A baseline comparison of three diagnostic groups using the Progress Monitoring Tool for Eating Disorders.

Utilisation of intensive inpatient treatment for eating disorders (EDs) has climbed in the last decade, illuminating a need for better consensus on what constitutes effective treatment and context-appropriate progress/outcome monitoring during residential stays. The novel Progress Monitoring Tool for Eating Disorders (PMED) measure is specifically designed for inpatient settings. Previous research supports the factorial validity and internal consistency of the PMED; however, additional work is needed to determine its appropriateness for complex patient populations. This study used measurement invariance (MI) testing to determine if the PMED administered at programme admission measures the same items in similar ways across patients with anorexia nervosa restricting- and binge-purge subtypes (AN-R; AN-BP) and bulimia nervosa (BN, N = 1121; Mage  = 24.33 years, SD = 10.20; 100% female). Progressively constrained models were used to determine the level of invariance upheld between the three groups. Results indicated that, while the PMED meets configural and metric MI, it does not display scalar invariance. Said otherwise, the PMED similarly assesses constructs and items across AN-R, AN-BP, and BN, however the same score overall may reflect different levels of psychopathology for patients in one diagnostic category versus another. Comparisons of severity between different EDs should be made with caution, however the PMED appears to be a sound tool for understanding the baseline functioning of patients with EDs in an inpatient setting.

Applying a Social Determinants of Health Framework to Guide Digital Innovations That Reduce Disparities in Chronic Disease.

ABSTRACT: Chronic diseases are among the top causes of global death, disability, and health care expenditure. Digital health interventions (e.g., patient support delivered via technologies such as smartphones, wearables, videoconferencing, social media, and virtual reality) may prevent and mitigate chronic disease by facilitating accessible, personalized care. Although these tools have promise to reach historically marginalized groups, who are disproportionately affected by chronic disease, evidence suggests that digital health interventions could unintentionally exacerbate health inequities. This commentary outlines opportunities to harness recent advancements in technology and research design to drive equitable digital health intervention development and implementation. We apply "calls to action" from the World Health Organization Commission on Social Determinants of Health conceptual framework to the development of new, and refinement of existing, digital health interventions that aim to prevent or treat chronic disease by targeting intermediary, social, and/or structural determinants of health. Three mirrored "calls to action" are thus proposed for digital health research: a) develop, implement, and evaluate multilevel, context-specific digital health interventions; b) engage in intersectoral partnerships to advance digital health equity and social equity more broadly; and c) include and empower historically marginalized groups to develop, implement, and access digital health interventions. Using these "action items," we review several technological and methodological innovations for designing, evaluating, and implementing digital health interventions that have greater potential to reduce health inequities. We also enumerate possible challenges to conducting this work, including leading interdisciplinary collaborations, diversifying the scientific workforce, building trustworthy community relationships, and evolving health care and digital infrastructures.

Real-time versus retrospective self-report assessment of loss-of-control eating in adults undergoing bariatric surgery.

OBJECTIVE: Loss-of-control (LOC) eating is common in adults undergoing bariatric surgery. Agreement between real-time and retrospective assessment methods is unclear. METHODS: Adults with severe obesity reported on LOC eating over the preceding 28 days via Eating Disorder Examination-Questionnaire (EDE-Q) items and in near real time over 10 days via ecological momentary assessment (EMA; involving daily repeated surveys delivered via smartphone in the natural environment), with both assessment forms completed before surgery and at 3, 6, and 12 months after surgery. Wilcoxon signed rank tests and generalized linear mixed models were used to compare participants' EDE-Q and EMA reports of subjectively and objectively large LOC episodes across time points. RESULTS: Participants reported subjectively large LOC episodes more frequently via EMA than EDE-Q across time points, although differences did not reach statistical significance (all p > 0.05). Conversely, objectively large LOC episodes were more frequently reported via EDE-Q than EMA, with differences reaching significance at 6 months post surgery only (p = 0.03). CONCLUSIONS: Agreement between real-time and retrospective assessments of LOC eating varied by episode size and time elapsed in the year following surgery. These findings should be considered when designing assessment batteries for bariatric surgery-seeking adults and when extrapolating research findings across studies with diverging methods of real-time versus retrospective self-report assessment of LOC eating in adults undergoing bariatric surgery.

