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The generalizability of study findings may be influenced by pre-enrollment trial procedures, including the use of behavioral run-in periods. The study goals were to determine whether behavioral run-in periods and other pre-enrollment processes affect outcomes in randomized trials of behavioral weight loss interventions that have contributed to clinical guidelines. The sample was behavioral weight loss intervention trials included in the 2018 U.S. Preventive Services Task Force systematic review. Information on pre-enrollment processes (total steps, in-person steps, behavioral run-in) was abstracted, and meta-regressions were conducted in 2022 to test whether pre-enrollment processes were associated with weight loss at 6 or 12 months and trial retention at 12 months. Across 80 trials, the median number of total pre-enrollment steps was 2 (range=1–5), and that of in-person pre-enrollment steps was 1 (range=0–4). Almost one-third of the trials (k =24; 30%) used a behavioral run-in. The most common run-in tasks were self-monitoring physical activity (k =9) or both physical activity and diet (k =6). Greater weight loss was observed in trials with behavioral run-ins at 6 months (−2.33 kg; 95% CI= −3.72, −0.93) and, to an attenuated extent, at 12 months (−0.86 kg; 95% CI= −1.72, 0.01) compared to those without run-ins. The total number of pre-enrollment steps was also associated with greater 6-month weight loss (−0.85 kg; 95% CI= −1.59, −0.11). Higher retention was associated with total number of pre-enrollment steps and in-person steps and marginally with the presence of run-ins. The use of more pre-enrollment processes is associated with greater weight loss in behavioral weight loss trials and may impact the generalizability of outcomes. [ABSTRACT FROM AUTHOR]

Given the broad benefits of physical activity (PA) but low PA levels among breast cancer survivors (i.e. women who have received a breast cancer diagnosis), innovative and evidence-based techniques are needed to motivate and support exercise. This study systematically reviews the use of behavior change techniques (BCTs) in digital PA interventions for breast cancer survivors. Studies were retrieved from five electronic databases and were included if they (i) sampled exclusively female breast cancer survivors aged >18 years, (ii) involved a digital intervention with the primary purpose of increasing PA, (iii) included a BCT component, (iv) used a randomized or quasi-randomized design, and (v) were published from January 2000 to May 2022. Two coders independently extracted data. Twenty primary studies met the inclusion criteria and were included in this review. All interventions used at least one BCT (mean 4 ± 1, range 2–13); self-monitoring (85%) and goal setting (79%) were the most common BCTs. Twelve of 20 (60%) studies reported improvements in PA behavior in the intervention vs. control group, and self-monitoring and goal setting were the most commonly used BCTs in these studies. Of the 93 total BCTs, 66 were not used in any interventions in the review, including critical constructs for PA behavior change (e.g. biofeedback). BCTs, important facilitators of PA behavior change, are being underutilized in digital PA interventions for breast cancer survivors. Future research should incorporate more diverse BCTs to explore if they can add to the effectiveness of digital interventions for this population. [ABSTRACT FROM AUTHOR]

Purpose: To determine characteristics of weight gain prevention programs that facilitate engagement. Design: Randomized factorial experiment (5 × 2). Setting: Recruited nationally online. Participants: Adults aged 18 to 75 with body mass index ≥25 who decline a behavioral weight loss intervention (n = 498). Measures: Participants were randomly presented with one of 10 possible descriptions of hypothetical, free weight gain prevention programs that were all low dose and technology-based but differed in regard to 5 behavior change targets (self-weighing only; diet only; physical activity only; combined diet, physical activity, and self-weighing; or choice between diet, physical activity, and self-weighing targets) crossed with 2 financial incentive conditions (presence or absence of incentives for self-monitoring). Participants reported willingness to join the programs, perceived program effectiveness, and reasons for declining enrollment. Analysis: Logistic regression and linear regression to test effects of program characteristics offered on willingness to initiate programs and programs' perceived effectiveness, respectively. Content analyses for open-ended text responses. Results: Participants offered the self-weighing-only programs were more willing to initiate than those offered the programs targeting all 3 behaviors combined (50% vs 36%; odds ratio [OR] = 1.79; 95% confidence interval [CI], 1.01-3.13). Participants offered the programs with financial incentives were more willing to initiate (50% vs 33%; OR = 2.08; 95% CI, 1.44-2.99) and anticipated greater intervention effectiveness (β =.34, P =.02) than those offered no financial incentives. Reasons for declining to initiate included specific program features, behavior targets, social aspects, and benefits. Conclusion: Targeting self-weighing and providing financial incentives for self-monitoring may result in greater uptake of weight gain prevention programs. Study Preregistration: https://osf.io/b9zfh, June 19, 2018. [ABSTRACT FROM AUTHOR]

Objective We examined effects of providing type 2 diabetes genetic risk feedback on controllability perceptions. Methods This is a secondary analysis of a randomized controlled trial in which overweight/obese Veterans Affairs patients without diabetes received conventional type 2 diabetes risk counseling that included either (1) personalized diabetes genetic risk feedback ( genetic risk arm) or (2) eye disease counseling ( comparison arm). Perceived diabetes control, and dietary and physical activity self-efficacy were compared between study arms, and between the comparison arm and each of 3 DNA-based genetic risk levels. Results Participants ( N = 531) were predominately male, middle-age, and African American. Immediately post-counseling, perceived diabetes control was higher for the genetic risk arm (risk levels combined) than the comparison arm ( p = 0.005). In analyses by genetic risk levels, low genetic risk participants reported higher perceived diabetes control than comparison participants ( p = 0.007). Immediately post-counseling, low genetic risk participants reported higher dietary self-efficacy in situations when mood is negative compared with controls( p = 0.01). At 3 months, no differences in constructs were observed. Conclusion Genetic risk feedback for diabetes has temporary effects on perceived controllability among patients with low genetic risk. Practice implications Clinicians and other stakeholders should consider the limited effects on behavior change of diabetes genetic risk feedback. [ABSTRACT FROM AUTHOR]

