Understanding public users' adoption of mobile health service

With the rapid development of mobile communication technology, the increase in the usage rate of mobile phones, recent advances in healthcare technology and current concerns arising over public health, mobile health has been attracting increasing attention. Although previous studies on the adoption of mobile services are quite extensive, few focus on public users' adoption of mobile health service MHS. In this study, we examine the determinants of user adoption of mobile health service based on the technology acceptance model TAM and health belief model HBM. We find that perceived usefulness and benefits, perceived barriers and external cues positively affect user attitude toward MHS. Likewise, perceived service availability significantly influences the perceived ease of use as well as perceived usefulness and benefits, which with attitude directly enhances intention. We also find that the usage purpose of MHS has moderating effects. Finally, implications for mobile health marketing are discussed.

[1]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[2]  Mark Shevlin,et al.  Testicular self-examination: a test of the health belief model and the theory of planned behaviour. , 2006, Health education research.

[3]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[4]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[5]  Zhaohua Deng,et al.  An empirical analysis of factors influencing users' adoption and use of mobile services in China , 2010, Int. J. Mob. Commun..

[6]  Saonee Sarker,et al.  Examining the success factors for mobile work in healthcare: A deductive study , 2009, Decis. Support Syst..

[7]  Jui-Chen Huang,et al.  Remote health monitoring adoption model based on artificial neural networks , 2010, Expert Syst. Appl..

[8]  James G Kahn,et al.  'Mobile' health needs and opportunities in developing countries. , 2010, Health affairs.

[9]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[10]  P D Mullen,et al.  A meta-analysis of studies of the Health Belief Model with adults. , 1992, Health education research.

[11]  Ritu Agarwal,et al.  Are Individual Differences Germane to the Acceptance of New Information Technologies , 1999 .

[12]  Henry Been-Lirn Duh,et al.  An exploratory study of ageing women's perception on access to health informatics via a mobile phone-based intervention , 2012, Int. J. Medical Informatics.

[13]  Shu-Ping Lin,et al.  Determinants of adoption of Mobile Healthcare Service , 2011, Int. J. Mob. Commun..

[14]  Richard J. Holden,et al.  The Technology Acceptance Model: Its past and its future in health care , 2010, J. Biomed. Informatics.

[15]  Eric Holmen.  TXTING4HEALTH: The Role of the Mobile Channel in the Health Care Industry and in the Sphere of Public Health , 2009 .

[16]  Jen-Her Wu,et al.  Mobile computing acceptance factors in the healthcare industry : A structural equation model , 2006 .

[17]  Paul Jen-Hwa Hu,et al.  Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories , 2002, Inf. Manag..

[18]  A. Giuffrida,et al.  Mobile Health: The Potential of Mobile Telephony to Bring Health Care to the Majority , 2009 .

[19]  Upkar Varshney,et al.  Pervasive Healthcare and Wireless Health Monitoring , 2007, Mob. Networks Appl..

[20]  Mihail Cocosila,et al.  Adoption of mobile ICT for health promotion: an empirical investigation , 2010, Electron. Mark..

[21]  Zhaohua Deng,et al.  Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China , 2010, Int. J. Inf. Manag..

[22]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[23]  I. Rosenstock.  Why people use health services. , 1966, The Milbank Memorial Fund quarterly.

[24]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[25]  Leo R. Vijayasarathy,et al.  Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model , 2004, Inf. Manag..

[26]  Charles Abraham,et al.  The health belief model , 2005 .

[27]  Kevin Patrick,et al.  Mobile health: the killer app for cyberinfrastructure and consumer health. , 2011, American journal of preventive medicine.

[28]  Henry Been-Lirn Duh,et al.  A study on Singaporean women's acceptance of using mobile phones to seek health information , 2011, Int. J. Medical Informatics.

[29]  A. Bandura.  Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychological review.

[30]  K. Glanz,et al.  Health Behavior and Health Education , 1990 .

[31]  Su-Chao Chang,et al.  An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry , 2008, Int. J. Medical Informatics.

[32]  C. Skinner,et al.  The health belief model. , 2008 .

[33]  Ming-Chien Hung,et al.  An empirical study of adopting mobile healthcare service: the family's perspective on the healthcare needs of their elderly members. , 2010, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[34]  Yan Xiao,et al.  A review and a framework of handheld computer adoption in healthcare , 2005, Int. J. Medical Informatics.

[35]  Vincent S. Lai,et al.  Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model , 2000, Decis. Support Syst..

[36]  Jørn Braa,et al.  DEVELOPING HEALTH INFORMATION SYSTEMS IN DEVELOPING COUNTRIES THE FLEXIBLE STANDARDS STRATEGY , 2006 .

[37]  José Manuel Ortega Egea,et al.  Explaining physicians' acceptance of EHCR systems: An extension of TAM with trust and risk factors , 2011, Comput. Hum. Behav..

[38]  Stephen Sutton,et al.  Predicting uptake of a routine cervical smear test: A comparison of the health belief model and the theory of planned behaviour , 2000 .

[39]  A. F. Salam,et al.  An extension of the technology acceptance model in an ERP implementation environment , 2004, Inf. Manag..

[40]  Fan-Yun Pai,et al.  Applying the Technology Acceptance Model to the introduction of healthcare information systems , 2011 .

[41]  Dag Svanæs,et al.  Mobile health IT: The effect of user interface and form factor on doctor-patient communication , 2012, Int. J. Medical Informatics.

[42]  M. Becker,et al.  The Health Belief Model: A Decade Later , 1984, Health education quarterly.

[43]  Ing-Long Wu,et al.  The adoption of mobile healthcare by hospital's professionals: An integrative perspective , 2011, Decis. Support Syst..

[44]  I. Rosenstock.  Historical Origins of the Health Belief Model , 1974 .

[45]  Melanie T Tucker,et al.  APPLICATION OF THE DIFFUSION OF INNOVATIONS THEORY AND THE HEALTH BELIEF MODEL TO DESCRIBE EMR USE AMONG ALABAMA FAMILY MEDICINE PHYSICIANS: A RURAL AND URBAN ANALYSIS , 2009 .

[46]  Rolph E. Anderson,et al.  Multivariate Data Analysis with Readings , 1979 .

[47]  Jeffrey J. Johnson,et al.  The adoption of computer security: an analysis of home personal computer user behavior using the health belief model , 2011 .

[48]  I. Rosenstock,et al.  Social Learning Theory and the Health Belief Model , 1988, Health education quarterly.