Testing the Pragmatic Effectiveness of a Consumer-Based Mindfulness Mobile App in the Workplace: Randomized Controlled Trial.

BACKGROUND: Mental health and sleep problems are prevalent in the workforce, corresponding to costly impairment in productivity and increased health care use. Digital mindfulness interventions are efficacious in improving sleep and mental health in the workplace; however, evidence supporting their pragmatic utility, potential for improving productivity, and ability to reduce employer costs is limited. OBJECTIVE: This pragmatic, cluster randomized controlled trial aimed to evaluate the experimental effects of implementing a commercially available mindfulness app-Calm-in employees of a large, multisite employer in the United States. Outcomes included mental health (depression, anxiety, and stress), sleep (insomnia and daytime sleepiness), resilience, productivity impairment (absenteeism, presenteeism, overall work impairment, and non-work activity impairment), and health care use (medical visit frequency). METHODS: Employees were randomized at the work site to receive either the Calm app intervention or waitlist control. Participants in the Calm intervention group were instructed to use the Calm app for 10 minutes per day for 8 weeks; individuals with elevated baseline insomnia symptoms could opt-in to 6 weeks of sleep coaching. All outcomes were assessed every 2 weeks, with the exception of medical visits (weeks 4 and 8 only). Effects of the Calm intervention on outcomes were evaluated via mixed effects modeling, controlling for relevant baseline characteristics, with fixed effects of the intervention on outcomes assessed at weeks 2, 4, 6, and 8. Models were analyzed via complete-case and intent-to-treat analyses. RESULTS: A total of 1029 employees enrolled (n=585 in the Calm intervention group, including 101 who opted-in to sleep coaching, and n=444 in waitlist control). Of them, 192 (n=88 for the Calm intervention group and n=104 for waitlist) completed all 5 assessments. In the complete-case analysis at week 8, employees at sites randomized to the Calm intervention group experienced significant improvements in depression (P=.02), anxiety (P=.01), stress (P<.001), insomnia (P<.001), sleepiness (P<.001), resilience (P=.02), presenteeism (P=.01), overall work impairment (P=.004), and nonwork impairment (P<.001), and reduced medical care visit frequency (P<.001) and productivity impairment costs (P=.01), relative to the waitlist control. In the intent-to-treat analysis at week 8, significant benefits of the intervention were observed for depression (P=.046), anxiety (P=.01), insomnia (P<.001), sleepiness (P<.001), nonwork impairment (P=.04), and medical visit frequency (P<.001). CONCLUSIONS: The results suggest that the Calm app is an effective workplace intervention for improving mental health, sleep, resilience, and productivity and for reducing medical visits and costs owing to work impairment. Future studies should identify optimal implementation strategies that maximize employee uptake and large-scale implementation success across diverse, geographically dispersed employers. TRIAL REGISTRATION: ClinicalTrials.gov NCT05120310; https://clinicaltrials.gov/ct2/show/NCT05120310.

The Indirect Effects of a Mindfulness Mobile App on Productivity Through Changes in Sleep Among Retail Employees: Secondary Analysis.

