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      Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study

      research-article
      , MSc 1 , , , PhD 1 , , DiplPsych 1 , , PhD 1 , , PhD, Prof Dr 1
      (Reviewer), (Reviewer), (Reviewer), (Reviewer), (Reviewer)
      JMIR mHealth and uHealth
      JMIR Publications
      technology acceptance, UTAUT2, mHealth, privacy concerns, trust

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          Abstract

          Background

          Mobile health (mHealth) care apps are a promising technology to monitor and control health individually and cost-effectively with a technology that is widely used, affordable, and ubiquitous in many people’s lives. Download statistics show that lifestyle apps are widely used by young and healthy users to improve fitness, nutrition, and more. While this is an important aspect for the prevention of future chronic diseases, the burdened health care systems worldwide may directly profit from the use of therapy apps by those patients already in need of medical treatment and monitoring.

          Objective

          We aimed to compare the factors influencing the acceptance of lifestyle and therapy apps to better understand what drives and hinders the use of mHealth apps.

          Methods

          We applied the established unified theory of acceptance and use of technology 2 (UTAUT2) technology acceptance model to evaluate mHealth apps via an online questionnaire with 707 German participants. Moreover, trust and privacy concerns were added to the model and, in a between-subject study design, the influence of these predictors on behavioral intention to use apps was compared between lifestyle and therapy apps.

          Results

          The results show that the model only weakly predicted the intention to use mHealth apps ( R 2=0.019). Only hedonic motivation was a significant predictor of behavioral intentions regarding both app types, as determined by path coefficients of the model (lifestyle: 0.196, P=.004; therapy: 0.344, P<.001). Habit influenced the behavioral intention to use lifestyle apps (0.272, P<.001), while social influence (0.185, P<.001) and trust (0.273, P<.001) predicted the intention to use therapy apps. A further exploratory correlation analysis of the relationship between user factors on behavioral intention was calculated. Health app familiarity showed the strongest correlation to the intention to use ( r=0.469, P<.001), stressing the importance of experience. Also, age ( r=–0.15, P=.004), gender ( r=–0.075, P=.048), education level ( r=0.088, P=.02), app familiarity ( r=0.142, P=.007), digital health literacy ( r=0.215, P<.001), privacy disposition ( r=–0.194, P>.001), and the propensity to trust apps ( r=0.191, P>.001) correlated weakly with behavioral intention to use mHealth apps.

          Conclusions

          The results indicate that, rather than by utilitarian factors like usefulness, mHealth app acceptance is influenced by emotional factors like hedonic motivation and partly by habit, social influence, and trust. Overall, the findings give evidence that for the health care context, new and extended acceptance models need to be developed with an integration of user diversity, especially individuals’ prior experience with apps and mHealth.

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          Most cited references78

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          Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology

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            User Acceptance of Information Technology: Toward a Unified View

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              Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology

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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                January 2022
                18 January 2022
                : 10
                : 1
                : e27095
                Affiliations
                [1 ] Human-Computer Interaction Center RWTH Aachen University Aachen Germany
                Author notes
                Corresponding Author: Eva-Maria Schomakers schomakers@ 123456comm.rwth-aachen.de
                Author information
                https://orcid.org/0000-0002-7650-2686
                https://orcid.org/0000-0003-4539-2119
                https://orcid.org/0000-0002-9030-6999
                https://orcid.org/0000-0002-6214-1461
                https://orcid.org/0000-0002-6105-4729
                Article
                v10i1e27095
                10.2196/27095
                8808343
                35040801
                df228397-6d29-4be5-a0e3-f983f9c2fb46
                ©Eva-Maria Schomakers, Chantal Lidynia, Luisa Sophie Vervier, André Calero Valdez, Martina Ziefle. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 18.01.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 11 January 2021
                : 3 March 2021
                : 9 April 2021
                : 24 September 2021
                Categories
                Original Paper
                Original Paper

                technology acceptance,utaut2,mhealth,privacy concerns,trust
                technology acceptance, utaut2, mhealth, privacy concerns, trust

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