ArticleBMC nursing2025
What matters most? Identifying key resource gain and loss factors affecting nurses' work engagement and job burnout in digital healthcare contexts.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Unveiling the psychological network of work alienation among nursing interns: A resource conservation perspective and network analysis.PloS one · 2026Article
- The association between compassion fatigue and nurses' creativity: the mediating role of ego depletion.Frontiers in psychology · 2026Article
- Patterns and Predictors of Self-Regulatory Fatigue Among Intensive Care Unit Nurses: A Person-Centered Latent Profile Analysis.Journal of nursing management · 2026Article
- The impact of mission valence on innovative work behavior among civil servants: the roles of harmonious passion, spiritual leadership, and the organization's fault-tolerant climate.Frontiers in psychology · 2025Article
- The impact mechanism of artificial intelligence dependence on college students' innovation capability: an empirical study from China.Frontiers in psychology · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundWork engagement and burnout are two of the most significant work states in nurses. The increasing prevalence of information and communication technologies (ICT) in the workplace means that nurses are required not only to actively embrace technological advancements for their own well-being and to enhance the quality of nursing care, but also to simultaneously learn to cope with the mental and physical health issues arising from ICT use. Nevertheless, research on the work status of Chinese nurses in the context of ICT demands remains scant, particularly in large-sample, multi-center empirical studies.
aimto investigate the distinct predictors of work engagement and job burnout among Chinese nurses in the context of ICT demands, and to clarify the differential mechanisms underlying these two work states.
methodsA cross-sectional survey (N = 1612) was conducted among Chinese nurses from January to February 2024, utilizing questionnaires to collect demographic information, work-related details, job resources, job stressors, work engagement and job burnout within the context of ICT usage. Descriptive statistics and one-way ANOVA were employed to identify control variables based on demographic and work-related information. Pearson correlation analysis explored relationships between job resources, job stressors, and nurses' work status. Regression models for work engagement and job burnout were constructed, with LASSO regression selecting the most critical influencing variables.
resultsThe LASSO regression model of nurses' work engagement includes seven explanatory variables, of which the ones that pass the significance test are harmonious work passion, positive affect, and self-efficacy. The LASSO regression model of nurses' job burnout included 9 variables, of which the statistically significant ones were ego depletion, negative affect, job insecurity, and ICT demands.
conclusionsThis study makes three innovative contributions. First, it identified three key resource gain factors that significantly related to nurses' work engagement. Second, it pinpointed four principal resource loss factors that contribute to nurses' burnout. Third, it distinguished between the two concepts of work engagement and burnout and examined the differentiated factors that influence them, thereby providing a nuanced understanding of the distinct mechanisms at play. CLINICAL TRIAL NUMBER: Not Applicable.
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