Optimizing relapse prevention and changing habits (REACH+) in anorexia nervosa.

INTRODUCTION: Relapse rates in anorexia nervosa (AN) are high, even after full weight restoration. This study aims to develop a relapse prevention treatment that specifically addresses persistent maladaptive behaviors (habits). Relapse Prevention and Changing Habits (REACH+) aims to support patients in developing routines that promote weight maintenance, encourage health, and challenge habits that perpetuate illness. The clinical trial design uses the Multiphase Optimization STrategy (MOST) framework to efficiently identify which components of treatment contribute to positive outcomes. METHODS: Participants will be 60 adults with AN who have achieved weight restoration in an inpatient setting. Treatment will consist of 6 months of outpatient telehealth sessions. REACH+ consists of behavior, cognitive, and motivation components, as well as food monitoring and a skill consolidation phase. A specialized online platform extends therapy between sessions. Participants will be randomly assigned to different versions of each component in a fractional factorial design. Outcomes will focus on maintenance of remission, measured by rate of weight loss and end-of-trial status. Interventions that contribute to remission will be included in an optimized treatment package, suitable for a large-scale clinical trial of relapse prevention in AN.

Identifying behavioral types of dietary lapse from a mobile weight loss program: Preliminary investigation from a secondary data analysis.

Success in behavioral weight loss (BWL) programs depends on adherence to the recommended diet to reduce caloric intake. Dietary lapses (i.e., deviations from the BWL diet) occur frequently and can adversely affect weight loss outcomes. Research indicates that lapse behavior is heterogenous; there are many eating behaviors that could constitute a dietary lapse, but they are rarely studied as distinct contributors to weight outcomes. This secondary analysis aims to evaluate six behavioral lapse types during a 10-week mobile BWL program (eating a large portion, eating when not intended, eating an off-plan food, planned lapse, being unaware of caloric content, and endorsing multiple types of lapse). Associations between weekly behavioral lapse type frequency and weekly weight loss were investigated, and predictive contextual characteristics (psychological, behavioral, and environmental triggers for lapse) and individual difference (e.g., age, gender) factors were examined across lapse types. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used a mobile BWL program for 10 weeks, self-weighed weekly using Bluetooth scales, completed daily ecological momentary assessment of lapse behavior and contextual characteristics, and completed a baseline demographics questionnaire. Linear mixed models revealed significant negative associations between unplanned lapses and percent weight loss. Unplanned lapses from eating a large portion, eating when not intended, and having multiple "types" were significantly negatively associated with weekly percent weight loss. A lasso regression showed that behavioral lapse types share many similar stable factors, with other factors being unique to specific lapse types. Results add to the prior literature on lapses and weight loss in BWL and provide preliminary evidence that behavioral lapse types could aid in understanding adherence behavior and developing precision medicine tools to improve dietary adherence.

Using ecological momentary assessment to better understand dietary lapse types.

Frequency of lapsing from a diet predicts weight loss failure, however previous studies have only utilized one definition of dietary lapse. No study has examined different types of lapse behaviors among individuals with overweight/obesity. The current study uses ecological momentary assessment (EMA) to examine predictors of three lapse types-eating a larger portion than intended, eating an unintended type of food, and eating at an unplanned time-in adults (N = 189; MBMI = 36.93 ±â€¯5.83 kg/m2; 82.0% female; Mage = 51.81 ±â€¯9.76 years) enrolled in a 12-month randomized controlled trial of two behavioral weight loss treatments. Participants completed 14 days of EMA at the start of treatment during which they indicated types of lapses that occurred with time and location of the lapse. Participants also responded to questions assessing current physical (e.g., hunger, tiredness), environmental (e.g., presence of "delicious" foods), and affective (e.g., loneliness, sadness) states at each prompt. Weight change was assessed at post-treatment. Separate generalized estimating equations were used to examine whether states prospectively predicted lapse occurrence at the next survey. Results indicated that lapse types differed significantly across time and location. Momentary increases in deprivation, hunger, and boredom increased likelihood of different lapse types. Lastly, we examined the prospective association between lapse type and weight loss. Eating at an unintended time was the only lapse type that predicted worse weight loss outcomes. Results support the theory that distinct lapse types exist, and that lapse types can be predicted by both momentary conditions and individual tendencies toward certain physical and affective states. However, not all lapse types may impact weight outcomes. Future research on behaviors that constitute dietary lapse is warranted and could inform personalized weight loss treatments.

