The role of trust and habit in the adoption of mHealth by older adults in Hong Kong: a healthcare technology service acceptance (HTSA) model.

BACKGROUND: Evidence from the literature suggests that mobile health (mHealth) services can potentially improve healthcare outcomes among older adults. Hence, the government of Hong Kong has recently taken several community and information technology (IT) services initiatives to train older adults on how to enhance their abilities and interest in using mHealth technology. Although mHealth services have been widely implemented globally, their adoption and use by older adults are very low, including those in Hong Kong. This study aims to understand key factors influencing mHealth use intention among the older Chinese population in Hong Kong. METHODS: We extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) as the basis of our conceptual framework. We applied Partial Least Squares path modeling method to conduct the Structural Equation Model (SEM) technique that allows measuring the theoretical validity of any conceptual framework. Convenience and snowball sampling methods were used to recruit participants aged 65 or above. In total, 201 valid responses were used for testing the theoretical validity of the proposed conceptual framework. RESULTS: The primary finding shows that the widely used UTAUT2 model falls short in explaining mHealth service acceptance behavior in the Chinese older population in Hong Kong. We further propose a simplified model, the Healthcare Technology Service Acceptance (HTSA) model, to understand the formation of mHealth service acceptance behavior. The findings show that trust is an important component of technology service acceptance intention behavior that was missing in the UTAUT2 model. The results also show that several antecedent factors (i.e., social influence, government policy, and service quality) are critical in forming technology trust beliefs. CONCLUSIONS: The study shows that the HTSA model can better explain mHealth acceptance behavior than the UTAUT2 model. This study advances knowledge in the mHealth technology adoption domain by proposing a simplified new version of the UTAUT2 model for understanding healthcare technology service acceptance and use intention among older adults. The findings of the study provide valuable information to the Hong Kong government and healthcare organizations for wider adoption of mHealth services, especially in older adults.

Factors influencing the elderly's adoption of mHealth: an empirical study using extended UTAUT2 model.

BACKGROUND: Despite the high usage of mobile phones in daily life in developing countries like Bangladesh, the adoption and usage of mHealth services have been significantly low among the elderly population. When searching previous studies, the researchers have found that no studies have empirically investigated whether the quality of life and service quality are significant for mHealth adoption by elderlies in Bangladesh. Hence, this study aimed to extend the Unified Theory of Acceptance and Use of Technology by adding service quality and the quality of life to empirically find the key factors that influence elderlies' intention to adopt and use mHealth services in Bangladesh. METHODS: A face-to-face structured questionnaire survey method was used to collect data from 493 elderlies (aged 60 years and above) in Bangladesh. The data were analyzed with the Structural Equations Modelling (SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). RESULTS: SEM results suggested that Social Influence, Hedonic Motivation, Price Value, Habit, and Service Quality had significant impact (p < 0.05) on the elderlies' behavioral intention to adopt mHealth services. Service Quality, Quality of Life, and elderlies' Habit were found significant in explaining the Use Behavior of mHealth services. Quality of Life did not show significant (p > 0.05) effect on Behavioral Intention, which is inconsistent with existing literature. In addition, fsQCA findings suggest how the intensity of the influencers may contribute to high versus low m-health behavioral outcomes. CONCLUSIONS: The findings have significant implications for theory, practice and future research as explained in the paper. The originality of this study is the integration of quality of life and service quality into UTUAT2 to explain the users' behavioural intention and use behaviour. Overall, the findings may contribute to shaping appropriate policies for designing and implementing mHealth services effectively for elderlies in developing countries.

An empirical study of factors influencing e-health services adoption among public in Saudi Arabia.

