title: Understanding primary care residency choices: a test of selected variables in the Bland-Meurer model.
abstract: OBJECTIVE
  This study tested the predictive validity of variables related to student characteristics of the Bland-Meurer Model of Career Decision-Making.
  
  
  METHODS
  A study was conducted using Association of American Medical Colleges' Graduate Student Questionnaire and career data from one medical school. Logistic regression analyses generated predictive models of primary care residency choice, including family medicine, general internal medicine, and pediatrics for 555 medical school graduates over five years.
  
  
  RESULTS
  Variables predictive of primary care residency choice were gender; student ratings of psychiatry, surgery, and internal medicine clerkships; not having participated in a research project in medical school; attitudes toward "the changing health care system on physicians" and "access to medical care"; and planned practice in a medically underserved area. Results differed for each field within each residency choice.
  
  
  CONCLUSIONS
  The Bland-Meurer Model may be used for variable selection in multivariate predictive models of family medicine, internal medicine and pediatrics residency choice. The authors' results may help guide admissions decisions, while providing medical educators and health care policymakers with a clearer picture of residency choice and a better understanding of how to meet the demands of selected patient populations.
authors.affiliation: Virginia Commonwealth University School of Medicine, Richmond, VA 23298-0048, USA. srlawson@vcu.edu
authors.forename: Sonya R
authors.initials: SR
authors.lastname: Lawson
authors.forename: J Dennis
authors.initials: JD
authors.lastname: Hoban
authors.forename: Paul E
authors.initials: PE
authors.lastname: Mazmanian
mesh_terms: D000328:Adult; D001290:Attitude; D002321:Career Choice; D002982:Clinical Clerkship; D003657:Decision Making; D003695:Delivery of Health Care; D005194:Family Practice / Q000193:education*; D005260:Female; D005544:Forecasting; D013502:General Surgery / Q000193:education; D006297:Health Services Accessibility; D006801:Humans; D007388:Internal Medicine / Q000193:education; D007396:Internship and Residency; D008297:Male; D008507:Medically Underserved Area; D017145:Models, Educational; D010372:Pediatrics / Q000193:education; D011320:Primary Health Care; D011570:Psychiatry / Q000193:education; D012106:Research / Q000193:education; D012737:Sex Factors; D013337:Students, Medical