Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis

BackgroundRising criticism about the risks associated with the use of mobile health apps necessitates a critical perspective to assess the use of these apps. A cost-benefit approach involving several moderating factors can be used to detect technology effects and individual-l...

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Main Author: Mano, Rita
Format: Article
Language:English
Published: JMIR Publications 2021-04-01
Series:JMIR Human Factors
Online Access:https://humanfactors.jmir.org/2021/2/e21251
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spelling doaj-33969d0ecb3442ca99488e7e1f921b412021-04-22T13:30:58ZengJMIR PublicationsJMIR Human Factors2292-94952021-04-0182e2125110.2196/21251Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling AnalysisMano, Rita BackgroundRising criticism about the risks associated with the use of mobile health apps necessitates a critical perspective to assess the use of these apps. A cost-benefit approach involving several moderating factors can be used to detect technology effects and individual-level push and pull factors related to health attitudes, lifestyle, and health management behaviors. ObjectiveWe introduce a cost-benefit perspective to examine how health attitudes related to mobile health apps and health situational factors (health crises, health changes, and hospitalization) affect the likelihood of adopting lifestyle and health management behaviors among app users. MethodsThe analysis is based on individuals’ reported use of mobile health apps. The sample included 1495 US adults aged over 18 years who were contacted by landline or cellphone. A total of 50.96% (762/1495) of the participants were women. A set of logistic regression models was used to predict lifestyle and health management behaviors among users considering variations in the extent of use, health attitudes, health situation, and socioeconomic characteristics. ResultsThe findings indicate that the proposed models were reasonably adequate. In all, 88.76% (1327/1495) of the cases were correctly classified regarding lifestyle behaviors, but only 71.97% (1076/1495) of the cases were correctly classified regarding health management behaviors. Although a large percentage of individuals changed their attitudes following the use of mobile health apps, only a small proportion adopted health management behaviors. The use of mobile health apps affected up to 67.95% (1016/1495) of the users for consultation and 71.97% (1076/1495) of the users for decision making. The model was effective for 88.76% (1327/1495) of the cases regarding lifestyle behaviors but only 71.97% (1076/1495) regarding health management behaviors. The moderating effect of regular use of mobile health apps significantly affects lifestyle (Wald=61.795; B=2.099; P<.005) but not health management behaviors (Wald=12.532; B=0.513; P=.01). These results collectively indicate that the use of mobile health apps for health management is partially effective. ConclusionsThe use of mobile health apps is a main route to instigate the process of health empowerment and shape health attitudes. However, an accurate assessment of the effectiveness of mobile health apps necessitates distinguishing between lifestyle and health management behaviors and adopting a cost-benefit approach because individuals facing health concerns, such as a chronic disease, health emergency, health crisis, or health change, consider their affordances and situational effects. These moderators generate a push and pull framework in the decision-making process that balances the costs and benefits of use.https://humanfactors.jmir.org/2021/2/e21251
collection DOAJ
language English
format Article
sources DOAJ
author Mano, Rita
spellingShingle Mano, Rita
Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis
JMIR Human Factors
author_facet Mano, Rita
author_sort Mano, Rita
title Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis
title_short Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis
title_full Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis
title_fullStr Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis
title_full_unstemmed Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis
title_sort mobile health apps and health management behaviors: cost-benefit modeling analysis
publisher JMIR Publications
series JMIR Human Factors
issn 2292-9495
publishDate 2021-04-01
description BackgroundRising criticism about the risks associated with the use of mobile health apps necessitates a critical perspective to assess the use of these apps. A cost-benefit approach involving several moderating factors can be used to detect technology effects and individual-level push and pull factors related to health attitudes, lifestyle, and health management behaviors. ObjectiveWe introduce a cost-benefit perspective to examine how health attitudes related to mobile health apps and health situational factors (health crises, health changes, and hospitalization) affect the likelihood of adopting lifestyle and health management behaviors among app users. MethodsThe analysis is based on individuals’ reported use of mobile health apps. The sample included 1495 US adults aged over 18 years who were contacted by landline or cellphone. A total of 50.96% (762/1495) of the participants were women. A set of logistic regression models was used to predict lifestyle and health management behaviors among users considering variations in the extent of use, health attitudes, health situation, and socioeconomic characteristics. ResultsThe findings indicate that the proposed models were reasonably adequate. In all, 88.76% (1327/1495) of the cases were correctly classified regarding lifestyle behaviors, but only 71.97% (1076/1495) of the cases were correctly classified regarding health management behaviors. Although a large percentage of individuals changed their attitudes following the use of mobile health apps, only a small proportion adopted health management behaviors. The use of mobile health apps affected up to 67.95% (1016/1495) of the users for consultation and 71.97% (1076/1495) of the users for decision making. The model was effective for 88.76% (1327/1495) of the cases regarding lifestyle behaviors but only 71.97% (1076/1495) regarding health management behaviors. The moderating effect of regular use of mobile health apps significantly affects lifestyle (Wald=61.795; B=2.099; P<.005) but not health management behaviors (Wald=12.532; B=0.513; P=.01). These results collectively indicate that the use of mobile health apps for health management is partially effective. ConclusionsThe use of mobile health apps is a main route to instigate the process of health empowerment and shape health attitudes. However, an accurate assessment of the effectiveness of mobile health apps necessitates distinguishing between lifestyle and health management behaviors and adopting a cost-benefit approach because individuals facing health concerns, such as a chronic disease, health emergency, health crisis, or health change, consider their affordances and situational effects. These moderators generate a push and pull framework in the decision-making process that balances the costs and benefits of use.
url https://humanfactors.jmir.org/2021/2/e21251
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