Standard behavioral weight loss interventions often set uniform physical activity (PA) goals and promote PA self-monitoring; however, adherence remains a challenge, and recommendations may not ...accommodate all individuals. Identifying patterns of PA goal attainment and self-monitoring behavior will offer a deeper understanding of how individuals adhere to different types of commonly prescribed PA recommendations (ie, minutes of moderate-to-vigorous physical activity MVPA and daily steps) and guide future recommendations for improved intervention effectiveness.
This study examined weekly patterns of adherence to step-based and minute-based PA goals and self-monitoring behavior during a 6-month online behavioral weight loss intervention.
Participants were prescribed weekly PA goals for steps (7000-10,000 steps/day) and minutes of MVPA (50-200 minutes/week) as part of a lifestyle program. Goals gradually increased during the initial 2 months, followed by 4 months of fixed goals. PA was self-reported daily on the study website. For each week, participants were categorized as adherent if they self-monitored their PA and met the program PA goal, suboptimally adherent if they self-monitored but did not meet the program goal, or nonadherent if they did not self-monitor. The probability of transitioning into a less adherent status was examined using multinomial logistic regression.
Participants (N=212) were predominantly middle-aged females with obesity, and 67 (31.6%) self-identified as a racial/ethnic minority. Initially, 73 (34.4%) participants were categorized as adherent to step-based goals, with 110 51.9% suboptimally adherent and 29 13.7% nonadherent, and there was a high probability of either remaining suboptimally adherent from week to week or transitioning to a nonadherent status. However, 149 (70.3%) participants started out adherent to minute-based goals (34 16% suboptimally adherent and 29 13.7% nonadherent), with suboptimally adherent seen as the most variable status. During the graded goal phase, participants were more likely to transition to a less adherent status for minute-based goals (odds ratio OR 1.39, 95% CI 1.31-1.48) compared to step-based goals (OR 1.24, 95% CI 1.17-1.30); however, no differences were seen during the fixed goal phase (minute-based goals: OR 1.06, 95% CI 1.05-1.08; step-based goals: OR 1.07, 95% CI 1.05-1.08).
States of vulnerability to poor PA adherence can emerge rapidly and early in obesity treatment. There is a window of opportunity within the initial 2 months to bring more people toward adherent behavior, especially those who fail to meet the prescribed goals but engage in self-monitoring. Although this study describes the probability of adhering to step- and minute-based targets, it will be prudent to determine how individual characteristics and contextual states relate to these behavioral patterns, which can inform how best to adapt interventions.
ClinicalTrials.gov NCT02688621; https://clinicaltrials.gov/ct2/show/NCT02688621.
Internet-delivered behavioral weight control is promising for expanding the reach and availability of weight management, but online programs produce lower weight losses than typically achieved in ...person. Financial incentives have been shown to increase weight losses. This study examined whether adding financial incentives for self-monitoring and achieving target weight losses increases weight losses attained in a fully online, group-based behavioral weight management program compared with the same program alone.
This study was an RCT.
Adults with overweight and obesity (n=418; 91% female; 28% minority) were recruited from 2 clinical centers.
The intervention was a 24-session online group-based behavioral weight control program with weekly synchronous chat sessions (Internet-only) or the same program with weekly financial incentives for self-monitoring body weight and dietary intake daily and for achieving target weight losses at 2 and 6 months (Internet + incentives).
This study measured weight loss at 6 months and treatment engagement (attendance, self-monitoring of body weight, dietary intake, and physical activity). Data were collected between February 2016 and August 2018, and analyses were completed in 2019.
Participants randomized to the Internet + incentives group lost more weight (−6.4 SD=5.5 kg) than those in the Internet-only group (−4.7 SD=6.6 kg; p<0.01). Further, a higher proportion of the Internet + incentives group achieved ≥5% weight loss (55%) than those in the Internet-only group (40%; p<0.05). Treatment engagement was higher in the Internet + incentives condition, with greater self-monitoring of behaviors targeted by incentives, as well as higher rates of behaviors not targeted and higher self-reported physical activity. Study retention was higher among those in the Internet + incentives condition (91%) than those in the Internet-only condition (81%; p=0.003).
