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Objectives <p>This study aimed to assess medical students’ attitudes toward integrating socioscientific issues (SSI) into female reproductive anatomy teaching across multiple academic years, using the novel case of China’s first uterus transplantation, and to apply artificial intelligence (AI)-based sentiment analysis to evaluate their emotional responses.</p> Results <p>A cross-sectional study was conducted among 163 medical students across three academic cohorts (2022, 2023, and 2024–2025) at a medical university in China. Over 95% of students rated the SSI-based teaching positively. AI-based sentiment analysis revealed that attitudes toward ethical questions varied: for embarrassment in close-relative transplantation, no significant differences were found across cohorts (χ² = 5.78, df = 4, <i>p</i> = 0.216); for adoption as an alternative to childbirth, attitudes also did not differ significantly (χ² = 6.62, df = 4, <i>p</i> = 0.157). Mean sentiment scores for ovarian transplantation were neutral to slightly negative across all cohorts (2022: -0.31; 2023: -0.08; 2024–2025: -0.12, weighted average of -0.17 for 2024 and − 0.02 for 2025).</p> Conclusions <p>SSI integration using a culturally relevant case was well-received by medical students. AI-based sentiment analysis proved a valuable tool for quantifying emotional responses. Attitudes toward ethical issues did not differ significantly across the three cohorts, suggesting a rationale for the sustained integration of SSI in preclinical curricula to foster ethical reasoning.</p>

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Medical students’ attitudes toward socioscientific issues in female reproductive anatomy teaching: a cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月16日

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  • Zhen-Zhen Kou,
  • Jing Gu,
  • Yan Wu,
  • Miao Tian,
  • Yi Li,
  • Yun-Qing Li

摘要

Objectives

This study aimed to assess medical students’ attitudes toward integrating socioscientific issues (SSI) into female reproductive anatomy teaching across multiple academic years, using the novel case of China’s first uterus transplantation, and to apply artificial intelligence (AI)-based sentiment analysis to evaluate their emotional responses.

Results

A cross-sectional study was conducted among 163 medical students across three academic cohorts (2022, 2023, and 2024–2025) at a medical university in China. Over 95% of students rated the SSI-based teaching positively. AI-based sentiment analysis revealed that attitudes toward ethical questions varied: for embarrassment in close-relative transplantation, no significant differences were found across cohorts (χ² = 5.78, df = 4, p = 0.216); for adoption as an alternative to childbirth, attitudes also did not differ significantly (χ² = 6.62, df = 4, p = 0.157). Mean sentiment scores for ovarian transplantation were neutral to slightly negative across all cohorts (2022: -0.31; 2023: -0.08; 2024–2025: -0.12, weighted average of -0.17 for 2024 and − 0.02 for 2025).

Conclusions

SSI integration using a culturally relevant case was well-received by medical students. AI-based sentiment analysis proved a valuable tool for quantifying emotional responses. Attitudes toward ethical issues did not differ significantly across the three cohorts, suggesting a rationale for the sustained integration of SSI in preclinical curricula to foster ethical reasoning.