Identifying the mechanisms through which behavioral weight-loss treatment improves food decision-making in obesity.

OBJECTIVES: Behavioral weight loss (BWL) programs are the recommended treatment for obesity, yet it is unknown whether these programs change one's ability to use self-control in food choices and what specific mechanisms support such change. Using experimental economics methods, we investigated whether changes in dietary behavior in individuals with obesity following BWL are driven by one or more of the following potential mechanisms: changes in the perception of the 1) health or 2) taste of food items, and/or 3) shifting decision weights for health versus taste attributes. Therefore, we compared these mechanisms between obese participants and lifetime normal weight controls (NW) both before and after BWL. METHODS: Females with obesity (N = 37, mean BMI = 33.2) completed a food choice task involving health ratings, taste ratings, and decision-making pre- and post-standard BWL intervention. NW controls (N = 30, BMI = 22.4) completed the same task. RESULTS: Individuals with obesity exhibited increased self-control (selecting healthier, less tasty food choices) post-treatment. However, their rates of self-control remained significantly lower than NW. We found no differences in initial health perceptions across groups, and no changes with treatment. In contrast, taste ratings and the relative value of taste versus health decreased following treatment. Although, post-treatment participants continued to perceive unhealthy foods as tastier and used less self-control than NW controls, they showed significant improvements in these domains following a BWL intervention. CONCLUSIONS: To help individuals improve dietary decisions, additional research is needed to determine how to make greater changes in taste preferences and/or the assignment of value to taste versus health attributes in food choices.

Pragmatic Implementation of Online Obesity Treatment and Maintenance Interventions in Primary Care: A Randomized Clinical Trial.

Importance: Behavioral weight loss interventions have achieved success in primary care; however, to our knowledge, pragmatic implementation of a fully automated treatment that requires little researcher oversight has not been tested. Moreover, weight loss maintenance remains a challenge. Objective: To evaluate the long-term effectiveness of an automated, online, behavioral obesity treatment program (Rx Weight Loss [RxWL]) at 12 months (primary end point) and 24 months when delivered pragmatically in primary care and to compare the effectiveness of 3 weight loss maintenance approaches. Design, Setting, and Participants: This randomized clinical trial of RxWL, an online weight loss program, recruited patients from a Rhode Island primary care network with approximately 60 practices and 100 physicians. Eligible participants were primary care patients aged 18 to 75 years with overweight or obesity who were referred by their nurse care manager and enrolled between 2018 and 2020. All participants were included in the intention-to-treat analysis, whereas only those who engaged with maintenance intervention were included in the per-protocol analysis. Data were analyzed from August 2022 to September 2023. Interventions: All participants were offered the same 3-month weight loss program, with randomization to one of three 9-month maintenance programs: control intervention (monthly online newsletters), monthly intervention (9 monthly video lessons and 1 week of self-monitoring per month), or refresher intervention (an introductory session and two 4-week periods of lessons and self-monitoring at 7 and 10 months). Main Outcomes and Measures: The primary outcome was weight change at 12 months using height and weight data collected from electronic medical records through 24 months. Results: Among the 540 participants (mean [SD] age, 52.8 [13.4] years; 384 females [71.1%]) in the intention-to-treat analysis, mean estimated 3-month weight loss was 3.60 (95% CI, -4.32 to -2.88) kg. At the 12-month primary end point, the amount of weight regained in the monthly (0.37 [95% CI, -0.06 to 0.81] kg) and refresher (0.45 [95% CI, 0.27 to 0.87] kg) maintenance groups was significantly less than that in the newsletter control maintenance group (1.28 [95% CI, 0.85 to 1.71] kg; P = .004). The difference in weight regain between the monthly and refresher maintenance groups was not statistically significant. This pattern persisted at 24 months. In the per-protocol analysis of 253 participants, mean weight loss at the end of the initial 3-month intervention was 6.19 (95% CI, -7.25 to -5.13) kg. Similarly, at 12 months there was less weight regain in the monthly (0.61 kg) and refresher (0.96 kg) maintenance groups than in the newsletter control maintenance group (1.86 kg). Conclusions and Relevance: Results of this randomized clinical trial indicate that pragmatic implementation of a 12-month automated, online, behavioral obesity treatment that includes 9 months of active maintenance produces clinically significant weight loss over 2 years in primary care patients with overweight or obesity. These findings underscore the importance of providing ongoing maintenance intervention to prevent weight regain. Trial Registration: ClinicalTrials.gov Identifier: NCT03488212.

