Associations between self-monitoring and weight change in behavioral weight loss interventions

Stephanie P Goldstein, Carly M Goldstein, Dale S Bond, Hollie A Raynor, Rena R Wing, J Graham Thomas, Stephanie P Goldstein, Carly M Goldstein, Dale S Bond, Hollie A Raynor, Rena R Wing, J Graham Thomas

Abstract

Objective: The current study is a secondary analysis of the Live SMART trial, a randomized controlled trial comparing a behavioral weight loss (BWL) condition delivered via smartphone (SMART) to a group-based BWL condition (GROUP) and a control condition (CONTROL). Given the established importance of self-monitoring for weight loss, the aims were to evaluate bidirectional associations between adherence to self-monitoring and weight change and to examine the moderating effect of treatment condition on these associations.

Method: Adults with overweight/obesity (n = 276; 83% women; 92.8% White; Mage = 55.1 years; Mbody mass index = 35.2 kg/m2) were instructed to self-monitor dietary intake, daily weight, and physical activity minutes via paper diaries in GROUP and CONTROL and via a smartphone application in SMART. All participants were weighed monthly at the research center. Adherence to self-monitoring was assessed via examination of self-monitoring records.

Results: Generalized linear mixed models revealed that adherence to self-monitoring of dietary intake, self-weighing, and physical activity for each month was associated with weight change throughout that month, such that increased frequency of self-monitoring led to greater weight loss (ps < .001). For the GROUP condition only, poorer weight losses in 1 month were prospectively associated with poor adherence to self-monitoring the following month (ps ≤ .01).

Conclusions: Results provide evidence of a bidirectional association between self-monitoring and weight change. Better self-monitoring was consistently associated with better weight loss across intervention and tracking modalities. Poorer weight loss was prospectively associated with poorer self-monitoring in group treatment, suggesting that social influences could drive adherence in this form of treatment. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Trial registration: ClinicalTrials.gov NCT01724632.

Conflict of interest statement

Disclosure: The authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.
Percentage of Missing Data: Self-monitoring and Percent Weight Loss Notes: Missing self-monitoring data are representative of records with no days of monitoring or records not turned in; Percent weight loss is representative of attendance at clinic visits (i.e., a value is missing if the participant did not attend the current and/or previous clinic visit for that particular month); Adherence to self-monitoring across conditions can be found in the primary outcomes paper (Thomas et al., 2019).
Figure 2.
Figure 2.
Prospective association between adherence to self-monitoring and %WL across treatment conditions. In (a), adherence to self-monitoring dietary intake is pictured, followed by adherence to self-monitoring weight (b) and physical activity (c). Note: Greater %WL is indicative of more weight loss

Source: PubMed

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