nach oben

Journal of Medical Systems

Erschienen in:

01.06.2012 | ORIGINAL PAPER

Engagement in E-Learning Opportunities: An Empirical Study on Patient Education using Expectation Confirmation Theory

verfasst von: Hsin-Kai Chou, I-Chun Lin, Lin-Chung Woung, Ming-Tsu Tsai

Erschienen in: Journal of Medical Systems | Ausgabe 3/2012

Einloggen, um Zugang zu erhalten

Abstract

Medical e-learning technology is widely employed to create an online platform for patients and healthcare providers alike. However, there are few studies that have investigated the reasons why some users reject e-learning technology usage after their initial experience. This study was conducted with the aim to better understand the factors leading to patients’ continued usage of e-learning technologies. The theoretical foundation was based on the expectation-confirmation theory (ECT). The questionnaire survey was conducted during a two-month period and covered a total sample of 281 outpatients in a regional-teaching hospital. We found that the intention to continue e-learning usage was significantly related to patients’ education level, expectation, perceived performance, confirmation and satisfaction. The use of this ECT model may provide administrators in the healthcare industry insights into the implementation of e-learning technologies. This research also opens up a new direction and enhances the completeness of related researches in the fields of medical informatics and health education.

Nur mit Berechtigung zugänglich

Whitehead, D., Health promotion and health education viewed as symbiotic paradigms: Bridging the theory and practice gap between them. J. Clin. Nurs. 12:796–805, 2003.CrossRef

Whitehead, D., Health promotion and health education: Advancing the concepts. J. Adv. Nurs. 47(3):311–320, 2004.MathSciNetCrossRef

Department of Health, The NHS Plan: A Plan for Investment, A Plan for Reform. The Stationery Office, London, 2000.

Department of Health, Working Together, Learning Together: a Framework for Lifelong Learning for the NHS. The Stationery Office, London, 2001.

Reis, J., McGinty, B., and Jones, S., An e-learning caregiving program for prostate cancer patients and family members. J. Med. Syst. 27(1):1–12, 2003.CrossRef

Chen, C. Y., Chang, R. E., Hung, M. C., and Lin, M. H., Assessing the quality of a web-based learning system for nurses. J. Med. Syst. 33(4):317–325, 2009.CrossRef

Yazici, A., Karakaya, Z., Dalgarno, B., et al., Changing our educational institutions: transition from traditional to e-learning programs. information technology based higher education and training, ITHET 2004. Proceedings of the Fifth International Conference. 121–24. 2004.

Yan, Z. Z., Yan, Z. Q., Chiang, M. H., and Chiang, E. J., The new storm of healthcare knowledge base. LinkMed Asia, Taipei, 2002.

Zhang, D., Zhao, J. L., Zhou, L., et al., Can e-Learning replace classroom earning. Commun. ACM 47:75–79, 2004.CrossRef

10.

Joint Healthcare Information Technology Alliance, Issue summary: e-health. [Public Policy Committee online report]. http://www.jhita.org/ehealth.htm. 2000.

11.

Austin, C. J., Information technology and the future of health service delivery. Hosp. Health Serv. Adm. 34(2):157–165, 1989.MathSciNet

12.

Kerwin, K. E., The role of the internet in improving healthcare quality. J. Healthc. Manage. 47(4):225–236, 2002.

13.

Houston, R. K., Cooper, L. A., Vu, H. T., Kahn, J., Toser, J., and Ford, D., Screening the public for depression through the internet. Psychiatr. Serv. 52(3):362–367, 2001.CrossRef

14.

Limayem, M., and Hirt, S. G., Force of habit and information systems usage: Theory and initial validation. J. Assoc. Inf. Syst. 4, Article 3, 2003.

15.

Nelson, A. E., E-learning: A practical solution for training and tracking in patient-care settings. Nurs. Adm. Q. 27(1):29–32, 2003.

16.

