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. 2025 Mar 17;25(1):387.
doi: 10.1186/s12913-025-12518-x.

How gender affects the mental health of healthcare workers across regions in Thailand

Affiliations

How gender affects the mental health of healthcare workers across regions in Thailand

Nattanicha Chairassamee et al. BMC Health Serv Res. .

Abstract

Background: A shortage of healthcare professionals in Thailand can cause mental health impairment, low quality of life, high resignation rates, and low-quality services to patients due to heavy responsibilities. With the increasing rate of females entering medical careers, gender has become a significant factor in assessing healthcare workers' mental health. This study explores the relationship between the mental health and gender of healthcare workers across geographic regions in Thailand.

Methods: The present study uses individual data of Thai healthcare workers from 2009 to 2015 and 2018-prior to the COVID-19 pandemic. We include overall mental health and work/job-related mental health. A linear regression with fixed effects is used to estimate the differentials of healthcare workers' gender on mental health issues.

Results: Female healthcare workers feel more depressed and less satisfied with their health management than males do, particularly in rural areas. Young female healthcare professionals have lower levels of happiness and life satisfaction than male workers do. Predictions of mental health levels from our regressions show that nurses in rural areas experience higher levels of mental health impairment than doctors do.

Conclusions: Female workers are more likely to feel depressed than males are, particularly in rural areas. We also find that nurses are less likely to be happy and satisfied with life than doctors are.

Keywords: Gender; Healthcare workers; Mental health; Thailand; Urban–rural.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Prediction of happiness level by occupation and area
Fig. 2
Fig. 2
Prediction of life satisfaction by occupation and area
Fig. 3
Fig. 3
Prediction of health management satisfaction by occupation and area
Fig. 4
Fig. 4
Prediction of depression feeling by occupation and area
Fig. 5
Fig. 5
Prediction of feeling job burnout by occupation and area
Fig. 6
Fig. 6
Prediction of exhausted feeling by occupation and area

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