BACKGROUND: Chronic sleep disturbance is prevalent among United States employees and associated with costly productivity impairment. Mindfulness interventions improve sleep (ie, insomnia and daytime sleepiness) and productivity outcomes, and mobile apps provide scalable means of intervention delivery. However, few studies have examined the effects of mindfulness mobile apps on employees, and no research to date has tested the role of sleep improvement as a potential mechanism of action for productivity outcomes. OBJECTIVE: This study examined the effects of Calm, a consumer-based mindfulness app, and sleep coaching, on productivity impairment among retail employees through the indirect effects of changes in insomnia and daytime sleepiness. METHODS: This study was a secondary analysis of data from a randomized controlled trial (N=1029) comparing the use of Calm (n=585, 56.9%) to a waitlist control (n=444, 43.2%) for 8 weeks among employees of a large retail employer in the United States. A subset of individuals with elevated insomnia symptoms also had access to brief sleep coaching with Calm (n=101, 9.8%). Insomnia symptom severity, daytime sleepiness, and productivity impairment (ie, absenteeism, presenteeism, overall productivity impairment, and non-work activity impairment) were assessed at baseline and weeks 2, 4, 6, and 8. Indirect effects were evaluated with latent growth curve modeling to test whether the Calm intervention (Calm group vs waitlist control) was effective in reducing work productivity impairment through changes in sleep disturbance. RESULTS: No significant main effects of Calm intervention on productivity impairment were detected for any outcome at α level of .05, with the exception of non-work activity impairment models, in which Calm intervention reduced non-work activity impairment over time (P=.01 and P=.02 for insomnia and sleepiness models, respectively). Significant indirect effects of insomnia were detected for presenteeism (P=.002), overall work productivity (P=.01), and non-work activity impairment (P=.002); Calm intervention produced significantly greater reductions in insomnia symptoms (relative to waitlist control), and decreases in insomnia were associated with decreases in work productivity impairment. There was no significant indirect effect of change in insomnia on changes in absenteeism (P=.20). Furthermore, we detected no significant indirect effects of daytime sleepiness on productivity impairment. CONCLUSIONS: We found that Calm (plus sleep coaching for a small subset of individuals) had beneficial effects on employee sleep, and these benefits on sleep were related to indirect effects on productivity impairment (ie, presenteeism, overall work productivity impairment, and non-work activity impairment). There were no overall main effects of Calm intervention on productivity impairment; however, insomnia appears to be a mechanism associated with benefits for employee productivity. This is one of the first studies to suggest that sleep benefits of a mindfulness mobile app may also indirectly relate to benefits for workplace productivity. TRIAL REGISTRATION: ClinicalTrials.gov NCT05120310; https://clinicaltrials.gov/ct2/show/NCT05120310.

Dietary lapses are associated with meaningful elevations in daily caloric intake and added sugar consumption during a lifestyle modification intervention.

Objective: Lapses from the dietary prescription in lifestyle modification interventions for overweight/obesity are common and impact weight loss outcomes. While it is expected that lapses influence weight via increased consumption, there are no studies that have evaluated how dietary lapses affect dietary intake during treatment. This study examined the association between daily lapses and daily energy and macronutrient intake during a lifestyle modification intervention. Methods: This study used an intensive longitudinal design to observe participants throughout a 6-month lifestyle modification intervention. Participants (n = 32) were adults with overweight/obesity (body mass index 25-50 kg/m2) and a diagnosed cardiovascular disease risk factor (e.g., hypertension) with a desire to lose weight. Participants underwent a gold-standard individual in-person lifestyle modification protocol consisting of 3 months of weekly sessions with 3 months of monthly sessions. Each participant's dietary prescription included a calorie target range that was based on their starting weight. Participants completed ecological momentary assessment (EMA; repeated daily smartphone surveys) every other week to self-report on dietary lapses and telephone-based 24-h dietary recalls every 6 weeks. Results: On days with EMA and recalled intake (n = 210 days), linear mixed models demonstrated significant associations between daily lapse and higher total daily caloric intake (B = 139.20, p < 0.05), more daily grams of added sugar (B = 16.24, p < 0.001), and likelihood of exceeding the daily calorie goal (B = 0.89, p < 0.05). The associations between daily lapse and intake of all other daily macronutrients were non-significant. Conclusions: This study contributes to literature suggesting that dietary lapses pose a threat to weight loss success. Results indicate that reducing lapse frequency could reduce overall caloric intake and added sugar consumption.

