small-group text messages. 3) Friend/Family Share: A friend or family member will view the participant's data via automated message. The primary outcome is weight loss at 24 months. Mediators and moderators of intervention effects will be tested. CONCLUSION: This study will provide a clear indication of whether data sharing can improve long-term weight loss. This study will be the first to discern the mechanisms of action through which each type of data sharing may be beneficial, and elucidate conditions under which the benefits of data sharing may be maximized.

Telehealth acceptance and commitment therapy for weight loss: Protocol of the WeLNES full scale randomized controlled trial.

Behavioral interventions delivered via one-on-one telephone coaching (hereafter referred to as telehealth) for weight loss have had great population-level reach but to date limited efficacy. Acceptance and Commitment Therapy (ACT) has promise to improve behavioral weight loss treatment efficacy by addressing the fundamental challenges of weight loss and maintenance: overeating in response to internal (e.g., stress) and external (e.g., high calorie foods) cues. Here we describe the Weight Loss, Nutrition, and Exercise Study (WeLNES) randomized controlled trial that is testing the efficacy of an ACT-based telehealth coaching intervention for weight loss in comparison to a Standard Behavioral Therapy (SBT)-based telehealth coaching intervention. A total of 398 adults with overweight or obesity are being recruited and randomized to either ACT or SBT telehealth coaching. Participants in both arms are offered twenty-five telehealth coaching sessions in year one and nine booster sessions in year two. All participants receive a Bluetooth-enabled scale to self-monitor weight and a Fitbit Inspire + Fitbit app for tracking diet and physical activity. The primary aim is to determine whether a greater proportion of ACT participants will achieve a clinically significant weight loss of ≥10% compared with SBT participants at 12-months. Secondary outcomes include change in weight from baseline to 6, 12, and 24-months. Whether the effect of ACT on weight loss is mediated by ACT processes and is moderated by baseline factors will also be examined. If ACT proves efficacious, ACT telehealth coaching will offer an effective, broadly scalable weight loss treatment-thereby making a high public health impact.

Optimizing digital health technologies to improve therapeutic skill use and acquisition alongside enhanced cognitive-behavior therapy for binge-spectrum eating disorders: Protocol for a randomized controlled trial.

OBJECTIVE: Adjunctive mobile health (mHealth) technologies offer promise for improving treatment response to enhanced cognitive-behavior therapy (CBT-E) among individuals with binge-spectrum eating disorders, but research on the key "active" components of these technologies has been very limited. The present study will use a full factorial design to (1) evaluate the optimal combination of complexity of two commonly used mHealth components (i.e., self-monitoring and microinterventions) alongside CBT-E and (2) test whether the optimal complexity level of these interventions is moderated by baseline self-regulation. Secondary aims of the present study include evaluating target engagement associated with each level of these intervention components and quantifying the component interaction effects (i.e., partially additive, fully additive, or synergistic effects). METHOD: Two hundred and sixty-four participants with binge-spectrum eating disorders will be randomized to six treatment conditions determined by the combination of self-monitoring condition (i.e., standard self-monitoring or skills monitoring) and microinterventions condition (i.e., no microinterventions, automated microinterventions, or just-in-time adaptive interventions) as an augmentation to 16 sessions of CBT-E. Treatment outcomes will be measured using the Eating Disorder Examination and compared by treatment condition using multilevel models. RESULTS: Results will clarify the "active" components in mHealth interventions for binge eating. DISCUSSION: The present study will provide critical insight into the efficacy of commonly used digital intervention components (i.e., skills monitoring and microinterventions) alongside CBT-E. Furthermore, results of this study may inform personalization of digital intervention intensity based on patient profiles of self-regulation. PUBLIC SIGNIFICANCE: This study will examine the relative effectiveness of commonly used components of application-based interventions as an augmentation to cognitive-behavioral therapy for binge eating. Findings from this study will inform the development of an optimized digital intervention for individuals with binge eating.

Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial.