Until now most of the studies concerning eHealth in Saudi Arabia are about the exploration of the national benefits from eHealth and the technical and infrastructural challenges in implementing eHealth rather than finding the factors influencing the users in adopting eHealth services. Further, the eHealth adoption rate in Saudi Arabia is low despite the scope of potential growth for the eHealth market. In this study, the authors added Trust, Privacy and System Quality factors to Technology Acceptance Model by considering the research context to examine the factors influencing eHealth services adoption. The proposed model was empirically tested based on the data collected, through survey questionnaire from 314 responses in Saudi Arabia. Structural Equation Modelling was followed to analysis and validates the proposed model based on partial least squares method using SmartPLS. Based on the findings, Perceived Usefulness in addition to Privacy significantly affect eHealth adoption. Moreover, Perceived Ease of Use factor has indirect effect on people perception toward eHealth services. Furthermore, the results show that System Quality and Trust are not influencing factors. This study is important for the healthcare policymakers for getting direction for future studies to avail the maximum benefits of eHealth in Saudi Arabia.

Antecedents of Perceived Service Quality of Online Education During a Pandemic: Configuration Analysis Based on Fuzzy-Set Qualitative Comparative Analysis.

BACKGROUND: During COVID-19 lockdown worldwide, classroom education continues remotely through online. The question remains, comparing with the face-to-face education, does online education has a similar satisfaction level among the students? There are only a few studies that examine the perceived service quality of online education. OBJECTIVE: The study aims to analyze the factors of perceived service quality of online education during a pandemic. RESEARCH DESIGN: A structured questionnaire elicits information from 147 students from different study backgrounds of various universities worldwide. The fuzzy-set qualitative comparative analysis (fsQCA) is used for data analysis and model design. Research constructs evaluation for reliability and internal consistency are subsequently performed. A snowball random sampling method is applied for data collection. RESULTS: Findings from the fsQCA analysis identify four core factors that underpin student satisfaction through positive perceived service quality of online education. Alternative paths are determined based on gender, students' current education status, and their loyalty toward online education. We also introduce two topologies of perceived quality regarding online education and student satisfaction. ORIGINALITY: Because of the primary nature of the data, this is firsthand experience gathered from different universities around the world who have willingly or unwillingly experienced online learning during the pandemic. The fsQCA technique for examining perceived service quality of online education. CONCLUSIONS: The findings contain a number of contributions, illustrating different topologies of the student from different backgrounds and their intention, satisfaction and loyalty towards e-learning, and identifying causal factors that influence willingness to recommend online education.

Blood Uric Acid Prediction With Machine Learning: Model Development and Performance Comparison.

BACKGROUND: Uric acid is associated with noncommunicable diseases such as cardiovascular diseases, chronic kidney disease, coronary artery disease, stroke, diabetes, metabolic syndrome, vascular dementia, and hypertension. Therefore, uric acid is considered to be a risk factor for the development of noncommunicable diseases. Most studies on uric acid have been performed in developed countries, and the application of machine-learning approaches in uric acid prediction in developing countries is rare. Different machine-learning algorithms will work differently on different types of data in various diseases; therefore, a different investigation is needed for different types of data to identify the most accurate algorithms. Specifically, no study has yet focused on the urban corporate population in Bangladesh, despite the high risk of developing noncommunicable diseases for this population. OBJECTIVE: The aim of this study was to develop a model for predicting blood uric acid values based on basic health checkup test results, dietary information, and sociodemographic characteristics using machine-learning algorithms. The prediction of health checkup test measurements can be very helpful to reduce health management costs. METHODS: Various machine-learning approaches were used in this study because clinical input data are not completely independent and exhibit complex interactions. Conventional statistical models have limitations to consider these complex interactions, whereas machine learning can consider all possible interactions among input data. We used boosted decision tree regression, decision forest regression, Bayesian linear regression, and linear regression to predict personalized blood uric acid based on basic health checkup test results, dietary information, and sociodemographic characteristics. We evaluated the performance of these five widely used machine-learning models using data collected from 271 employees in the Grameen Bank complex of Dhaka, Bangladesh. RESULTS: The mean uric acid level was 6.63 mg/dL, indicating a borderline result for the majority of the sample (normal range <7.0 mg/dL). Therefore, these individuals should be monitoring their uric acid regularly. The boosted decision tree regression model showed the best performance among the models tested based on the root mean squared error of 0.03, which is also better than that of any previously reported model. CONCLUSIONS: A uric acid prediction model was developed based on personal characteristics, dietary information, and some basic health checkup measurements. This model will be useful for improving awareness among high-risk individuals and populations, which can help to save medical costs. A future study could include additional features (eg, work stress, daily physical activity, alcohol intake, eating red meat) in improving prediction.

