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The purpose of this study was to explore the factors affecting adoption of mHealth services among the older women in Bangladesh. As this portion of the total population is rapidly increasing in Dhaka City.

Using the technology acceptance model as a theoretical framework, this study introduces perceived reliability, price value and technology anxiety as new factor reflecting the user’s reliability, beliefs and monetary concerns in the acceptance of mHealth services. A structured survey was conducted to collect the required data from convenience sampling of 271 mHealth end users from Dhaka city in Bangladesh.

The study confirmed that perceived usefulness, perceived reliability; price value and technology anxiety had a significant impact on mHealth adoption. Ease of use did not influence on the adoption of mHealth services.

To the best of the authors’ knowledge, this study is one of the first to investigate the determinant of mHealth adoption among older Women. Moreover, the insights from this study could benefit mHealth services providers and policymakers in implementing more effective marketing strategies to increase the acceptability of mHealth services.

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

Today, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects.

After a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS.

The results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies.

This paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region.

The COVID-19 pandemic has created a devastating effect on public health. As “social distance” is a highly effective preventive measure of this pandemic, close contact between a patient and physician is strongly discouraged where possible. Consequently, mobile health (mHealth) technology is taking its momentum to fulfil this gap. The purpose of this study is, therefore, to empirically investigate the moderating as well as the direct role of situational constraint and health consciousness in the unified theory of acceptance and use of technology (UTAUT) constructs to understand the adoption and use behavior of mHealth care services amid pandemic.

Data were collected from existing mHealth users using an online survey questionnaire in Bangladesh. SmartPLS 3.0 and SPSS 23.0 were used for partial least squares-structural equation modeling.

Situational constraint and health consciousness both have strong direct positive effects on both behavioral intention (in all models) and use behavior (in Models 2 and 3). Further, this study revealed that effort expectancy remains insignificant in both direct and interaction effects whereas social influence becomes insignificant in interaction effects from direct significant effect (Models 1 and 2). Besides, the study reported that the relationship between behavioral intention and use behavior is moderated by situational constraint.

To the best of the authors’ knowledge, this study is the first in terms of mHealth empirical investigation considering the current pandemic situation. The incorporation of the situational constraint and health consciousness into the UTAUT model provides a holistic framework to understand the influence of the adoption and use behavior of mHealth amid pandemic.

Mobile health (mHealth) service is an Australian Government initiative aiming to improve the quality of health-care services. However, little is known about Australian health consumers’ willingness to adopt mHealth. The purpose of this paper is to study the usage behavior of mHealth service users in Australia. While various factors may impact users’ willingness to accept mHealth, this research investigates factors influencing the mHealth adoption decisions of the Australian health-care consumers, and the moderating impact of demographic factors on the usage behavior (UB) of mHealth services which has been rarely addressed in an Australian setting in the past.

The theoretical framework is based on the technology acceptance model (TAM). Data were collected from residents of the Australian Capital Territory using a survey questionnaire and examined using partial least squares structural equation modeling.

The proposed mHealth usage model demonstrated a good fit and indicated that perceived usefulness, perceived ease of use, social influence, service quality and government influence are critical issues shaping mHealth UB. The moderation analysis revealed that users’ demographics, namely, gender, age and education are instrumental in broadening the understanding of UB of mHealth service in Australia.

The findings will inform health-care service providers about the critical importance of the key factors driving the usage of mHealth services. Health-care providers and relevant authorities can develop targeted communication strategies that maximize the acceptance of mHealth services. Furthermore, deeper understanding of users’ demographic profiles would enable health-care service providers to promote their services to the right clients.

The above findings on the factors and user demographics informing the usage of mHealth services have unique practical, contextual and theoretical implications.

Despite the enormous potential of mobile health (mHealth), identifying the asymmetric relationship among the predictors towards intention to use (ITU) of mHealth tends to remain unresolved. This study aims to investigate the predictors and their asymmetric effects on ITU of mHealth through patients and healthcare professionals.

An integrated information systems (IS) model with four additional constructs has been developed to analyze symmetric and asymmetric effects on ITU of mHealth. An exploratory survey on 452 mHealth users with prior experience was conducted to evaluate the model using a mixed-method approach including partial least squares-based structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) technique.

The findings show that facilitating conditions, personal awareness building, perceived enjoyment, effort expectancy and perceived usefulness have predictive power for ITU of mHealth. In contrast, fsQCA reveals four more alternative solutions, including the main drivers explored by PLS-SEM. The results indicate that various conditions that were not crucial in PLS-SEM analysis are shown to be sufficient conditions in fsQCA.

This study contributes to theory by integrating self-actualization factors (i.e. personal awareness building, patients as decision support unit) into the IS model. And practically, this study makes an essential contribution to users' ITU of mHealth, enabling relevant stakeholders to build strategies to implement mHealth successfully.

