PURPOSE: To examine medical school characteristics, in particular federal funding for biomedical research, as they relate to the graduates' choices of family medicine, general internal medicine, general pediatrics, or all three specialties. METHOD: Data were collected for 121 U.S. medical schools, including information on funding, faculty, curricula, and other school characteristics. In addition, a questionnaire was mailed to the schools requesting information about non-federal funding for primary care, primary care department characteristics, and primary care representation on the admission, curriculum, and promotion and tenure committees. Analyses were carried out separately for each specialty and for all three combined. The first multiple regression analysis was done to predict specialty choice (proximate predictors), the second to predict the predictors of specialty choice (intermediate predictors), and the third to predict those predictors (distal predictors). RESULTS: Prediction was best for family medicine practice. Interest at matriculation and required third-year and fourth-year time in primary care were the two best proximate predictors. The best predictors of initial interest were the percentage of rural students and special programs for primary care, while the best predictors of required time in primary care were funding for family medicine and the percentage of faculty in family medicine (intermediate predictors). The best predictor of the percentage of faculty in family medicine was funding for family medicine (distal predictor). CONCLUSION: The results suggest that the most effective way to increase the number of physicians with generalist practices is to increase the number of students interested in a family medicine career at matriculation.
PURPOSE: To examine medical school characteristics, in particular federal funding for biomedical research, as they relate to the graduates' choices of family medicine, general internal medicine, general pediatrics, or all three specialties. METHOD: Data were collected for 121 U.S. medical schools, including information on funding, faculty, curricula, and other school characteristics. In addition, a questionnaire was mailed to the schools requesting information about non-federal funding for primary care, primary care department characteristics, and primary care representation on the admission, curriculum, and promotion and tenure committees. Analyses were carried out separately for each specialty and for all three combined. The first multiple regression analysis was done to predict specialty choice (proximate predictors), the second to predict the predictors of specialty choice (intermediate predictors), and the third to predict those predictors (distal predictors). RESULTS: Prediction was best for family medicine practice. Interest at matriculation and required third-year and fourth-year time in primary care were the two best proximate predictors. The best predictors of initial interest were the percentage of rural students and special programs for primary care, while the best predictors of required time in primary care were funding for family medicine and the percentage of faculty in family medicine (intermediate predictors). The best predictor of the percentage of faculty in family medicine was funding for family medicine (distal predictor). CONCLUSION: The results suggest that the most effective way to increase the number of physicians with generalist practices is to increase the number of students interested in a family medicine career at matriculation.
Authors: Maureen T Connelly; Amy M Sullivan; Antoinette S Peters; Nancy Clark-Chiarelli; Natasha Zotov; Nina Martin; Steven R Simon; Judith D Singer; Susan D Block Journal: J Gen Intern Med Date: 2003-03 Impact factor: 5.128
Authors: James C Rosser; Timothy B Legare; Charles Jacobs; Katherine M Choi; Jeffrey P Fleming; Jamie Nakagiri Journal: Surg Endosc Date: 2018-04-02 Impact factor: 4.584