An Adaptive Telephone Coaching Intervention for Patients in an Online Weight Loss Program: A Randomized Clinical Trial.

Importance: Weight loss (WL) during the first month of a behavioral program is associated with longer-term WL. Testing of translatable and adaptive obesity programs is needed. Objective: To compare brief, extended, and no telephone coaching for individuals with suboptimal response (ie, 1-month WL <4%) within an online WL program. Design, Setting, and Participants: This randomized clinical trial with enrollment between March 2019 and April 2022 (data collection completed May 2023) was conducted at an academic research center in the US. Eligible participants included adults aged 18 to 70 years with daily access to internet and a body mass index between 25 and 45. Interventions: All participants received an automated online WL program (4 months) and WL maintenance program (8 months), consisting of video lessons, self-monitoring, and personalized feedback. Participants were randomized, such that individuals with suboptimal response received either brief telephone coaching (3 calls during weeks 5-8), extended telephone coaching (12 calls during weeks 5-16), or no coaching (control). Coaching included education, problem solving, and goal setting, and promoted engagement with the online program. Main Outcomes and Measures: The primary outcomes were percent weight change and proportion of participants achieving 5% or greater WL at 4 and 12 months. A priori hypotheses for WL were that WL for extended coaching would be greater than for brief coaching, and both extended and brief coaching would be greater than no coaching (control). A longitudinal mixed-effects model with participant-specific intercept was used to examine intervention effects on percent WL at 4 and 12 months. Secondary analyses focused on program engagement and cost/kilogram of WL. Results: The study included a total of 437 participants who reported WL at 1 month (mean [SD] age, 50.8 [11.4] years; mean [SD] BMI, 34.6 [5.0]; 305 female [69.8%] and 132 male [30.2%]) with 148 randomized to extended coaching, 143 assigned to brief coaching, and 146 assigned to the control group. Of all participants, 346 (79.2%) were considered to have a suboptimal response. WL at 4 months was significantly greater in the extended coaching group (mean [SD] WL, -7.0% [5.1%]) and brief coaching group (mean [SD] WL, -6.2% [4.7%]) vs the control group (mean [SD] WL, -4.5% [4.7%]) (P < .001). Similarly, the proportion of participants achieving 5% or greater WL at 4 months was greater in the extended coaching group (89 participants [65.9%]) and brief coaching group (77 participants [58.5%]) vs control group (46 participants [36.5%]) (P < .001). At 12 months, a similar pattern was observed for achievement of 5% WL or greater (extended coaching, 63 participants [48.1%]; brief coaching, 58 participants [45.9%]; control, 38 participants [32.8%]; P = .03). Percent WL at 12 months was significantly higher in extended coaching vs control (mean [SD] WL for extended coaching, -5.5% [6.7%]; mean [SD] WL for control, -3.9% [7.4%]; P = .03) but not for brief coaching (mean [SD] WL, -4.9% [6.1%]).Both the brief and extended coaching groups watched more lessons and self-monitored on more days compared with the control group. The cost per additional kilogram of WL, beyond that of the control group, was $50.09 for brief coaching and $92.65 for extended coaching. Conclusions and Relevance: In this randomized clinical trial testing an adaptive intervention, the provision of coaching for individuals with suboptimal response improved WL and was cost-effective; further testing in clinical settings (eg, health care systems) is warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT03867981.