While mHealth has revolutionized healthcare and the prior literature only showed linear relationships, this empirical study revealed asymmetrical relationships among the determinants of ITU of mHealth. Thus, this study extends to the growing body of literature on the use of mHealth technology in the least developing nation.

The emergence of mobile health (mHealth) products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth technologies would not be beneficial unless they are adopted and used by their target users. This study identifies key factors affecting the usage of mHealth apps based on user usage data collected from an mHealth app.

Using a dataset collected from an mHealth app named mPower, developed for patients with Parkinson's disease (PD), this paper investigated the effects of disease diagnosis, disease progression and mHealth app difficulty level on app usage, while controlling for user information. App usage is measured by five different activity counts of the app.

The results across five measures of mHealth app usage vary slightly. On average, previous professional diagnosis and high user performance scores encourage user participation and engagement, while disease progression hinders app usage.

The findings potentially provide insights into better design and promotion of mHealth products and improve the capability of health management of patients with chronic diseases.

Studies on the mHealth app usage are critical but sparse because large-scale and reliable mHealth app usage data are limited. Unlike earlier works based solely on survey data, this research used a large user usage data collected from an mHealth app to study key factors affecting app usage. The methods presented in this study can serve as a pioneering work for the design and promotion of mHealth technologies.

The implementation of mobile health (mHealth) in developing countries seems to be stuck in a pattern of successive pilot studies that struggle for mainstream implementation. This study addresses the research question: what existing health-related structures, properties and practices are presented by rural areas of developing countries that might inhibit the implementation of mHealth initiatives?

This study was conducted using a socio-material approach, based on an exploratory case study in West Africa. Interviews and participant observation were used to gather data. A thematic analysis identified important social and material agencies, practices and imbrications which may limit the effectiveness of mHealth apps in the region.

Findings show that, while urban healthcare is highly structured, best practice-led, rural healthcare relies on peer-based knowledge sharing, and community support. This has implications for the enacted materiality of mobile technologies. While urban actors see mHealth as a tool for automation and the enforcement of responsible healthcare best practice, rural actors see mHealth as a tool for greater interconnectivity and independent, decentralised care.

This study has two significant limitations. First, the study focussed on a region where technology-enabled guideline-driven treatment is the main mHealth concern. Second, consistent with the exploratory nature of this study, the qualitative methodology and the single-case design, the study makes no claim to statistical generalisability.

To the authors' knowledge, this is the first study to adopt a socio-material view that considers existing structures and practices that may influence the widespread adoption and assimilation of a new mHealth app. This helps identify contextual challenges that are limiting the potential of mHealth to improve outcomes in rural areas of developing countries.

The COVID-19 outbreak has worsened the issues of obesity and overweight in Indonesia. Technologies related to mHealth are becoming more popular for its capability to lessen obesity, if enabled by patient-focussed consultation. The paper assesses influential determinants of medium workout for obese and overweight adults post-COVID-19.

A total of 1,171 participants who self-stated being overweight and called on a health professional in the previous year are chosen using cross-sectional survey. Participants stated their mHealth tracking behaviours, viewpoints regarding obesity, bodily activities and consultation post-COVID-19 epidemic. This study uses structural equation modelling to assess inter-variables relationships.

Patient–professional e-consultation is substantially related to mHealth tracking adoption and transformations in adults' obesity-associated viewpoints, forecasting adequate workout post-COVID-19. The results indicate the necessity of patient-focussed consultation meetings to incorporate communications about mHealth technology and available techniques of joining in bodily activities.

The research is the first effort to assess primary information from obese and overweight Indonesian adults post-COVID-19 epidemic (January–July 2022). The population can take advantage of pointed health interferences employing mHealth innovations. The results propose that health professionals must involve patients through mHealth technologies and attempt to enhance digital health knowledge to advance bodily activities nationally.

The emergence of mHealth applications has led to the rise of health-based services delivered over smartphones. Younger people are often found to be more innovative toward technology, especially related to smartphones (Rai et al., 2013). Most mHealth application downloaders are continually shifting between applications because of the hyper-competition making achieving loyal consumers challenging (Racherla et al., 2012). The purpose of this paper is to study the determinants that help increase young consumers mHealth application loyalty. This study integrates self-determination theory (SDT), gamification elements and engagement to examine loyalty.

A valid sample of 263 college student’s data was obtained for data analysis from a survey conducted in multiple campuses of the Delhi University in India.

The three psychological needs: need for autonomy, need for competence and need for relatedness, showed a positive impact on intrinsic motivation. From the gamification factors; perceived playfulness, the level of challenge and social interaction, only the first two showed a positive impact on extrinsic motivation. Both motivation factors influence engagement, showing a frequent interaction with the application, leading to loyalty.

Previous studies examined the adoption of mHealth services, this study is one of the first to examine young consumers’ loyalty in using mhealth apps. It sheds light on the existing literature and contributes to research on mHealth applications by determining the factors that lead to loyalty by the young consumers.