A meta-analysis of e-health applications acceptance

Determinants of the intention to use mHealth in the future: Evidence from an intervention study of patients with chronic diseases in Slovenia

BACKGROUND

Mobile health (mHealth) implementation is crucial for developing sustainable healthcare systems, but it faces the challenge of user acceptance. Extending traditional acceptance models allows for the cognitive, emotional and social aspects of engaging with mHealth to be captured, creating a more comprehensive understanding of users' intentions to use it in the future. User-centred intervention studies based on users' real experiences with mHealth are essential for accurate assessments and for improving upon studies that rely merely on anticipated mHealth use.

METHODS

An intervention study was conducted with 103 patients with at least one chronic condition (type 2 diabetes and/or arterial hypertension) who had used an mHealth service for three months. They were recruited through purposive sampling at a community health centre in Slovenia. Path analysis was applied to the survey data collected after a three-month testing period to validate an explanatory model with eight hypotheses.

RESULTS

The intensity of mHealth use affected usability, which in turn affected acceptability, the psychosocial impacts of engagement with mHealth and intention for future use. The results showed that the intensity of mHealth use did not affect mHealth acceptability. Likewise, acceptability did not affect the psychosocial impacts of engagement with mHealth or the intention for its future use. Notably, perceptions of the psychosocial impacts of mHealth had no significant effect on the intention for future use.

CONCLUSION

Usability and intensity of use play a central role in the post-intervention usage of mHealth, offering valuable insights for policymakers and healthcare providers involved in the delivery of mHealth-based treatment to patients with chronic diseases.

A meta-analysis of technology acceptance in healthcare from the consumer's perspective

Consumer-oriented health care technologies are increasingly available and transforming global health delivery systems. However, there is a paucity of research that systematically investigates health care technology acceptance from the consumer's perspective. This study conducts a literature review and meta-analysis to examine consumers' adoption intentions toward health care technologies. The findings suggest that technology acceptance models are transferable to health care technology with modifications, and factors such as perceived risks, technology performance expectancy, consumer trust, and habit significantly correlate with consumers' adoption intentions. This study provides valuable insights into health care technology management and practical implications for health care service designers, providers, and regulatory authorities.

Digital Maturity as a Strategy for Advancing Patient Experience in US Hospitals

Patient experience is globally recognized as an important indicator of health system performance, linked to health system quality and improving patient outcomes. Post COVID-19, health systems have embraced digital health and advanced digital transformation efforts; however, the relationship between digital health and patient experience outcomes is not well-documented. Using HCAHPS hospital survey data to measure patient experience, and HIMSS EMRAM Maturity Model data to measure digital maturity, a cross-sectional design using multivariate analyses examined the impact of digital maturity on patient experience in US hospitals. Our analysis shows that advanced digital maturity in US hospitals is associated with stronger patient experience outcomes, particularly relative to communication with nurses, doctors, and communication about medicines and therapies. The findings suggest that there are significant differences in patient experience associated with teaching versus nonteaching hospitals, urban versus rural hospitals. As hospitals advance and progress digital transformation initiatives, evidence to inform how transformation efforts can engage and advance patient experience will contribute to health system performance well into the future.

Analysis of factors inhibiting the customer engagement of eHealth in India: Modeling the barriers using ISM-Fuzzy MICMAC analysis

INTRODUCTION

The current study aims to evaluate and measure the relationship between the customer engagement barriers influencing the adoption of eHealth in India. Previous studies have shown that low levels of engagement can lead to worse health outcomes, so this study is an expanded version of those findings to highlight those challenges.

METHODOLOGY

For this, the study followed three phases of research: factor identification through a review of the literature; expert opinion for selecting key and pertinent factors for the study; and application of interpretive structural modelling approach to capture the proper association between various factors. Using fuzzy-MICMAC analysis, the factors were divided into independent, dependent, autonomous and linkage categories.

RESULTS

A model is created in this study that shows the relationship between different barriers that aid the Indian healthcare industry in better implementation and also Indian citizens in better adoption of eHealth services. According to the research and derived model, some of the biggest obstacles in the eHealth are need of product portfolio, Lack of Customer support and Low first call resolution rate.

CONCLUSION

This study contributes to the body of knowledge by offering novel perspective into the types of hierarchical relationships that exist among barriers. These insights will be valuable to academicians and practitioners interested in India's healthcare market and its strategic expansion.

