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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.

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.

This paper discusses the need for government and healthcare organization to implement mobile phone-based solutions for healthcare during the Coronavirus (Covid-19) pandemic. It also highlights the challenges and/or barriers to the rapid introduction, implementation and management of these and other innovative solutions to health service delivery during the current situation

The data include both qualitative and quantitative, collected from the primary interview-based case study and questionnaire survey. It also uses insights from the general populations, healthcare professionals and health information technology developers to understand the role of a mobile health intervention in the COVID-19 pandemic outbreak.

Healthcare professionals and health information technology developers are confident that the use of mobile health technology and applications has the ability to assist in monitoring and controlling the COVID-19 outbreak. The key advantages of using mobile phone technology are: increased awareness, improved assistance in tracking and testing casualties, improved assistance in seeking and scheduling health information and medical appointments, increased social distancing, improved overall productivity and quality of life. However, data demonstrated that lack of awareness and accessibility or unwillingness to use the technology, complex healthcare needs, application infrastructure, policies and a dearth of training and support are all barriers to successful implementation of this useful tool.

This research has the potential to make a significant impact on government and healthcare policy through presenting a coherent argument for the importance of designing and deploying mobile health technology and applications for the general population.

prior literature in this domain is inadequate in explaining the importance of mobile phone-based healthcare solutions for health service and during serious disease outbreaks and, in particular, within the Indian context. The findings of this study can be used by government and healthcare organizations to improve health governance during the current global pandemic.

Using smart mobile devices, called mobile health (mHealth), facilitates providing health services, speeds up the process and reduces the costs and complications of direct services. Also, mHealth has many capabilities and applications in epidemic and pandemic outbreaks. This study aimed to systematically review the mHealth adoption researches in epidemic/pandemic outbreaks and provide some suggestions for future research for tackling for COVID-19.

The results produced in this study are based on the literature analysis of 36 articles on mHealth adoption. To find the relevant studies; searches were done in PubMed, Google, Web of Science and Scopus by related keywords during 2020–2022. After selecting the studies based on the inclusion and exclusion criteria, data were collected by using PRIZMA methods for systematically reviewing the literature.

Of the 727 retrieved studies, 36 studies related to mHealth services during the pandemic situation were included. This has been performed by collecting data including demographic details, methodological details, limitations and significance of relationships between the constructs from the available articles based on the mHealth services. All studies emphasized the positive effect of mHealth for usage in epidemic/pandemic outbreaks.

The main applications of mHealth for epidemic/pandemic outbreaks included public health aspects, data management, educational programs, diagnosis as well as treatment. mHealth is an appropriate method for encountering epidemic/pandemic outbreaks due to its extensive applications. In the pandemic outbreak of COVID-19, mHealth is one of the best choices to use in the patient-physician relationship as Tele-visits, using in fever coach, providing real-time information for healthcare providers, population monitoring and detecting the diseases based on data obtained from different locations. These findings will help the mHealth providers to design their services accordingly.

This study contributes to the researchers and academicians by providing relevant information regarding the mHealth during the COVID-19 pandemic. This is the first time initiative to explore the research questions and future research direction for the researchers during the COVID-19 outbreak. Based on this, we present a comprehensive and actionable research agenda and practical implications.

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.

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 purpose of this paper is threefold: first, to draw health managers’, clinicians’, entrepreneurs’ and mobile apps designers’ attention toward new mobile health applications (mHealth apps); second, to define mHealth apps design characteristics intended for doctors; and third, to highlight how mHealth apps can be designed using quality function deployment/house of quality (QFD/HOQ) techniques from doctors’ perspectives.

Data were collected through a survey and in-depth interviews with doctors to understand their needs and attitudes toward mHealth apps. Analytic hierarchy process, QFD and HOQ methods were used to analyze data.

Doctors agreed that mHealth apps provide them with the tools to improve their service and to become more efficient. Once the 12 doctors’ wants were collected, they were prioritized according to their significance and used for mHealth apps development. Eight technical characteristics that cater to doctors’ expectations were sorted. The authors suggest that mHealth app designers need to provide design requirements recommended by health personnel for a higher satisfaction level.

Healthcare managers are focusing on increasing their efficiency, patient satisfaction and care quality, and decreasing costs. For these purposes, mHealth revolution and mHealth apps have high potential for improving doctor effectiveness and healthcare quality. This study is among the first to: define Turkish doctors’ wants from mHealth apps; elaborate the app’s technical characteristics; and increase design quality, which is implied in improving app design. This research makes a significant contribution to define doctors’ wants from mHealth apps, to elaborate their technical characteristics and to increase mHealth apps design quality using QFD.

The purpose of this article is to provide a general review of the health-care needs in Kenya which focuses on the role of community engagement in facilitating access and diminishing barriers to quality care services. Health-care concerns throughout Kenya and the culture of Kenyan’s health-care practices care are considered.

A comprehensive review covered studies of community engagement from 2000 till present. Studies are collected using Google Scholar, PubMed, EBSCOhost and JSTOR and from government and nongovernment agency websites. The approach focuses on why various populations seek health care and how they seek health care, and on some current health-care delivery models.

Suggestions for community engagement, including defining the community, are proposed. A model for improved health-care delivery introduces community health workers (CHWs), mHealth technologies and the use of mobile clinics to engage the community and improve health and quality of care in low-income settings.

The results emphasize the importance of community engagement in building a sustainable health-care delivery model. This model highlights the importance of defining the community, setting goals for the community and integrating CHWs and mobile clinics to improve health status and decrease long-term health-care costs. The implementation of these strategies contributes to an environment that promotes health and wellness for all.

This paper evaluates health-care quality and access issues in Kenya and provides sustainable solutions that are linked to effective community engagement. In addition, this paper adds to the limited number of studies that explore health-care quality and access alongside community engagement in low-income settings.

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.

A rapid increase in global smartphone ownership and digital health technologies offers the potential for mobile phone applications (apps) to deliver mental health interventions. The purpose of this paper is to bring together evidence reporting on mental health mobile apps to gain an understanding of the quality of current evidence, the positive and adverse effects of apps and the mechanisms underlying such effects.

A systematic search was carried out across six databases, for any systematic reviews or meta-analyses conducted up to 2020. Review quality was assessed using the Assessment of Multiple Systematic Reviews.

Across a total of 24 articles, a variety of clinical outcomes were assessed. Most compelling support was shown for apps targeting anxiety symptoms; some evidence favoured the use of apps for depression symptoms. Less evidence was available for the remaining clinical symptoms such as bipolar disorder, schizophrenia, post-traumatic stress disorder, sleep disorders and substance use. Overall, there was limited evidence pertaining to adverse effects and change mechanisms and a lack of quality reporting across a large proportion of included reviews. The included reviews demonstrate the need for further robust research before apps are recommended clinically.

This paper makes a valuable contribution to the current status of research and reviews investigating mental health mobile apps. Recommendations are made for improved adherence to review guidelines and to ensure risk of bias is minimised.