Exploring Technology Acceptance Models: A Systematic Review of Health Application Adoption in Asian Countries - Damanik, Ferina Septiani; Widayanti, Anna Wahyuni; Wiedyaningsih, Chairun (Faculty of Pharmacy, Universitas Gadjah Mada, 2025)
Background: Health applications are a crucial technological advancement in healthcare, enhancing service quality and access to essential information. Despite this, challenges in implementation and user adaptation remain. Evaluating these applications is vital, and the Technology Acceptance Model (TAM) provides a dependable framework for assessing user acceptance and meeting its intended goals.Objectives: This review aims to explore the use of the TAM method for evaluating health applications adoption in Asia, focusing on ease of use, usefulness, user attitudes, and factors affecting technology acceptance.Methods: The method used is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles were gathered using PubMed and ScienceDirect employing Boolean search terms. The search focuses on technology acceptance and health applications, combined with the names of Asian countries. Eligible studies must describe the technology acceptance model of a health application in Asia. Quality assessment is performed using JBI and data are systematically extracted and analyzed.Results: A total of 11 original articles meet the inclusion criteria from 2428 articles. TAM plays a pivotal role in understanding the adoption of healthcare technology in Asia. TAM original constructs are widely used, with some integrating additional factors. Continued integration and modification of TAM will enhance its utility in addressing evolving healthcare challenges, ultimately improving healthcare outcomes across diverse user settings. TAM's adaptability and integration with theories like PMT and SUS improve its relevance across various healthcare settings and user contexts.Conclusion: Future research should mitigate biases, employ longitudinal and comparative analyses, and integrate TAM with complementary theories to advance healthcare technology adoption.