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Factors influencing nurses' satisfaction to online learning approach: a cross ICU analysis.
- Source :
-
BMC Nursing . 8/12/2024, Vol. 23 Issue 1, p1-9. 9p. - Publication Year :
- 2024
-
Abstract
- Background: Given the increasing complexity of illnesses and rapid pace of technological advancements in professional training, it is vital to offer nurses ample opportunities to hone their clinical expertise and skills, particularly in ensuring the delivery of premier medical care. This study aimed to determine the factors and predictors influencing nurses' satisfaction with adopting mobile learning approaches in intensive care unit healthcare settings. Additionally, it sought to investigate the applicability of the technology acceptance model in explaining their inclinations and validating the measurement scales employed in the research. Methods: The study employed a cross-sectional survey research design, utilizing a technology acceptance questionnaire and a learning satisfaction questionnaire. The survey was conducted in six intensive care unit departments. A total of 212 participants completed the survey as the primary instrument. Rigorous assessments were conducted to establish the content validity and ensure instrument reliability. Results: The findings demonstrated that perceived usefulness was the most influential factor affecting nurses' intentions to embrace mobile learning approaches, with perceived ease of use emerging as the principal determinant of perceived usefulness. Conclusions: Incorporating mobile learning methodologies is paramount to increasing the calibration of professional nursing education programs. By effectively integrating digital information technology and tools, nursing educators can overcome teaching challenges, deliver innovative clinical nursing education content through mobile learning approaches, and foster optimal development in the field. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MOBILE apps
*INTENSIVE care nursing
*RESEARCH funding
*HOSPITAL nursing staff
*DESCRIPTIVE statistics
*STRUCTURAL equation modeling
*CHI-squared test
*JOB satisfaction
*NURSES' attitudes
*ONLINE education
*LEARNING strategies
*DATA analysis software
*COMPUTER assisted instruction
*CONFIDENCE intervals
Subjects
Details
- Language :
- English
- ISSN :
- 14726955
- Volume :
- 23
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- BMC Nursing
- Publication Type :
- Academic Journal
- Accession number :
- 178968845
- Full Text :
- https://doi.org/10.1186/s12912-024-02194-3