Farrell, M., Learning differently: E learning in nurse education. Nurs. Manage. 13(6):14, 2006.

17.

Gao, M. J., Application of e-learning to continuing medical education. Taiwan Med. J. 45:32–33, 2002.

18.

Mehanna, W. N., E-learning: Principles and tools. Health Inf. Internet 51:5, 2006.

19.

Pratt, R., Pellowe, C., Adams, J., and Loveday, H., Beating the bug. Nurs. Manage. 12(10):24, 2006.

20.

Harden, R. M., Trends and the future of postgraduate medical education. Emerg. Med. J. 23:798–802, 2006.CrossRef

21.

Wakefield, A. B., The expectations and experiences of blended learning approaches to patient safety education. Nurse Educ. Pract. 8:54–61, 2008.CrossRef

22.

Heetebry, I., Hatcher, M., and Tabriziani, H., Web based health education. E-learning for weight management. J. Med. Syst. 29(6):611–617, 2005.CrossRef

23.

Divanis, G., E-Learning and the NHS. Br. J. Healthcare Comput., Inf. Manage. 23(2):31–33, 2006.

24.

Oliver, R. L., A cognitive model for the antecedents and consequences of satisfaction. J. Mark. Res. 17:460–469, 1980.CrossRef

25.

Dabolkar, P. A., Shepard, C. D., and Thorpe, D. I., A comprehensive framework for service quality: An investigation of critical conceptual and measurement issues through a longitudinal study. J. Retail. 76(2):139–173, 2000.CrossRef

26.

Anderson, E. W., and Sullivan, M. W., The antecedents and consequences of customer satisfaction for firms. Mark. Sci. 12(2):125–143, 1993.CrossRef

27.

Oliver, R. L., Cognitive, affective, and attribute bases of the satisfaction response. J. Consum. Res. 20:418–430, 1993.CrossRef

28.

Patterson, P. G., Johnson, L. W., and Spreng, R. A., Modeling the determinants of customer satisfaction for business-to-business professional services. J. Acad. Mark. Sci. 25(1):4–17, 1997.CrossRef

29.

Spreng, R. A., MacKenzie, S. B., and Olshavsky, R. W., A reexamination of the determinants of consumer satisfaction. J. Mark. 60:15–32, 1996.CrossRef

30.

Bhattacherjee, A., Understanding information systems continuance: An expectation-confirmation model. MIS Q. 25(3):351–370, 2001.CrossRef

31.

Hsu, M. H., Chiu, C. M., and Ju, T. L., Determinants of continued use of the WWW: An integration of two theoretical models. Ind. Manage. Data Syst. 104(9):766, 2004.CrossRef

32.

McKinney, V., Yoon, K., and Zahedi, F., The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Inf. Syst. Res. 13(3):296, 2002.CrossRef

33.

Davis, F. D., Bagozzi, R. P., and Warshaw, P. R., User acceptance of computer technology: A comparison of two theoretical models. Manage. Sci. 35(8):982–1003, 1989.CrossRef

34.

Wang, C., Hsu, Y., and Fang, W., Acceptance of technology with network externalities: An empirical study of internet instant messaging services. JITTA 6(4):15–28, 2004.

35.

Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., and Pahnila, S., Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Res. 14(3):224–235, 2004.CrossRef

36.

Hsu, C. L., and Lin, J. C., Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Inf. Manage. 45:65–74, 2008.CrossRef

37.

Hsu, C. L., and Lu, H. P., Consumer behavior in on-line game communities: A motivational factor perspective. Comput. Hum. Behav. 23:1642–1659, 2007.CrossRef

38.

DeLone, W. H., and McLean, E. R., The DeLone and McLean model of information systems success: A ten-year update. J. Manage. Inf. Syst. 19(4):9–30, 2003.

39.

Bharati, P., and Chaudhury, A., An empirical investigation of decision-making satisfaction in web-based decision support systems. Decis. Support Syst. 37(2):187–197, 2004.CrossRef

40.

