How Accurate are Recalls of Self-Weighing Frequency? Data from a 24-Month Randomized Trial

Perspectives on the Form, Magnitude, Certainty, Target, and Frequency of Financial Incentives in a Weight Loss Program

PURPOSE

Financial incentives are a promising approach to enhance weight loss outcomes; however, little guidance exists on the optimal incentive structure.

DESIGN

Mixed methods.

SETTING

An online weight management trial, combining outcome (i.e., weight loss) and behavioral (i.e., self-weighing, dietary self-monitoring, and steps) incentives over 12 months (up to $665).

SUBJECTS

116 participants who completed the incentive preference assessment at the 18-month follow-up visit.

METHOD

Response distributions on the form, magnitude, certainty, and target of the incentives and content analysis of the qualitative responses.

RESULTS

Nearly all (96.6%) participants indicated they liked receiving electronic Amazon gift cards, more so than the alternatives presented. Most participants (81.0%) thought they would have lost a similar amount of weight if the incentives were smaller. Few (18.1%) indicated they would have preferred a lottery structure, but 50.8% indicated the variable incentive schedule was beneficial during the maintenance period. Most (77.6%) felt incentives were most helpful when starting to lose weight. In both phases, most participants (85.3% and 72.4%, respectively) indicated appropriate behaviors were incentivized. Participants had mixed views on whether outcome or behavioral incentives were most motivating.

CONCLUSION

There was notable variation in preferences for the magnitude, duration, and timing of incentives; it will be important to examine in future research whether incentive design should be tailored to individual preferences.

Consistency With and Disengagement From Self-monitoring of Weight, Dietary Intake, and Physical Activity in a Technology-Based Weight Loss Program: Exploratory Study

BACKGROUND

Digital self-monitoring tools offer promise to improve adherence to self-monitoring of weight and weight-related behaviors; however, less is known regarding the patterns of participant consistency and disengagement with these tools.

OBJECTIVE

This study characterizes the consistency of use and time to disengagement with digital self-monitoring tools during a 6-month weight loss intervention and investigates whether the provision of phone-based intervention improved self-monitoring adherence.

METHODS

Participants were 54 adults with overweight or obesity (mean age 49.6 years, SD 12.4 years; mean BMI 32.6 kg/m², SD 3.2 kg/m²) enrolled in a pilot trial assessing the impact of self-monitoring technology (Fitbit Zip, Aria scale, and smartphone app), with and without additional interventionist contact, on weight loss. All participants received weight loss education and were asked to self-monitor weight, dietary intake, and physical activity daily throughout the 6-month program. Consistency was defined as the number of weeks that participants adhered to self-monitoring recommendations (7 out of 7 days). Disengagement was defined as the first of 2 consecutive weeks that the 7-day self-monitoring adherence goal was not met. Wilcoxon signed-rank tests were used to examine differences in consistency and disengagement by behavioral targets. t tests (2-tailed) and Cox proportional hazards models were used to examine whether providing additional interventionist contact would lead to significant improvements in consistency and time to disengagement from self-monitoring tools, respectively. Linear regressions were used to examine associations between consistency, time to disengagement, and weight loss.

RESULTS

Participants consistently self-monitored physical activity for more weeks (mean 17.4 weeks, SD 8.5 weeks) than weight (mean 11.1 weeks, SD 8.5 weeks) or dietary intake (mean 10.8 weeks, SD 8.7 weeks; P<.05). Similarly, participants had a significantly longer time to disengagement from self-monitoring of physical activity (median 19.5 weeks) than weight (4 weeks) or dietary intake (10 weeks; P<.001). Participants randomized to receive additional interventionist contact had significantly greater consistency and longer time to disengagement for self-monitoring of dietary intake compared with participants who did not (P=.006); however, there were no statistically significant differences between groups for self-monitoring of weight or physical activity (P=.24 and P=.25, respectively). Greater consistency and longer time to disengagement were associated with greater weight loss for self-monitoring of weight and dietary intake (P<.001 and P=.004, respectively) but not for physical activity (P=.57).

CONCLUSIONS

Results demonstrated that self-monitoring adherence differed by behavioral target, with greater consistency and longer time to disengagement associated with lower-burden tools (ie, self-monitoring of physical activity). Consistent with supportive accountability theory, additional interventionist contact improved consistency and lengthened time to disengagement from self-monitoring of dietary intake. Given the observed associations between consistency, disengagement, and weight loss outcomes, it is important to identify additional methods of increasing consistency and engagement with digital self-monitoring tools.

Distinguishing early patterns of physical activity goal attainment and weight loss in online behavioral obesity treatment using latent class analysis

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.

Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users

Background

Frequent self-weighing is associated with successful weight loss and weight maintenance during and after weight loss interventions. Less is known about self-weighing behaviors and associated weight change in free-living settings.

Objective

This study aimed to investigate the association between the frequency of self-weighing and changes in body weight in a large international cohort of smart scale users.

Methods

This was an observational cohort study with 10,000 randomly selected smart scale users who had used the scale for at least 1 year. Longitudinal weight measurement data were analyzed. The association between the frequency of self-weighing and weight change over the follow-up was investigated among normal weight, overweight, and obese users using Pearson’s correlation coefficient and linear models. The association between the frequency of self-weighing and temporal weight change was analyzed using linear mixed effects models.

