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Factors Influencing Intention to Use Smart-based Continuing Nurse Education

스마트 기술 기반 간호사 보수교육 프로그램 활용의도의 영향요인

  • Received : 2016.01.09
  • Accepted : 2016.02.19
  • Published : 2016.02.28

Abstract

Purpose: There is increasing attention to smart-learning as a new education paradigm. The purpose of this study was to identify the level of intention to use smart-based Continuing Nurse Education (CNE) and factors influencing intention to use smart-based CNE. Methods: Participants were 486 nurses from 14 organizations, including 12 hospitals, a nurses association, and an office of education. Data were collected from November 5 to 18, 2014 using self-report questionnaires. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation, and stepwise multiple regression. Results: The mean score for intention to use smart-based CNE was 6.34 out of 10. The factors influencing intention to use smart-based CNE were nursing informatics competency, current unit career, and smartphone addiction. These variables explained 10% of variance in intention to use smart-based CNE. Conclusion: The findings of this study suggest that efforts to enhance the nursing informatics competency of nurses could increase usage rate of smart-based CNE. The CNE policy makers will find this study very useful and the findings of this study will help to provide insight into the best way to develop smart-based CNE.

Keywords

References

  1. Ministry of Health and Welfare. A study on the actual condition of continuing education in healthcare professionals. Seoul: Ministry of Health and Welfare; 2013. Available from: http://www.prism.go.kr/homepage/researchCommon/retrieveResearchDetailPopup.do?research_id=1351000-201300214.
  2. Kwon S, Yun S. A study on the effect of e-learning characteristic on the adoption intention. Korea Society of Information Technology Applications. 2007;7(1):126-142.
  3. Lee J, Lee JK. Conceptualizing e-learning. Interdisciplinary Journal of Adult & Continuing Education. 2005;8(3):1-31.
  4. Noh KS, Ju SH, Jung JT. An exploratory study on concept and realization conditions of smart learning. Journal of Digital Convergence. 2011;9(2):79-88.
  5. Lim K. Research on developing instructional design models for enhancing smart learning. Journal of Korean Association of Computer Education. 2011;14(2):33-45.
  6. Gormley DK. Considerations when developing online continuing education programs in nursing. Journal for Nurses in Professional Development. 2013;29(3):149-151. http://dx.doi.org/10.1097/NND.0b013e318291c47d
  7. Kim MS, Park JH. Development of a drug dosage calculation learning smartphone application. Journal of the Korea Academia-Industrial Cooperation Society. 2013;14(5): 2251-2261. http://dx.doi.org/10.5762/KAIS.2013.14.5.2251
  8. Yoo IY, Lee YM. The effects of mobile applications in cardiopulmonary assessment education. Nurse Education Today. 2015;35(2):e19-e23. http://dx.doi.org/10.1016/j.nedt.2014.12.002
  9. Pyo MY, Kim JY, Sohn JO, Lee ES, Kim HS, Kim KO, et al. The effects of an advanced cardiac life support training via smartphone's simulation application on nurses' knowledge and learning satisfaction. Journal of Korean Clinical Nursing Research. 2012;18(2):228-238. https://doi.org/10.22650/JKCNR.2012.18.2.228
  10. Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: A comparison of two theoretical models. Management Science. 1989;35(8):982-1003. http://dx.doi.org/10.1287/mnsc.35.8.982
  11. Khanh NTV, Gim G. Factors influencing mobile-learning adoption intention: An empirical investigation in high education. Journal of Social Sciences. 2014;10(2):51-62. http://dx.doi.org/10.3844/jssp.2014.51.62
  12. Smith SE, Drake LE, Harris JGB, Watson K, Pohlner PG. Clinical informatics: A workforce priority for 21st century healthcare. Australian Health Review. 2011;35(2):130-135. http://dx.doi.org/10.1071/AH10935
  13. Walker PH, Walker JM. Nursing informatics: Opportunities for administrators, clinicians, educators, and researchers. Journal of the American Psychiatric Nurses Association. 1995;1(1):22-29. http://dx.doi.org/10.1177/107839039500100107
  14. Kim MH, Kim MS, Chae SW, Kim YS. Relationship of nursing informatics competency and self-leadership among hospital nurses. Korean Academy of Nursing Administration. 2007;13(2):176-183.
  15. Kim MS. Role of self-leadership in the relationship between organizational culture and informatics competency. Journal of Korean Academy of Nursing. 2009;39(5):731-740. http://dx.doi.org/10.4040/jkan.2009.39.5.731
  16. Lee SA. Over half of the workers feel that "I was addicted to smartphone"... They use 5.2 mean hours daily. Korea JoongAng Daily. 2015 July 15.
  17. Kim HJ, Kim JH, Jeong SH. Predictors of smartphone addiction and behavioral patterns. Journal of Cybercommunication Academic Society. 2012;29(4):55-93.
  18. Li M. The effect of flow and addiction of mobile game on user's satisfaction and loyalty [master's thesis]. Seoul: Seoul National University; 2006
  19. Lee JH. Exploring the explanatory factors between active smartphoneuse and smartphone addiction: Focused on use behavior and resilience [master's thesis]. Seoul: Sogang University; 2015
  20. Staggers N, Gassert CA, Curran C. Informatics competencies for nurses at four levels of practice. Journal of Nursing Education. 2001;40(7):303-316.
  21. Kim MS. Validity and reliability of informatics competencies for nurses among Korean nurses. Korean Journal of Adult Nursing. 2008;20(3):470-480.
  22. National Information Society Agency. A survey on internet addiction. Seoul: National Information Society Agency; 2014. Report No.: NIA V-RER-14112. Available from: http://www.nia.or.kr/bbs/board_view.asp?BoardID=201408061323065914&id=15626&Order=020303&search_target=&keyword=&Flag=020000&nowpage=1&objpage=0.
  23. Akour H. Determinants of mobile learning acceptance: an empirical investigation in higher education [dissertation]. Oklahoma: Oklahoma State University; 2009.
  24. Han SM, Lee HS. Nurses' reasons for participation in continuing nursing education. Journal of Vocational Education Research. 2010;29(2):189-204.
  25. Go JH, Han MR, Hur J. The analysis of raw data of completion of off-line continuing education in nursing in Seoul, 2008-2012. Journal of Digital Convergence. 2014; 12(6):527-538. http://dx.doi.org/10.14400/JDC.2014.12.6.527
  26. Han S, Kim S. Analysis of learner competencies through digital textbooks and smart-learning. Journal of the Korean Association of Information Education. 2015;19(2):207-214. http://dx.doi.org/10.14352/jkaie.2015.19.2.207
  27. Heo HO, Lim KY, Kim HJ, Lee HW. Validation of the assessment instrument for teacher competency for SMART education. Journal of Korean Association for Educational Information and Media. 2013;19(2):151-173.
  28. Eley R, Fallon T, Soar J, Buikstra E, Hegney D. Barriers to use of information and computer technology by Australia's nurses: A national survey. Journal of Clinical Nursing. 2009;18(8):1151-1158. http://dx.doi.org/10.1111/j.1365-2702.2008.02336.x
  29. Kim M. A study on educational application of smart devices for enhancing the effectiveness of problem solving learning. Journal of Internet Computing and Services. 2014;15(1): 143-156. http://dx.doi.org/10.7472/jksii.2014.15.1.143
  30. Ajzen I, Madden TJ. Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology. 1986;22(5): 453-474. http://dx.doi.org/10.1016/0022-1031(86)90045-4

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