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Effect of HPM Factors on Adoption Attitude of u-Health System: Moderating Effects of Gender

u-Health 시스템의 수용 태도에 대한 건강증진모형의 요인 영향: 남·녀 조절효과 중심

  • Yang, Youngbae (Dept. of Management Information Systems, Jeju National University) ;
  • Kim, Mincheol (Dept. of Management Information Systems, Jeju National University)
  • 양영배 (제주대학교 경영정보학과) ;
  • 김민철 (제주대학교 경영정보학과)
  • Received : 2015.04.28
  • Accepted : 2015.07.20
  • Published : 2015.07.28

Abstract

The aim of this study is to find the factors affecting attitude on u-health system using Pender's Health Promotion Model (HPM) and also, analyze the moderating effect of gender variable in research model. To assess the proposed research model based on HPM, this study adopted Partial Least Square (PLS) method using Smartpls 2.0 version for the evaluation of research model. Thus, this study used survey questionnaire in order to collect useful data to potential users of u-health system. As a result of analysis, the examined variables explain 29% of variance on attitude to use of the u-health system. According to the PLS analysis, self efficacy and perceived benefits showed significantly positive relationship on attitude to use of u-health system. In addition, on the moderating effect of gender variable, female had more interest on self efficacy for positive attitude on use of u-health system.

본 연구의 목적은 Pender의 건강증진모형(HPM)을 활용하여 유헬스 시스템에 대한 태도에 영향을 미치는 요인들을 찾는데 있고, 또한 제시된 연구 모형에서 성별 변수의 조절 효과를 분석하는데 있다. 이러한 건강증진모형에 근거하여 제시된 연구모형을 평가하기 위하여, 본 연구는 Smartpls 버전 2.0을 활용하여 부분최소자승법(PLS) 방법을 적용하였다. 따라서 본 연구는 잠재적 사용자들에게 유용한 데이터를 수집하기 위하여 설문조사를 실시하였다. 분석 결과, 연구모형에서 유헬스 시스템의 사용 태도에 대해 29% 정도의 설명력을 보여주었고, 경로에서 자기 효능감과 인지된 이점이 그 태도에서 유의한 통계적 관계를 나타냈다. 그리고 성별 변수의 조절 효과와 관련하여, 유헬스 시스템의 사용태도 측면에서 자기 효능감을 높일수록 여성이 남성보다 더 높은 관심을 가짐을 알 수 있었다.

Keywords

References

  1. Korea Electronic Communication Institute, Study on the Korean Health Project typed and market forecasting, 2005.
  2. National Information Society Agency, Introduction of smart public health services, IT Policy Research Series, 2011.
  3. Kang, S. U. & Kim, J. Y., Economic Effect and Growth Strategy of u-Health. Samsung Economic Research Institute Research Report, 2007.
  4. Kang, S. W., Kim, J. Y., Economic impact and growth strategy of u-Health, Seri Research Report, 2007.
  5. Park, G. S., Research on Utilizing U-Health to Provide Telehealthcare to the Elderly in Rural Areas, e-Business Trade, 13(1), 2012.
  6. Kim, K, H., Market analysis and institutional maintenance plan of Korea U-health industry, The e-Business Studies, 14(2), 3-24, 2013.
  7. National Information Society Agency, Introduction of smart public health services, IT Policy Research Series, 2011.
  8. Kim, G. D. & Song, I. K., u-healthcare service needs and develop plan, Korean Society for internet Information, 10(3), 9-17, 2009.
  9. Daegu Regional Innovation Agency, 2007.
  10. Medical Observer, 2007.
  11. Ministry for Health and Welfare, 2008.
  12. Pender, N. J. Health Promotion in Nursing Practice, 2nd Edition, Appleton and Lange Stamford, Connecticut, 1987.
  13. Baek, Y. M. Prediction Model of White-collar Male Workers Health Promotion Act. Doctoral Dissertation, Graduate School, Ehaw Woman's University, 2005.
  14. Choe, Y. H., A Study of Supportive Nursing Mediation that Influences on Family Support Act and Patient Role Act. Doctoral Dissertation, Graduate School, Yonsei University, 1984.
  15. Pender, N. J. The Health-Promoting lifestyle profile: Development and Psychometric characteristics. Nursing research, 1987.
  16. Pender, N. J. Health Promotion in Nursing Practice, 3rd. ed, Appleton and Lange Stanford, Connecticut, 1996.
  17. Okazaki, S. & Mendez, F., Exploring convenience in mobile commerce: Moderating effects of gender. Computers in Human Behavior 29, 1234-1242, 2013. https://doi.org/10.1016/j.chb.2012.10.019
  18. Todman, J. & Day, K., Computer anxiety: The role of psychological gender. Computers in Human Behavior 22(5), 856-869, 2006. https://doi.org/10.1016/j.chb.2004.03.009
  19. Venkatesh, V. & Morris, M. G., Why do not men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly 24(1), 115-139, 2000. https://doi.org/10.2307/3250981
  20. Yang, B. & Lester, D., Gender differences in e-commerce. Applied Economics 37, 2077-2089, 2005. https://doi.org/10.1080/00036840500293292
  21. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. Multivariate dataan alysis(5thed.). Upper Saddle River, NJ: Prentice Hall, 1998.
  22. Chin, W. W., The partialleast squares approach for structure ale quation modeling in Modern Methods for Business Research, George A. Marcoulides(ed.), Lawrence Erbaum Associates, NewYork, 295-336, 1998.
  23. Fornell, C., & Bookstein, F. L. Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440-452, 1982. https://doi.org/10.2307/3151718
  24. Hair, J. F., Ringle, C. M., & Sarstedt, M., PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139-151, 2011. https://doi.org/10.2753/MTP1069-6679190202
  25. Yang, Y. B., & Kim, M., A Study on Behavioral Intention on u-Health using Health Promotion Model, Journal of the Korea Institute of Information and Communication Engineering, 19(3), 747-755, 2015. https://doi.org/10.6109/jkiice.2015.19.3.747