Spouse-assisted interventions can improve health behaviors, but mechanisms of action are unknown. This study evaluated mediators of dietary and physical activity outcomes during a spouse-assisted intervention to improve low-density lipoprotein cholesterol. This is a secondary analysis of data from a randomized controlled trial comparing usual care (n = 128) to a spouse-assisted lifestyle change intervention (n = 127) comprising nine monthly goal setting telephone calls to participants and support planning calls to spouses over 11 months. Structural equation modeling was used to examine if the intervention influenced the putative mediators of participant self-efficacy and perceived spousal support at 6 months (i.e. action test); if changes in putative mediators at 6 months were associated with changes in diet and physical activity outcomes at 11 months (i.e. conceptual test); and if treatment condition effects on outcomes at 11 months were mediated by its effects on the 6-month putative mediators (i.e. indirect effects test). Participants were 94.9% male, 64.9% white and were 61.3 years old on average. The action test showed that the intervention increased dietary self-efficacy (p < .001) and perceived spousal support for diet (p < .001) and physical activity (p < .01) at 6 months. The conceptual test showed that increases in participant physical activity self-efficacy at 6 months were associated with increases in physical activity frequency (p = .01) and duration (p = .04) at 11 months; other putative mediators were not associated with changes in outcomes at 11 months. The indirect effects tests did not support a mediating role for self-efficacy or perceived spousal support. Intervention-induced changes in spousal support and dietary self-efficacy did not translate into behavior change. Other mechanisms may be driving behavior change. [ABSTRACT FROM PUBLISHER]

Background: Choosing a diet rather than being prescribed one could improve weight loss. Objective: To examine whether offering choice of diet improves weight loss. Design: Double-randomized preference trial of choice between 2 diets (choice) versus random assignment to a diet (comparator) over 48 weeks. (ClinicalTrials.gov: NCT01152359) Setting: Outpatient clinic at a Veterans Affairs medical center. Patients: Outpatients with a body mass index of at least 30 kg/m2. Intervention: Choice participants received information about their food preferences and 2 diet options (low-carbohydrate diet [LCD] or low-fat diet [LFD]) before choosing and were allowed to switch diets at 12 weeks. Comparator participants were randomly assigned to 1 diet for 48 weeks. Both groups received group and telephone counseling for 48 weeks. Measurements: The primary outcome was weight at 48 weeks. Results: Of 105 choice participants, 61 (58%) chose the LCD and 44 (42%) chose the LFD; 5 (3 on the LCD and 2 on the LFD) switched diets at 12 weeks, and 87 (83%) completed measurements at 48 weeks. Of 102 comparator participants, 53 (52%) were randomly assigned to the LCD and 49 (48%) were assigned to the LFD; 88 (86%) completed measurements. At 48 weeks, estimated mean weight loss was 5.7 kg (95% Cl, 4.3 to 7.0 kg) in the choice group and 6.7 kg (Cl, 5.4 to 8.0 kg) in the comparator group (mean difference, -1.1 kg [Cl, -2.9 to 0.8 kg]; P = 0.26). Secondary outcomes of dietary adherence, physical activity, and weight-related quality of life were similar between groups at 48 weeks. Limitations: Only 2 diet options were provided. Results from this sample of older veterans might not be generalizable to other populations. Conclusion: Contrary to expectations, the opportunity to choose a diet did not improve weight loss [ABSTRACT FROM AUTHOR]

Aim Dietary changes occurring during weight loss interventions can vary. The present study tested if pretreatment psychosocial, dietary and demographic factors were associated with changes in fat intake and fruit and vegetable intake during a weight loss intervention. Methods This analysis includes participants who lost at least four kilograms during the initial six month weight loss phase (phase I) of the Weight Loss Maintenance Trial, a group format behavioural intervention emphasising a low-fat diet and increased physical activity. Multiple linear regression was used to determine associations between pretreatment psychosocial, dietary, physical activity, and demographic variables and changes from pretreatment to six months in fat intake and fruit and vegetable intake. Results Participants ( n = 1032) were 63.4% female, 62.4% non- African American, and had a mean age of 55.6 and BMI of 34.1 kg/m2. Being African American ( P < 0.0001) and higher baseline kilojoule intake ( P < 0.01) were associated with smaller reductions in fat intake. Being African American ( p < 0.001) and older age ( P = 0.02) were associated with smaller increases in fruit and vegetable intake, whereas a history of 10 or more past weight loss episodes of at least 10 lb (4.5 kg; P < 0.01) was associated with greater increases. Conclusions Few psychosocial factors examined contributed to variability in dietary change. Even when achieving meaningful weight losses during a behavioural weight loss intervention, African Americans may make fewer beneficial changes in fat and fruit and vegetable intake than non- African Americans. [ABSTRACT FROM AUTHOR]