Prediction of intended career choice in family medicine using artificial neural networks

Background: Due to the importance of family medicine and a relative shortage of doctors in this discipline, it is important to know how the decision to choose a career in this field is made. Objective: Since this decision is closely linked to students 'attitudes towards family medicine, we were interested in identifying those attitudes that predict intended career choice in family medicine. Methods: A cross-sectional study was performed among 316 final-year medical students of the Ljubljana Medical Faculty in Slovenia. The students filled out a 164-item questionnaire, developed based on the European definition of family medicine and the EURACT Educational Agenda, using a seven-point Likert scale containing attitudes towards family medicine. The students also recorded their interest in family medicine on a five-point Likert scale. Attitudes were selected using a feature selection procedure with artificial neural networks that best differentiated between students who are likely and students who are unlikely to become family physicians. Results: Thirty-one out of 164 attitudes predict a career in family medicine, with a classification accuracy of at least 85%. Predictors of intended career choice in family medicine are related to three categories: understanding of the discipline, working in a coherent health care system and person-centredness. The most important predictor is an appreciation of a long-term doctor-patient relationship. Conclusion: Students whose intended career choice is family medicine differ from other students in having more positive attitudes towards family physicians' competences and towards characteristics of family medicine and primary care.