Impact of caring for COVID-19 patients on nurses’ distance learning progress
Abstract
We sought to understand the impact of disruption of nurses’ daily routines by COVID-19 on their participation in Continuing Professional Education. We analyzed learning logs of 194 nurses enrolled in a 12-month distance learning course, one cohort from March 2019 to February 2020, and one from March 2020 to February 2021, during the COVID-19 pandemic. Monthly login frequency was significantly higher in March 2020 than in March 2019, and significantly lower in April 2020 than in April 2019, which we associate with increased COVID-19 cases, hospitalizations, and deaths in April 2020. From March 2020 to August 2020, login frequency was significantly higher for nurses without previous distance learning experience, suggesting that their distance learning strategies were not yet established. During September and October 2020, login frequency was significantly higher, from which we infer previous procrastination. We found no significant differences between login frequencies of nurses who cared for COVID-19 patients and those who did not. The results of our study suggest that stressors imposed by the COVID-19 pandemic significantly hindered distance learning progress whether or not nurses directly cared for COVID-19 patients. Based on our findings, we recommend screening distance learning experiences and providing mentoring and learning support to mitigate interference with distance learning progress during times of heightened professional and personal stress.
References
Treatment of Discharge and Work Restrictions for Patients with Novel Coronavirus Infection under the Law Concerning Prevention of Infectious Diseases and Medical Care for Patients with Infectious Diseases. https://www.mhlw.go.jp/content/000745527.pdf (in Japanese).
V.C. Cheng, S.C. Wong, J.H. Chen, C.C. Yip, V.W. Chuang, O.T. Tsang, V.W.M. Chuang, S. Sridhar, J.F.W. Chan, P.-L. Ho, and K.Y. Yuen, “Escalating infection control response to the rapidly evolving epidemiology of the coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 in Hong Kong,” Infection Control & Hospital Epidemiology, vol. 41, no. 5, 2020, pp. 493–498.
A.M. Dondorp, M. Hayat, D. Aryal, A. Beane, and M.J. Schultz, “Respiratory Support in COVID-19 Patients, with a Focus on Resource-Limited Settings,” The American Journal of Tropical Medicine and Hygiene, vol. 102, no. 6, 2020, pp. 1191–1197.
T. Lammers, A. M. Sofias, R. van der Meel, R. Schiffelers, G. Storm, F. Tacke, ... and J. M. Metselaar, “Dexamethasone Nanomedicines for COVID-19,” Nature Nanotechnology, vol. 15, no. 8, 2020, pp. 622–624.
E.K. McCreary, and D.C Angus, “Efficacy of Remdesivir in COVID-19,” JAMA, vol. 324, no. 11, 2020, pp. 1041–1042.
X. Elharrar, Y. Trigui, A.M. Dols, F. Touchon, S. Martinez, E. Prud’homme, and L. Papazian, “Use of Prone Positioning in Nonintubated Patients with COVID-19 and Hypoxemic Acute Respiratory Failure,” JAMA, vol. 323, no. 22, 2020, pp. 2336–2338.
M. Beaudoin, G. Kurtz, I. Jung, K. Suzuki, and B.L. Grabowski, Online Learner Competencies: Knowledge, Skills, and Attitudes for Successful Learning in Online Settings. IAP, 2013.
J. Thurmond, S. Cross, D. Byers, D. Todd, J. Rogers, K. Reid, and E. Winstead, "A Descriptive Study Examining Undergraduate Student Experiences during the COVID-19 Pandemic," International Journal Nursing and Health Care Science, vol. 1, no. 8, 2021, pp. 2021–2041.
G. Piccoli, R. Ahmad, and B. Ives, “Web-Based Virtual Learning Environments: A Research Framework and a Preliminary Assessment of Effectiveness in Basic IT Skill Training,” MIS Quarterly, vol. 25, no.4, 2001, pp. 401–426.
J. Davies, and M. Graff, “Performance in e-learning: Online Participation and Student Grades,” British Journal of Educational Technology, vol. 36, no.4, 2005, pp. 657-663.
J.L. Hung, and K. Zhang, “Revealing Online Learning Behaviors and Activity Patterns and Making Predictions with Data Mining Techniques in Online Teaching,” MERLOT Journal of Online Learning and Teaching, vol. 4, no.4, 2008, pp. 426–437.
M. Saqr, U. Fors, and M. Tedre, “How Learning Analytics Can Early Predict Underachieving Students in a Blended Medical Education Course,” Medical Teacher, vol. 39, no.7, 2017, pp. 757–767.
M.S. Yagi, R. Murakami, S. Tsuzuku, M. Suzuki, H. Nakano, and K. Suzuki, “Distance Learning for Nurses: Using Learning Analytics to Build a Learning Support Program,” The Journal of Information and Systems in Education, vol. 19, no. 1, 2020, pp. 1–8. Ministry of Health, Labour and Welfare, "Content of Programs," https://www.mhlw.go.jp/file/06-Seisakujouhou-10800000-Iseikyoku/0000077911.pdf (in Japanese).
World Health Organization. https://covid19.who.int/region/wpro/country/jp (in Japanese).
F. Agyei, J. Bayuo, P. Baffour, and C. Laari, “Surviving to Thriving: A Meta-Ethnography
of the Experiences of Healthcare Staff Caring for Persons with COVID-19,” BMC
Health Services Research, in review, 2021; doi:10.21203/rs.3.rs-139341/v1
K.S. Kitchener, and P.M. King, “The Reflective Judgment Model: Transforming Assumptions Adult Knowing,” Fostering Critical Reflection in Adulthood, J. Mezirow, Ed., Jossey-Bass Publishers, 1990, pp. 159–176.
S.D. Brookfield, “Transformative Learning as Ideology Critique,” Learning as Transformation: Critical Perspectives on a Theory in Progress, J. Mezirow, Ed., Jossey-Bass Publishers, 2000, pp. 125–146.
J.N. Choi, and S.V. Moran, “Why Not Procrastinate? Development and Validation of a New Active Procrastination,” The Journal of Social Psychology, vol. 149, no. 2, 2009, pp. 195–212.
