Impact of job crafting and perceived supervisor support on nurses’ work engagement: The mediating role of job satisfaction
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DOIhttp://dx.doi.org/10.21511/ppm.24(2).2026.36
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Article InfoVolume 24 2026, Issue #2, pp. 536–549
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Type of the article: Research Article
Abstract
Work engagement among nurses is a critical determinant of healthcare quality and patient safety. However, the psychological mechanism through which job resources foster nurses’ work engagement in non-Western healthcare contexts remains insufficiently understood. This study aims to examine the mediating role of job satisfaction in the relationship between job crafting, perceived supervisor support, and work engagement among nurses in a hospital setting. A cross-sectional survey was conducted between February and May 2025 using partial least squares structural equation modeling (PLS-SEM) on 279 valid responses (84.3% response rate) collected from four private hospitals. The results supported that job crafting has a significant positive effect on work engagement (β = 0.633, p < 0.001) and job satisfaction (β = 0.187, p = 0.003). Furthermore, perceived supervisor support significantly influences job satisfaction (β = 0.542, p < 0.001) but does not have a significant direct effect on work engagement (β = 0.016, p = 0.787). Mediation analysis reveals that job satisfaction partially mediates the relationship between job crafting and work engagement (β = 0.037, p = 0.038). Further, job satisfaction was found to fully mediate the relationship between perceived supervisor support and work engagement (β = 0.106, p = 0.002). These findings highlight the pivotal role of job satisfaction as a psychological mechanism linking job resources and proactive behaviors to nurses’ work engagement in hospital settings.
Acknowledgment
This work was supported by the Research Institute and Community Development of Universitas Andalas under Grant (121/UN16.19/PT.01.03/PMDSU/2025).
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JEL Classification (Paper profile tab)J28, J29, M54, I11
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References61
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Tables5
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Figures2
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- Figure 1. Conceptual framework
- Figure 2. Measurement model assessment
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- Table 1. Demographics
- Table 2. Reliability and validity
- Table 3. Fornell-Larcker criterion
- Table 4. Heterotrait-monotrait values
- Table 5. Hypothesis testing
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