Empirical Analysis of the Three-dimensional Structure of Clinical Reasoning Ability and Construction of Targeted Python Case Library from the Perspective of Cluster Analysis

Nana MENG; Lu SUN; Shenquan CHEN; Wenwen GUO; Haisi LIANG

doi:10.12259/j.issn.2095-610X.S20251219

Volume 46 Issue 12

Dec. 2025

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Article Navigation > Journal of Kunming Medical University > 2025 > 46(12): 162-170

Nana MENG, Lu SUN, Shenquan CHEN, Wenwen GUO, Haisi LIANG. Empirical Analysis of the Three-dimensional Structure of Clinical Reasoning Ability and Construction of Targeted Python Case Library from the Perspective of Cluster Analysis[J]. Journal of Kunming Medical University, 2025, 46(12): 162-170. doi: 10.12259/j.issn.2095-610X.S20251219

Citation:

Nana MENG, Lu SUN, Shenquan CHEN, Wenwen GUO, Haisi LIANG. Empirical Analysis of the Three-dimensional Structure of Clinical Reasoning Ability and Construction of Targeted Python Case Library from the Perspective of Cluster Analysis[J]. Journal of Kunming Medical University, 2025, 46(12): 162-170. doi: 10.12259/j.issn.2095-610X.S20251219

Citation:

Nana MENG, Lu SUN, Shenquan CHEN, Wenwen GUO, Haisi LIANG. Empirical Analysis of the Three-dimensional Structure of Clinical Reasoning Ability and Construction of Targeted Python Case Library from the Perspective of Cluster Analysis[J]. Journal of Kunming Medical University, 2025, 46(12): 162-170. doi: 10.12259/j.issn.2095-610X.S20251219

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Empirical Analysis of the Three-dimensional Structure of Clinical Reasoning Ability and Construction of Targeted Python Case Library from the Perspective of Cluster Analysis

doi: 10.12259/j.issn.2095-610X.S20251219

1.
Department of Obstetrics and Pediatrics，Clinical Medical School，Zhaoqing Medical College，Zhaoqing Guangdong 526000
2.
Department of Pediatrics，Guangzhou Women and Children’s Medical Center，Guangzhou Guangdong 510623
3.
Department of Surgery，The First People’s Hospital of Zhaoqing，Zhaoqing Guangdong 526000，China

Received Date: 2025-08-29
Available Online: 2025-12-10
Publish Date: 2025-12-25

Abstract

Abstract

Objective To clarify the internal structure and population characteristics of clinical reasoning ability among clinical medical interns, construct targeted training tools, and provide evidence for clinical reasoning education reform. Methods A multi-center stratified sampling method was adopted to select 321 clinical medicine interns who underwent clinical internships in 6 hospitals from July 2023 to April 2024. A self-designed "Clinical Thinking Ability Assessment Questionnaire" was used for the survey. Correlation analysis and factor analysis were conducted to explore the ability structure, while K-means clustering was applied to identify group characteristics. Based on these findings, a Python case library was designed and its effectiveness was verified through a randomized controlled trial. Results Clinical thinking ability demonstrated a three-dimensional structure comprising "diagnostic association, decision-making for treatment planning, and knowledge application, " with a cumulative variance explanation rate of 84.21%. Multi-population validation showed good model fit （χ²/df = 2.31～2.45, RMSEA = 0.065～0.069）. Clustering analysis identified three ability groups: high （33.33%）, moderate （42.68%）, and low （23.99%）, with statistically significant differences across all dimensions （P < 0.01）. After intervention with the case library, the improvement of core shortcoming dimensions in the intervention group was significantly higher than that in the control group （diagnostic relevance of high-ability group: F = 32.67; scheme decision-making ability of medium-ability group: F = 48.32; knowledge application ability of low-ability group: F = 41.56, all P < 0.01）. Conclusion The three-dimensional structure and population characteristics of clinical thinking ability provide targeted guidance for precision training. The Python case library facilitates the transition of clinical thinking cultivation toward "data-driven" approaches.
- Clinical thinking ability,
- Three-dimensional structure,
- Cluster analysis,
- Targeted case library,
- Python technology

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References(23)

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