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Factors associated with occupational calling among psychiatric nurses: a Bayesian network model analysis

Yu Ai et al · Nature Portfolio · 2026

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Abstract To investigate the current status of occupational calling among psychiatric nurses, identify its correlated factors, and explore the probabilistic dependencies and network structure using a Bayesian network model. In June 2024, a convenience sample of 216 psychiatric nurses was recruited from a tertiary Grade A hospital in Mianyang City. Participants completed a questionnaire including demographic characteristics and scales for occupational calling, job involvement, professional identity, and work-family conflict. LASSO regression was used to screen key factors associated with occupational calling, and Bayesian network analysis was performed to explore the interrelationships among these factors. The mean score for occupational calling was 3.72 ± 0.65.Mean scores for job involvement, professional identity, and work-family conflict were 4.50 ± 1.36, 5.48 ± 0.74, and 2.61 ± 0.67, respectively. LASSO regression identified educational level (β=-0.19),nursing position(POST)(β = 0.08), professional title (β = 0.01), employment type (β = 0.06), professional identity (β = 0.20), work-family conflict (β = -0.19), and job involvement (β = 0.13) as factors associated with occupational calling, with professional identity showing the strongest association. The Bayesian network further revealed that POST, professional title, work-family conflict, and job involvement were directly associated with occupational calling, whereas educational level and employment type were indirectly linked to occupational calling through professional identity and job involvement, respectively. LASSO coefficient path analysis indicated that professional identity and job involvement maintained stronger and more stable associations across varying penalty levels, while demographic factors showed weaker and less stable associations. Occupational calling among psychiatric nurses is associated with a combination of demographic and psychosocial factors. LASSO coefficient path analysis demonstrated that psychosocial factors—particularly professional identity and job involvement—showed stronger and more stable associations with occupational calling than demographic characteristics whereas Work-family conflict exhibited a stable negative association throughout the regularization path. These findings provide preliminary evidence that strategies targeting the enhancement of professional identity, promotion of job involvement, and alleviation of work-family conflict may be associated with higher levels of occupational calling in this population.

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APA 7

al, Y. A. E. (2026). Factors associated with occupational calling among psychiatric nurses: a Bayesian network model analysis. https://doi.org/10.1038/s41598-026-44809-6

MLA

al, Yu Ai et. "Factors associated with occupational calling among psychiatric nurses: a Bayesian network model analysis." 2026. https://doi.org/10.1038/s41598-026-44809-6.

Chicago

al, Yu Ai et. 2026. "Factors associated with occupational calling among psychiatric nurses: a Bayesian network model analysis.". https://doi.org/10.1038/s41598-026-44809-6.

Harvard

al, Y. A. E. 2026, Factors associated with occupational calling among psychiatric nurses: a Bayesian network model analysis, Nature Portfolio, available at: https://doi.org/10.1038/s41598-026-44809-6 [Accessed 7 Aug. 2026].

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Title
Factors associated with occupational calling among psychiatric nurses: a Bayesian network model analysis
Author / contributors
Yu Ai et al
Publisher
Nature Portfolio
Publication year
2026
ISSN
2045-2322
ISSN
2045-2322
Language
English

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