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Obesity is a prevalent health care issue associated with disability, premature morality, and high costs. Behavioral weight management interventions lead to clinically significant weight losses in overweight and obese individuals; however, many individuals are not able to participate in these face-to-face treatments due to limited access, cost, and/or time constraints. Technological advances such as widespread access to the Internet, increased use of smartphones, and newer behavioral self-monitoring tools have resulted in the development of a variety of eHealth weight management programs. In the present paper, a summary of the most current literature is provided along with potential solutions to methodological challenges (e.g., high attrition, minimal participant racial/ethnic diversity, heterogeneity of technology delivery modes). Dissemination and policy implications will be highlighted as future directions for the field of eHealth weight management.

Background: Worksite wellness programs typically produce modest weight losses. We examined whether an efficacious Internet behavioral weight loss program could be successfully implemented in a worksite setting., Methods: Participants were 75 overweight or obese employees/dependents of a large healthcare system who were given access to a 12-week Internet-based, multicomponent behavioral weight loss program. Assessments occurred at baseline, Month 3 (end of intervention), and Month 6 (follow-up)., Results: Retention was excellent (93% at Month 3 and 89% at Month 6). Intent-to-treat analyses demonstrated that participants lost an average (±SE) of -5.8 ± .60 kg from baseline to Month 3 and regained 1.1 ± .31 kg from Month 3 to Month 6; overall, weight loss from baseline to Month 6 was -4.7 ± .71 kg, p < .001. Men lost more weight than women, p = .022, and individuals who had a college degree or higher lost more weight than those with less education, p = .005. Adherence to viewing lessons (8 of 12) and self-monitoring (83% of days) was excellent and significantly associated with weight loss, ps < .05., Conclusions: An Internet-based behavioral weight management intervention can be successfully implemented in a worksite setting and can lead to clinically significant weight losses. Given the low costs of offering this program, it could easily be widely disseminated.

Social inequalities are an important contributor to the global burden of disease within and between countries. Using digital technology in health promotion and healthcare is seen by some as a potential lever to reduce these inequalities; however, research suggests that digital technology risks re-enacting or evening widening disparities. Most research on this digital health divide focuses on a small number of social inequality indicators and stems from Western, educated, industrialized, rich, and democratic (WEIRD) countries. There is a need for systematic, international, and interdisciplinary contextualized research on the impact of social inequality indicators in digital health as well as the underlying mechanisms of this digital divide across the globe to reduce health disparities. In June 2023, eighteen multi-disciplinary researchers representing thirteen countries from six continents came together to discuss current issues in the field of digital health promotion and healthcare contributing to the digital divide. Ways that current practices in research contribute to the digital health divide were explored, including intervention development, testing, and implementation. Based on the dialogue, we provide suggestions for overcoming barriers and improving practices across disciplines, countries, and sectors. The research community must actively advocate for system-level changes regarding policy and research to reduce the digital divide and so improve digital health for all. [ABSTRACT FROM AUTHOR]

Extended-care interventions have been demonstrated to improve maintenance of weight loss after the end of initial obesity treatment; however, it is unclear whether these programs are similarly effective for African American versus White participants. The current study examined differences in effectiveness of individual versus group telephone-based extended-care on weight regain, compared to educational control, in 410 African American (n = 82) and White (n = 328) adults with obesity (mean ± SD age = 55.6 ± 10.3 years, BMI = 36.4 ± 3.7 kg/m2). After controlling for initial weight loss, multivariate linear models demonstrated a significant interaction between treatment condition and race, p =.048. Randomization to the individual telephone condition produced the least amount of weight regain in White participants, while the group condition produced the least amount of weight regain in African American participants. Future research should investigate the role of social support in regain for African American versus White participants and examine whether tailoring delivery format by race may improve long-term outcomes. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the roles of frequency and consistency of self-weighing in promoting weight-loss maintenance.Methods: Participants were 74 adults who completed a 3-month internet-based weight-loss program followed by a 9-month no-intervention maintenance period. Frequency of self-weighing was defined as the number of days that participants self-weighed during the maintenance period via a study-provided smart scale. Consistency was defined as the number of weeks that participants self-weighed at a certain frequency, with multiple minimum thresholds examined. Hierarchical regression analyses were used to assess associations among frequency, consistency, and weight change during the maintenance period.Results: Greater consistency was significantly associated with less weight regain when defined as the number of weeks that participants self-weighed on ≥6 d/wk or 7 d/wk (P values < 0.05). Contrary to hypotheses, frequency was not associated with weight change (P = 0.141), and there was not a significant interaction between frequency and consistency.Conclusions: Results demonstrate that consistency of self-weighing may be more important than total frequency for preventing weight regain after the end of a weight-loss program. Further, results suggest that a high level of consistency (self-weighing for ≥6 d/wk or 7 d/wk) may be necessary to promote successful weight-loss maintenance. [ABSTRACT FROM AUTHOR]

