Rebecca A. Krukowski

Background: The provision of self‐monitoring feedback has been demonstrated to improve weight loss program outcomes; however, there is little evidence to support how this feedback should be delivered. Micro‐randomized factorial trial designs can examine the proximal impact of intervention components, but their feasibility and acceptability in the context of behavioral weight management programs remain unknown. Methods: The current pilot study evaluated the feasibility and acceptability of procedures for a micro‐randomized factorial trial designed to optimize the provision of self‐monitoring feedback messages in behavioral weight management programs. Adults with obesity were provided with an initial Weight Loss 101 education session and asked to self‐monitor dietary intake, physical activity, and weight daily (using an app, activity monitor, and e‐scale). They were then randomized each week for 16 weeks (using a 2 ⁴ factorial design) to receive or not receive each of four feedback components (feedback on calorie goal attainment, diet quality, physical activity goal attainment, or to support goal setting) sent via text with a link to an individualized website. Results: Of the 28 participants enrolled (86% women; mean ± SD BMI = 37.2 ± 6.6 kg/m ² ), most (93%) completed the study; participants self‐monitored dietary intake, physical activity, and weight on 65%, 87%, and 76% of possible days, respectively. Most weekly feedback messages were viewed (92%); 63% were rated and 90% of rated messages were deemed helpful. Conclusions: Trial procedures were both feasible and acceptable among adults with obesity. Findings can inform the design of future micro‐randomized factorial trials.

Objective: According to psychological theories including Social Cognitive Theory and Control Theory as well as empirical evidence, self-monitoring of diet is an effective behavior change technique, yet adherence is often low. Indeed, daily self-monitoring may not be necessary for clinically meaningful outcomes, though evidence on what constitutes enough self-monitoring is observational. This preregistered study experimentally tested whether different frequencies of self-monitoring fruit and vegetable (FV) intake produce differential changes in FV intake, body weight, and psychological constructs.Methods: Participants were randomly assigned to three conditions: 18, 24, or 30 self-monitoring days across a 30-day period. In total, 166 participants (70.5% women; age: M = 25.3, SD = 9.5; BMI: M = 23.8, SD = 3.0) completed the study. Psychological constructs included dietary self-efficacy and the perceived ability to identify patterns in one’s diet, set goals accordingly, and recognize which changes are needed.Results: A mixed ANOVA found a main effect for time, p < .001, but not condition, p = .123, and a non-significant interaction effect, p = .280, indicating that FV intake increased in all three conditions and that changes did not differ between conditions. No weight changes were found. Significant declines in psychological constructs over time were observed in at least one condition (ps ≤ .003), with particularly strong and consistent declines in dietary self-efficacy.Conclusions: The study provides experimental evidence that daily self-monitoring is not required to achieve meaningful changes in FV intake. Lower-frequency self-monitoring may represent a feasible and less burdensome approach to dietary behavior change.

Introduction: Participants in behavioral weight management programs are typically provided with weekly interventionist‐crafted self‐monitoring feedback; however, there is a lack of empirical evidence regarding optimal feedback construction. Methods: Using a Delphi method, experts ( N = 67) provided perspectives regarding the optimal focus, frequency, interactivity, and modality of feedback messages. Directed content analyses were used to analyze qualitative data, and descriptive statistics were used to summarize quantitative data. Results: Experts' views on the modality (e.g., email, app notification) varied, and participant preference and practicality were noted as key considerations. Experts ranked 8 feedback components as most important: problem solving, goal setting prompts, calorie intake and physical activity goal attainment, diet tracking frequency, weight trajectory (since the last message and since the start of the program), and diet quality. More experts endorsed the “sandwich” approach (i.e., positive comments along with strategies for change) for those experiencing weight loss challenges (95%) than for those experiencing weight loss success (55%). Overall, 82% noted that personalized feedback was important, but they were not always able to provide it due to time restrictions/personnel cost (75% identified these as key barriers). Conclusions: Although most experts viewed personalized self‐monitoring feedback as important, time/cost considerations in crafting this feedback are critical. Future experimental studies should be used to evaluate the expert recommendations gathered from this Delphi study.

Introduction: Previous research investigating trajectories of weight change after quitting smoking has been limited due to infrequent weight measurements; newer e-scales data facilitate more frequent weight measurement. We explored the rate of weight gain and when weight change stabilized via secondary data analyses from the post-cessation weight management-focused “Fit & Quit” trial. Aims and Methods: After completion of one of three randomized weight intervention conditions, all participants located in the United States completed a behavioral smoking cessation intervention with varenicline pharmacotherapy in 2018–2022. Participants were asked to weigh daily on study-provided e-scales throughout the 12-month study. Mixed-effects models were performed to characterize weight change over time and to test whether the intervention condition or gender impacted the temporal rate of weight change (n = 132). Results: Rate of weight change in the first month after quitting smoking was most rapid, at + 0.0111 kg/day. To identify when weight stabilized, we use a fifth-degree polynomial model and found that participants began gaining weight immediately after quitting, with the rate of gain peaking around the 21st day. Weight gain continued at a lower, but still statistically significant, rate until approximately 70 days after cessation, after which the weight began to plateau. All intervention condition groups had similar rates of weight gain, with no gender differences in the rate of weight gain. Conclusions: The first month after quitting smoking was a particularly vulnerable time period for weight gain. Future programs combining weight management and smoking cessation should emphasize maintenance of weight management strategies within the first month after quitting smoking. Implications: Future post-cessation weight management programs should prioritize maintenance of weight management strategies within the first month after quitting smoking, regardless of the type of weight management strategy or the gender of the participants. Studies examining post-cessation weight gain should ensure measurement of weight gain for at least 2–3 months after quitting smoking. Trial Registration: The trial is registered on clinicaltrials.gov (NCT03156660).

