The development of an instrument to predict patients’ adoption of mHealth in the developing world

Addotey-Delove, Michael; Scott, Richard E.; Mars, Maurice

doi:10.1016/j.imu.2022.100898

Cited by 10 publications

(4 citation statements)

References 45 publications

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“…This indicates that users with good abilities to take advantage of internet tend to feel less uncomfortable about using telehealth. The finding resonates with previous studies that the level of literacy has associations with acceptance of the telehealth; the knowledge about the internet, as well as the ability to understand the knowledge and usage of telehealth, are incentives of being more confident with using telehealth [ 53 , 54 ]. However, internet literacy is not found to have a significant impact on insecurity, suggesting that rich experiences on the internet do not indicate a significantly lower perception of telehealth's potential risks.…”

Section: Empirical Analysis and Discussionsupporting

confidence: 87%

Psychological antecedents of telehealth acceptance: A technology readiness perspective

Zhou

Liu

et al. 2023

International Journal of Disaster Risk Reduction

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Section: Empirical Analysis and Discussionsupporting

confidence: 87%

Psychological antecedents of telehealth acceptance: A technology readiness perspective

Zhou

Liu

et al. 2023

International Journal of Disaster Risk Reduction

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“…Under the medical development background, a new-type medical style, known as mHealth (abbreviation for “Mobile Health”), has appeared. Propelled by the development of information technologies and government policy support, the development of mHealth has been an irresistible trend [ 10 ]. By changing the traditional medical models, mHealth can significantly improve the resource allocation efficiency, lower the social medical cost and improve people’s overall health level [ 11 , 12 ].…”

Section: Introductionmentioning

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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“…TAM and UTAUT also have noted limitations. For example, Ward [ 57 ] found that issues that affect health worker’s information technology / information system acceptance do not only revolve around the individual’s personal decision to use the technology, which is the main focus of TAM and UTAUT, but also on the organisational setting within which the system is deployed, in addition to the sociocultural and emotion factors. Similarly TAM and UTAUT have been criticised for their focus on settings where use of technology is voluntary unlike many healthcare settings [ 34 ], which this study addresses by using empirical findings from actual mHealth implementations.…”

Section: Discussionmentioning

confidence: 99%

A healthcare workers’ mHealth adoption instrument for the developing world

Addotey-Delove

Scott

Mars

2022

BMC Health Serv Res

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Introduction Healthcare workers’ adoption of mHealth is critical to the success or failure of clinician based mHealth services in the developing world. mHealth adoption is affected or promoted by certain factors, some of which are peculiar to the developing world. Identifying these factors and evaluating them will help develop a valid and reliable measuring instrument for more successful prediction of mHealth adoption in the future. The aim of this study was to design and develop such an instrument. Method A Healthcare workers’ mHealth Adoption Questionnaire (HmAQ) was developed based on five constructs identified through a prior literature review: multi-sectorial engagement and ownership; staffing and technical support; reliable infrastructure; usefulness and stewardship; and intention to adopt. After testing face and content validity, the questionnaire was administered to 104 nurses and midwives in the Ewutu-Senya district of the Central Region of Ghana who used a maternal mHealth intervention. After data collection confirmatory factor analysis and structural equation modelling were applied and the Healthcare Worker mHealth Adoption Impact Model (HmAIM) developed. Results Exploratory factor analysis showed the eigenvalue of all five components to be significant (cumulative total greater than 1.0). Bartlett’s Test of Sphericity was significant, the Kaiser-Meyer-Olkin value was 0.777, and the mean Cronbach’s α value was 0.82 (range 0.81–0.83). Confirmatory factor analysis showed that constructs for the HmAQ were within acceptable limits and valid. Structural equation modelling showed the causal relationships between components. This resulted in development of the HmAIM. A modified model was then developed using the averages of individual construct items. This model showed strong correlation among the constructs. Further research will be required to understand new dimensions of mHealth adoption as a result of emerging technology needs, new complexities in the healthcare work environment, and how different cadres of healthcare workers respond to it. Conclusion The study presents a valid and reliable instrument, the HmAIM, to serve as a tool for assessment of healthcare workers’ mHealth adoption in the developing world. Use of the instrument will enhance the likelihood of successful adoption of mHealth implementations.

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The development of an instrument to predict patients’ adoption of mHealth in the developing world

Cited by 10 publications

References 45 publications

Psychological antecedents of telehealth acceptance: A technology readiness perspective

Psychological antecedents of telehealth acceptance: A technology readiness perspective

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

A healthcare workers’ mHealth adoption instrument for the developing world

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