Redesigning Portable Health Clinic Platform as a Remote Healthcare System to Tackle COVID-19 Pandemic Situation in Unreached Communities.

Medical staff carry an inordinate risk of infection from patients, and many doctors, nurses, and other healthcare workers are affected by COVID-19 worldwide. The unreached communities with noncommunicable diseases (NCDs) such as chronic cardiovascular, respiratory, endocrine, digestive, or renal diseases became more vulnerable during this pandemic situation. In both cases, Remote Healthcare Systems (RHS) may help minimize the risk of SARS-CoV-2 transmission. This study used the WHO guidelines and Design Science Research (DSR) framework to redesign the Portable Health Clinic (PHC), an RHS, for the containment of the spread of COVID-19 as well as proposed corona logic (C-Logic) for the main symptoms of COVID-19. Using the distributed service platform of PHC, a trained healthcare worker with appropriate testing kits can screen high-risk individuals and can help optimize triage to medical services. PHC with its new triage algorithm (C-Logic) classifies the patients according to whether the patient needs to move to a clinic for a PCR test. Through modified PHC service, we can help people to boost their knowledge, attitude (feelings/beliefs), and self-efficacy to execute preventing measures. Our initial examination of the suitability of the PHC and its associated technologies as a key contributor to public health responses is designed to "flatten the curve", particularly among unreached high-risk NCD populations in developing countries. Theoretically, this study contributes to design science research by introducing a modified healthcare providing model.

Mobile health interventions in developing countries: A systematic review.

This study reviews the quality of evidence reported in mobile health intervention literature in the context of developing countries. A systematic search of renowned databases was conducted to find studies related to mobile health applications published between a period of 2013 and 2018. After a methodological screening, a total of 31 studies were included for data extraction and synthesis. The mobile health Evidence Reporting and Assessment checklist developed by the World Health Organization was then used to evaluate the rigor and completeness in evidence reporting. We report several important and interesting findings. First, there is a very low level of familiarity with the mobile health Evidence Reporting and Assessment checklist among the researchers and mobile health intervention designers from developing countries. Second, most studies do not adequately meet the essential criteria of evidence reporting mentioned in the mobile health Evidence Reporting and Assessment checklist. Third, there is a dearth of application of design science-based methods and theory-based frameworks in developing mobile health interventions. Fourth, most of the mobile health interventions are not ready for interoperability and to be integrated into the existing health information systems. Based on these findings, we recommend for robust and inclusive study plans to deliver highly evidence-based reports by mobile health intervention studies that are conducted in the context of developing countries.

Impacts of Anthropometric, Biochemical, Socio-demographic, and Dietary Habits Factors on the Health Status of Urban Corporate People in a Developing Country.

This study focused on urban corporate people and applied multinomial logistic regression (MLR) to identify the impact of anthropometric, biochemical, socio-demographic and dietary habit factors on health status. Health status is categorized into four levels: healthy, caution, affected, and emergent. A cross-sectional study, based on convenience sampling method, was conducted to select 271 employees from 18 institutions under the Grameen Bank Complex, Dhaka, Bangladesh. Biochemical measurements such as blood uric acid are highly significant variables in the MLR model. When holding other factors as constants, with a one-unit increase in blood uric acid, a person is 11.02 times more likely to be "emergent" compared to "caution". The odds are also higher, at 1.82, for the blood uric acid to be "affected" compared "caution". The results of this study can help to prevent a large proportion of non-communicable diseases (NCDs) by reducing the most significant risk factor: blood uric acid. This study can contribute to the establishment of combined actions to improve disease management.