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.

Traditional versus developmental measures of weight suppression: Exploring their relationships with bulimic psychopathology.

OBJECTIVE: Weight suppression (WS) is related to a wide variety of eating disorder characteristics. However, individuals with eating disorders usually reach their highest premorbid weight while still developing physically. Therefore, a more sensitive index of individual differences in highest premorbid weight may be one that compares highest premorbid z-BMI to current z-BMI (called developmental weight suppression [DWS] here). METHOD: In this exploratory study, we compared the relationships between traditional weight suppression (TWS) and DWS and a variety of measures related to bulimic psychopathology in 91 females (M age, 25.2; 60.5% White), with clinical or sub-clinical bulimia nervosa. RESULTS: TWS and DWS were correlated (r = 0.40, p < 0.001). TWS was only significantly related to a measure of physical activity whereas DWS was related to 14 outcomes. DWS showed consistent positive relations with behavioural outcomes (e.g., binge eating) but consistent negative relations with cognitive/affective outcomes (e.g., weight concerns). CONCLUSIONS: Findings indicated much more consistent relationships between the novel DWS measure and bulimic characteristics than with the TWS measure. DWS showed both positive and negative relations with bulimic symptoms, though these findings require replication to confirm their validity. Consistent evidence indicated that the two WS measures served as mutual suppressor variables.

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.

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.

Energy, Attentiveness, and Fatigue After Bariatric Surgery and Associations with Daily Physical Activity and Weight Loss: an Ecological Momentary Assessment Study.

PURPOSE: Energy and fatigue are thought to improve after bariatric surgery. Such improvements could be related to weight loss and/or increased engagement in day-to-day health behaviors, such as moderate-to-vigorous physical activity (MVPA). This study used ecological momentary assessment (EMA) to evaluate several aspects of energy/fatigue in real-time in patients' natural environment during the first year after surgery and assessed the associations of percent total weight loss (%TWL) and daily MVPA with daily energy/fatigue levels. METHODS: Patients (n = 71) undergoing Roux-en-Y gastric bypass or sleeve gastrectomy rated their energy, alertness and attentiveness (averaged to create an "attentiveness" rating), and tiredness and sleepiness (averaged to create a "fatigue" rating) via smartphone-based EMA at 4 semi-random times daily for 10 days at pre-surgery and 3-, 6-, and 12 months post-surgery. Daily MVPA minutes were assessed via accelerometry. Weight was measured in clinic. RESULTS: Energy ratings initially increased from pre- to post-surgery, before leveling off/decreasing by 12 months (p < 0.001). Attentiveness and fatigue ratings did not change over time. %TWL was unrelated to any ratings, while MVPA related to both energy and attentiveness but not fatigue. Participants reported more energy on days with more total MVPA min (p = 0.03) and greater attentiveness on days with more total (p < 0.001) and bouted (p = 0.02) MVPA. CONCLUSIONS: While more research is needed to confirm causality, results suggest that greater daily MVPA is associated with increased daily energy and attentiveness among bariatric surgery patients, independent of %TWL. Findings add to growing evidence of MVPA's potential benefits beyond energy expenditure in the context of bariatric surgery.

Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to generate personalized predictions of symptom trajectories among patients receiving treatment for EDs, and compared model performance to a simpler logistic regression prediction model. METHOD: Participants were adolescent girls and adult women (N = 333) presenting for residential ED treatment. Self-report progress assessments were completed at admission, discharge, and weekly throughout treatment. Latent growth mixture modeling previously identified three latent treatment response trajectories (Rapid Response, Gradual Response, and Low-Symptom Static Response) and assigned a trajectory type to each patient. Machine learning models (support vector, k-nearest neighbors) and logistic regression were applied to these data to predict a patient's response trajectory using data from the first 2 weeks of treatment. RESULTS: The best-performing machine learning model (evaluated via area under the receiver operating characteristics curve [AUC]) was the radial-kernel support vector machine (AUCRADIAL = 0.94). However, the more computationally-intensive machine learning models did not improve predictive power beyond that achieved by logistic regression (AUCLOGIT = 0.93). Logistic regression significantly improved upon chance prediction (MAUC[NULL] = 0.50, SD = .01; p <.001). DISCUSSION: Prediction of ED treatment response trajectories is feasible and achieves excellent performance, however, machine learning added little benefit. We discuss the need to explore how advance knowledge of expected trajectories may be used to plan treatment and deliver individualized interventions to maximize treatment effects.

