The Conceptualization of Integrated Consumer Health Informatics Utilization Framework
The purpose of this paper is to propose an integrated
consumer health informatics utilization framework that can be used
to gauge the online health information needs and usage patterns
among Malaysian women. The proposed framework was developed
based on four different theories/models: Use and Gratification
Theory, Technology Acceptance 3 Model, Health Belief Model, and
Multi-level Model of Information Seeking. The relevant constructs
and research hypotheses are also presented in this paper. The
framework will be tested in order for it to be used successfully to
identify Malaysian women-s preferences of online health information
resources and health information seeking activities.
[1] Eysenbach G. Consumer health informatics. BMJ 24; 320(7251): 1713-
1716, June 2000.
[2] Shortliffe EH, Perrault L. Medical informatics: Computer applications
in health care. Reading, MA: Addison-Wesley, 1990.
[3] Moorman C, Matulich E. A model of consumers- preventive health
behaviors: The role of health motivation and health ability. J Consum
Res; 20: pp. 208-28, 1993.
[4] Pasinlioglu T. Health education for pregnant women: The role of
background characteristics. Patient Educ Couns; 53:101-6, 2003.
[5] Wiltshire J, Cronin K, Sarto GE, Brown R. Self-advocacy during the
medical encounter: Use of health information and racial/ethnic
differences. Med Care; 44: pp. 100-9, 2006.
[6] Gilmour, J. A. Reducing disparities in the access and use of Internet
health information. A discussion paper. International Journal of Nursing
Studies, 44, pp. 1270-1278, 2007.
[7] Lemire, M., Sicotte, C. & Pare, G. Internet use and the logics of
personal empowerment in health. Health Policy, 88, pp. 130-140, 2008.
[8] Marton, C. Understanding how women seek health information on the
web. PhD thesis. University of Toronto, Toronto. Available at:
http://hdl.handle.net/1807/29808 (accessed 1 December 2011), 2011.
[9] Yun, E. K. & Park, H.-A. Consumers- disease information-seeking
behavior on the Internet in Korea. Journal of Clinical Nursing, 19, pp.
2860-2868, 2010.
[10] Davis, F. D. Perceived usefulness, perceived ease of use, and user
acceptance of information technology. MIS Quarterly 13(3): 319-340,
1989.
[11] Rosenstock, I. Historical origins of the health belief model. Health
Education Monographs. Vol. 2 No. 4, 1974.
[12] Katz, E., Blumler, J. G., & Gurevitch, M. Ulilization of mass
communication by the individual. In J. G. Blumler, & E. Katz (Eds.).
The uses of mass communications: Current perspectives on
gratifications research. Beverly Hills: Sage. pp. 19-32, 1974.
[13] Venkatesh, V. Bala, H. Technology acceptance model 3 and a research
agenda on interventions. Decision Sciences 39(2): pp. 273-315, 2008.
[14] Venkatesh, V.,Morris, M. G., Davis, G. B., Davis, F. D. User
acceptance of information technology: Toward a unified view. MIS
Quarterly 27(3): pp. 425-478, 2003.
[15] Hung, P. W., Johnson, S. B., Kaufman, D. R. & Mendonça, E. A. A
multi-level model of information seeking in the clinical domain. Journal
of Biomedical Informatics, 41, pp. 357-370, 2008.
[16] Stretcher V. J., and Rosenstock I. M. The health belief model. In Health
Behavior and Health Education: Theory, Research, and Practice, 2nd ed.
San Francisco: Jossey-Bass. pp. 41-59, 1997.
[17] Ajzen, I. The theory of planned behavior. Organizational Behavior and
Human Decision Processes, 50, pp. 179-211, 1991.
[18] Yoo, E.-Y. & Robbins, L. S. Understanding middle-aged women's
health information seeking on the web: A theoretical approach. Journal
of the American Society for Information Science and Technology, 59,
pp. 577-590, 2008.
[19] Norris, P. Digital divide: Civic engagement, information poverty and the
internet worldwide. Cambridge, 2001.
[20] Hardiker, N. R. & Grant, M. J. Factors that influence public engagement
with eHealth: A literature review. International Journal of Medical
Informatics, 80, pp. 1-12, 2011.
[21] Griffiths, K.M. Christensen, H. Website quality indicators for
consumers. Journal of Medical Internet Research Vol 7 (5), pp. 1-11,
2005.
[22] Cappel, J. J. & Huang, Z. A usability analysis of company websites. The
Journal of Computer Information Systems, vol 48, no. 1, pp. 117-123,
2007.
[23] Pan, Y. & Zinkhan, G. M. Exploring the impact of online privacy
disclosures on consumer trust. Journal of Retailing, 82, pp. 331-338,
2006.
[24] O-Grady, L. Future directions for depicting credibility in health care
web sites. International Journal of Medical Informatics, 75, pp. 58-65,
2006.
[25] Pak, R., Price, M., and Thatcher, J.B. Age-sensitive design of online
health information: Comparative usability study. Journal of Medical
Internet Research. 11(4): e45, 2009.
[1] Eysenbach G. Consumer health informatics. BMJ 24; 320(7251): 1713-
1716, June 2000.
