Determinants Impacting User Behavior towards Emergency Use Intentions of m-Health Services in Taiwan

Determining information system end-user satisfaction and continuance intension with a unified modeling approach

With the different characters of datatypes and large amount of data going to be managed in open-source database, localization to the specific linguistics is the major concern in Ethiopia, as the nation used different datatypes compared to the Gregorian systems. In this regard Amharic localization in open-source database can handle the difficulties in managing data for governmental and non-governmental organizations. Amharic Extension Module was introduced to governmental organizations for the data management capabilities. But, there is no research that can explore the system's quality, the users' satisfaction and intension of continuance of Amharic Extension Module from the perspective of both computer literates and illiterates. Therefore, this research work attempt or try to empirically examine and analyze the system quality, the users' satisfaction and intension of continuance of Amharic Extension Module from the perspective of all users in POESSA The major purpose/aim of this study/research is to brand or make up the research break/gap in the area of localization specific to the Amharic locals, and to show the implication of the practical and theoretical way based on the results of the research. For this purpose, questionnaires were used for the collection of the research data. A total of 395 copies of the questionnaires were distributed and 385 of them are collected without any problem from the organization indicated herewith. The statistical analysis tools such as SPSS and AMOS, and methods such as Structural equation model were used for the analysis of the research data. The results of the research recommended and suggested that system quality can significantly influence confirmation. Meanwhile, confirmation can directly and significantly influence perceived usefulness, performance expectations, and satisfaction. Additionally, performance expectation, perceived usefulness and confirmation can significantly impact/influence satisfaction. The satisfaction directly and most importantly and significantly influences the continuance intension. Finally, the research delivers/provides a concert indication for the legitimacy and validity of the integrated and combined models of UTUAT, ECTM, and D&M ISS in the field of localizations which can be a hypothetical and theoretical foundation for Amharic Extension Module-AEM users' and services of it.

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study

BACKGROUND

Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.

OBJECTIVE

We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.

METHODS

Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.

RESULTS

In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).

CONCLUSIONS

Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Modeling Consumer Acceptance and Usage Behaviors of m-Health: An Integrated Model of Self-Determination Theory, Task-Technology Fit, and the Technology Acceptance Model

Although mobile health (m-health) has great potential to reduce the cost of medical care and improve its quality and efficiency, it is not widely accepted by consumers. In addition, there is still a lack of comprehensive insight into m-health acceptance, especially among consumers with different demographic characteristics. This study aimed to explore the factors affecting consumers' acceptance and usage behaviors of m-health and to examine whether their roles differ by demographic characteristics. A comprehensive m-health acceptance model was proposed by integrating factors from the Self-Determination Theory, Task-Technology Fit, and Technology Acceptance Model. Survey data were collected from 623 Chinese adults with at least 6 months of m-health usage experience and analyzed using structural equation modeling techniques. Multi-group analyses were performed to assess whether the model relationships were different across gender, age, and usage experience. The results indicated that relatedness and competence were significant motivational antecedents of perceived ease of use. Task-technology fit and the perceived ease of use significantly affected the perceived usefulness. The perceived ease of use and perceived usefulness were significant determinants of consumer usage behaviors of m-health and together explained 81% of its variance. Moreover, the relationships among autonomy, perceived usefulness, and usage behaviors of m-health were moderated by gender. Consumer usage behaviors of m-health were affected by factors such as self-motivation (i.e., relatedness and competence), technology perceptions (i.e., perceived ease of use and perceived usefulness), and task-technology fit. These findings provide a theoretical underpinning for future research on m-health acceptance and provide empirical evidence for practitioners to promote the better design and use of m-health for healthcare activities.

Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study

OBJECTIVES

Mobile health applications are instrumental in the self-management of chronic diseases like diabetes. Technology acceptance models such as Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) have proven essential for predicting the acceptance of information technology. However, earlier research has found that the constructs "perceived disease threat" and "trust" should be added to UTAUT2 in the mHealth acceptance context. This study aims to evaluate the extended UTAUT2 model for predicting mHealth acceptance, represented by behavioral intention, using mobile diabetes applications as an example.

METHODS

We extended UTAUT2 with the additional constructs "perceived disease threat" and "trust". We conducted a web-based survey in German-speaking countries focusing on patients with diabetes and their relatives who have been using mobile diabetes applications for at least 3 months. We analysed 413 completed questionnaires by structural equation modelling.

RESULTS

We could confirm that the newly added constructs "perceived disease threat" and "trust" indeed predict behavioural intention to use mobile diabetes applications. We could also confirm the UTAUT2 constructs "performance expectancy" and "habit" to predict behavioural intention to use mobile diabetes applications. The results show that the extended UTAUT2 model could explain 35.0% of the variance in behavioural intention.

DISCUSSION

Even if UTAUT2 is well established in the information technologies sector to predict technology acceptance, our results reveal that the original UTAUT2 should be extended by "perceived disease threat" and "trust" to better predict mHealth acceptance.

CONCLUSION

Despite the newly added constructs, UTAUT2 can only partially predict mHealth acceptance. Future research should investigate additional mHealth acceptance factors, including how patients perceive trust in mHealth applications.

