Strengthening the Trialability for the Intention to Use of mHealth Apps Amidst Pandemic: A Cross-Sectional Study

Jilani, Munshi Muhammad Abdul Kader; Moniruzzaman, Md.; Dey, Mouri; Alam, Edris; Uddin, Md. Aftab

doi:10.3390/ijerph19052752

Cited by 10 publications

(5 citation statements)

References 65 publications

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“…This result is consistent with the determinants of the trialability of mHealth apps, which involve assessing whether mobile health applications meet users' adoption standards (27). Additionally, it aligns with the research findings on the trialability of mHealth apps among the Y generation in Bangladesh, where it is considered a crucial antecedent to the intention of mobile health application usage (84). It suggests that when the public can assess the effectiveness and benefits of a medical app through trial or firsthand experience, they are more likely to be interested in it, thus perceiving its value.…”

Section: Discussion and Conclusion 51 Key Findingssupporting

confidence: 86%

“…In the context of this study, observability refers to the extent to which the effects of a TA are easily visible to others. TA, as software, are relatively easy to observe because they can be readily seen, downloaded, and used on smart devices (83)(84)(85). When users can intuitively perceive the positive effects of such an application, such as improvements in healthcare, convenience, time and resource savings, and better connections with healthcare professionals, they are more likely to trust and adopt the application (6,86).…”

Section: Observabilitymentioning

confidence: 99%

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The determinants of public acceptance of telemedicine apps: an innovation diffusion perspective

Liu,

Son,

Cao

2023

Front. Public Health

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With the rapid advancement of information technology, telemedicine apps have gradually become an indispensable tool for providing patients with more convenient, efficient, and accessible healthcare services. However, the successful implementation of these apps largely depends on widespread acceptance among the public. To thoroughly investigate the factors influencing the public’s acceptance of these apps and the relationships between these factors, this study developed a theoretical model based on the Diffusion of Innovation theory and the Theory of Perceived Value. To validate this model, we conducted a survey of 387 residents in Beijing, China, and employed structural equation modeling to analyze the collected data. The research findings indicate that attributes of innovation diffusion, including relative advantage, compatibility, complexity, trialability, and observability, significantly and positively influence the public’s perceived value. Particularly noteworthy is that perceived value partially mediates the relationship between innovation attributes and public acceptance, emphasizing the crucial role of perceived value in the public decision-making process. This study employed a theory-driven approach to elucidate the acceptance of telemedicine apps and offers fresh insights into the existing literature. By integrating the research paradigms of innovation diffusion and customer perceived value, we provide a coherent explanation of how individual cognitive processes lead to acceptance behavior. In summary, this research enriches the existing theoretical studies on the acceptance of telemedicine apps and holds positive implications for healthcare practice.

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Section: Discussion and Conclusion 51 Key Findingssupporting

confidence: 86%

Section: Observabilitymentioning

confidence: 99%

The determinants of public acceptance of telemedicine apps: an innovation diffusion perspective

Liu,

Son,

Cao

2023

Front. Public Health

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“…Following the research work of Hsu et al, Wang and Lin [ 39 ] combined the innovation diffusion theory with the task-technology fit model to further verify factors influencing the user intention of big data analytics in mobile cloud health care systems. Additionally, Jiani et al [ 40 ] carried out a survey of mHealth behavioral intention under the background of COVID-19. Results shed light on the fact that the trialability compatibility of mHealth was positively related to the behavioral intention to use.…”

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

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

Tian

2022

IJERPH

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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.

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“…Naturally, the present generation in Bangladesh enjoys the formal learning opportunities provided by technology in educational institutions and social groups, which proxies their absorption capacity to reshape their attitudes and perception to overcome techno-centric obstacles. They strongly believe that their tech-directed knowledge encourages them to adopt AI-based technologies in changing situations (Jilani et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Technology Adoption and Human Resource Management Practices: The Use of Artificial Intelligence for Recruitment in Bangladesh

Islam

Mamun

Afrin

et al. 2022

South Asian Journal of Human Resources Management

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Artificial intelligence (AI) is now considered indispensable in undertaking operational activities, especially in the area of human resource analytics. However, in practice, the rate of the adoption of such modern algorithms in organisations is still in its early stages. Consequently, the primary objective of this study is to identify the main antecedents of the adoption of AI-based technologies in recruitment, using the lens of the unified theory of acceptance and use of technology (UTAUT) model, alongside perceived credibility and moderating variables, in the context of an emerging nation in South Asia, namely Bangladesh. Data were collected from 283 human resource professionals employed in different manufacturing and service firms in Bangladesh through the administration of a questionnaire, which was analysed by applying PLS-SEM. The outcomes of the study show that all the direct hypothesised relationships were found to be significant, apart from the extended variable of perceived credibility. However, no moderating effect of gender or firm size was found in any of the hypothesised propositions. Finally, policy implications and recommendations for future researchers are proposed.

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Strengthening the Trialability for the Intention to Use of mHealth Apps Amidst Pandemic: A Cross-Sectional Study

Cited by 10 publications

References 65 publications

The determinants of public acceptance of telemedicine apps: an innovation diffusion perspective

The determinants of public acceptance of telemedicine apps: an innovation diffusion perspective

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

Technology Adoption and Human Resource Management Practices: The Use of Artificial Intelligence for Recruitment in Bangladesh

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