住院医师心理健康生态评估与职业倦怠预测

Mental Health Ecology Assessment and Burnout Prediction among Resident Physicians

摘要: 职业倦怠是影响住院医师规范化培训质量、职业发展和患者安全的重要问题。既往研究多以个体心理量表识别倦怠结果，对教学互动、组织支持、科室文化和制度安排等情境因素关注不足。心理健康生态评估以生态系统理论、工作要求–资源模型和自我决定理论为基础，将规培医师的心理状态置于临床学习环境中考察，有助于解释职业倦怠的形成机制并识别可干预的风险来源。本文梳理心理健康生态评估的理论基础与核心维度，分析Mini-CEX、OSCE等形成性评价工具及多源数据在倦怠预测中的应用价值，讨论量表开发、纵向验证、模型解释、隐私保护和组织干预等关键问题。建立兼顾个体状态与科室环境的动态评估体系，可推动职业倦怠管理由事后筛查转向风险前移，为规培质量持续改进提供依据。

Abstract: Burnout has become an important concern in standardized residency training because of its associations with impaired professional development, reduced quality of care, and patient-safety risks. Conventional assessment mainly relies on individual psychological scales and therefore provides limited information about contextual determinants embedded in clinical training. Mental health ecology assessment draws on ecological systems theory, the job demands-resources model, and self-determination theory. It examines residents’ psychological status in relation to supervisory interaction, organizational resources, departmental culture, and institutional arrangements, thereby identifying modifiable antecedents of burnout. This review summarizes the theoretical basis and core domains of mental health ecology assessment, discusses the potential of workplace-based assessment tools such as the mini-Clinical Evaluation Exercise and the Objective Structured Clinical Examination, and analyzes the use of multisource data for burnout prediction. Methodological priorities include scale development, multicenter longitudinal validation, interpretable modeling, privacy protection, and linkage between risk signals and organizational interventions. A dynamic assessment system that integrates individual well-being with the clinical learning environment may shift burnout management from retrospective screening to prospective risk stratification and support continuous quality improvement in residency training.