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This study examined the determinants of mobile health (M-Health) application, adoption, usage and discontinuation among corporate workers diagnosed with hypertension and diabetes in Ghana.

The diffusion innovation and reasoned action theories were employed using an exploratory design. Three hundred corporate workers diagnosed with diabetes and hypertension from three health facilities for the past six months were sampled for the study using a multi-stage sampling technique and administered questionnaires. Descriptive statistics and logistic regression tools were employed in the analysis of data.

The study found a significant number of factors influencing m-health applications adoption, usage and discontinuity. These factors include nature and demand of job, perceived advantage, compatibility, complexity, triability, aesthetics and trust. Aesthetics emerged as the strongest predictive factor for the adoption, usage and discontinuity of use among diabetic and hypertensive corporate workers. With the adoption of M-Health applications, compatibility, as well as nature and demand of job, were significant predictors. With the usage of M-Health applications, complexity, triability, aesthetics and trust were significant predictors. Moreover, perceived advantage, compatibility, complexity and triability influenced significantly the choice to discontinue using M-Health applications. The study concluded that M-Health application functionalities play a valuable role in patients’ intention to adopt, use and discontinue the use of an M-Health application in Ghana.

This exploratory study offers in-depth insight into how major M-Health application features affect its adoption, usage and discontinuity, providing crucial information for future research and the improvement of chronic condition healthcare delivery.

Drawing on the adapted unified theory of acceptance and use of technology (UTAUT2) framework in the bottom of pyramid (BoP) context, this paper examines the number of causal recipes that foster m-health adoption in a developing country (Bangladesh). This paper aims to propose an extended UTAUT2 model along with identifying the necessary and sufficient factors affecting the m-health adoption intention in the BoP market.

The research model was empirically tested, combining two approaches: structural equation modelling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). Data were collected from 221 housemaids and female security guards who earn around US$6 per day.

The SEM results revealed that while performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions, perceived cost (PC) and technology anxiety (TA) significantly influence the behavioural intention of BoP markets, hedonic motivation is the non-significant predictor. The fsQCA revealed that the two necessary conditions, PC and SI, can be combined with TA to increase the possibility of the success of m-health adoption in the BoP market.

For practitioners concerned with fostering the m-health adoption intention in BoP markets, the present study, which points out equifinality, recommends integrating the PC and SI in several combinations with PE, EE and TA.

To the best of the authors’ knowledge, no previous studies using the UTAUT2 theory examined the m-health services in the BoP market. This study contributes empirical data to the predominantly theoretical literature by offering a deeper understanding of the inclusion of TA and PC in several combinations with other UTUAT2 factors as predictors for explaining the m-health adoption intention of BoP markets.

The acceptance of mobile health (m-health) applications, especially those of a preventive nature, by individuals, is not well understood. Despite the benefits offered by m-health applications in improving and sustaining health and well-being through various avenues, widespread adoption is yet to be seen. Within this context, this study aims to reveal the enabling factors and barriers that influence the use of m-health applications among Generation Z (Gen-Z).

The Unified Theory of Acceptance and Use of Technology (UTAUT) was extended with e-health literacy, trust and enjoyment constructs. Data from a survey study on 312 Gen-Z members were analysed via structural equation modelling, shedding light on the reasons why new generations adopt m-health apps.

The findings indicate that social influence and enjoyment are the most significant factors influencing the use of m-health apps. The significant impact of performance and effort expectancy on intentions was also confirmed by the results. Moreover, privacy risk was identified as a barrier to adoption. The results also indicated that the strong influence of trust on privacy risk can be used to offset those privacy concerns.

The findings highlight that hedonic motivation, which is commonly overlooked in health settings, plays an important role in m-health app use. Thus, promoting mobile app features that provide enjoyment will be influential in attracting the younger generation.

The context of the study differs from the norm and focuses on a regional health tourism hub, Turkey, situated at the crossroads of Europe and Asia. UTAUT model is modified with relevant constructs, namely, enjoyment, e-health literacy and privacy risk, to better fit the m-health context.

