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      Factors affecting physicians using mobile health applications: an empirical study

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          Abstract

          Background

          Mobile health applications (mHealth apps) have created innovative service channels for patients with chronic diseases. These innovative service channels require physicians to actively use mHealth apps. However, few studies investigate physicians’ participation in mHealth apps.

          Objective

          This study aims to empirically explore factors affecting physicians’ usage behaviors of mHealth apps. Based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and mHealth apps features, we propose a research model including altruism, cognitive trust, and online ratings.

          Methods

          We collected data from physicians who have used mHealth apps and conducted a factor analysis to verify the convergence and discriminative effects. We used a hierarchical regression method to test the path coefficients and statistical significance of our research model. In addition, we adopted bootstrapping approach and further analyzed the mediating effects of behavioral intention between all antecedent variables and physicians’ usage behavior. Finally, we conducted three robustness analyses to test the validity of results and tested the constructs to verify the common method bias.

          Results

          Our results support the effects of performance expectancy, effort expectancy, social influence, and altruism on the behavioral intentions of physicians using mHealth apps. Moreover, facilitating conditions and habits positively affect physicians using mHealth apps through the mediating effort of behavioral intention. Physicians’ cognitive trust and online rating have significant effects on their usage behaviors through the mediating efforts of behavioral intention.

          Conclusions

          This study contributes to the existing literature on UTAUT2 extension of physicians’ acceptance of mHealth apps by adding altruism, cognitive trust, and online ratings. The results of this study provide a novel perspective in understanding the factors affecting physicians’ usage behaviors on mHealth apps in China and provide such apps’ managers with an insight into the promotion of physicians’ active acceptance and usage behaviors.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12913-021-07339-7.

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          Most cited references68

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          Common method biases in behavioral research: A critical review of the literature and recommended remedies.

          Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
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            User Acceptance of Information Technology: Toward a Unified View

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              Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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                Author and article information

                Contributors
                peiwwu@bjtu.edu.cn
                rtzhang@bjtu.edu.cn
                jingluan@bjtu.edu.cn
                mhzhu@bjtu.edu.cn
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                4 January 2022
                4 January 2022
                2022
                : 22
                : 24
                Affiliations
                GRID grid.181531.f, ISNI 0000 0004 1789 9622, Department of Information Management, School of Economics and Management, , Beijing Jiaotong University, ; Beijing, China
                Article
                7339
                10.1186/s12913-021-07339-7
                8729011
                34983501
                e7ca4aac-f687-41d5-98bb-f8fb35fac22e
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 29 September 2021
                : 24 November 2021
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Health & Social care
                mhealth apps,physicians usage behavior,altruism,cognitive trust,online rating,utaut2

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