The Changing Paradigm of Health and Mobile Phones

Abstract

This article describes how widespread adoption of mobile technology in healthcare is an innovation that is inevitable today in both developed and emerging markets around the world. Mobile health services (m-Health) act as an effective, accessible and affordable means of providing healthcare knowledge to users directly from providers. Despite such benefits of m-Health services, rapid adoption is not yet occurring, particularly in emerging markets. The main barrier is mostly the cynical behavior of users regarding this medium of healthcare services. The aim of this article is to examine underlying factors that can influence future use intentions of m-Health services. Conceptual model of the study identifies service qualities like reliability, privacy, responsiveness, empathy and information quality along with facilitating conditions, trust, effort expectancy and performance expectancy as significant constructs that influences users' overall perceptions of m-Health services, along with moderating effects of age and gender. Limitations and implications for practice and research are also discussed.

Do mobile health (mHealth) services ensure the quality of health life? An integrated approach from a developing country context

“…EE has appeared as the next most vital factor influencing mHealth services usage. In addition to expected usefulness, the young generation in Bangladesh expects less effort to accelerate the adoption rate of mHealth services (Nisha, Iqbal, and Rifat 2019). Similar outcomes with respect to this relationship are evident in several earlier studies in IS interface (Lallmahomed et al 2013;Isabel Maria Macedo 2017).…”

Factors Influencing Behavioural Intention to Adopt the QR-Code Payment

“…Facilitating conditions refer to the user perceptions of the availability of the resources and support to utilise a given technology (Venkatesh et al, 2012). Facilitating conditions make the use of technology easier and influence the adoption of mobile technology (Nisha et al, 2019). Venkatesh et al (2003) formulate facilitating conditions construct from the model of PC utilisation (Thompson et al, 1991), perceived behavioural control (Ajzen 1991;Taylor & Todd, 1995) and compatibility (Moore & Benbasat, 1991).…”

Examining Users’ Adoption of Precision Medicine: The Moderating Role of Medical Technical Knowledge

“…For example, UTAUT has been used to investigate consumers' use of online shopping platforms [20], electronic banks [21], intelligent robots [22], and social media [23]. Others have applied UTAUT or UTAUT2 models in the medical field to study mobile healthcare [7][8][9], e-health services [10], virtual health communities [11], smart medical services [12], and personal health files [24].…”

“…At present, most research on the factors that influence the acceptance of emerging technologies is based on the unified theory of acceptance and use of technology (UTAUT). Studies have found, for example, that factors such as performance expectation, effort expectation, social influence, and convenience affect the adoption of mobile medicine [7][8][9], electronic medical services [10], virtual health communities [11], and intelligent medical services [12]. Compared to previous studies, the present one used both the UTAUT model and the health belief model (HBM) to explore the factors affecting consumers' willingness to use PM.…”