Abstract:
This study examined the behavioral determinants influencing digital healthcare adoption in Pakistan by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT-3) with Perceived Risk Theory. Data were obtained from 300 urban participants residing in Karachi, Lahore, and Islamabad using a non-random convenience sampling method. The research model tested 13 independent constructs to predict behavioral intention to use (BIU), adopt (BIA), and recommend (BIR). The findings provide a perspective on understanding behavioral intention, highlighting the influence of habits, performance expectancy, and privacy concerns. Habit was the strongest positive predictor of digital health engagement, followed by social influence, and performance expectancy. Perceived privacy risk emerged as the main negative influence, reflecting concerns regarding data security. Effort expectancy, hedonic motivation, and facilitating conditions were statistically insignificant, suggesting that functional expectations and trust override usability in this context. This study validates an integrated UTAUT-3 and Perceived Risk model in a low-trust, technology-transitioning environment. These findings emphasize the need to design privacy-focused platforms with habit-forming features and engage healthcare influencers to enhance social acceptance. Although the urban-centric design limits generalizability, the findings provide insights for policymakers and developers aiming to foster digital health ecosystems in Pakistan and emerging markets.