Evaluation of intervention components to maximize outcomes of behavioral obesity treatment delivered online: A factorial experiment following the multiphase optimization strategy framework.

BACKGROUND: Behavioral lifestyle intervention (BLI) is recommended as a first-line treatment for obesity. While BLI has been adapted for online delivery to improve potential for dissemination while reducing costs and barriers to access, weight losses are typically inferior to gold standard treatment delivered in-person. It is therefore important to refine and optimize online BLI in order to improve the proportion of individuals who achieve a minimum clinically significant weight loss and mean weight loss. STUDY DESIGN: Five experimental intervention components will be tested as adjuncts to an established 12-month online BLI: virtual reality for BLI skills training, interactive video feedback, tailored intervention to promote physical activity, skills for dysregulated eating, and social support combined with friendly competition. Following the Multiphase Optimization Strategy (MOST) framework, the components will first be refined and finalized during Preparation Phase pilot testing and then evaluated in a factorial experiment with 384 adults with overweight or obesity. A priori optimization criteria that balance efficacy and efficiency will be used to create a finalized treatment package that produces the best weight loss outcomes with the fewest intervention components. Mediation analysis will be conducted to test hypothesized mechanisms of action and a moderator analysis will be conducted to understand for whom and under what circumstances the interventions are effective. CONCLUSION: This study will provide important information about intervention strategies that are useful for improving outcomes of online BLI. The finalized treatment package will be suitable for testing in a future randomized trial in the MOST Evaluation Phase.

Latent trajectories of eating disorder treatment response among female patients in residential care.

OBJECTIVE: Eating disorder (ED) treatment outcomes are highly variable from beginning to end of treatment; however, little is known about differential trajectories during the course of treatment. This study sought to characterize heterogeneous patterns of ED treatment response during residential care. METHOD: Participants were adolescent girls and adult women (N = 360) receiving residential ED treatment for anorexia nervosa, bulimia nervosa, binge-eating disorder, other specified feeding or eating disorder, unspecified feeding or eating disorder, or avoidant/restrictive food intake disorder. Self-report symptom assessments were completed at admission, discharge, and approximately weekly throughout the residential stay to assess curvilinear patterns of change. Latent growth mixture modeling was applied to identify subgroups of patients with similar treatment response trajectories. RESULTS: Three latent groups emerged, including gradual response (58.3%; steady improvements from admission to discharge), rapid response (23.9%; steep early improvements that were maintained through discharge), and low-symptom static response (17.8%; nearly nonclinical self-reported symptoms at admission that remained static through discharge). Groups differed on important clinical characteristics, such as body mass index, endorsement of compensatory behaviors, severity of global ED psychopathology at admission, and degree of symptom improvement by end of treatment. DISCUSSION: Patients follow heterogeneous response patterns in residential ED treatment, and these patterns are associated with differential treatment outcome. Future work should explore whether these trajectories are associated with differential outcomes at follow-up and whether tailoring clinical intervention to a patient's trajectory type can improve treatment response.

Development and validation of a progress monitoring tool tailored for use in intensive eating disorder treatment.

