The role of trust and habit in the adoption of mHealth by older adults in Hong Kong: a healthcare technology service acceptance (HTSA) model

Abstract

Background Evidence from the literature suggests that mobile health (mHealth) services can potentially improve healthcare outcomes among older adults. Hence, the government of Hong Kong has recently taken several community and information technology (IT) services initiatives to train older adults on how to enhance their abilities and interest in using mHealth technology. Although mHealth services have been widely implemented globally, their adoption and use by older adults are very low, including those in Hong Kong. This study aims to understand key factors influencing mHealth use intention among the older Chinese population in Hong Kong. Methods We extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) as the basis of our conceptual framework. We applied Partial Least Squares path modeling method to conduct the Structural Equation Model (SEM) technique that allows measuring the theoretical validity of any conceptual framework. Convenience and snowball sampling methods were used to recruit participants aged 65 or above. In total, 201 valid responses were used for testing the theoretical validity of the proposed conceptual framework. Results The primary finding shows that the widely used UTAUT2 model falls short in explaining mHealth service acceptance behavior in the Chinese older population in Hong Kong. We further propose a simplified model, the Healthcare Technology Service Acceptance (HTSA) model, to understand the formation of mHealth service acceptance behavior. The findings show that trust is an important component of technology service acceptance intention behavior that was missing in the UTAUT2 model. The results also show that several antecedent factors (i.e., social influence, government policy, and service quality) are critical in forming technology trust beliefs. Conclusions The study shows that the HTSA model can better explain mHealth acceptance behavior than the UTAUT2 model. This study advances knowledge in the mHealth technology adoption domain by proposing a simplified new version of the UTAUT2 model for understanding healthcare technology service acceptance and use intention among older adults. The findings of the study provide valuable information to the Hong Kong government and healthcare organizations for wider adoption of mHealth services, especially in older adults.

Application and Challenges of the Technology Acceptance Model in Elderly Healthcare: Insights from ChatGPT

“…Positive attitudes toward using technology are likely to enhance acceptance and adoption among the elderly. [1,5,7,16,[25][26][27][28][29][30] Behavioral Intention to Use (BI):…”

“…Behavioral intention reflects their readiness to adopt the technology for managing their healthcare needs. [7,25,27,31] Subjective Norms (SN):…”

“…Elderly users may hesitate to adopt healthcare technologies if they perceive them as unreliable or if there are doubts about the trustworthiness of the technology providers. [8,27,30,70,71] Lack of Tailored Interventions:…”

“…Parallelly, Perceived Ease of Use (PEOU) assumes significance, gauging the elderly individuals' belief in the technology being user-friendly and effortlessly navigable [8,[14][15][16]24,25,[81][82][83][84]. Attitude Toward Using (ATU) encapsulates their overall evaluation of adopting specific healthcare technologies, where positive attitudes significantly influence acceptance [1,5,7,16,[25][26][27][28][29][30]. Behavioral Intention to Use (BI) delves into the expressed willingness of the elderly to embrace these technologies in the future, underscoring their readiness to manage healthcare needs digitally [7,25,27,31].…”

Data-driven approach to quantify trust in medical devices using Bayesian networks

“…In addition to technical advances, trust in WMD is essential for their continued acceptance and adoption by patients, health professionals, and institutions. 1 Trust depends on multiple factors, including sensor accuracy, 2,3 device security, 4,5 data privacy, 6,7 and reliable collection through several layers and units of a WMD by the network of sensors. 8,9 If the data generated by WMD cannot be trusted, it could jeopardize the trustworthiness of the entire system.…”