Kulkarni, U. R., Ravindran, S., and Freeze, R., A knowledge management success model: Theoretical development and empirical validation. J. Manage. Inf. Syst. 23(3):309–347, 2006.CrossRef

41.

National Science and Technology Program for e-Learning. Department of Health. URL http://elnpweb.ncu.edu.tw/english/english2.htm. 2005.

42.

Child, S., Blenkinsopp, E., Hall, A., and Walton, G., Effective e-learning for health professions and students- barriers and their solutions. A systematic review of the literature- finds from the HeXL project. Health Inf. Libr. J. 22(Suppl.2):20–32, 2005.CrossRef

43.

Docherty, A., and Sandhu, H., Student-perceived barriers and facilitators to e-learning in continuing professional development in primary care. Educ. Prim. Care 17:343–353, 2006.

44.

Bhattacherjee, A., An empirical analysis of the antecedents of electronic commerce service continuance. Decis. Support Syst. 32(2):201–214, 2001.CrossRef

45.

Davis, F. D., and Venkatesh, V., Toward preprototype user acceptance testing of new information systems implications for software project management. IEEE Trans. Eng. Manage. 51(1):31–46, 2004.CrossRef

46.

Thiele, J. E., Allen, C., and Stucky, M., Effects of web-based instruction on learning behaviors of undergraduate and graduate students. Nurs. Health Care Perspect. 20:199–203, 1999.

47.

Clark, D., Psychological myths in e-learning. Med. Teach. 24:598–604, 2002.CrossRef

48.

Turchin, A., and Lehmann, C. U., Active learning centre: utilization patterns of an interactive educational world wide web site. Proceedings of the AMIA Symposium. 627–37, 1999.

49.

DeLone, W. H., and McLean, E. R., Information systems success: The quest for the dependent variable. Inf. Syst. Res. 3(1):60–95, 1992.CrossRef

50.

DeLone, W. H., and McLean, E. R., The DeLone and McLean model of information systems success: A ten-year update. J. Manage. Inf. Syst. 19(4):9–30, 2003.

51.

Rai, A., Lang, S. S., and Welker, R. B., Assessing the validity of IS success models: An empirical test and theoretical analysis. Inf. Syst. Res. 13(1):50–69, 2002.CrossRef

52.

Bolton, R. N., and Lemon, K. N., A dynamic model of customers’ usage of services: Usage as an antecedent and consequence of satisfaction. J. Mark. Res. 36(5):171–186, 1999.CrossRef

53.

Harrold, M. W., and Newton, G. D., Development and evaluation of computer-based tutorials in biochemistry and medicine chemistry. Am. J. Pharm. Educ. 62:24–30, 1998.

54.

Morris, D., E-learning in the common learning curriculum for health and social care professionals. Health Inf. Libr. J. 22(Suppl.2):66–88, 2005.

55.

Straub, D., Limayem, M., and Karahanna, E., Measuring system usage: Implications for IS theory testing. Manage. Sci. 41(8):1328–1342, 1995.CrossRef

Titel: Engagement in E-Learning Opportunities: An Empirical Study on Patient Education using Expectation Confirmation Theory
verfasst von: Hsin-Kai Chou
I-Chun Lin
Lin-Chung Woung
Ming-Tsu Tsai
Publikationsdatum: 01.06.2012
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 3/2012
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-010-9630-9

Springer Medizin

Abstract

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 3/2012

Design and Evaluation of a Service Oriented Architecture for Paperless ICU Tarification

Using Recommendation to Support Adaptive Clinical Pathways

Automated Diagnosis of Diabetes Using Heart Rate Variability Signals

Singular Value Decomposition Based Feature Extraction Technique for Physiological Signal Analysis

Economic and Quality Scheduling for Effective Utilization of Operating Rooms

Automatic Detection of the Existence of Subarachnoid Hemorrhage from Clinical CT Images