An Interactive Simulation to Change Outcome Expectancies and Intentions in Adults With Type 2 Diabetes: Within-Subjects Experiment.

摘要: Background: Computerized simulations are underutilized to educate or motivate patients with chronic disease. Objective: The aim of this study was test the efficacy an interactive, personalized simulation that demonstrates acute effect physical activity on blood glucose. Our goal its effects activity-related outcome expectancies and behavioral intentions among adults type 2 diabetes mellitus (T2DM). Methods: In within-subjects experiment, potential participants were emailed a link website directed through 7 tasks: (1) consent; (2) demographics, baseline intentions, self-reported walking; (3) orientation diurnal glucose curve; (4) expectancy, measured by novel drawing task in which use their mouse draw expected difference curve if they had walked; (5) interactive simulation; (6) postsimulation expectancy second task; (7) final measures impressions website. To our primary hypothesis participants’ regarding walking would shift toward presented simulation, we used paired t compare differences between change area under two drawings. whether walk increased, tests. assess intervention’s usability, collected both quantitative qualitative data perceptions tasks simulation. Results: A total 2019 individuals visited 1335 (566 males, 765 females, 4 others) provided complete data. Participants largely late middle-aged (mean=59.8 years; standard deviation=10.5), female 56.55% (755/1335), Caucasian 77.45% (1034/1335), lower income 64.04% (855/1335) t1334=3.4, P ≤.001). hypothesis, coming week increase, also supported; general intention (mean difference=0.31/7, t1001=10.8, P<.001) minutes last versus planned for difference=33.5 min, t1334=13.2, increased. Finally, examination feedback suggested some difficulty understanding This led post-hoc subset analysis. analysis, markedly stronger, suggesting further work is needed determine moderators Conclusions: efficacious changing T2DM. We discuss applications results design mobile health (mHealth) interventions. [JMIR Diabetes 2018;3(1):e2]