Investigating m-Health Acceptance from a Protection Motivation Theory Perspective: Gender and Age Differences.
BACKGROUND
Mobile health (m-health) services are becoming increasingly important and widely accepted. However, empirical studies on potential users' m-health acceptance behavior remain underexplored. Indeed, m-health adoption is not only a technology acceptance behavior, but also a health-related behavior.


METHODS
Based on the Protection Motivation Theory, this article explores users' m-health adoption behavior from the perspectives of threat appraisal and coping appraisal, and also examines the moderating role of gender and age through a survey of potential users. The survey was conducted among 500 potential m-health service participants.


RESULTS
Our results show that threat appraisal and coping appraisal factors influence adoption intention through attitude. It is also found that gender and age play different moderating roles with threat appraisal and coping appraisal factors.


CONCLUSIONS
Gender and age play different roles between threat appraisal and coping appraisal factors in the acceptance of m-health. Implications for research and practice are discussed.
1 e-Health Research Institute, School of Management, Harbin Institute of Technology , Harbin, China .
Xitong
X
Guo
1 e-Health Research Institute, School of Management, Harbin Institute of Technology , Harbin, China .
Xiaocui
X
Han
1 e-Health Research Institute, School of Management, Harbin Institute of Technology , Harbin, China .
Xiaofei
X
Zhang
1 e-Health Research Institute, School of Management, Harbin Institute of Technology , Harbin, China .
Yuanyuan
Y
Dang
2 Xingyi People's Hospital , Xingyi, China .
Chun
C
Chen
D000223:Adaptation, Psychological; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D001292:Attitude to Computers; D005260:Female; D006801:Humans; D033182:Intention; D008297:Male; D008875:Middle Aged; D009042:Motivation; D010342:Patient Acceptance of Health Care; D012737:Sex Factors; D017216:Telemedicine / Q000706:statistics & numerical data*
Protection Motivation Theory; age differences; coping appraisal; gender differences; mobile health; threat appraisal