Hoj TH, Covey EL, Jones AC, Haines AC, Hall PC, Crookston BT, West JH. How Do Apps Work? An Analysis of Physical Activity App Users' Perceptions of Behavior Change Mechanisms.
JMIR Mhealth Uhealth 2017;
5:e114. [PMID:
28778846 PMCID:
PMC5561388 DOI:
10.2196/mhealth.7206]
[Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 04/22/2017] [Accepted: 06/10/2017] [Indexed: 12/27/2022] Open
Abstract
Background
Physical activity apps are commonly used to increase levels of activity and health status. To date, the focus of research has been to determine the potential of apps to influence behavior, to ascertain the efficacy of a limited number of apps to change behavior, and to identify the characteristics of apps that users prefer.
Objective
The purpose of this study was to identify the mechanisms by which the use of physical activity apps may influence the users’ physical activity behavior.
Methods
This study used a cross-sectional survey of users of health-related physical activity apps during the past 6 months. An electronic survey was created in Qualtrics’ Web-based survey software and deployed on Amazon Mechanical Turk. Individuals who had used at least one physical activity app in the past 6 months were eligible to respond. The final sample comprised 207 adults living in the United States. 86.0% (178/207) of respondents were between the ages of 26 and 54 years, with 51.2% (106/207) of respondents being female. Behavior change theory informed the creation of 20 survey items relating to the mechanisms of behavior change. Respondents also reported about engagement with the apps, app likeability, and physical activity behavior.
Results
Respondents reported that using a physical activity app in the past 6 months resulted in a change in their attitudes, beliefs, perceptions, and motivation. Engagement with the app (P<.001), frequency of app use (P=.03), and app price (P=.01) were related to the reported impact of the behavior change theory or mechanisms of change. The mechanisms of change were associated with self-reported physical activity behaviors (P<.001).
Conclusions
The findings from this study provide an overview of the mechanisms by which apps may impact behavior. App developers may wish to incorporate these mechanisms in an effort to increase impact. Practitioners should consider the extent to which behavior change theory is integrated into a particular app when they consider making recommendations to others wishing to increase levels of physical activity.
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