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Evaluating the predictors of mobile health acceptance among Zimbabwean university students during the COVID-19 era: an integrated framework

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dc.contributor.author Dangaiso, Phillip
dc.contributor.author Jaravaza, Divaries Cosmas
dc.contributor.author Mukucha, Paul
dc.date.accessioned 2026-05-12T09:36:30Z
dc.date.available 2026-05-12T09:36:30Z
dc.date.issued 2023-12-23
dc.identifier.citation Dangaiso, P., Jaravaza, D. C., & Mukucha, P. (2024). Evaluating the predictors of mobile health acceptance among Zimbabwean university students during the COVID-19 era: an integrated framework. Cogent Social Sciences, 10(1), 2299141. en_US
dc.identifier.uri https://doi.org/10.1080/23311886.2023.2299141
dc.identifier.uri https://ir.cut.ac.zw:8080/xmlui/handle/123456789/760
dc.description.abstract The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or popularly the Corona Virus Disease 2019 (CO VID-19) pandemic brought significant public health challenges globally. During the crisis, mobile health (m-health) services were implemented to expedite fast, convenient and reliable dissemination of health information to the public. Meanwhile, the adoption of m-health faced high uncertainty alike other CO VID-19 regulatory methods. This study examines the antecedents of m-health acceptance among Zimbabwean university students. Whilst research on m-health adoption during the pandemic is still scarce, this study becomes the first to integrate the Unified Theory of Acceptance and Use of Technology (UTA UT) and the Theory of Planned Behavior (TPB) to predict m-health adoption in a developing country. An explanatory design and a quantitative research approach were employed. Based on 271 valid responses, Structural Equation Modelling was used to estimate the proposed model. The findings revealed the positive effect of performance expectancy, effort expectancy, facilitating conditions, attitudes, behavioral norms, perceived behavioral control on behavioral intention to adopt m-health with a higher R square value (80.4%) than the original UTA UT model. The study also confirmed the positive influence of behavioral intention on m-health usage (R square = 41.5%). Health promoters were urged to design messages that stimulate positive attitudes, appeal to social groupings and improve user’s self-efficacy. M-health services should also foster use simplicity, ease of use and health value to entice m-health adoption among consumers. The study also provides an important baseline for the integration of behavioral theoretical models to enhance their predictive strength. en_US
dc.language.iso en en_US
dc.publisher Tailor & Francis en_US
dc.subject Mobile health acceptance en_US
dc.subject performance expectancy en_US
dc.subject effort expectancy en_US
dc.subject facilitating conditions en_US
dc.subject attitudes en_US
dc.subject subjective norms en_US
dc.subject perceived behavioral control en_US
dc.title Evaluating the predictors of mobile health acceptance among Zimbabwean university students during the COVID-19 era: an integrated framework en_US
dc.type Article en_US
dc.identifier.orcid 0000-0002-4495-0601 en_US
dc.identifier.orcid 0000-0002-8930-1242 en_US
dc.identifier.orcid 0000-0002-6264-6574 en_US


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