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Deep Structure Usage of Electronic Patient Records: Enhancing the Influence of Nurses' Professional Commitment to Decrease Turnover Intention: Deep Structure Usage and Turnover.
- Source :
- Journal of Nursing Management; 11/10/2024, Vol. 2024, p1-11, 11p
- Publication Year :
- 2024
-
Abstract
- Background: Organizational turnover exacerbates the shortage of nurses in the global workforce. However, no study has yet explored how deep structure usage—nurses' integration of electronic patient records into nursing practice delivery—reduces their turnover intention and moderates the impact of affective, continuance, and normative professional commitment on their turnover intention. Aims: To ascertain (1) the linkage between the deep structure usage of electronic patient records and nurses' organizational turnover intention and (2) the moderating role of deep structure usage on the associations between elements of commitment (affective, continuance, and normative) and turnover intention. Methods: Using a cross‐sectional survey and proportionate random sampling by ward unit, we collected data from 417 full‐time nurses via a self‐administered questionnaire. We performed hierarchical regression analyses to test the study hypotheses. Results: Deep structure usage was not directly related to organizational turnover intention (β = −0.07, p = 0.06). However, the results suggested that deep structure usage may enhance the effect of high affective commitment on nurses' organizational turnover intention (β = −0.09, p = 0.04), while potentially mitigating the effect of low continuance commitment on organizational turnover intention (β = 0.10, p = 0.01). Conclusions: Deep structure usage of electronic patient records helps to ease nurses' workload and facilitates their retention, which is particularly due to their affective commitment (attachment) but not their continuance commitment (switching costs). Implications for Nursing Management: Nursing management may advise hospital management that medical records systems need to be improved and fully embedded for nursing care delivery, as a more in‐depth use of these systems can help to retain nurses. [ABSTRACT FROM AUTHOR]
- Subjects :
- CROSS-sectional method
EMPLOYEE retention
RESEARCH funding
HOSPITAL nursing staff
LABOR turnover
STATISTICAL sampling
QUESTIONNAIRES
DESCRIPTIVE statistics
INFORMATION technology
ELECTRONIC health records
INTENTION
COMMITMENT (Psychology)
DATA analysis software
REGRESSION analysis
EMPLOYEES' workload
Subjects
Details
- Language :
- English
- ISSN :
- 09660429
- Volume :
- 2024
- Database :
- Complementary Index
- Journal :
- Journal of Nursing Management
- Publication Type :
- Academic Journal
- Accession number :
- 180805445
- Full Text :
- https://doi.org/10.1155/2024/5822368