Consistent exercise timing as a strategy to increase physical activity: A feasibility study.

Introduction/Purpose: Observational research suggests that consistent exercise timing could be leveraged to promote moderate-to-vigorous physical activity (MVPA) among adults with obesity. However, the feasibility and acceptability of prescribed consistent exercise timing in a free-living setting is unknown. The purpose of this study was to assess the feasibility and acceptability of prescribed consistent exercise timing in a free-living setting among inactive adults with obesity (primary) and to compare MVPA timing prescriptions and characterize exercise barriers/facilitators (secondary). Methods: Using a within-subjects design, inactive adults with obesity (n=15) were randomized in counterbalanced order to three 3-wk exercise timing conditions separated by 2-wk washout periods: 1) consistent morning, 2) consistent evening, and 3) choice timing (control). Feasibility was assessed using prespecified benchmarks. Acceptability and preferred timing were assessed with questionnaires post-intervention. Secondarily, exercise timing and MVPA were assessed via accelerometry and nightly surveys and barriers/facilitators were assessed with nightly surveys. Results: All feasibility benchmarks were achieved (e.g., timing adherence = 69.9% via accelerometry and 87.4% via self-report (target: ≥60%)). Consistent exercise timing was acceptable (mean rating = 3.7 of 5 (target: ≥3.5)). Choice was the most popular prescription. There were medium- to large-sized effects (partial η2 of 0.09-0.16) of condition on MVPA; MVPA was higher during the morning and evening conditions versus choice condition. Facilitators were similar across conditions, while some barriers were time specific. Conclusion: Prescribed exercise timing in a free-living setting appears feasible and acceptable. While choice timing was most preferred, consistent timing appeared most effective for increasing MVPA. Data warrant larger trials to test the efficacy and mechanisms of consistent exercise timing as a translational strategy for promoting MVPA. Pending findings from a fully powered randomized trial, practitioners interested in promoting MVPA among their patients or clients could consider encouraging exercise at a consistent time day-to-day.

Contextual influences on implementation of online behavioral obesity treatment in primary care: formative evaluation guided by the consolidated framework for implementation research.

Online behavioral obesity treatment is a promising first-line approach to weight management in primary care. However, little is known about contextual influences on implementation. Understand qualitative contextual factors that affect the implementation process, as experienced by key primary care stakeholders implementing the program. Online behavioral obesity treatment was implemented across a 60-clinic primary care practice network. Patients were enrolled by nurse care managers (NCMs; N = 14), each serving 2-5 practices. NCMs were randomized to one of two implementation conditions-"Basic" (standard implementation) or "Enhanced" (i.e., with added patient tracking features and more implementation strategies employed). NCMs completed qualitative interviews guided by the Consolidated Framework for Implementation Research (CFIR). Interviews were transcribed and analyzed via directed content analysis. Emergent categories were summarized by implementation condition and assigned a valence according to positive/negative influence. Individuals in the Enhanced condition viewed two aspects of the intervention as more positively influencing than Basic NCMs: Design Quality & Packaging (i.e., online program aesthetics), and Cost (i.e., no-cost program, clinician time savings). In both conditions, strongly facilitating factors included: Compatibility between intervention and clinical context; Intervention Source (from a trusted local university); and Evidence Strength & Quality supporting effectiveness. Findings highlight the importance of considering stakeholders' perspectives on the most valued types of evidence when introducing a new intervention, ensuring the program aligns with organizational priorities, and considering how training resources and feedback on patient progress can improve implementation success for online behavioral obesity treatment in primary care.