Adding financial incentives to a program delivered fully online increases weight losses compared with the program alone and can achieve weight losses comparable to in-person programs, offering potential for substantial geographic reach.
This study is registered at www.clinicaltrials.gov NCT02688621.
Objective
Dietary self‐monitoring is consistently related to both short‐ and long‐term weight loss, but typically declines over time. Adopting an abbreviated approach to self‐monitoring might reduce ...burden and potentially increase engagement while maintaining efficacy.
Methods
Using a Delphi‐type study, experts were queried about abbreviated self‐monitoring approaches that might best balance efficacy and burden and asked to identify when these approaches might best be implemented within a behavioral weight loss program. Experts were surveyed three times until consensus was reached.
Results
Experts identified three main categories of promising strategies for abbreviated self‐monitoring regardless of whether individuals have been successful with weight loss or full dietary self‐monitoring: (1) self‐weighing only, (2) reducing the foods/beverages self‐monitored to those that are often less routine and higher in caloric density, and (3) reducing the number of days per week to engage in full dietary self‐monitoring. Experts recommended transitioning to abbreviated self‐monitoring after 2 weeks of no self‐monitoring among individuals who were struggling and after reaching 5%–10% weight loss among successful individuals.
Conclusions
These expert opinions offer a foundation to experimentally manipulate promising strategies for reducing burden and increasing long‐term engagement in self‐monitoring, with a goal of enhancing long‐term weight control.
Behavioral weight loss programs often prescribe physical activity (PA) goals in terms of minutes/week of moderate-to-vigorous PA (MVPA) and steps/day. However, the impact of meeting each type of goal ...prescription on weight loss is unclear, particularly in digitally-based (eHealth/mHealth) programs. This secondary analysis of a randomized trial examined the effects of meeting steps-based and minutes-based goals on weight loss in an eHealth behavioral weight control program.
Adults in the control arm received a 6-month online behavioral weight loss intervention with prescribed weekly goals for daily steps and minutes of MVPA. The number of weeks steps-based and minutes-based goals were met (≥100% and ≥75% thresholds) based on self-reported PA were examined as predictors of 6-month weight loss among those providing weight outcomes (n = 172; 81% of control arm) using a systems regression approach.
Participants (BMI 35.6 kg/m
2
; 90.1% female; 48.7 years of age) met weekly goals for MVPA (7.1 ± 6.4 weeks) more often than steps (3.5 ± 5.5 weeks, P < .001). Meeting the steps goals (β = .24, P < .001) and MVPA goals (β = .20, P < .001) were each statistically significant predictors of weight loss at the 100% threshold; their total effects were not statistically different from one another (χ
2
= 1.12, P = .29). Similarly, at the 75% threshold for steps goals (β = .19, P < .001) and MVPA goals (β = .19, P < .001), each independently predicted weight loss; no differences were detected in their total effects (χ
2
= .01, P = .92). The probability of reaching ≥5% weight loss was comparable between meeting the steps goals and MVPA goals at both adherence thresholds.
Greater attainment of PA goals prescribed as steps and minutes of MVPA independently contribute to similar weight loss outcomes in a 6-month online behavioral weight loss intervention. Future research should determine whether promoting adherence to combined steps-based and minutes-based goals produces better weight loss than utilizing either goal alone and identify strategies that improve adherence.
Objective
This study examined the impact of a financial incentive scheme integrating process and outcome incentives across weight‐loss induction and weight maintenance on 18‐month weight outcomes.
...Methods
This was a randomized controlled trial. Participants with overweight or obesity (n = 418; 91% female; 28% racial/ethnic minority) were randomized to an 18‐month, online, group‐based behavioral weight‐control program (Internet‐Only) or the same program with financial incentives provided for 12 months, contingent on self‐regulatory weight‐control behaviors (self‐weighing, dietary self‐monitoring, and physical activity) and weight‐outcome benchmarks (Internet+Incentives). No financial incentives were provided from Months 13 to 18 to examine the durability of weight‐control behaviors and outcomes without incentives.
