FACTORS ASSOCIATED WITH HA GO ADOPTION: A POPULATION-BASED STUDY...
Author(s)
Junjie Huang, PhD, Chenwen Zhong, PhD, Martin Chi Sang Wong, MD.
The Chinese University of Hong Kong, Hong Kong SAR, China.
The Chinese University of Hong Kong, Hong Kong SAR, China.
OBJECTIVES: HA Go is a comprehensive one-stop healthcare platform designed to improve patients' healthcare journey and support self-management. This study aims to explore public perceptions of HA Go and identify factors associated with its download and usage.
METHODS: A cross-sectional study was conducted among Hong Kong residents aged 18 years or older. Participants completed an online questionnaire collecting socio-demographic data, self-reported health status, and attitudes and perceptions regarding HA Go. Chi-square tests were used to examine differences between users and non-users. Univariable and multivariable logistic regression models were performed to identify factors significantly associated with HA Go usage.
RESULTS: A total of 1,100 participants were included (535 males, 564 females). Of these, 672 (61.1%) reported using HA Go. The most commonly cited facilitators for downloading or using the app were its record management and health management features. Key barriers included misconceptions about doctors' familiarity with personal records, lack of recommendations to use the app, and concerns about data privacy. Participants also emphasized the importance of improving privacy and security, enhancing patient engagement, and increasing public awareness to promote HA Go adoption. Multivariable logistic regression showed that HA Go usage was positively associated with older age, having both voluntary and private health insurance, self-reported poor health, having chronic diseases, perceiving a higher level of facilitators, and perceiving a lower level of barriers.
CONCLUSIONS: This study highlights that HA Go is widely adopted among Hong Kong residents, particularly those who are older, have chronic conditions, or perceive greater benefits and fewer barriers to its use. To further enhance uptake and user experience, targeted efforts to improve privacy protections, promote patient engagement, and raise public awareness are essential.
METHODS: A cross-sectional study was conducted among Hong Kong residents aged 18 years or older. Participants completed an online questionnaire collecting socio-demographic data, self-reported health status, and attitudes and perceptions regarding HA Go. Chi-square tests were used to examine differences between users and non-users. Univariable and multivariable logistic regression models were performed to identify factors significantly associated with HA Go usage.
RESULTS: A total of 1,100 participants were included (535 males, 564 females). Of these, 672 (61.1%) reported using HA Go. The most commonly cited facilitators for downloading or using the app were its record management and health management features. Key barriers included misconceptions about doctors' familiarity with personal records, lack of recommendations to use the app, and concerns about data privacy. Participants also emphasized the importance of improving privacy and security, enhancing patient engagement, and increasing public awareness to promote HA Go adoption. Multivariable logistic regression showed that HA Go usage was positively associated with older age, having both voluntary and private health insurance, self-reported poor health, having chronic diseases, perceiving a higher level of facilitators, and perceiving a lower level of barriers.
CONCLUSIONS: This study highlights that HA Go is widely adopted among Hong Kong residents, particularly those who are older, have chronic conditions, or perceive greater benefits and fewer barriers to its use. To further enhance uptake and user experience, targeted efforts to improve privacy protections, promote patient engagement, and raise public awareness are essential.
Conference/Value in Health Info
2026-09, ISPOR Asia Pacific 2026, Bangkok, Thailand
Value in Health, Volume 55, Issue S1
Code
MT1
Topic
Medical Technologies
Topic Subcategory
Digital Health
Disease
No Additional Disease & Conditions/Specialized Treatment Areas