Pragmatic implementation of a fully automated online obesity treatment in primary care.

OBJECTIVE: Behavioral obesity treatment implemented in primary care is efficacious but typically involves face-to-face or phone contact. This study evaluated enrollment, engagement, and 12-week weight loss in a fully automated online behavioral weight-loss intervention implemented pragmatically in a primary care network. METHODS: As part of routine primary care, providers and nurse care managers offered a no-cost online obesity treatment program to 1,721 patients. Of these, 721 consented and were eligible (aged 18-75 years with BMI ≥ 25 kg/m2 and internet access), and 464 started the program. The program included 12 weekly online lessons, a self-monitoring platform, and automated feedback. RESULTS: More than one-quarter of patients who were offered the program (26%) initiated treatment. In intent-to-treat analyses using all data available, mean 12-week weight change was -5.10% (SE = 0.21). Patients who submitted their weights on all 12 weeks (37% of 464) lost an estimated 7.2% body weight versus 3.4% in those submitting less frequently. CONCLUSIONS: This fully automated online program, implemented into the routine workflow of a primary care setting without any human counseling or researcher involvement, produced clinically meaningful short-term weight loss. Greater program engagement was associated with greater weight loss; efforts are needed to understand barriers to engagement.

Examination of the relationship between lapses and weight loss in a smartphone-based just-in time adaptive intervention.

We developed a smartphone-based just-in-time adaptive intervention (JITAI), called OnTrack, that provides personalized intervention to prevent dietary lapses (i.e., nonadherence from the behavioral weight loss intervention diet). OnTrack utilizes ecological momentary assessment (EMA; repeated electronic surveys) for self-reporting lapse triggers, predicts lapses using machine learning, and provides brief intervention to prevent lapse. We have established preliminary feasibility, acceptability, and efficacy of OnTrack, but no study has examined our hypothesized mechanism of action: reduced lapse frequency will be associated with greater weight loss while using OnTrack. This secondary analysis investigated the association between lapse frequency and the weekly percentage of weight loss. Post hoc analyses evaluated the moderating effect of OnTrack engagement on this association. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used OnTrack with a digital weight loss program for 10 weeks. Engagement with OnTrack (i.e., EMA completed and interventions accessed) was recorded automatically, participants self-reported dietary lapses via EMA, and weighed weekly using Bluetooth scales. Linear mixed models with a random effect of subject and fixed effect of time revealed a nonsignificant association between weekly lapses and the percentage of weight loss. Post hoc analyses revealed a statistically significant moderation effect of OnTrack engagement such that fewer EMA and interventions completed conferred the expected associations between lapses and weight loss. Lapses were not associated with weight loss in this study and one explanation may be the influence of engagement levels on this relationship. Future research should investigate the role of engagement in evaluating JITAIs.

Comparing ecological momentary assessment to sensor-based approaches in predicting dietary lapse.

Ecological momentary assessment (EMA; brief self-report surveys) of dietary lapse risk factors (e.g., cravings) has shown promise in predicting and preventing dietary lapse (nonadherence to a dietary prescription), which can improve weight loss interventions. Passive sensors also can measure lapse risk factors and may offer advantages over EMA (e.g., objective, automatic, semicontinuous data collection), but currently can measure only a few lapse predictors, a notable limitation. This study preliminarily compared the burden and accuracy of commercially available sensors versus established EMA in lapse prediction. N = 23 adults with overweight/obesity completed a 6-week commercial app-based weight loss program. Participants wore a Fitbit, enabled GPS tracking, completed EMA, and reported on EMA and sensor burden poststudy via a 5-point Likert scale. Sensed risk factors were physical activity and sleep (accelerometer), geolocation (GPS), and time, from which 233 features (measurable characteristics of sensor signals) were extracted. EMA measured 19 risk factors, lapse, and categorized GPS into meaningful geolocations. Two supervised binary classification models (LASSO) were created: the sensor model predicted lapse with 63% sensitivity (true prediction rate of lapse) and 60% specificity (true prediction rate of non-lapse) and EMA model with 59% sensitivity and 72% specificity. EMA model accuracy was higher, but self-reported EMA burden (M = 2.96, SD = 1.02) also was higher (M = 1.50, SD = 0.94). EMA model accuracy was superior, but EMA burden was higher than sensor burden. Findings highlight the promise of sensors in contributing to lapse prediction, and future research may use EMA, sensors, or both depending on prioritization of accuracy versus participant burden.