The purpose of this study is to propose and test a model to explain users’ intention to adopt m-health devices and divide the importance of antecedents for users to adopt m-health devices based on the stimulus-organism-response (S-O-R) framework.

This research conducted an online survey with m-health app users and collected 562 valid responses. A hybrid SEM-ANN approach was employed to evaluate the research model and hypotheses.

The results show that motivation (M), opportunity (O), and ability (A) affect users’ flow experience and loyalty and further affect their adoption intention of m-health technology. Opportunity plays a more critical role in m-health adoption intention than ability.

This study comprehensively examined the factors that affect users’ deep engagement and m-health adoption from the perspective of MOA. It used the hybrid SEM-ANN method to divide the critical role of motivation, opportunity and ability, providing a new analysis approach for studying information technology (IT) behavior.

The purpose of this study was to create a theoretical model by combining the technology acceptance model (TAM) with the theory of technology readiness (TR) and then empirically test it to identify the key factors influencing older citizens’ intention to adopt and use mobile health (m-health), which has emerged as a tool to facilitate health-care rights for all.

The convenience sampling method was used to collect data from 465 respondents aged 60 and up from the Delhi-National capital region of India using a questionnaire survey method. The data collected for this study were analyzed using partial least squares structural equation modeling using SmartPLS 3.0.

The study’s findings indicate that all TR components influence perceived usefulness (PU) and ease of use. The exception is discomfort, which does not affect perceived ease of use (PEOU). Furthermore, PU and PEOU influenced the older citizen’s attitude toward m-health, and attitude influenced their intention to use m-health applications.

To the best of the authors’ knowledge, this is the first study to apply the TAM in combination with TR index to examine the acceptability of m-health consulting by the older citizen in an emerging economy like India.

m-health services for different age groups are becoming an emerging field in the health-care industry, especially in low-resource environments such as developing countries such as Bangladesh. Hence, this study’s primary aim is to identify the factors that influence the middle-aged and elderly’s intention to use m-health services.

This study applied the extended version of the unified theory of acceptance and use of technology to explore middle-aged and elderly’s intention to use m-health services. There were 235 respondents, of which 123 (52.34%) were in the middle-aged group, whereas 112 (47.66%) were in the older group. Both groups were found to have more male participants than female participants. The partial least square (PLS) method was used to analyze data.

The study found that performance expectancy, effort expectancy, facilitating condition, technological anxiety and resistance to change (p < 0.05) had a significant influence on middle-aged intention to use m-health services. Social influence and perceived physical condition (p > 0.05) had no significant effect on middle-aged intention to use m-health services. On the other hand, performance expectancy, effort expectancy, facilitating condition and resistance to change (p <* 0.05) significantly influenced the elderly’s intention to use m-health services. However, the social impact of perceived physical condition and technological anxiety (p > 0.05) had no significant effect on the elderly’s intention to use m-health services.

A good number of studies are available in the current literature, examining the factors adoption of m-health services in both developed and developing economy context. However, very few studies examine the factors that influence behavioral intention to use m-health services concerning the two different age groups, such as middle-aged and elderly. Moreover, to the best of the authors’ knowledge, there is a shortage of literature on this topic built on the comparative analysis between the two age groups.

Mobile health, i.e. m-Health possesses huge potential, especially to the developing countries and remote locations of developed countries. The success of such systems may create a healthier society through eradicating health incidents, which cannot otherwise be addressed with “brick and mortar” type of health systems. The purpose of this paper is to develop an m-Health success model from users’ perspective and validate in a developing country context.

Epistemologically, positivist approach has been adopted for the current research. An initial research model was developed from existing information system (IS) literature, which was then validated with survey data applying partial least square structural equation modelling (PLS-SEM).