Purpose: This study examined the effect of intervention treatment preference in a post-smoking cessation weight management trial. Design & Setting: Participants were randomized to a weight management intervention (Stability, Loss, or Bibliotherapy); all participants received a standard smoking cessation program. Adults aged 18+ were recruited from Memphis, TN, and nationally. Participants: Individuals were eligible if they had a BMI of 22 kg/m ² or greater. Measures: Participants were asked about their preferred weight intervention at screening. Weight change and self-reported point-prevalence abstinence were assessed (Month 12). Participants rated perceived effectiveness, difficulty (screening, Month 2), and intervention satisfaction (Month 12). Analysis: We examined the effect of intervention preference match on 12-month weight change, smoking cessation, perceived effectiveness, difficulty, and satisfaction. Results: Participants (n = 305) were majority female (68%); white (52%); and had overweight/obesity (87%). At screening, most participants perceived the Loss intervention as most effective; at Month 2, Stability was perceived as most effective. The Stability intervention was perceived as easiest at screening and Month 2. Those who were matched to their treatment preference had greater 12-month weight loss, but similar rates of smoking cessation. Conclusions: Participants who were matched to their preference were more successful in preventing post-cessation weight gain, compared to those who were not matched. Future research should systematically test intervention preference effects with the aim of precision health.

PURPOSE: Oral adjuvant endocrine therapy (AET) reduces the risk of cancer recurrence and death for women with hormone receptor–positive (HR+) breast cancer. Because of adverse symptoms and socioecologic barriers, AET adherence rates are low. We conducted post hoc analyses of a randomized trial of a remote symptom and adherence monitoring app to evaluate characteristics associated with higher app use, satisfaction, and how app use was associated with AET adherence. METHODS: Patients prescribed AET were randomly assigned to receive one of three intervention conditions: app, app + feedback, or enhanced usual care. Baseline and 6-month follow-up surveys, app use, and pillbox-monitored AET adherence data for app and app + feedback participants were used. Logistic regression evaluated the association between sociodemographic/clinical characteristics and app utilization and satisfaction, and how app use was associated with AET adherence (>80%). RESULTS: Overall, 163 women with early-stage HR+ breast cancer were included; 35.0% had high app use (≥75% of weeks enrolled). No sociodemographic characteristics were associated with app use. Satisfaction with the app was higher among those who were younger (88.9% for age 31-49 years v 54.9% for age 65+ years, P < .001), identified as White (76.8% v 60.1% for Black, P = .045), had lower health literacy (85.4% v 68.2% with higher health literacy, P = .017), or were nonurban residents (85.7% v 68.6% for urban, P = .021). Most participants (90.3%) with high app use were AET-adherent compared with 66.8% for those with lower app use ( P < .001). CONCLUSION: Use of a remote monitoring app was similar across sociodemographic characteristics, and more frequent app use was associated with a higher likelihood of 6-month AET adherence. Encouraging women to monitor medication adherence and communicate adverse symptoms could improve AET adherence.

: Healthy gestational weight gain (GWG) is associated with improved pregnancy and delivery outcomes. Previous literature shows provider advice and expectations regarding GWG significantly associated with GWG outcomes. In this study, we explore the influence of these factors on GWG in a military population in this secondary analysis of data from a randomized controlled trial. Participants (N = 377) came from a completed randomized controlled trial focused on behavioral interventions for healthy GWG and/or postpartum weight loss among TRICARE beneficiaries. At baseline, participants filled out a 5-item questionnaire assessing provider advice and self-expectations for GWG. For the actual GWG primary outcome variable, we calculated the difference between the weight obtained in the first trimester and the weight obtained at 36 weeks of gestation. We used regression models to assess the predictive ability of expectations about GWG on actual GWG. Participants with higher baseline BMIs were more likely to expect excessive GWG as defined by the National Academy of Medicine (NAM; Overweight: 46.3%, Obesity: 65.4%). Participants’ expectations showed a significant association with actual GWG (OR 2.1, 95% CI 1.29–3.41, p = 0.003). Most participants (64.7%) reported no provider advice about how much weight to gain during their pregnancy. Of those who did receive advice, 55.4% reported that it was within the NAM guidelines. The study documented infrequent provider advice about GWG in a large sample of TRICARE beneficiaries (i.e., both active duty and non-active duty individuals) and supported an association between self-expectations and later actual GWG. Future studies might test strategies to increase/improve provider advice regarding GWG and to aid pregnant individuals in shaping and achieving their GWG expectations. The trial was prospectively registered on clinicaltrials.gov (NCT 03057808) on February 20, 2017.