OBJECTIVE: Despite calls for routine use of progress and outcome monitoring in private and intensive treatment centres for eating disorders (EDs), existing measures have limited relevance to these supervised treatment settings. This study sought to develop and validate the progress monitoring tool for eating disorders, a multidimensional measure for progress monitoring in the context of intensive ED treatment. METHOD: Thirty-seven items were generated by a team of content experts, clinicians, and administrative staff from the target treatment setting. Adolescent and adult females (N = 531) seeking residential ED treatment completed the items at admission as part of the clinic's routine assessment battery; 83% were retained for repeat assessment at discharge. Exploratory factor analysis was conducted for preliminary measure development. RESULTS: Results yielded a five-factor, 26-item structure explaining 50% of total variance. Final construct domains included weight and shape concern, ED behaviours and urges, emotion avoidance, adaptive coping, and relational connection. The measure demonstrated adequate internal consistency, sensitivity to change during treatment, and convergence with validated assessment measures. CONCLUSIONS: Preliminary data support the progress monitoring tool for eating disorders as a novel and valid multidimensional measure of treatment-relevant constructs. This measure may have utility in measuring treatment progress for patients receiving intensive treatment for EDs.

Weight variability during self-monitored weight loss predicts future weight loss outcome.

BACKGROUND: Obesity treatments often do not produce long-term results. It is therefore critical to better understand biological and behavioral correlates or predictors of future weight change. OBJECTIVE: We tested the hypothesis that greater weight variability, independent of total body weight change, during early weight loss would predict degree of long-term success. SUBJECTS/METHODS: We included 24,009 American users of the Withings smart scale with over a year's worth of self-monitored weight data. Multilevel modeling was used to calculate weight variability as the root mean square error around participants' weight trajectory regression line, using weekly average weights from the first 12 weeks of weight loss. Linear regressions were then used to examine whether weight variability predicted weight change from week 12 to week 48, 72, and 96. RESULTS: Greater weight variability predicted less weight loss/more weight regain at week 48 (b ± SE: 1.18 ± 0.17, p < 0.001), week 72 (b ± SE: 1.45 ± 0.21, p < 0.001), and week 96 (b ± SE: 1.45 ± 0.23, p < 0.001), controlling for baseline BMI and overall weight change during the first 12 weeks. An interaction effect was found between weight variability and baseline BMI such that the relationship between weight variability and later weight change was stronger in individuals with lower baseline BMI. CONCLUSIONS: This study found that in a large population sample, weight variability early on during weight loss significantly predicted longer term weight loss outcomes. The results provide further support that weight variability be considered an important predictor of future weight change. Research is needed to understand the mechanisms underlying this effect.

Qualitative perceptions of and preferences for the research process among patients with eating disorders.

OBJECTIVE: Low participation and retention rates are persistent problems in eating disorder (ED) research. In order to improve the research process, this study used a qualitative approach to examine factors promoting and limiting research study participation among patients with EDs, and their preferences during research. METHOD: Five 90-min focus groups were conducted with adult women (N = 29) enrolled at a residential ED treatment facility. Facilitators asked a series of open-ended questions about participants' experiences, opinions, and preferences with regard to ED treatment research. Transcript analysis identified themes using a consensual qualitative research approach. RESULTS: It was revealed that preventing others' suffering, improving ED treatment, and having low participant burden were major themes facilitating research participation. Major barriers to research participation included concern that research interferes with self-care/recovery, burdensome nature of study design, and demeanor of the researchers/institutions involved with the study. Patients believed that the format of research assessments could be improved by better assessing the nuances of ED behaviors, examining non-ED outcomes, and including more open-ended questions. Patients anticipated that challenges in recovery, feelings of guilt, and logistical barriers could interfere with their ability to complete follow-up research assessments. DISCUSSION: Factors related to the recruitment process, assessment format, follow-up methods, and communication throughout the research process may need to be addressed to increase participation and retention rates. Findings indicate that recruitment strategies should include emphasizing the broader impact of the research and increasing sensitivity to the nature of patients with EDs experiences.

The independent and interacting effects of weight suppression and admission body mass index on treatment weight change in patients with anorexia nervosa or bulimia nervosa.