Results

The eligible sample consisted of 9768 participants (6515/9768, 66.7% men; mean age 41.5 years; mean BMI 26.8 kg/m2). Of the participants, 4003 (4003/9768, 41.0%), 3748 (3748/9768, 38.4%), and 2017 (2017/9768, 20.6%) were normal weight, overweight, and obese, respectively. During the mean follow-up time of 1085 days, the mean weight change was –0.59 kg, and the mean percentage of days with a self-weigh was 39.98%, which equals 2.8 self-weighs per week. The percentage of self-weighing days correlated inversely with weight change, r=–0.111 (P<.001). Among normal weight, overweight, and obese individuals, the correlations were r=–0.100 (P<.001), r=–0.125 (P<.001), and r=–0.148 (P<.001), respectively. Of all participants, 72.5% (7085/9768) had at least one period of ≥30 days without weight measurements. During the break, weight increased, and weight gains were more pronounced among overweight and obese individuals: 0.58 kg in the normal weight group, 0.93 kg in the overweight group, and 1.37 kg in the obese group (P<.001).

Conclusions

Frequent self-weighing was associated with favorable weight loss outcomes also in an uncontrolled, free-living setting, regardless of specific weight loss interventions. The beneficial associations of regular self-weighing were more pronounced for overweight or obese individuals.

Minority and low-income patients are less likely to have a scale for self-weighing in their home: A survey in primary care

Daily self-weighing is a weight management behaviour that requires a scale; however, scale ownership may be cost-prohibitive for some patients. Our objective was to understand the proportion of primary care patients with a scale at home, and factors associated with home scale access, to potentially inform future interventions that facilitate scale access. Cross sectional survey of 216 adult patients from three primary care clinics: mixed-income urban/suburban (n = 68); mixed-income urban (n = 70); low-income urban (n = 74). The dependent variable was presence of a home scale; bivariate associations were conducted with variables including demographics, insurance type, clinic setting and self-reported height/weight. Mean age was 53 years; 71% women; 71% racial minority; mean body mass index 32 kg/m2 . Overall, 56% had a home scale. Most (79%) white patients owned a scale, compared to 46% of racial minority patients (P < .01); 33% of low-income patients owned scale, compared to over 66% of patients at the clinics serving mixed-income populations (P < .01). Most low-income urban clinic patients do not own a home scale. Because self-weighing is an effective weight-management behaviour, clinicians could consider assessing scale access, and future research should assess the health impact of providing scales to patients with overweight/obesity who desire weight loss or maintenance.

Frequency and Consistency of Self-Weighing to Promote Weight-Loss Maintenance

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.

Measurement Equivalence of E-Scale and In-Person Clinic Weights

OBJECTIVE

The current study aimed to determine whether electronic scale (e-scale) weight measurements are concordant with in-person clinic weights.

METHODS

E-scale and in-person clinic weight measurements from 248 active duty military personnel enrolled in a weight-loss intervention study were used. E-scale and clinic measurements were matched and tested to determine whether measurements were significantly different from each other. Equivalence between the two measurements was tested among the cohort and when stratifying by gender, BMI, race, and age. The study also examined whether matching the times of clinic and e-scale measurements or averaging multiple measurements was optimal, and whether using e-scale and clinic measurements from the same day or across a specified amount of time was acceptable.

RESULTS

Overall, e-scale and clinic measurements were significantly different from each other but did not differ from equality. Additionally, using e-scale and clinic weight measurements that were taken on the same day may be a preferable method compared with using measurements within a week of each other, which leads to weight underprediction among e-scale measurements.

CONCLUSIONS

E-scales display good measurement concordance. E-scales may be helpful when studying highly mobile populations, such as military personnel, and could potentially eliminate the need for in-person visits.

Accuracy of Self-Report Versus Objective Smart-Scale Weights During a 12-Week Weight Management Intervention

OBJECTIVE

Greater frequency of self-weighing has been associated with greater weight loss in weight management interventions, but little is known regarding the accuracy of self-reported weight data.

METHODS

Agreement between objective smart-scale and self-reported weight data was assessed in 74 adults (age = 50.7 years; BMI = 31.2 kg/m² ) enrolled in a 12-week, Internet-based weight management program. Participants were asked to self-weight daily using a study-provided smart scale and to self-report weights via the study website.

RESULTS

There was strong agreement between smart-scale and self-reported weight values (intraclass correlation = 0.982) but only moderate agreement regarding frequency of self-weighing assessed via each method (κ = 0.491; P < 0.0001). Greater self-weighing frequency was associated with greater weight loss across measures (all P < 0.001). Compared with days when participants did both, weights were 0.66 kg higher on days when participants self-weighed via the smart scale but did not self-report weight (8% of days) and 0.58 kg higher on days when they self-reported weight but did not self-weigh via the smart scale (4% of days; all P < 0.0001).

CONCLUSIONS

Results suggest that self-reported weight values are similar to smart-scale measurements; however, either method alone may underestimate self-weighing frequency. Furthermore, missing self-weighing data should not be treated as ignorable because weights may be higher than those observed on nonmissing days.