Getting Connected to M-Health Technologies through a Meta-Analysis

The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users' perceptions regarding the acceptance of m-health technologies based on a synthesis of meta-analysis studies on the subject in the literature. Using the relations and constructs proposed in the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) technology acceptance model, the methodological approach utilized a meta-analysis to raise the effect of the main factors on the Behavioral Intention to Use m-health technologies. Furthermore, the model proposed also estimated the moderation effect of gender, age, and timeline variables on the UTAUT2 relations. In total, the meta-analysis utilized 84 different articles, which presented 376 estimations based on a sample of 31,609 respondents. The results indicate an overall compilation of the relations, as well as the primary factors and moderating variables that determine users' acceptance of the studied m-health systems.

Digital Transformation in Healthcare: Technology Acceptance and Its Applications

Technological innovation has become an integral aspect of our daily life, such as wearable and information technology, virtual reality and the Internet of Things which have contributed to transforming healthcare business and operations. Patients will now have a broader range and more mindful healthcare choices and experience a new era of healthcare with a patient-centric culture. Digital transformation determines personal and institutional health care. This paper aims to analyse the changes taking place in the field of healthcare due to digital transformation. For this purpose, a systematic bibliographic review is performed, utilising Scopus, Science Direct and PubMed databases from 2008 to 2021. Our methodology is based on the approach by Wester and Watson, which classify the related articles based on a concept-centric method and an ad hoc classification system which identify the categories used to describe areas of literature. The search was made during August 2022 and identified 5847 papers, of which 321 fulfilled the inclusion criteria for further process. Finally, by removing and adding additional studies, we ended with 287 articles grouped into five themes: information technology in health, the educational impact of e-health, the acceptance of e-health, telemedicine and security issues.

Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis

The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics.

Adhoc Setup of an Online Mental Health Self-Help Program During the COVID-19 Pandemic: Description of the Development and Implementation Processes and Analysis of Its Users’ and Usage Profiles

Background

The COVID-19 pandemic hit Austria in March 2020. This led to a considerable reduction in outpatient psychiatric therapies. People with mental disorders as well as with newly emerging mental health issues found themselves with very limited treatment options. Within only a few days our hospital set up an online mental health self-help program which went online in its first version on the first day of the lockdown in Austria. The process of this development and implementation process alongside with the user’s and usage data for the program are presented here.

Methods

A small core team initiated the development of the program on a low-budget basis and using mostly freely available digital resources. The program had to be free of costs for its users and easy to navigate. Each self-help module contains a text description of the topic, a self-rating questionnaire and several psychoeducational 2–5 min videos. These videos explain, e.g., interactions of mental stress and the immune system or the vicious circle of anxiety. Additional videos provide easy to learn techniques like breathing and relaxation exercises.

Results

We illustrate the implementation of this program following the replicating effective program (REP) model. We provide a detailed description of the implementation process starting from a simple website to a smartphone-based application with registered user area and instantaneous reporting of self-rating questionnaire results to users. The described process could be used as a model for the setup of similar programs in a very short time. As an indicator of acceptance, we report 46,100 unique video views and 3,937 completed questionnaires in the first year of use. The most accessed videos were those on anxiety, relaxation and resilience. Analysis of the sociodemographic user data indicate that they were mostly young (< 45 years; 59.7%), females (77.5%) and previously mentally healthy individuals (74.5%). An example of the collected psychometric questionnaire data over time is given.

Conclusion

We show that it is possible to set up an online mental health self-help program ad hoc and without extensive prior planning, which enabled us to dynamically respond to a new situation. We are now planning on keeping the program active for a longer period of time to supplement and expand traditional treatment settings also outside the COVID-19 pandemic.

Online health management continuance and the moderating effect of service type and age difference: A meta-analysis

Numerous empirical studies have been carried out to explore factors of online health management continuance. However, results were not unified. We thus conducted a meta-analysis to identify influential factors and potential moderators. A systematic literature search was performed in nine databases (PubMed, Web of Science, the Cochrane Library, Ovid of JBI, CINAHL, Embase, CNKI, VIP, and CBM) published up to December 2020 in the English or Chinese language. Meta-analysis of combined effect size, heterogeneity, moderator analysis, publication bias assessment, and inter-rater reliability was conducted. Totally 41 studies and 12 pairwise relationships were identified. Confirmation, perceived usefulness, satisfaction, information quality, service quality, perceived ease of use, and trust were all critical predictors. Service type and age difference showed their moderating effects respectively. The perceived usefulness was more noteworthy in medical service than health and fitness service. The trust was more noteworthy in young adults. The results confirmed the validity and robustness of the Expectation Confirmation Model, Information Systems Success Model, and trust theory in online health management continuance. Moderators included but are not limited to age difference and service type. The elderly research in the healthcare context and other analytical methods such as qualitative comparative analysis should be applied in the future.

