Supervisory support and use of emotion (UOE) as predictors of turnover intention in healthcare: Evidence from Bosnia and Herzegovina

Lejla Šehanović & Nereida Hadžiahmetović

Human Systems Management2026https://doi.org/10.1177/01672533261438011article
ABDC C
Weight
0.50

What the paper says

Background High turnover among healthcare professionals continues to undermine care quality and organizational performance, particularly in resource-constrained systems. Understanding the psychological and supervisory factors that retain staff is therefore essential to sustaining effective healthcare delivery. Objectives This study investigates whether the Use of Emotions (UOE), a dimension of emotional intelligence, and the quality of supervision influence turnover intention among healthcare employees. It further tests whether supervision mediates the relationship between UOE and turnover intention. Method A cross-sectional survey was conducted among clinicians and healthcare staff across the Federation of Bosnia and Herzegovina. Validated instruments measured UOE, supervision quality, and turnover intention. Data were examined using confirmatory factor analysis and structural equation modeling to evaluate the measurement properties and test the hypothesized mediation. Results The measurement model demonstrated strong fit and discriminant validity. UOE positively predicted supervision quality, while supervision was negatively associated with turnover intention. The direct UOE–turnover link became insignificant when supervision was included, with bootstrapped analyses confirming a robust indirect effect. Conclusion Findings highlight supervision as a key mechanism through which emotional intelligence is associated with lower turnover intention. Enhancing supervisory quality and emotional regulation capacities may substantially strengthen workforce stability in healthcare settings.

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https://doi.org/https://doi.org/10.1177/01672533261438011

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@article{lejla2026,
  title        = {{Supervisory support and use of emotion (UOE) as predictors of turnover intention in healthcare: Evidence from Bosnia and Herzegovina}},
  author       = {Lejla Šehanović & Nereida Hadžiahmetović},
  journal      = {Human Systems Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/01672533261438011},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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