Factors affecting social accountability of medical schools in the Korean context: exploratory factor and multiple regression analyses.

The concept of social accountability of medical schools is becoming increasingly important worldwide, and numerous frameworks and evaluation tools have been developed. This study examined how global concepts work in a specific context by identifying the factors affecting medical schools' social accountability performance in the Korean context. A survey was conducted with 40 current deans of medical schools and 15 medical education experts in Korea to assess their opinions on the implementation of social accountability of medical schools. A questionnaire survey comprising five key factors, including 39 items, was developed based on a literature review. Exploratory factors were analyzed to derive factors affecting social accountability Multiple regression analysis was conducted to determine the importance of each factor in the implementation of social accountability of medical schools. The exploratory factor analysis revealed that eight factors in three areas influenced the implementation of social accountability by medical schools. The hardware (H) area included the declaration of social accountability and physicians, organizations and systems for implementing social accountability, and physical environment and finance. The software (S) area included curriculum design-related social accountability and monitoring and evaluation system. The partner (P) area included the proximity between partners, building partnerships among stakeholders, and interactions between partners. Multiple regression analysis revealed that 'interactions between partners' had the greatest impact on the implementation of social accountability of medical schools. It is a social accountability implementation model that reflects global principles within the Korean context. The HSP model is significant in that individual medical schools can be used in establishing mandated mechanisms for accreditation. Future studies could adapt this model to study standards and indicators in other contexts.