Primary care clinicians' perspectives on clinical decision support to enhance outcomes of online obesity treatment in primary care: A qualitative formative evaluation.

OBJECTIVE: Online behavioral treatment for obesity produces clinically-meaningful weight losses among many primary care patients. However, some patients experience poor outcomes (i.e., failure to enroll post-referral, poor weight loss, or premature disengagement). This study sought to understand primary care clinicians' perceived utility of a clinical decision support system (CDSS) that would alert clinicians to patients' risk for poor outcome and guide clinician-delivered rescue interventions to reduce risk. METHODS: Qualitative formative evaluation was conducted in the context of an ongoing pragmatic clinical trial implementing online obesity treatment in primary care. Interviews were conducted with 14 nurse care managers (NCMs) overseeing patients' online obesity treatment. Interviews inquired about the potential utility of CDSS in primary care, desired alert frequency/format, and priorities for alert types (non-enrollment, poor weight loss, and/or early disengagement). We used matrix analysis to generate common themes across interviews. RESULTS: Nearly all NCMs viewed CDSS as potentially helpful in clinical practice. Alerts for patients at risk for disengagement were of highest priority, though all alert types were generally viewed as desirable. Regarding frequency and delivery mode of patient alerts, NCMs wanted to balance the need for prompt patient intervention with minimizing clinician burden. Concerns about CDSS emerged, including insufficient time to respond promptly and adequately to alerts and the need to involve other support staff for patients requiring ongoing rescue intervention. CONCLUSIONS: NCMs view CDSS for online obesity treatment as potentially feasible and clinically useful. For optimal implementation in primary care, CDSS must minimize clinician burden and facilitate collaborative care.

Refining an algorithm-powered just-in-time adaptive weight control intervention: A randomized controlled trial evaluating model performance and behavioral outcomes.

Suboptimal weight losses are partially attributable to lapses from a prescribed diet. We developed an app (OnTrack) that uses ecological momentary assessment to measure dietary lapses and relevant lapse triggers and provides personalized intervention using machine learning. Initially, tension between user burden and complete data was resolved by presenting a subset of lapse trigger questions per ecological momentary assessment survey. However, this produced substantial missing data, which could reduce algorithm performance. We examined the effect of more questions per ecological momentary assessment survey on algorithm performance, app utilization, and behavioral outcomes. Participants with overweight/obesity (n = 121) used a 10-week mobile weight loss program and were randomized to OnTrack-short (i.e. 8 questions/survey) or OnTrack-long (i.e. 17 questions/survey). Additional questions reduced ecological momentary assessment adherence; however, increased data completeness improved algorithm performance. There were no differences in perceived effectiveness, app utilization, or behavioral outcomes. Minimal differences in utilization and perceived effectiveness likely contributed to similar behavioral outcomes across various conditions.

Weight loss in Weight Watchers Online with and without an activity tracking device compared to control: A randomized trial.