Gold standard behavioral weight loss (BWL) is limited by the availability of expert clinicians and high cost of delivery. The artificial intelligence (AI) technique of reinforcement learning (RL) is an optimization solution that tracks outcomes associated with specific actions and, over time, learns which actions yield a desired outcome. RL is increasingly utilized to optimize medical treatments (e.g., chemotherapy dosages), and has very recently started to be utilized by behavioral treatments. For example, we previously demonstrated that RL successfully optimized BWL by dynamically choosing between treatments of varying cost/intensity each week for each participant based on automatic monitoring of digital data (e.g., weight change). In that preliminary work, participants randomized to the AI condition required one-third the amount of coaching contact as those randomized to the gold standard condition but had nearly identical weight losses. The current protocol extends our pilot work and will be the first full-scale randomized controlled trial of a RL system for weight control. The primary aim is to evaluate the hypothesis that a RL-based 12-month BWL program will produce non-inferior weight losses to standard BWL treatment, but at lower costs. Secondary aims include testing mechanistic targets (calorie intake, physical activity) and predictors (depression, binge eating). As such, adults with overweight/obesity (N = 336) will be randomized to either a gold standard condition (12 months of weekly BWL groups) or AI-optimized weekly interventions that represent a combination of expert-led group, expert-led call, paraprofessional-led call, and automated message). Participants will be assessed at 0, 1, 6 and 12 months.

Application of machine learning to discover interactions predictive of dietary lapses.

The purpose of this study it to build a machine learning model to predict dietary lapses with comparable accuracy, sensitivity, and specificity to previous literature while recovering predictor interactions. The sample for the current study consisted of merged data from two separate studies of individuals with obesity/overweight (total N = 87). Participants completed six ecological momentary assessment surveys per day where they were asked about 16 risk factors of lapse and if they had lapsed from their dietary prescriptions since the previous survey. Alcohol consumption and self-efficacy were the most prevalent in the top 10 stable interactions. Alcohol consumption decreased the protective effect of self-efficacy, motivation, and planning. Higher planning predicted higher risk for lapse only when consuming alcohol. Low motivation, hunger, cravings, and lack of healthy food availability increased the protective effect of self-efficacy. Higher self-efficacy increased risk effect of positive mood and having recently eaten a meal on lapse. For individuals with lower levels of self-efficacy, planning increased the risk of lapse. Alcohol intake and self-efficacy interact with several variables to predict dietary lapses, and these interactions should be targeted in just-in-time adaptive interventions that deliver interventions for lapses.

The role of everyday activities on likelihood of dietary lapse: an ecological momentary assessment study.

Developing a more nuanced understanding of factors predicting risk of dietary lapse (i.e., instances of non-adherence to a reduced calorie diet) is important, because dietary lapses contribute to suboptimal weight outcomes. The study investigated, for the first time, how various everyday activities affected likelihood of dietary lapses at two timescales-both in-the-moment, and in the hours after engaging in an activity. Participants (N = 107) with overweight/obesity in a behavioral weight loss program completed ecological momentary assessment surveys on dietary adherence and daily activities for 3 weeks at mid-treatment. Generalized estimating equations revealed that socializing predicted greater concurrent lapse risk, while work/school, doing chores, cooking, or practicing a spiritual activity/prayer/meditation were associated with reduced lapse risk. In terms of subsequent effects, cooking and indoor hobbies were associated with greater lapse risk in the next few hours, whereas spiritual activity/meditation was associated with reduced risk. Certain activities may have affected concurrent and subsequent lapse risk due to: their influence on the presence of tempting food, the compatibility of engaging in the activity and eating simultaneously, and the reward reaped from the activity (potentially reducing desire for food-related reward). Findings speak to the importance of attending to the timescale of relationships between activities and lapses, which has clinical implications for providing nuanced and optimally timed interventions for overweight/obesity.

Gamification and neurotraining to engage men in behavioral weight loss: Protocol for a factorial randomized controlled trial.

Over 70% of men are overweight, and most desire weight loss; however, men are profoundly underrepresented in weight loss programs. Gamification represents a novel approach to engaging men and may enhance efficacy through two means: (1) game-based elements (e.g., streaks, badges, team-based competition) to motivate weight control behaviors and (2) arcade-style "neurotraining" to enhance neurocognitive capacities to resist the temptation of unhealthy foods and more automatically select healthy foods. This study will use a 2 × 2 factorial design to examine the independent and combinatory efficacy of gamification and inhibitory control training (ICT). Men with overweight/obesity (N = 228) will receive a 12-month mobile weight loss program that incorporates behavioral weight loss strategies (e.g., self-monitoring, goal setting, stimulus control). Men will be randomly assigned to a non-gamified or gamified version, and an active or sham ICT. A game design company will create the program, with input from a male advisory panel. Aims of the project are to test whether a gamified (versus non-gamified) weight loss program and/or ICT (versus sham) promotes greater improvements in weight, diet, and physical activity; whether these treatment factors have combinatory or synergistic effects; to test whether postulated mechanisms of action (increased engagement, for gamification, and inhibitory control, for ICT) mediate treatment effects; and whether baseline gameplay frequency and implicit preferences for ICT-targeted foods moderate effects. It is hoped this study will contribute to improved mHealth programs for men and enhance our understanding of the impact of gamified elements and neurocognitive training on weight control.