Women Using Mobile Phones for Health Communication Are More Likely to Use Prenatal and Postnatal Services in Bangladesh: Cross-Sectional Study.

BACKGROUND: The public health system in Bangladesh has been struggling to provide coverage and utilization of basic maternal health care services in pursuit of achieving maternal and child mortality-related goals. Interestingly, the rapid popularization of mobile technology in the country is transforming the landscape of health care access and delivery. However, little is known regarding the use of mobile phones from the perspective of maternal health care service utilization. OBJECTIVE: In this study, we aimed to investigate the prevalence and sociodemographic pattern of mobile phone use for health services among women and relationship between the use of mobile phone use and the uptake of essential maternal health services (MHSs). METHODS: Cross-sectional data from the Bangladesh Demographic and Health Survey on 4494 mothers aged between 15 and 39 years were used in the analysis. Using mobile phones to get health services or advice was hypothesized to have a positive association with the uptake of basic MHSs (antenatal care, ANC, facility delivery services, postnatal care) and postnatal care for the newborn. Data were analyzed using bivariate and multivariable techniques. RESULTS: More than a quarter (1276/4494, 28.4%; 95% CI 26.8-30.3) of the women aged 15-39 years reported using mobile phones to get health services with significant sociodemographic variations in the use of mobile phones. Analysis of the specific purposes revealed that, in most cases, mobile phones were used to contact service providers and consult with the same about what to do, whereas a smaller proportion reported using mobile phone for the purposes of arranging money and transportation. Multivariable analysis showed that compared with respondents who reported not using mobile phones for health care services, those who used them had higher odds of making 3+ ANC visits and delivering at a health facility. The odds were slightly higher for rural residents than for those in the urban areas. CONCLUSIONS: The findings of this study conclude that women who use mobile phones are more likely to use ANC and professional delivery services than those who do not. More in-depth studies are necessary to understand the mechanism through which mobile phone-based services enhance the uptake of maternal health care.

Patient Acceptance of e-Health Services in Saudi Arabia: An Integrative Perspective.

Background: e-Health has been expansively considered as a technological intervention for fundamental enhancement in the healthcare sector to mitigate the enormous demand and supply of healthcare in both developed and developing nations. In 2000, the Saudi government established a committee for health reform to develop an information technology strategic plan for healthcare and for deploying e-health applications within the country. The objective of e-health systems was to provide better healthcare to patients and to increase the efficiency of healthcare organizations. Despite numerous e-health interventions to provide healthcare services, very little is studied about the adoption process of e-health from users' viewpoints in Saudi Arabia. This study minimizes this knowledge gap by studying the factors affecting the adoption and acceptance of e-health in the context of Saudi Arabia.Materials and Methods: This study has combined theTechnology Acceptance Model and Theory of Planned Behavior frameworks to evaluate the factors influencing the patient acceptance of e-health services in Saudi Arabia. Data were collected from patients at various private and public hospitals in Saudi Arabia. The partial least square technique based on structural equation modeling was applied to analyze the survey data.Results: The study shows the significant influence of perceived usefulness and perceived ease of use on the attitude. Furthermore, attitude and subjective norm (p < 0.05) significantly influence patient behavioral intention (BI) to use e-health services. However, perceived behavioral control (p > 0.05) had no significant influence on patient BI to use e-health services.Conclusions: The findings of this study might be useful to policymakers, the government, and healthcare service providers in Saudi Arabia and other developing countries.

Big Data Based m-Health Application to Prevent Health Hazards: A Design Science Framework.

