Open AccessJournal Article
Understanding the acceptance of mobile health services: a comparison and integration of alternative models
TLDR
In this article, the authors proposed a unified model of health technology acceptance in the context of mobile health services based on performance expectancy, effort expectancy, social influence, facilitating conditions, and threat appraisals.Abstract:
The advancement of mobile technology and the increasing importance of health promote the boom in mobile health services (MHS) around the world. Although there have been several studies investigating the health technology acceptance behavior from a variety of theoretical perspectives, they have not provided a unified understanding. To fill this research gap, this paper: (1) reviews the health technology acceptance literature and discusses three prominent models (e.g., the technology acceptance model, the theory of planned behavior or the unified theory of use and acceptance of technology, and the protection motivation theory), (2) empirically compares the three models, and (3) formulates and empirically validates the unified model in the context of mobile health services. In the unified model of health technology acceptance, we propose that users’ intention to use mobile health services is determined by five key factors: performance expectancy, effort expectancy, social influence, facilitating conditions, and threat appraisals. The results show that the unified model outperforms the three alternative models by significantly improving the R-squares. Finally, the implications for theory and practice are put forward.read more
Citations
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Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model
Rakibul Hoque,Golam Sorwar +1 more
TL;DR: This study confirms the applicability of UTAUT model in the context of mHealth services among the elderly in developing countries like Bangladesh and provides valuable information for mHealth service providers and policy makers in understanding the adoption challenges and the issues.
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An empirical study of wearable technology acceptance in healthcare
Yiwen Gao,He Li,Yan Luo +2 more
TL;DR: This study is among the first to investigate healthcare wearable device from behavioral perspective and helps to comprehensively understand emerging health information technology (HIT) acceptance from technology, health, and privacy perspectives.
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Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM)
TL;DR: In this article, the authors investigated the factors influencing the acceptance of telemedicine services among the rural population of Pakistan using the technology acceptance model (TAM) with the inclusion of several other antecedents, such as ease of use, technological anxiety, social influence, perceived ease of usefulness, trust, facilitating conditions, perceived risk and resistance to technology.
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What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age
Yang Zhao,Qi Ni,Ruoxin Zhou +2 more
TL;DR: A meta-analysis conducted to develop a comprehensive framework regarding the adoption of individual mobile health services and analyzed the moderating effect of age indicated that perceived usefulness, perceived ease of use, perceived vulnerability and perceived severity all have significant impacts on individual attitude.
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Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective
TL;DR: Individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus), and if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device.
References
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The theory of planned behavior
TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.
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Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Claes Fornell,David F. Larcker +1 more
TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
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Common method biases in behavioral research: a critical review of the literature and recommended remedies.
TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.
Perceived Usefulness, Perceived Ease of Use, and User
TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.
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Perceived usefulness, perceived ease of use, and user acceptance of information technology
TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.