A Randomized Controlled Trial of CBT+: A Clinician-Controlled, Just-In-Time, Adjunctive Intervention for Bulimia-Spectrum Disorders.

Cognitive Behavior Therapy (CBT) for bulimia nervosa (BN) requires patient skill utilization (use of treatment skills) and skill acquisition (successful skill use) for symptom improvement. Treatment outcomes are unsatisfactory, possibly due to poor skill acquisition and utilization by post-treatment. Just-in-time adaptive interventions (JITAIs), momentary interventions delivered at opportunities for skill practice, may improve skill acquisition and utilization. Participants (N = 56 individuals with bulimia-spectrum eating disorders) completed electronic self-monitoring in CBT+ and received JITAIs or no JITAIs alongside 16 sessions of CBT. Feasibility, acceptability, target engagement, and treatment outcomes were evaluated. JITAIs demonstrated feasibility and acceptability. Treatment outcomes and target engagement did not differ between conditions. The lack of group differences in target engagement and treatment outcomes may be explained by skill use self-monitoring promoting skill utilization and acquisition or low statistical power. Our findings suggest that JITAIs are feasible and acceptable during CBT for BN and warrant additional study.

Testing reward processing models of obesity using in-the-moment assessments of subjective enjoyment of food and non-food activities.

OBJECTIVE: Although altered reward processing is proposed to play a key role in obesity maintenance, the role of food enjoyment and enjoyment of non-food naturally rewarding activities ("non-food enjoyment") in obesity maintenance remains unknown. This study examined how food and non-food enjoyment were associated with baseline body mass index (BMI) and weight loss (WL) following year-long behavioral WL treatment. METHODS: At baseline, participants (MAge = 51.81; 73.8 % White, N = 279) with overweight/obesity completed a 7-day ecological momentary assessment (EMA) protocol inquiring about pleasure/enjoyment derived from eating and non-food activities over the past few hours. Participants also completed retrospective self-report measures of food/non-food enjoyment. With linear regressions, associations between EMA food/non-food enjoyment and BMI and post-treatment WL were examined. Race was included as a covariate. RESULTS: EMA and retrospective food/non-food enjoyment measures had modest concordance, providing preliminary psychometric support for the EMA measures. Partially consistent with hypotheses, greater EMA food enjoyment was associated with lower BMI (B = -1.03, p = .01) and with greater WL, though the latter association was not statistically significant (B = 1.15, p = .07). Exploratory analyses suggested that race was associated with food enjoyment (non-White participants had greater food enjoyment than White participants, d = 0.81, p = .005), and that race may have affected associations between food enjoyment and weight outcomes. Associations between non-food enjoyment and weight outcomes were small and nonsignificant (ps > .93). CONCLUSIONS: Results suggest enjoyment from food, but not from non-food domains, is associated with weight outcomes.

The Role of Physical Activity in Long-term Weight Loss: 36-month Results From a Randomized Controlled Trial.

BACKGROUND: Physical activity (PA) may promote long-term weight loss, but facilitating high levels of PA in behavioral weight loss programs is challenging. PURPOSE: This study reports the 36-month follow-up of a behavioral weight loss trial that tested the efficacy of increasing the emphasis on PA during treatment and using traditional or acceptance-based therapy (ABT) for this purpose. We also examined the extent to which long-term weight loss differed by PA pattern and tested if individual differences in eating behavior moderated this relationship. METHODS: Participants (N = 320) were randomized to (1) standard behavioral weight loss treatment (BT), (2) BT with a focus on PA, or (3) ABT with a focus on PA. Weight loss and PA were measured at 24- and 36-month follow-up. RESULTS: There were no differences between conditions in weight loss or PA at 24 or 36 months. Participants consistently engaging in high PA experienced the greatest weight losses. The positive impact of PA on weight loss was more pronounced among those with low emotional eating and those who believed that exercise did not affect their appetite. CONCLUSIONS: Findings emphasize the difficulty of improving long-term PA among adults with overweight/obesity beyond what standard behavioral weight loss treatment achieves. This study highlights the need to develop new PA treatment strategies, and suggests that ABT for weight loss may be more effective when applied to eating behavior versus PA. Results also demonstrate the importance of addressing problematic eating behavior and cognitions to fully realize the benefits of PA for weight loss. CLINICAL TRIAL INFORMATION: ClinicalTrials.gov identifier: NCT02363010.