BACKGROUND: Every year about three million Muslims visit the Holy City of Makkah in Saudi Arabia to perform the Hajj. Because of the large number of people present during this period, pilgrims can be subjected to many health hazards. An adequate system to minimize these health hazards is needed to support the pilgrims who attend the Hajj. This study justifies the need for developing a large data-based m-Health application to identify the health hazards encountered during the Hajj. MATERIALS AND METHODS: In developing a big data-based m-Health application, this study follows the framework suggested by Hevner. The design of the science framework allows the development of a technological solution (i.e., design artifact) of the problem through a series of actions. The design involves rigorous knowledge of the environmental factors, including knowledge of the construction and evaluation of technological solutions, that are important and relevant to an existing problem. RESULTS: Based on the design science framework, the process of artifact development can be classified into Artifact Design, Artifact Implementation, and Artifact Evaluation. This paper presents the Artifact Design step for the design of the big data-based m-Health application, which has an Environmental Relevance Cycle, a Knowledge-based rigor Cycle, and an Artifice development and design cycle. The big data-based m-Health application is a prototype and must be evaluated using the evaluation-and-feedback loop process until the optimum artifact is completely built and integrated into the system. CONCLUSION: Development of a big data-based m-Health application using a design science framework can support the effective and comprehensive plan of the government of Saudi Arabia for preventing and managing Hajj-related health issues. Our proposed model for developing and designing a big data-based m-Health application could provide direction for developing the most advanced solution for dealing with the Hajj-related health issues in the future.

Investigating Factors Affecting Elderly's Intention to Use m-Health Services: An Empirical Study.

BACKGROUND: m-Health as an important part of e-health has recently become one of the most influential initiative in healthcare sector all over the world. In developing countries healthcare service providers started to provide m-health services from the last few years. Despite the widespread acceptance of mobile phones, the adoption of m-health among elderly is significantly low in developing countries. However, little research has been conducted to explore factors influencing elderly's intention to use m-health services particularly in developing countries. The objective of this study is to identify the factors that influence the elderly's intention to use m-health services. MATERIALS AND METHODS: To assess elderly's intention to use m-health services, this study applied the Unified Theory of Acceptance and Use of Technology (UTAUT). Data were collected from participants of age 60 years and above. The partial least square method based on structural equation modeling was used to analyze data. RESULTS: The study found that performance expectancy, effort expectancy, social influence, and perceived credibility (p < 0.05) had significant influence on elderly's intention to use m-health services. However, facilitating condition (p > 0.05) had no significant influence on elderly's intention to use m-health services. CONCLUSIONS: The findings of this study may become beneficial for the governments, policy makers, and healthcare service providers in developing countries.

Disparities in the use of mobile phone for seeking childbirth services among women in the urban areas: Bangladesh Urban Health Survey.

BACKGROUND: In Bangladesh, similar to its other South Asian counterparts, shortage of health workers along with inadequate infrastructure constitute some of the major obstacles for the equitable provision of reproductive healthcare services, particularly among the marginalized and underserved neighbourhoods. However, given the rapidly expanding broadband communication and mobile phone market in the country, the application of eHealth and mHealth technologies offer a window of opportunities to minimise the impact of socioeconomic barriers and promote the utilization of maternal healthcare services thereby. In the present study we aimed to investigate 1) the prevalence of usage of mobile phones for seeking childbirth services, 2) neighbourhood and socioeconomic disparities in the use, and 3) association between using mobile phones and the uptake of postnatal care among mothers and neonates. METHODS: Data for the present study came from Bangladesh Urban Health Survey 2013. Study subjects were 9014 married women aged between 15 and 49 years. RESULTS: The overall rate of use of mobile phone was highest in City Corporation non-Slum areas (16.2%) and lowest in City Corporation Slum areas (7.4%). The odds of using mobile for seeking childbirth services were significantly higher among those who were living in non-slum areas, and lower among those who never attended school and lived in poorer households. Results also indicated that women in the slum areas who used mobile phone for childbirth service seeking, were 4.3 times [OR = 4.250;95% CI = 1.856-9.734] more likely to receive postnatal care for themselves, and those from outside the city-corporation areas were 2.7 times [OR = 2.707;95% CI = 1.712-4.279] more likely to receive postnatal care for the newborn. CONCLUSION: Neighbourhood, educational and economic factors were significantly associated with the mobile phone utilization status among urban women. Promoting access to better education and sustainable income earning should be regarded as an integral part to the expansion of mHealth for maternal healthcare seeking behaviour.