Drivers for Teleconsultation Acceptance in Brazil: Patients’ Perspective during the COVID-19 Pandemic

ABSTRACT Context: teleconsultation can be a strategic technological tool for patients to access quality healthcare while dealing with resource challenges within health industry. It can be particularly relevant during and after the COVID-19 pandemic, when the social distancing world had to scramble for new technological solutions to offer quality healthcare services with reduced personal contact. Objective: our research proposes an integrative technology acceptance model to evaluate the drivers of teleconsultation adoption by patients, aligning constructs from the technology acceptance model with other drivers, such as technology readiness, trust, and self-efficacy. Methods: analyses included descriptive statistics and structural equations modeling based on survey’s data from a sample of 415 consumers. Results: results indicate significant relationships between the assessed constructs, with particular relevance on the effects of perceived usefulness, anteceded by trust and technology readiness, on attitude and intention to use teleconsultation. Conclusion: our findings provide helpful insights for health organizations and regulators associated with the diffusion of teleconsultation. The study findings also indicate that the challenging COVID-19 pandemic context may be affecting patients’ intention to adopt teleconsultation.

Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study

BACKGROUND

An increasing number of mobile health (mHealth) apps are becoming available for download and use on mobile devices. Even with the increase in availability and use of mHealth apps, there has still not been a lot of research into understanding the intention to use this kind of apps.

OBJECTIVE

The purpose of this study was to investigate a technology acceptance model (TAM) that has been specially designed for primary health care applications.

METHODS

The proposed model is an extension of the TAM, and was empirically tested using data obtained from a survey of mHealth app users (n=310). The research analyzed 2 additional external factors: promotion of health and health benefits. Data were analyzed with a PLS-SEM software and confirmed that gender moderates the adoption of mHealth apps in Spain. The explanatory capacity (R2 for behavioral intention to use) of the proposed model was 76.4%. Likewise, the relationships of the external constructs of the extended TAM were found to be significant.

RESULTS

The results show the importance of healthy habits developed by using mHealth apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of eHealth as an agent for transforming attitudes; additionally, as more health benefits are obtained, ease of use becomes greater. Perceived usefulness (PU; β=.415, t0.001;4999=3.442, P=.001), attitude toward using (β=.301, t0.01;499=2.299, P=.02), and promotion of health (β=.210, t0.05;499=2.108, P=.03) were found to have a statistically significant impact on behavior intention to use eHealth apps (R2=76.4%). Perceived ease of use (PEOU; β=.179, t0.01;499=2.623, P=.009) and PU (β=.755, t0.001;499=12.888, P<.001) were found to have a statistically significant impact on attitude toward using (R2>=78.2%). Furthermore, PEOU (β=.203, t0.01;499=2.810, P=.005), health benefits (β=.448, t0.001;499=4.010, P<.001), and promotion of health (β=.281, t0.01;499=2.393, P=.01) exerted a significant impact on PU (R2=72.7%). Finally, health benefits (β=.640, t0.001;499=14.948, P<.001) had a statistically significant impact on PEOU (R2=40.9%), while promotion of health (β=.865, t0.001;499=29.943, P<.001) significantly influenced health benefits (R2=74.7%).

CONCLUSIONS

mHealth apps could be used to predict the behavior of patients in the face of recommendations to prevent pandemics, such as COVID-19 or SARS, and to track users' symptoms while they stay at home. Gender is a determining factor that influences the intention to use mHealth apps, so perhaps different interfaces and utilities could be designed according to gender.

Healthcare at Your Fingertips: The Acceptance and Adoption of Mobile Medical Treatment Services among Chinese Users

Mobile health (mHealth) services have recently been receiving increasing attention. However, there is a lack of knowledge about how users accept and adopt mobile medical treatment (MMT) services, some of the most promising mHealth services that aim to extend the patient-physician relationship beyond the conventional clinic environment. To fill this research gap, this study proposes a research model for predicting consumers' acceptance behavior toward MMT services based on the Technology Acceptance Model (TAM). A survey was conducted among 303 Chinese MMT service users to evaluate the proposed model and relevant hypotheses using partial least squares. Several key findings were summarized from the results: (1) the attitude toward using MMT, technology anxiety, and trust are significantly associated with users' behavioral intention to use MMT services; (2) the perceived ease of use, perceived usefulness, and trust significantly influence users' attitude toward using MMT services; (3) the perceived interactivity, perceived personalization, and privacy concerns have significant impacts on users' perceptions of ease of use, usefulness, and trust toward MMT services. The current findings have both theoretical and practical implications that may guide practitioners and researchers to better understand consumers' acceptance of MMT services.