Associations between behaviour change technique clusters and weight loss outcomes of automated digital interventions: a systematic review and meta-regression.

Automated digital interventions for weight loss represent a highly scalable and potentially cost-effective approach to treat obesity. However, current understanding of the active components of automated digital interventions is limited, hindering efforts to improve efficacy. Thus, the current systematic review and meta-analysis (preregistration: PROSPERO 2021-CRD42021238878) examined relationships between utilisation of behaviour change techniques (BCTs) and the efficacy of automated digital interventions for producing weight loss. Electronic database searches (December 2020 to March 2021) were used to identify trials of automated digital interventions reporting weight loss as an outcome. BCT clusters were coded using Michie's 93-item BCT taxonomy. Mixed-effects meta-regression was used to examine moderating effects of BCT clusters and techniques on both within-group and between-group measures of weight change. One hundred and eight conditions across sixty-six trials met inclusion criteria (13,672 participants). Random-effects meta-analysis revealed a small mean post-intervention weight loss of -1.37 kg (95% CI, -1.75 to -1.00) relative to control groups. Interventions utilised a median of five BCT clusters, with goal-setting, feedback and providing instruction on behaviour being most common. Use of Reward and Threat techniques, and specifically social incentive/reward BCTs, was associated with a higher between-group difference in efficacy, although results were not robust to sensitivity analyses.

Using Continuous Glucose Monitoring to Detect and Intervene on Dietary Restriction in Individuals With Binge Eating: The SenseSupport Withdrawal Design Study.

BACKGROUND: Dietary restraint is a key factor for maintaining engagement in binge eating among individuals with binge eating disorder (BED) and bulimia nervosa (BN). Reducing dietary restraint is a mechanism of change in cognitive behavioral therapy (CBT) for individuals with BN and BED. However, many individuals who undergo CBT fail to adequately reduce dietary restraint during treatment, perhaps owing to difficulty in using treatment skills (eg, regular eating) to reduce dietary restraint during their daily lives. The SenseSupport system, a novel just-in-time, adaptive intervention (JITAI) system that uses continuous glucose monitoring to detect periods of dietary restraint, may improve CBT to reduce dietary restraint during treatment by providing real-time interventions. OBJECTIVE: This study aimed to describe the feasibility, acceptability, and initial evaluation of SenseSupport. We presented feasibility, acceptability, target engagement, and initial treatment outcome data from a small trial using an ABAB (A=continuous glucose monitoring data sharing and JITAIs-Off, B=continuous glucose monitoring data sharing and JITAIs-On) design (in which JITAIs were turned on for 2 weeks and then turned off for 2 weeks throughout the treatment). METHODS: Participants (N=30) were individuals with BED or BN engaging in ≥3 episodes of ≥5 hours without eating per week at baseline. Participants received 12 sessions of CBT and wore continuous glucose monitors to detect eating behaviors and inform the delivery of JITAIs. Participants completed 4 assessments and reported eating disorder behaviors, dietary restraint, and barriers to app use weekly throughout treatment. RESULTS: Retention was high (25/30, 83% after treatment). However, the rates of continuous glucose monitoring data collection were low (67.4% of expected glucose data were collected), and therapists and participants reported frequent app-related issues. Participants reported that the SenseSupport system was comfortable, minimally disruptive, and easy to use. The only form of dietary restraint that decreased significantly more rapidly during JITAIs-On periods relative to JITAIs-Off periods was the desire for an empty stomach (t43=1.69; P=.049; Cohen d=0.25). There was also a trend toward greater decrease in overall restraint during JITAs-On periods compared with JITAIs-Off periods, but these results were not statistically significant (t43=1.60; P=.06; Cohen d=0.24). There was no significant difference in change in the frequency of binge eating during JITAIs-On periods compared with JITAIs-Off periods (P=.23). Participants demonstrated clinically significant, large decreases in binge eating (t24=10.36; P<.001; Cohen d=2.07), compensatory behaviors (t24=3.40; P=.001; Cohen d=0.68), and global eating pathology (t24=6.25; P<.001; Cohen d=1.25) from pre- to posttreatment. CONCLUSIONS: This study describes the successful development and implementation of the first intervention system combining passive continuous glucose monitors and JITAIs to augment CBT for binge-spectrum eating disorders. Despite the lower-than-anticipated collection of glucose data, the high acceptability and promising treatment outcomes suggest that the SenseSupport system warrants additional investigation via future, fully powered clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT04126694; https://clinicaltrials.gov/ct2/show/NCT04126694.