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April 1, 2026Women s Health Nursing0 citationsOpen Access

Factors influencing childbearing intention among married childless female nurses in Korea: a quantile regression approach

YJYoonjoo JungMKMoonjeong Kim

Key Points

  • This study aims to identify the determinants of childbearing intention among married childless female nurses in Korea.
  • Recruited 141 married, childless female nurses under 45 from seven Korean cities.
  • Participants completed a self-administered survey on various psychosocial factors and childbearing intention.
  • Data analyzed included descriptive statistics, correlation coefficients, and quantile regression.
  • Moderate levels of childbearing intention and self-actualization were reported by participants.
  • Age was a significant predictor of childbearing intention in multiple regression analysis.
  • At higher percentiles, age, educational level, and social support emerged as significant factors influencing childbearing intention.

Abstract

Purpose: South Korea’s rapid fertility decline, shaped by intertwined psychosocial and structural factors, is more severe than that observed in other Asia-Pacific and European countries. This study aimed to identify how determinants of childbearing intention vary among married, childless female Korean nurses using quantile regression. Methods: Married, childless female nurses younger than 45 years were recruited from seven cities in Korea. Participants (n=141) completed a self-administered survey between August and September 2024 on childbearing intention, health-related quality of life (HRQoL), self-actualization, social support, economic stability, and self-esteem. Data were analyzed using descriptive statistics, Pearson correlation coefficients, multiple linear regression, and quantile regression. Results: Participants reported moderate levels of childbearing intention and self-actualization, higher levels of HRQoL and social support, and moderate or higher levels of economic stability and self-esteem. In the multiple regression analysis, only age (B=1.67, p<.001) was a significant predictor of childbearing intention. Quantile regression revealed additional patterns: at the 60th percentile, age (B=1.89, p=.011), higher educational level (B=2.25, p=.040), and social support (B=1.06, p=.015) were significant, whereas at the 80th percentile, age (B=2.34, p=.001) and social support (B=1.41, p=.016) remained significant. These findings indicate that social support was strongly associated with childbearing intention among nurses with higher intention levels. Conclusion: Determinants of childbearing intention differed according to intention level, underscoring the value of moving beyond mean-based analyses. For married, childless female nurses, individualized interventions that enhance social support and account for age, educational level, and work-family context may be more effective than uniform, population-wide approaches in supporting childbearing intention.

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Cite This Study

Jung et al. (2026) studied this question.

synapsesocial.com/papers/69cd7a815652765b073a7b4chttps://doi.org/10.4069/whn.2026.03.03
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