Cost and Time Effectiveness Analysis of a Telemedicine Service in Bangladesh.

Telemedicine has great potential to overcome geographical barriers to providing access to equal health care services, particularly for people living in remote and rural areas in developing countries like Bangladesh. A number of telemedicine systems have been implemented in Bangladesh. However, no significant studies have been conducted to determine either their cost effectiveness or efficiency in reducing travel time required by patients. In addition, very few studies have analyzed the attitude and level of satisfaction of telemedicine service recipients in Bangladesh. The aim of this study was to analyze the cost and time effectiveness of a telemedicine service, implemented through locally developed PC based diagnostic equipment and software in Bangladesh, compared to conventional means of providing those services. The study revealed that the introduced telemedicine service reduced cost and travel time on average by 56% and 94% respectively compared to its counterpart conventional approach. The study also revealed that majority of users were highly satisfied with the newly introduced telemedicine service. Therefore, the introduced telemedicine service can be considered as a low cost and time efficient health service solution to improve health care facilities in the remote rural areas in Bangladesh.

An empirical study of mHealth adoption in a developing country: the moderating effect of gender concern.

BACKGROUND: mHealth has become a valuable tool for providing health care services in developing countries. Despite the potential benefits of mHealth, its adoption remains a very challenge in developing countries like Bangladesh. The aim of this study is to investigate the factors that affect the adoption of mHealth services in Bangladesh using Extended Technology Acceptance Model (TAM). METHODS: Data were collected from over 250 respondents in Dhaka, Bangladesh. The data were analyzed using the Partial Least Squares (PLS) method, a statistical analysis technique based on the Structural Equation Modeling (SEM). RESULTS: The study found that perceived ease of use, perceived usefulness and subjective norm (p < 0.05) had significant positive impact on the intention to adopt mHealth services. Surprisingly, the effects of personal innovativeness in IT (p > 0.05) on mHealth adoption were insignificant. This study also revealed that gender was strongly associated with the adoption and use of mHealth in developing countries. CONCLUSIONS: The findings of this study can be used by government, policy makers, and mobile phone Company to maximize the acceptance of mHealth services in Bangladesh. The paper concludes with a discussion of research results and draws several implications for future research.

Cultural Influence on Adoption and Use of e-Health: Evidence in Bangladesh.

BACKGROUND: E-health is an important initiative among the public and private hospitals in Bangladesh in the last few years. The factors influencing e-health adoption have been a well-investigated research area in both developed and developing countries. However, there have been only a few studies exploring the role of cultural factors in the adoption and use of e-health, particularly in developing countries. In this study, we investigated the influence of culture on the adoption of e-health in Bangladesh. MATERIALS AND METHODS: This study developed a more adequate research framework by integrating Hofstede's cultural dimension model and the Technology Acceptance Model (TAM). A structured questionnaire was used to collect data from respondents in different private and public hospitals in Bangladesh. The partial least squares method, a statistical analysis technique based on the Structural Equation Model, was used to analyze the collected data. RESULTS: The study found that cultural dimensions such as Power Distance, Masculinity, and Restraint had significant impacts on Intention to Use e-Health, whereas Uncertainty Avoidance, Collectivism, and Pragmatism had no significant impact on Intention to Use e-Health in Bangladesh. The results also revealed that Perceived Usefulness was a significant indicator of e-health adoption decisions, whereas Perceived Ease of Use was an insignificant predictor of e-health adoption. CONCLUSIONS: The findings of this study may assist governments, organizations, and policy makers to understand the key factors affecting e-health adoption and to develop strategies and policies to enhance e-health services in Bangladesh.