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Impact of technological acceptance on application-based engagement among type 2 diabetes patients: local insights and
Afeefa Tahira1, Mohamad Haniki Nik Mohamed1, Mohamed Hassan Elnaem2
1Pharmacy Practice Department, Kulliyyah of Pharmacy, International Islamic University, Kuantan, Pahang, Malaysia.
Background:
Acceptability and sustained engagement of mobile health (mHealth) applications in resource-limited settings for chronic disease management are suboptimal. Research on mHealth applications overlooks contextual factors affecting the translation of their acceptance to long-term usage.
Methods:
This study examined contextual factors using questionnaire developed by Technological Acceptance Models (TAM) and Expectation Confirmation Theory (ECT), to study the influence of technology acceptance (TA) on Sustained App-based Engagement and Use (ABEU) among Type 2 Diabetes Mellitus (T2DM) patients. Data were collected through purposive sampling from 397 T2DM patients across public and private hospitals in four provinces of Pakistan. Exploratory factor analysis, confirmatory factor analysis, and structural equation modelling validated hypothesised relationships.
Results:
Model depicted a strong, positive effect of TA on ABEU (β = 0.65, p < 0.001), indicating acceptance led to sustained use of mHealth. Based on β ≥ 0.50 for acceptance and engagement, Social image boost, Confidence boost, Better health through app use, and Doctors' recommendations were important cultural factors. Satisfaction, Better sugar levels, Confidence in App use, Search and download ability, and Easy access to reliable information were critical contextual factors. Better health facilities, Time-saving, and Internet speed and connectivity were key infrastructural factors. Improved health facilities, faster internet speeds, and reliable connectivity were boosted through users' confidence and enhanced self-image, encouraging them to engage, supported by increased satisfaction and perceived health benefits.
Conclusion:
TA significantly impacted ABEU through contextual, cultural and infrastructural factors in mHealth adoption, underscoring the need for actionable insights to improve mHealth adoption and retention.
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