Research has suggested that there may be a bidirectional association between stress and physical activity; however, much of this work has been conducted in athletes or adults with normal weight. The current study investigated the bidirectional association between stress and physical activity in adults with overweight and obesity. For a full year, during and after a 12-week, Internet-based weight loss program, 74 participants (BMI = 31.2 kg/m2) were asked to report stress and minutes of physical activity each week. An increase in stress was associated with less physical activity during the same week and predicted fewer minutes of physical activity the following week. Finally, each 1 h increase in physical activity on a given week was associated with a small decrease in stress ratings the following week. Results confirmed the bidirectional association between stress and physical activity in a sample of adults with overweight/obesity, and supported results highlighting stress as a barrier to physical activity. Future studies should investigate whether adding intervention components to decrease stress or to reinforce physical activity can improve physical activity engagement in this population. [ABSTRACT FROM AUTHOR]

Objective: Although the trajectory of weight change during and/or after behavioral weight management interventions is believed to include a period of weight loss followed by maintenance and later regain, the sparse data produced by existing study designs (conducting assessments at 3- to 6-month intervals) have limited investigation into the precise pattern.Methods: Seventy-five adults were asked to self-weigh daily via "smart" scales during a 12-week, Internet-based weight loss program and for an additional 9 months with no further intervention. Longitudinal change-point mixed-effect models were used to characterize overall weight change patterns and identify when individuals moved from weight loss to maintenance/regain.Results: Analyses suggested a three-phase model. During the first phase, participants lost weight at a (mean ± SE) rate of -0.46 ± 0.04 kg/wk; after 77.66 ± 3.96 days, they transitioned to regain (0.07 ± 0.02 kg/wk). The next transition occurred at 222.55 ± 7.23 days, after which the rate of regain decreased slightly (0.06 ± 0.02 kg/wk). Exploratory analyses identified baseline/demographic factors predicting the timing of transition points and slope of weight change within phases.Conclusions: In contrast to the hypothesized trajectory, results demonstrated that participants transitioned immediately from weight loss to regain (with no "maintenance" period) and later to a slower rate of regain. Future studies should investigate whether extended-care programs change or merely delay this pattern. [ABSTRACT FROM AUTHOR]

Objective: Daily self-weighing is an effective weight loss strategy. Little is known about "micro" factors influencing nonadherence to self-weighing (e.g., daily overeating). It was hypothesized that increased caloric intake on a given day would increase odds of not self-weighing the following day.Methods: Daily self-reports of weight and caloric intake were collected from 74 adults with overweight and obesity (mean BMI = 31.2 ± 4.5 kg/m2 , age = 50.6 ± 10 years, 69% female, 87% Caucasian) throughout a 12-week Internet-based weight management intervention. Multilevel logistic regression investigated odds of nonadherence to self-weighing on a given day based on the previous day's caloric intake.Results: Self-monitoring adherence was high (weights: 87%; calories: 85%); adherence was associated with greater 12-week weight loss (weighing: r = -0.24, P = 0.04; calories: r = -0.26, P = 0.04). Increased caloric intake on a given day, relative to the individual's average intake, was associated with increased odds of nonadherence to self-weighing the next day (F(1,5106)  = 12.66, P = 0.0004, β = 0.001). For example, following a day of eating 300 calories more than usual, odds of not self-weighing increased by 1.33.Conclusions: Odds of nonadherence to self-weighing increased following a day with higher-than-usual caloric intake. Weight management interventions collecting daily self-monitoring data could provide support to participants who report increased caloric intake to prevent self-weighing nonadherence. [ABSTRACT FROM AUTHOR]