Results
Weight‐loss induction at Month 6 was significantly greater for Internet+Incentives than Internet‐Only (6.8% vs. 4.9%, respectively, p = 0.01). Individuals receiving incentives were significantly more likely to maintain weight loss ≥ 5% at Month 12 (45% in Internet+Incentives vs. 32% in Internet‐Only, p < 0.02) and remain weight stable (39% vs. 27%, respectively, p < 0.01). Internet+Incentives participants also reported significantly greater behavioral engagement through Month 12. However, once incentives ceased, there were no differences in sustained weight outcomes (Month 18), and engagement declined dramatically.
Conclusions
Despite promoting greater treatment engagement and initial weight loss, financial incentives as offered in this study did not promote better extended weight control.
To comprehensively assess the extent to which the decline in cardiorespiratory fitness (CRF) with age differs between sexes.
This study used data from the Aerobics Center Longitudinal Study, ...conducted between September 1974 and August 2006, consisting primarily of White adults from middle-to-upper socioeconomic strata restricted to adults without type 2 diabetes mellitus (33,742 men and 9,415 women). Quantile regression models were used to estimate the differences in age-associated changes in CRF between the sexes, estimated using a maximal treadmill test.
For adults aged up to 45 years, significant differences in slopes relating to age and CRF between men and women were observed for all adjusted percentiles of CRF other than the 90th percentile; women reported significantly greater declines in CRF per year. For those aged 45-60 years and those older than 60 years, no significant differences in age-related declines in CRF were observed between the sexes.
This study found that compared with men, the onset of decline in CRF was found to occur earlier and at lower CRF percentiles in women. This is of particular concern, given that compared with men, women already tend to have lower CRF levels. These findings suggest that maintaining the levels of physical activity sufficient to maintain moderate-to-high levels of fitness is particularly important for women earlier during adulthood.
Objective
Weight control programs that incorporate group sessions produce greater weight losses, but this has not been explored in the context of online programs. Further, counselor‐crafted ...self‐monitoring feedback is a core element of lifestyle interventions, although pre‐scripted, modular feedback which does not require detailed counselor review may adequately promote weight loss. The current study explored the weight losses achieved in an online program that included facilitated group sessions, as well as outcomes when counselor‐crafted self‐monitoring feedback was provided.
Methods
A 2 × 2 pilot factorial randomized participants (90% women) with overweight/obesity (N = 73) to facilitated group sessions (yes/no) and type of feedback (counselor‐crafted/pre‐scripted, modular) within a 16‐week online behavioral weight control program. Weight change outcomes were collected digitally. Treatment engagement and intervention delivery time were also tracked.
Results
Individuals offered weekly facilitated online group sessions lost more weight (−5.3% ± 4.9%) than those receiving the same digital program without group sessions (−3.1% ± 4.0%; p = 0.04). Those receiving group sessions also demonstrated significantly greater treatment engagement. Individuals receiving pre‐scripted, modular feedback lost significantly more weight (−5.3% ± 4.8%) than those receiving the more traditional counselor‐crafted feedback (−3.1% ± 4.1%; p = 0.04), but treatment engagement did not differ between conditions. However, interventionist time required to provide feedback was markedly lower for pre‐scripted than counselor‐crafted feedback (1.4 vs. 3.5 h per participant over 16 weeks, respectively, p = 0.01).
Conclusions
Incorporating weekly facilitated online group sessions significantly increased weight losses achieved in a digital lifestyle program. Further, pre‐scripted, modular feedback required significantly less staff time than counselor‐crafted feedback without diminishing weight losses. Thus, group sessions and pre‐scripted feedback warrant consideration when designing digital lifestyle programs.