The results summarise that continuance intention (CI) of m-Health services is dependent on perceived value (PV) and user satisfaction (STF); PV positively influences STF. Moreover, platform quality, quality of medical advice, and interaction quality have positive and direct effect on PV and STF; finally, CI drives to better quality of health life.

The findings of this study provide strategic implications to health managers and practitioners recognising the determinants of m-Health success and comprehending their relationships. It is underscored that, in order to secure the success of an m-Health system in a given society both human and technology-related components are vital and therefore should be taken care of.

This is the first attempt that develops and validates an m-Health system success model, particularly from the context of a country with low-health profile. Moreover, the contextualisation of the related variables and extension of existing IS success models is theoretically original.

The evolution of e-health technologies presents promising alternatives for health-care excellence. Despite the benefits arising from mobile e-health (m-health) and wearables technologies, the literature stands many contradictories signs regarding how users accept and engage in using these technologies. This study aims to synthesize the estimations about m-health user acceptance technologies.

A meta-analytic structural equation modeling was carried out using the 778 relationships estimated by 100 previous research. The estimations follow the relations and constructs proposed in the UTAUT2 technological acceptance model.

The results indicate the performance expectancy, effort expectancy, social influence and habit constructs are most important for predicting the behavioral intention of use of m-health technologies. The Latin American users of e-health technologies are still underestimated in the literature.

The study presents a guide to understanding the acceptance process of m-health technologies and delivers a general orientation for developing new m-health devices considering their acceptance by users.

Knowledge is a key success factor in achieving competitive advantage. The purpose of this paper is to examine how mobile health technology facilitates knowledge management (KM) practices to enhance a public health service in an emerging economies context. Specifically, the acceptance of a knowledge-resource application by community health workers (CHWs) to deliver breast cancer health care in India, where resources are depleted, is explored.

Fieldwork activity conducted 20 semi-structured interviews with frontline CHWs, which were analysed using an interpretive inductive approach.

The application generates knowledge as a resource that signals quality health care and yields a positive reputation for the public health service. The CHW’s acceptance of technology enables knowledge generation and knowledge capture. The design facilitates knowledge codification and knowledge transfer of breast cancer information to standardise quality patient care.

KM insights are provided for the implementation of mobile health technology for frontline health-care professionals in an emerging economies context. The knowledge-resource application can deliver breast cancer care, in localised areas with the potential for wider contexts. The outcomes are valuable for policymakers, health service managers and KM practitioners in an emerging economies context.

The legacy of the mobile heath technology is the normalisation of breast cancer discourse and the technical up-skilling of CHWs.

First, this paper contributes three propositions to KM scholarship, in a public health care, emerging economies context. Second, via an interdisciplinary theoretical lens (signalling theory and technology acceptance model), this paper offers a novel conceptualisation to illustrate how a knowledge-resource application can shape an organisation’s KM to form a resource-based competitive advantage.

Increasingly popular mobile health technology is creating a new paradigm for the delivery of care to patients involving a role of the pharmacist. This study aims to propose a renewed patient–pharmacist relationship in this environment and present an empirical case study investigating the influence of key variables, including the consumer’s attitude toward personalized monitoring performed by the pharmacist, on the intention to adopt a mobile health app. Other drivers identified were ease of use and perceived usefulness of the app, individual and health-related factors (perceived vulnerability and severity of health condition, social norms and innovativeness with technology) and quality of relationship with the pharmacist.

A self-administered online survey was completed by 356 Canadian mobile device owners of more than 40 of age. Analyses were performed using structural equation modeling.

The main factor driving adoption intentions was perceived usefulness followed by the respondent’s innovativeness with technology and perceived vulnerability of his/her health condition. Attitude toward personalized monitoring depends primarily on the relationship with the pharmacist. No relationship was found between adoption intentions and attitude toward personalized monitoring.

This research features a multidisciplinary approach by using variables from relational marketing, information technology and health and inclusion of the pharmacist (vs physician) as a health consultant, offering relevant marketing avenues for pharmacists.