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What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age
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2018 | International Journal of Information Management | Citations: 0
Authors: Zhao, Yang; Ni, Qi; Zhou, Ruoxin

Abstract: As an emerging ﬁeld in the healthcare industry, mobile health service has been p ... Expand

Abstract: As an emerging ﬁeld in the healthcare industry, mobile health service has been paid more and more attention in recent years. To explore the key determinants of individual attitude and behavioral intention, this study, based on 35 related empirical researches, conducted a meta-analysis to develop a comprehensive framework regarding the adoption of individual mobile health services and analyzed the moderating eﬀect of age. Through descriptive statistics, reliability statistics, and correlation analysis, the results of meta-analysis indicate that perceived usefulness, perceived ease of use, perceived vulnerability and perceived severity all have signiﬁcant impacts on individual attitude, while perceived usefulness, perceived ease of use, subjective norm, trust, perceived risk and attitude signiﬁcantly inﬂuence behavioral intention. The moderator analysis conﬁrmed that diﬀerent age groups have speciﬁc moderating eﬀects on mobile health services adoption, and results suggest that perceived ease of use, perceived vulnerability and perceived severity are more important factors for middle-aged and older users to use mobile health services. Collapse

Semantic filters: health behaviour theory

Topics: mobile health mobile system behavioral intention perceived ease of use user acceptance

Methods: meta analysis correlation analysis descriptive statistic conceptual modelling literature sample

Theories: technology acceptance theory health behaviour theory technology acceptance model unified theory of acceptance and use of technology
Routine Use of Mobile Health Services in the Presence of Health Consciousness

2016 | International Conference on Information Systems | Citations: 0
Authors: Meng, Fanbo; Guo, Xitong; Peng, Zeyu; Lai, Kee-hung; Vogel, Doug

Abstract: As digitization of health care evolves, mobile health (mHealth) becomes increasi ... Expand

Abstract: As digitization of health care evolves, mobile health (mHealth) becomes increasingly globally important. Mobile health service providers spend enormous effort and investment in mHealth service design and implementation to promote routine use. As the health consciousness of the public increases, it becomes difficult for both mHealth service providers and scholars to distinguish contributions of increased use. In this study, we integrate an individual’s heath consciousness with the elaboration likelihood model (ELM) to examine routine use intention and likelihood of opting-in to mHealth services. A survey with 270 subjects was conducted to test this research model and related hypotheses. Results confirm that mHealth service matching and source credibility influence routine use intention. Interestingly, health consciousness does not directly impact routine use intention but does strengthen the relationship with source credibility. However, there is no moderating effect with respect to mHealth service matching. Reasoning and implications for theory and practice are discussed. Collapse

Semantic filters: health behaviour theory

Topics: mobile health usage intention technology adoption behavioral intention health information system

Methods: survey focus group structural equation modeling personal interview qualitative interview

Theories: elaboration likelihood model health behaviour theory technology acceptance theory
Preventive Adoption of Information Security Behaviors

2013 | International Conference on Information Systems | Citations: 0
Authors: Wynn, Donald; Williams, Clay; Karahanna, Elena; Madupalli, Ramana

Abstract: Many tools and safe computing practices are available to information system user ... Expand

Abstract: Many tools and safe computing practices are available to information system users to help them avoid the negative outcomes due to information security threats. Yet many users do not use these tools and practices. We seek to understand the factors influencing organizational users’ adoption of preventive information security behaviors. These behaviors are similar to those which individuals practice to prevent negative health outcomes. A new model incorporating the primary antecedents of users’ intentions related to preventive security, the Preventive Adoption Model (PAM), is presented and tested. PAM is derived from health behavior theories (health belief model, protection motivation theory, and theory of planned behavior) and integrates key constructs specific to the information security context. Results of the study suggest that users’ beliefs regarding the threats and their avoidability, the proposed preventive actions, and their individual capabilities have an impact on their intentions to perform the prescribed behaviors. Collapse

Semantic filters: health behaviour theory

Topics: cybersecurity behavior data security IT security threat self efficacy missing data

Methods: survey partial least squares regression descriptive statistic statistical hypothesis test statistical power analysis

Theories: theory of planned behavior protection motivation theory health belief model health behaviour theory

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Found 3 articles

What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age

Routine Use of Mobile Health Services in the Presence of Health Consciousness

Preventive Adoption of Information Security Behaviors