OBJECTIVE: Weight suppression (WS) and body mass index (BMI) have predicted weight change in individuals with eating disorders, but the interaction between these variables is understudied. Furthermore, WS is usually measured as absolute WS-the numeric difference between current weight and highest past weight-overlooking the potentially important influence of how much a person weighed at their highest historical weight. METHOD: The current study investigated the independent and interacting effects of BMI and two measures of WS at admission on residential treatment weight change. WS measures included absolute WS and the relative WS index, the percentage of total body weight lost from highest past weight. Participants were women with anorexia nervosa (n = 357) or bulimia nervosa (n = 293) who provided complete data, 87% of the eligible treatment sample. RESULTS: In both diagnostic subsamples, BMI, absolute WS, and the relative WS index all significantly predicted weight change. The interaction between BMI and WS predicted weight change, but only when the relative WS index was used. DISCUSSION: Results highlight the potential importance of considering an individual's weight and weight history when predicting their treatment weight change and support the importance of utilizing both methods of calculating WS in future research.

Mediating role of experiential avoidance in the relationship between anxiety sensitivity and eating disorder psychopathology: A clinical replication.

OBJECTIVE: This study sought to examine whether anxiety sensitivity was associated with eating disorder (ED) symptom severity among patients with severe EDs, and to determine whether this relationship was mediated by experiential avoidance. METHOD: Adolescent and adult females (N = 625) seeking residential ED treatment completed self-report measures of anxiety sensitivity, experiential avoidance, and ED psychopathology. Linear regression evaluated the cross-sectional association between ED symptom severity and three dimensions of anxiety sensitivity (social, physical, and cognitive). Regression-based mediation analysis with bootstrapping tested the associations among the three dimensions of anxiety sensitivity and ED symptom severity through experiential avoidance. RESULTS: The social dimension of anxiety sensitivity was positively associated with severity of ED psychopathology. Experiential avoidance mediated this association. DISCUSSION: ED symptoms in this sample were more severe among patients who endorsed greater concern about appearing nervous or anxious to others. The current results indicate that this relationship was driven by a tendency to avoid experiences that evoke emotional discomfort. If replicated, these findings suggest that targeting both social anxiety sensitivity and experiential avoidance may improve ED treatment outcomes. Further study of the mechanistic relationships among social anxiety sensitivity, experiential avoidance, and ED psychopathology, is warranted.

Rationale and design for a pragmatic effectiveness-implementation trial of online behavioral obesity treatment in primary care.

BACKGROUND: Current guidelines recommend behavioral intervention to achieve a modest weight loss (e.g., 3-5%) as a first-line obesity treatment. Online behavioral obesity treatment, delivered via the Rx Weight Loss (RxWL) program, produces clinically significant initial weight losses. However, the program's pragmatic utility in routine medical care has yet to be tested. Further, additional research is needed to determine how best to extend the RxWL program to facilitate weight loss maintenance. This paper summarizes methods for a pragmatic trial aimed at identifying optimal methods for implementation of RxWL in primary care and evaluating relative effectiveness of two approaches to weight loss maintenance. STUDY DESIGN: RxWL will be implemented in a network of approximately 60 primary care clinics. Implementation outcomes (program uptake and completion metrics) will be compared between a Basic Implementation Intervention consisting primarily of access to RxWL, and an Enhanced Implementation Intervention with additional training in strategies for motivating and supporting patients in their use of RxWL and online clinician support tools for tracking patient progress. Second, two intervention approaches (Monthly Lessons versus Refresher Courses) within the RxWL patient platform will be tested against an educational control condition, and effects on 1-year weight loss maintenance will be compared. CONCLUSION: This study will provide essential information about the feasibility and utility of online obesity treatment in primary care. It will provide novel information on two approaches to weight loss maintenance for patients in this setting. This project fills key gaps in evidence regarding best practices for obesity treatment in primary care.