[2] Shortliffe EH, Perrault L. Medical informatics: Computer applications
in health care. Reading, MA: Addison-Wesley, 1990.
[3] Moorman C, Matulich E. A model of consumers- preventive health
behaviors: The role of health motivation and health ability. J Consum
Res; 20: pp. 208-28, 1993.
[4] Pasinlioglu T. Health education for pregnant women: The role of
background characteristics. Patient Educ Couns; 53:101-6, 2003.
[5] Wiltshire J, Cronin K, Sarto GE, Brown R. Self-advocacy during the
medical encounter: Use of health information and racial/ethnic
differences. Med Care; 44: pp. 100-9, 2006.
[6] Gilmour, J. A. Reducing disparities in the access and use of Internet
health information. A discussion paper. International Journal of Nursing
Studies, 44, pp. 1270-1278, 2007.
[7] Lemire, M., Sicotte, C. & Pare, G. Internet use and the logics of
personal empowerment in health. Health Policy, 88, pp. 130-140, 2008.
[8] Marton, C. Understanding how women seek health information on the
web. PhD thesis. University of Toronto, Toronto. Available at:
http://hdl.handle.net/1807/29808 (accessed 1 December 2011), 2011.
[9] Yun, E. K. & Park, H.-A. Consumers- disease information-seeking
behavior on the Internet in Korea. Journal of Clinical Nursing, 19, pp.
2860-2868, 2010.
[10] Davis, F. D. Perceived usefulness, perceived ease of use, and user
acceptance of information technology. MIS Quarterly 13(3): 319-340,
1989.
[11] Rosenstock, I. Historical origins of the health belief model. Health
Education Monographs. Vol. 2 No. 4, 1974.
[12] Katz, E., Blumler, J. G., & Gurevitch, M. Ulilization of mass
communication by the individual. In J. G. Blumler, & E. Katz (Eds.).
The uses of mass communications: Current perspectives on
gratifications research. Beverly Hills: Sage. pp. 19-32, 1974.
[13] Venkatesh, V. Bala, H. Technology acceptance model 3 and a research
agenda on interventions. Decision Sciences 39(2): pp. 273-315, 2008.
[14] Venkatesh, V.,Morris, M. G., Davis, G. B., Davis, F. D. User
acceptance of information technology: Toward a unified view. MIS
Quarterly 27(3): pp. 425-478, 2003.
[15] Hung, P. W., Johnson, S. B., Kaufman, D. R. & Mendonça, E. A. A
multi-level model of information seeking in the clinical domain. Journal
of Biomedical Informatics, 41, pp. 357-370, 2008.
[16] Stretcher V. J., and Rosenstock I. M. The health belief model. In Health
Behavior and Health Education: Theory, Research, and Practice, 2nd ed.
San Francisco: Jossey-Bass. pp. 41-59, 1997.
[17] Ajzen, I. The theory of planned behavior. Organizational Behavior and
Human Decision Processes, 50, pp. 179-211, 1991.
[18] Yoo, E.-Y. & Robbins, L. S. Understanding middle-aged women's
health information seeking on the web: A theoretical approach. Journal
of the American Society for Information Science and Technology, 59,
pp. 577-590, 2008.
[19] Norris, P. Digital divide: Civic engagement, information poverty and the
internet worldwide. Cambridge, 2001.
[20] Hardiker, N. R. & Grant, M. J. Factors that influence public engagement
with eHealth: A literature review. International Journal of Medical
Informatics, 80, pp. 1-12, 2011.
[21] Griffiths, K.M. Christensen, H. Website quality indicators for
consumers. Journal of Medical Internet Research Vol 7 (5), pp. 1-11,
2005.
[22] Cappel, J. J. & Huang, Z. A usability analysis of company websites. The
Journal of Computer Information Systems, vol 48, no. 1, pp. 117-123,
2007.
[23] Pan, Y. & Zinkhan, G. M. Exploring the impact of online privacy
disclosures on consumer trust. Journal of Retailing, 82, pp. 331-338,
2006.
[24] O-Grady, L. Future directions for depicting credibility in health care
web sites. International Journal of Medical Informatics, 75, pp. 58-65,
2006.
[25] Pak, R., Price, M., and Thatcher, J.B. Age-sensitive design of online
health information: Comparative usability study. Journal of Medical
Internet Research. 11(4): e45, 2009.
@article{"International Journal of Business, Human and Social Sciences:58674", author = "Norfadzila and S.W.A. and Balakrishnan and V. and A. Abrizah", title = "The Conceptualization of Integrated Consumer Health Informatics Utilization Framework", abstract = "The purpose of this paper is to propose an integrated
consumer health informatics utilization framework that can be used
to gauge the online health information needs and usage patterns
among Malaysian women. The proposed framework was developed
based on four different theories/models: Use and Gratification
Theory, Technology Acceptance 3 Model, Health Belief Model, and
Multi-level Model of Information Seeking. The relevant constructs
and research hypotheses are also presented in this paper. The
framework will be tested in order for it to be used successfully to
identify Malaysian women-s preferences of online health information
resources and health information seeking activities.", keywords = "Consumer Health Informatics, Consumer
Preferences, Information Needs and Usage Patterns, Online Health
Information, Women Studies", volume = "6", number = "3", pages = "347-5", }
