Effect of adherence to self-monitoring of diet and physical activity on weight loss in a technology-supported behavioral intervention

Abstract

BackgroundExamination of mediating behavioral factors could explain how an intervention works and thus provide guidance to optimize behavioral weight-loss programs. This study examined the mediating role of adherence to self-monitoring of diet and physical activity on weight loss in a behavioral weight-loss trial testing the use of personal digital assistants (PDA) for self-monitoring.MethodsMediation analysis was conducted to examine the possible mediating role of adherence to self-monitoring of diet and physical activity between treatments using varying self-monitoring methods (paper record, PDA, and PDA with daily tailored feedback messages) and weight loss.FindingsThe sample (N = 210) was predominantly white (78%) and female (85%). Compared to a paper record, using a PDA for self-monitoring diet (P = 0.027) and physical activity (P = 0.014) had significant direct effects on weight loss at 12 months, as well as a significant indirect effect on outcomes through improved adherence to self-monitoring (PS < 0.001). Receiving an automated daily feedback message via PDA only had a significant indirect effect on weight through self-monitoring adherence to diet (P = 0.004) and physical activity (P = 0.002).ConclusionsAdherence to self-monitoring of diet and physical activity is important as the underlying mechanism in this technology-supported behavioral weight-loss intervention.

A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial (Preprint)

“…The comparative findings revealed the mobile group participants had higher group session attendance and higher patient engagement and adherence to self-monitoring of multiple behaviors than the paper group, which was consistent with previous studies reporting higher adherence to self-monitoring rates using electronic diaries compared to paper diaries among overweight or obese populations [26,27]. In the diabetes population, a study planning to use a mobile application to support patient self-management did not recruit enough patients [28].…”

“…Fourth, our measure on adherence to self-monitoring of physical activity depended on patient adherence to the recommended physical activity behaviors. While this approach has been used in several other studies [26,33], it may underestimate the actual adherence to self-monitoring of physical activity. For example, our adherence to self-monitoring of physical activity was lower than adherence dietary self-monitoring, which could suggest that participants did not exercise at all on that particular day, they did not bother to enter 0 for exercise minutes, and instead, they left it blank.…”

Adherence as a predictor of weight loss in a commonly used smartphone application

“…Specifically, the adherence variable relied on time stamped data rather than self-reported data or the use of a sensor to indicate self-monitoring. In a previous trial [12], adherence was measured via a sensor which was able to detect whether the recording device was being used; however, it was unable to measure what information was recorded. A more objective, ecologically valid adherence measure was used in this study.…”

“…Electronic methods of self-monitoring by Web or mobile devices show increased rates of adherence over paper-andpencil methods of monitoring [10][11][12], suggesting that smartphone applications (apps) may be used to facilitate self-monitoring.…”

Does monitoring goal progress promote goal attainment? A meta-analysis of the experimental evidence.

“…The effect sizes did not differ significantly when studies with cluster randomized designs were included (d + = 1.98 and 0.40 for effects on progress monitoring and goal attainment, respectively) versus excluded (d + = 1.96 and 0.40, respectively), Q(1) = 0.33 and 0.02, p = 0.57 and 0.89. 6 The 20 studies used in the mediation analysis were Akers, Cornett, Savla, Davy, and Davy (2012), Boutelle, Kirschenbaum, Baker, and Mitchell (1999), Chambliss, Huber, Finlay, McDoniel, Kitzman-Ulrich, and Wilkinson (2011), Cussler et al (2008, Duran et al (2010), Gokee-La Rose, Gorin, andWing (2009), Hellerstedt andJeffrey (1997, behavior-focused phone group), Helsel et al (2007), Kempf, Tankova, and Martin (2013), ), Morgan et al (2009), Nguyen, Gill, Wolpin, Steele, and Benditt (2009), Pellegrini et al (2012), Runyan, Steenbergh, Bainbridge, Daugherty, Oke, and Fry (2013, Samuel-Hodge et al (2009), Tate et al (2001, Tan, Maganee, Chee, Lee, andTan (2011), Wang, Sereika, Chasens, Ewing, Matthews, andBurke (2012), Webber, Tate, and Bowling (2008), and Wing, Crane, Thomas, Kumar, and Weinberg (2010) if participants in the comparison condition were also asked to monitor their progress -a methodological feature that led to smaller effect sizes for progress monitoring. 7 For the purposes of this analysis we recomputed the effect size for goal attainment using only the measures for which the primary studies reported the correlation between the frequency of progress monitoring and goal attainment.…”