title: Prediction of intended career choice in family medicine using artificial neural networks.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Family Medicine, Medical faculty, University of Ljubljana , Ljubljana , Slovenia.
authors.forename: Marija
authors.initials: M
authors.lastname: Petek Šter
authors.forename: Igor
authors.initials: I
authors.lastname: Švab
authors.forename: Branko
authors.initials: B
authors.lastname: Šter
mesh_terms: D001291:Attitude of Health Personnel; D002321:Career Choice; D002982:Clinical Clerkship; D003430:Cross-Sectional Studies; D003657:Decision Making; D005194:Family Practice / Q000193:education / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D017524:Slovenia; D013337:Students, Medical / Q000706:statistics & numerical data*
keywords: Medical students; artificial neural networks; attitudes; family medicine; intended career choice