Factor analysis of job training needs and construction of a training model based on "P4 medicine" for medical staff in military rest homes and sanatoriums
10.3760/cma.j.cn116021-20250122-02130
- VernacularTitle:基于“P4”医学理念的干休所和疗养院医疗人员岗位培训需求因子分析及培训模型构建
- Author:
Yi WANG
1
;
Wei ZENG
1
;
Qiao DU
1
;
Tao HE
1
;
Yu YANG
1
;
Dan TAN
1
Author Information
1. 陆军军医大学第二附属医院急诊科，重庆 400037
- Publication Type:Journal Article
- Keywords:
P4 medicine;
Training need;
Factor analysis
- From:
Chinese Journal of Medical Education Research
2025;24(10):1327-1334
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore a factor analysis method for job training needs based on "P4 medicine", and to provide evidence-based support for optimizing continuing education systems for medical staff in military rest homes and sanatoriums.Methods:A cross-sectional study was conducted with 95 medical staff from military rest homes and sanatoriums within the support system who participated in job training at Xinqiao Hospital. A structured questionnaire was developed based on the "P4 medicine" framework. After two rounds of Delphi expert consultation, 46 core indicators were selected. A principal component analysis was used to extract common factors, and a model of hierarchical needs was constructed by combining varimax rotation and entropy weight methods.Results:Four common factors were extracted, accounting for 81.564% cumulative variance. The first factor "dynamic updating of geriatric medical knowledge" (31.83%) covered clinical core competencies in managing geriatric comorbidities and recognizing critical values. The second factor "emergency responsiveness and personalized care" (26.05%) focused on military medical regulations, emergency treatment protocols, and tailored interventions. The third factor "multidisciplinary collaboration and leadership development" (12.41%) emphasized team reorganization in combat-ready scenarios. The fourth factor "integration of intelligent technologies" (11.29%) reflected data-driven decision-making needs. Entropy weight analysis highlighted dynamic medical knowledge updates (e.g., emergency skills with a weight of 0.050) and AI applications with a weight of 0.019 among the top 10% high-weight indicators.Conclusions:The "P4 medicine" effectively delineates the multidimensional training needs of grassroots medical personnel. Its four-dimensional structure (predictive, normative, collaborative, and innovative) provides a theoretical framework for curriculum design. We recommend constructing tiered training modules prioritizing technology-enabled mechanisms to enhance the precision and sustainability of geriatric healthcare services.