OBJECTIVE: To evaluate a commercial online weight loss program and activity tracker, which are popular but have unknown efficacy. METHODS: Two hundred seventy-nine participants with BMI 27 to 40 kg/m2 were randomized to 12 months of the Weight Watchers Online program alone (WWO) or with the ActiveLink® activity tracking device (WWO+AL) or an online newsletter (Control). RESULTS: Weight losses at 3 months were significantly greater in WWO (2.7 kg [95% confidence interval (CI), 2.0-3.5 kg] than Control (1.3 kg [95% CI, 0.5-2.0 kg]; P = 0.01); neither differed from WWO+AL (2.0 kg [95% CI, 1.3-2.7 kg]; Ps > 0.56). Significantly more WWO participants (24.5%) achieved ≥ 5% weight loss at 3 months than Control (9.4%) (P = 0.01); neither differed from WWO+AL (17.6%) (Ps = 0.13-0.28). At 12 months, there were no significant differences between groups in weight loss (Ps > 0.52). WWO (25.5%) continued to have a higher proportion of participants achieving ≥ 5% weight loss than Control (12.9%) (P = 0.04); neither differed from WWO+AL (14.3%) (Ps > 0.10). There were no significant between-group differences in change in physical activity (Ps > 0.17). CONCLUSIONS: WWO produced significantly more weight loss at 3 months relative to Control, but not at 12 months. Significantly more WWO than Control participants lost ≥ 5% at both 3 and 12 months. Participants receiving an activity tracking device did not achieve greater weight loss or physical activity increases than those in a Control condition.

A randomized trial of an acceptance-based behavioral intervention for weight loss in people with high internal disinhibition.

OBJECTIVE: To determine whether an acceptance-based behavioral intervention (ABBI) produces better weight losses than standard behavioral treatment (SBT) among individuals reporting high internal disinhibition. METHODS: Participants were 162 adults with overweight or obesity (mean BMI 37.6 kg/m2 ) randomly assigned to ABBI or SBT. Both interventions provided the same calorie intake target, exercise goal, and self-monitoring skills training. SBT incorporated current best practice interventions for addressing problematic thoughts and emotions. ABBI utilized acceptance-based techniques based on Acceptance and Commitment Therapy. ABBI and SBT were compared on weight change and internal disinhibition change over 24 months. RESULTS: Mixed models analysis showed mean weight loss at 24 months was -4.1% (SE = 0.88) for ABBI and -2.4% (SE = 0.87) for SBT (P = 0.204). Secondary analyses showed that the ABBI group regained less weight from the end of treatment to the final follow-up (4.6 vs. 7.1 kg; P = 0.005), and that a significantly higher proportion of ABBI participants achieved a 5% weight loss (38% vs. 25%; P = 0.038) at 24 months. CONCLUSIONS: Results suggest that ABBI could be helpful for improving the maintenance of weight loss for individuals who report high internal disinhibition.

Exercise improves quality of life in bariatric surgery candidates: results from the Bari-Active trial.

OBJECTIVE: To examine the impact of a pre-bariatric surgery physical activity intervention (PAI), designed to increase bout-related (≥10 min) moderate to vigorous PA (MVPA), on health-related quality of life (HRQoL). METHODS: Analyses included 75 adult participants (86.7% female; BMI = 45.0 ± 6.5 kg m(-2)) who were randomly assigned to 6 weeks of PAI (n = 40) or standard pre-surgical care (SC; n = 35). PAI received 6 individual weekly counseling sessions to increase walking exercise. Participants wore an objective PA monitor for 7 days and completed the SF-36 Health Survey at baseline and post-intervention to evaluate bout-related MVPA and HRQoL changes, respectively. RESULTS: PAI increased bout-related MVPA from baseline to post-intervention (4.4 ± 5.5 to 21.0 ± 21.4 min day(-1)) versus no change (7.9 ± 16.6 to 7.6 ± 11.5 min day(-1)) for SC (P = 0.001). PAI reported greater improvements than SC on all SF-36 physical and mental scales (P < 0.05), except role-emotional. In PAI, better baseline scores on the physical function and general health scales predicted greater bout-related MVPA increases (P < 0.05), and greater bout-related MVPA increases were associated with greater post-intervention improvements on the physical function, bodily pain, and general health scales (P < 0.05). CONCLUSIONS: Increasing PA preoperatively improves physical and mental HRQoL in bariatric surgery candidates. Future studies should examine whether this effect improves surgical safety, weight loss outcomes, and postoperative HRQoL.