Predictors of Walking App Users With Comparison of Current Users, Previous Users, and Informed Nonusers in a Sample of Dutch Adults: Questionnaire Study
BackgroundThe last decade has seen a substantial increase in the use of mobile health apps and research into the effects of those apps on health and health behaviors. In parallel, research has aimed at identifying population subgroups that are more likely to use those health apps. Current evidence is limited by two issues. First, research has focused on broad health apps, and little is known about app usage for a specific health behavior. Second, research has focused on comparing current users and current nonusers, without considering subgroups of nonusers. ObjectiveWe aimed to provide profile... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2021 |
Reihe/Periodikum: | JMIR mHealth and uHealth, Vol 9, Iss 5, p e13391 (2021) |
Verlag/Hrsg.: |
JMIR Publications
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Schlagwörter: | Information technology / T58.5-58.64 / Public aspects of medicine / RA1-1270 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26628264 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.2196/13391 |
BackgroundThe last decade has seen a substantial increase in the use of mobile health apps and research into the effects of those apps on health and health behaviors. In parallel, research has aimed at identifying population subgroups that are more likely to use those health apps. Current evidence is limited by two issues. First, research has focused on broad health apps, and little is known about app usage for a specific health behavior. Second, research has focused on comparing current users and current nonusers, without considering subgroups of nonusers. ObjectiveWe aimed to provide profile distributions of current users, previous users, and informed nonusers, and to identify predictor variables relevant for profile classification. MethodsData were available from 1683 people who participated in a Dutch walking event in Amsterdam that was held in September 2017. They provided information on demographics, self-reported walking behavior, and walking app usage, as well as items from User Acceptance of Information Technology, in an online survey. Data were analyzed using discriminant function analysis and multinomial logistic regression analysis. ResultsMost participants were current walking app users (899/1683, 53.4%), while fewer participants were informed nonusers (663/1683, 39.4%) and very few were previous walking app users (121/1683, 7.2%). Current walking app users were more likely to report walking at least 5 days per week and for at least 30 minutes per bout (odds ratio [OR] 1.44, 95% CI 1.11-1.85; P=.005) and more likely to be overweight (OR 1.72, 95% CI 1.24-2.37; P=.001) or obese (OR 1.49, 95% CI 1.08-2.08; P=.005) as compared with informed nonusers. Further, current walking app users perceived their walking apps to be less boring, easy to use and retrieve information, and more helpful to achieve their goals. Effect sizes ranged from 0.10 (95% CI 0.08-0.30) to 1.58 (95% CI 1.47-1.70). ConclusionsThe distributions for walking app usage appeared different from the distributions for more general health ...