Abstract
Physical activity (PA) goal adherence is consistently associated with greater weight loss during behavioral obesity treatment, and early weight loss response predicts future weight loss ...success. However, it remains unclear which behaviors during the initial weeks of treatment distinguish responders from nonresponders and might be effective targets for improving treatment outcomes. To characterize subgroups with distinct patterns of PA goal adherence during the initial 2 months of an online, group-based weight control program and determine associations between these patterns and 6-month weight loss. Participants received an online behavioral obesity intervention with PA goals and daily self-monitoring. Weekly adherence to step goals and moderate-to-vigorous PA (MVPA) minute goals based on self-monitoring records were examined using latent class analysis. Body weight was objectively measured at 0, 2, and 6 months. Participants (N = 212; 91.5% female, 31.6% race/ethnic minority, mean body mass index: 35.8 ± 5.9 kg/m2) clustered into three subgroups based on early goal attainment: “Both PA Goals,” “MVPA Goals Only,” and “Neither PA Goal.” The “Both PA Goals” class had significantly greater 6-month weight loss (estimated mean weight loss 95% CI: −9.4% 7.4 to 11.5) compared to the “MVPA Goals Only” (−4.8% 3.4 to 6.1) and “Neither PA Goal” classes (−2.5% 1.4 to 3.6). Individuals meeting both PA goals early in treatment achieve greater weight losses than those meeting MVPA but not step goals, pointing to the need to explore factors associated with nonadherence to each of the PA goals to better understand these potential targets for treatment refinement and adaptive interventions.
Lay Summary
This study is the first to characterize subgroups of individuals engaged in a behavioral weight control program with distinct patterns of early physical activity (PA) goal attainment. These early PA patterns emerged as a novel factor associated with subsequent weight loss and provide an important lens to view early treatment engagement. The greatest weight losses were seen in the subgroup likely to meet program goals for both weekly minutes of moderate-to-vigorous PA and daily steps. Understanding the factors associated with PA goal attainment during the initial 2 months of a behavioral weight control program may provide insights that will allow early identification of likely treatment success and detect individuals at risk for reduced weight losses, which could signal individuals for whom additional or different support may then be directed to increase weight loss success.
This commentary provides an overview of how tailored physical activity intervention development may benefit from 1) improving the engagement of diverse knowledge users in co-design and 2) gaining a better understanding of the ethical considerations that may affect the use of technology to support tailored interventions.
Gamification represents a promising approach for facilitating positive social interactions among groups of individuals and is increasingly being leveraged in physical activity (PA) interventions to ...promote enhanced intervention engagement and PA outcomes. Although African American (AA) adults experience disparities associated with health conditions that can be ameliorated with increased PA, little is known about how best to culturally target PA gamification strategies for this population. The purpose of this study was to gather perspectives from AA adults residing in the Southeast United States and subsequently identify themes to help inform the cultural adaptation of an existing electronic and mobile health (e/mHealth) gamification- and theory-based PA intervention for teams of insufficiently active AA adults.
An AA moderator facilitated six online focus groups among AA adults (n=42; 93% female; 45.09±9.77 years; 34.40±57.38 minutes/week of reported moderate-intensity equivalent PA), using a semi-structured focus group guide. Drawing from a content analysis approach, transcripts were coded and salient themes were identified.
The focus groups revealed the following seven themes: (I) motivation (team-based gamification motivating); (II) accountability (team-based gamification promotes accountability); (III) competition (competitive elements attractive); (IV) weekly challenges (prefer to choose weekly PA challenges); (V) leaderboard feedback (preference for viewing steps and active minutes via a leaderboard); (VI) cultural relevancy (prefer elements reflective of their race and culture that promote team unity); (VII) teammate characteristics (mixed preferences regarding ideal sociodemographic characteristics and starting PA level of teammates).
Integrating team-based gamification in an e/mHealth-based PA intervention may be acceptable among AA adults. The identification of specific design preferences and perceptions of the value of the social environment points to the need to consider surface-level and deep structure cultural targeting when developing and further exploring best practices regarding gamified PA interventions for insufficiently active AAs.
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