How do mini games affect female users of mobile commerce? Improving platform satisfaction through game use intention

Combining games with mobile commerce applications has been a trend in recent years. Mobile commerce is attracting a large number of people, especially females, to play mini games on the platform. The gamification of mobile commerce may affect users’ platform satisfaction. This study aims to explore the intention of female users to play mobile commerce games and its impact on platform satisfaction. We collected data from females in China who played mobile commerce games and then used a structural equation model to test the various hypotheses we made. The results showed that game use intention fully mediated the impact of performance expectation, hedonic motivation, and social influence on platform satisfaction. Effort expectation had no significant impact on game use intention but had a positive impact on platform satisfaction. Game use intention had a positive impact on platform satisfaction. The frequency of playing games and the amount of money spent on the platform were positively correlated with game use intention. Females over 25 years old preferred to play mobile commerce games. This study provides a theoretical reference and practical enlightenment and makes a specific contribution to the development of mobile commerce platform and the application of gamification. However, this study has limitations in terms of test samples, research methods and research content, and further research on mobile commerce is required in the future.

Determinants of the Mobile Health Continuance Intention of Elders with Chronic Diseases: An Integrated Framework of ECM-ISC and UTAUT

With the deepening of population aging in China, chronic diseases are a major public health concern that threatens the life and health of nationals. Mobile health or mHealth can effectively monitor chronic diseases, which holds vital significance to the alleviation of social pressure caused by aging. To patients with chronic diseases, mHealth cannot give full play to its value, only when it is used in the long term. However, there is not yet research exploring mHealth continuance intention from the perspective of elders with chronic diseases. So, this research represents the first attempt to empirically analyze mHealth continuance intention from the perspective of elders with chronic diseases. The purpose of this research is to make up the research gap of the mHealth field and to put forward theoretical and practical implications based on research results. To obtain research data, a questionnaire was conducted. A total of 926 copies were collected online and 527 copies were collected offline. The structural equation model (SEM) was used for data analysis. Research results suggest that confirmation can significantly influence satisfaction, performance expectancy and effort expectancy. Meanwhile, confirmation and performance expectancy can significantly influence satisfaction. Additionally, effort expectancy, performance expectancy, social influence and facilitating conditions can directly and significantly influence continuance intention. Among them, performance expectancy can directly influence continuance intention in the most significant way. This research provides solid evidence for the validity of the integrated model of ECM-ISC and UTAUT in the mHealth field, which can be a theoretical basis for mHealth operators' product R&D.

Stimuli Influencing Engagement, Satisfaction, and Intention to Use Telemedicine Services: An Integrative Model

Telemedicine ensures quality, cost-effective, and equally accessible healthcare services for everyone. Nonetheless, a poor usage rate could curb its progression in developing cultures like Bangladesh. Therefore, this research examines how external stimuli promote the continuous usage intentions of synchronous telemedicine services through engagement and satisfaction by deploying the stimulus-organism-response framework. A final sample of 312 telemedicine users was analyzed using the structural equation modeling in AMOS. The average age of the participants was 26.28 (std. deviation 5.53), and their average use of telemedicine was 2.39 times (std. deviation 1.31) over the last six months. This study empirically endorsed that the stimuli, including performance expectancy, information quality, and contamination avoidance, as well as organismic factors such as engagement and satisfaction, directly impacted the continuance desires for telemedicine use. In addition, the analyses validated the mediation roles of engagement and satisfaction. Furthermore, performance and effort expectancies influenced engagement, which affected satisfaction along with performance expectancy, functionality, and information quality. Accordingly, telemedicine facilitators should integrate these critical attributes into the system to sustain engagement, satisfaction, and usage intentions. This study has pioneered the effects of performance and effort expectancies on continuous usage intentions facilitated by engagement and satisfaction in the telemedicine landscape.

Determining Factors Affecting the Acceptance of Medical Education eLearning Platforms during the COVID-19 Pandemic in the Philippines: UTAUT2 Approach

eLearning has been the medium of delivery of medical educational institutions to address the scarcity of medical professionals during the COVID-19 pandemic. In this study, the Unified Theory of Acceptance and Use of Technology (UTAUT2) was extended to determine the factors affecting the acceptance of eLearning platforms to medical education in the Philippines during the COVID-19 pandemic. A total of 360 medical students voluntary participated and answered an online questionnaire that consisted of 40 questions. Structural Equation Modeling (SEM) indicated that performance expectancy was found to have the highest effect on behavioral intention, which was followed by learning value and instructor characteristics. A high behavioral intention was found to affect the actual use of eLearning platforms. Interestingly, social influence and habit were found not to be significant to behavioral intentions. This study is the first study that has explored the acceptance of eLearning platforms among medical students in the Philippines during the COVID-19 pandemic. The findings can be a theoretical guideline of the Commission on Higher Education of the Philippines for eLearning platforms. Finally, the framework would be very valuable for enhancing the open innovation in eLearning platforms in medical fields worldwide.