Mobile technology to give a resource-based knowledge management advantage to community health nurses in an emerging economies context

Purpose

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.

Design/methodology/approach

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

Findings

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.

Practical implications

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.

Social implications

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

Originality/value

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.

Digitalization and Physician Learning: Individual Practice, Organizational Context, and Social Norm

INTRODUCTION

The emerging context of online platforms and digitally engaged patients demands new competencies of health care professionals. Although information and communication technologies (ICTs) can strengthen continuous professional development (CPD) and learning at work, more research is needed on ICT for experiential and collegial learning.

METHODS

The study builds on prior qualitative research to identify issues and comprises a quantitative assessment of ICT usage for learning in health care. A survey was administered to Swedish physicians participating in a CPD program as part of specialist medical training. Conclusions focused specifically on learning dimensions are drawn from correlation analyses complemented with multiple regression.

RESULTS

The findings show that physicians' actual use of ICT is related to perceived performance, social influence, and organizational context. Social norm was the most important variable for measured general usage, whereas performance expectancy (perceived usefulness of ICT) was important for ICT usage for learning. The degree of individual digitalization affects performance and, in turn, actual use.

DISCUSSION

The study highlights the need to incorporate ICT effectively into CPD and clinical work. Besides formal training and support for specific systems, there is a need to understand the usefulness of digitalization integrated into practice. Moving beyond instrumentalist views of technology, the model in this study includes contextualized dimensions of ICT and learning in health care. Findings confirm that medical communities are influencers of use, which suggests that an emphasis on collegial expectations for digital collaboration will enhance practitioner adaptation.

Checking the potential shift to perceived usefulness-The analysis of users' response to the updated electronic health record core features

OBJECTIVE

The primary objective of this paper is to identify the main factors which have an impact on the users' attitude towards the functionalities representing the perceived ease of use and to those representing the perceived usefulness. Another objective is to examine whether there occurred a shift towards the perceived usefulness of users' behavior over a period of time. To support these objectives, two different cases are examined - the case in which users are simultaneously offered basic and updated functionalities, and the one in which users are offered a completely new set of features. The results of this study are expected to exert a significant impact on a further development of new software components, as well as the updates of the existing ones.

MATERIAL AND METHODS

As the starting point, there were employed the user behavior indicators defined in similar researches and conducted in the countries with a similar cultural background or with a comparatively similar national healthcare system. What ensued was an updated set of functionalities offered within the electronic health record based medical information system. Instead of the survey being posted, the effects of implanted updates were measured through the analysis of the collected data. The data collected in the Nis Primary and Ambulatory Care Center during a four-year period represented the material used in the research. The obtained records indicating the usage of the initial and updated visit registration form, as well as the usage of the new types of visits, were examined in relation to the technology acceptance model and integrated behavior model.

RESULTS

The response to the initial functionalities, perceived as easy to use, was high as expected since they kept the users in their "comfort zone". As regards the updated features, the ones corresponding to the perceived usefulness, the initial overall acceptance rate was 60%, while the overall increase of their acceptance was around 20%. The overall usage of the newly introduced features was doubled in some cases throughout the four-year period, while some of them were not accepted as expected.

DISCUSSION

Carefully designed additional functionalities, aimed to improve the most common daily activities, have a significant potential to be accepted by the medical professionals. The shift from the perceived ease of use to the perceived usefulness is not uniform, nor is its use in different departments or by the users of the same department. A higher acceptance rate was observed in the departments with more complex administrative procedures, as well as among the users having contacts with more patients and using the system for a longer period.

CONCLUSION

When accepting new features, medical professionals will initially choose the simpler ones with obvious benefits. If the usage of a feature triggers indirect benefits, the number of examined patients is of a crucial importance for the acceptance of that feature. In the event of the advanced functionality with an extended set of options competing with the simple functionality covering basic requirements, the latter will be used. A feature design, together with a proper training, system stability and ensuring utilization, represent a key point for increasing the positive impact that the information system can have in many application areas, including the healthcare.