Effects of Goal Type and Reinforcement Type on Self-Reported Domain-Specific Walking Among Inactive Adults: 2×2 Factorial Randomized Controlled Trial

Abstract

Background: WalkIT Arizona was a 2×2 factorial trial examining the effects of goal type (adaptive versus static) and reinforcement type (immediate versus delayed) to increase moderate to vigorous physical activity (MVPA) among insufficiently active adults. The 12-month intervention combined mobile health (mHealth) technology with behavioral strategies to test scalable population-health approaches to increasing MVPA. Self-reported physical activity provided domain-specific information to help contextualize the intervention effects.

Objective: The aim of this study was to report on the secondary outcomes of self-reported walking for transportation and leisure over the course of the 12-month WalkIT intervention.

Methods: A total of 512 participants aged 19 to 60 years (n=330 [64.5%] women; n=425 [83%] Caucasian/white, n=96 [18.8%] Hispanic/Latinx) were randomized into interventions based on type of goals and reinforcements. The International Physical Activity Questionnaire-long form assessed walking for transportation and leisure at baseline, and at 6 months and 12 months of the intervention. Negative binomial hurdle models were used to examine the effects of goal and reinforcement type on (1) odds of reporting any (versus no) walking/week and (2) total reported minutes of walking/week, adjusted for neighborhood walkability and socioeconomic status. Separate analyses were conducted for transportation and leisure walking, using complete cases and multiple imputation.

Results: All intervention groups reported increased walking at 12 months relative to baseline. Effects of the intervention differed by domain: a significant three-way goal by reinforcement by time interaction was observed for total minutes of leisure walking/week, whereas time was the only significant factor that contributed to transportation walking. A sensitivity analysis indicated minimal differences between complete case analysis and multiple imputation.

Conclusions: This study is the first to report differential effects of adaptive versus static goals for self-reported walking by domain. Results support the premise that individual-level PA interventions are domain- and context-specific and may be helpful in guiding further intervention refinement.

Trial registration: Preregistered at clinicaltrials.gov: (NCT02717663) https://ichgcp.net/clinical-trials-registry/NCT02717663.

International registered report identifier (irrid): RR2-10.1016/j.cct.2019.05.001.

Keywords: adaptive intervention; behavioral intervention; exercise; goals; health behavior; health promotion; mHealth; population health; reward; walking.

Conflict of interest statement

Conflicts of Interest: None declared.

©Mindy L McEntee, Alison Cantley, Emily Foreman, Vincent Berardi, Christine B. Phillips, Jane C. Hurley, Melbourne F. Hovell, Steven Hooker, Marc A. Adams. Originally published in JMIR Formative Research (http://formative.jmir.org), 04.12.2020.

Figures

Figure 1

Participant flow.

Figure 2

Split violin plots showing distribution of self-reported walking at baseline (BL), 6 months (6M), and 12 months (12M). Horizontal lines indicate 25th, 50th, and 75th percentiles computed from density estimates.

Figure 3

Reinforcement by time interaction in negative binomial count model 2 for leisure walking at baseline (BL), 6 months (6M), and 12 months (12M).

Figure 4

Goal by reinforcement by time interaction in negative binomial count model 3 for leisure walking at baseline (BL), 6 months (6M), and 12 months (12M).

Figure 5

Reinforcement by time interaction in negative binomial count model 2 for transportation walking at baseline (BL), 6 months (6M), and 12 months (12M).

Figure 6

Goal by time interaction in negative binomial count model 1 for transportation biking at baseline (BL), 6 months (6M), and 12 months (12M).

Figure 7

Reinforcement by time interaction in negative binomial count model 2 for transportation biking at baseline (BL), 6 months (6M), and 12 months (12M).

Figure 8

Goal by reinforcement by time interaction for negative binomial hurdle model 3 for transportation biking at baseline (BL), 6 months (6M), and 12 months (12M).

Figure 9

Goal by reinforcement by time interaction in negative binomial count model 3 for transportation biking at baseline (BL), 6 months (6M), and 12 months (12M).