Literature DB >> 9347720

Predicting Who Will Choose a Family Medicine Residency.

Louise Nasmith, Heather Rubenstein, Howard Goldstein, Donald Sproule, Elaine D Franco, Pierre Tellier.   

Abstract

PURPOSE: To create and evaluate a screening instrument and a revised interview format for use in the selection of family medicine residents at the McGill University Faculty of Medicine.
METHOD: The screening tool consisted of two sections: an assessment of academic performance (the TASS) and an evaluation of applicantsʼ generalist versus specialist orientation (the GSSS); each applicantʼs file was assessed by two raters. The revised interview included specific questions and scenarios related to family medicine. All three parts were tested on 143 applicants from outside the region of Quebec in 1994–95. The results on both parts of the screening tool and the interview were compared with the studentsʼ first choices of residency and then were compared with the performances of the 24 accepted into the program as reflected in their first six-month summative evaluation forms. Data were analyzed through several statistical methods.
RESULTS: Only the GSSS accurately predicted the applicantsʼ first choices (for agreement between both raters: sensitivity, 81%; specificity, 70%; accuracy, 78%). No significant association was found when comparing matching applicantsʼ scores obtained during the selection process with their scores on the six-month evaluation forms.
CONCLUSION: The GSSS may prove useful as a tool in the review of applicantsʼ files. More studies are needed to reevaluate the use of the interview in the selection process and to help determine whether any selection instrument can accurately predict applicantsʼ subsequent performances in a residency.Acad. Med. 1997;72:908–912.

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Year:  1997        PMID: 9347720     DOI: 10.1097/00001888-199710000-00022

Source DB:  PubMed          Journal:  Acad Med        ISSN: 1040-2446            Impact factor:   6.893


  7 in total

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2.  Racial, ethnic, and affluence differences in elderly patients' use of teaching hospitals.

Authors:  Theodore J Iwashyna; Farr A Curlin; Nicholas A Christakis
Journal:  J Gen Intern Med       Date:  2002-09       Impact factor: 5.128

3.  Interhospital transfer patients discharged by academic hospitalists and general internists: Characteristics and outcomes.

Authors:  Lauge Sokol-Hessner; Andrew A White; Katherine F Davis; Shoshana J Herzig; Samuel F Hohmann
Journal:  J Hosp Med       Date:  2015-11-20       Impact factor: 2.960

4.  Association Between Teaching Status and Mortality in US Hospitals.

Authors:  Laura G Burke; Austin B Frakt; Dhruv Khullar; E John Orav; Ashish K Jha
Journal:  JAMA       Date:  2017-05-23       Impact factor: 56.272

5.  Pediatric high-impact conditions in the United States: retrospective analysis of hospitalizations and associated resource use.

Authors:  Rebecca L Miller; Achamyeleh Gebremariam; Folafoluwa O Odetola
Journal:  BMC Pediatr       Date:  2012-06-08       Impact factor: 2.125

Review 6.  Patient outcomes with teaching versus nonteaching healthcare: a systematic review.

Authors:  Panagiotis N Papanikolaou; Georgia D Christidi; John P A Ioannidis
Journal:  PLoS Med       Date:  2006-09       Impact factor: 11.069

7.  Does interhospital transfer improve outcome of acute myocardial infarction? A propensity score analysis from the Cardiovascular Cooperative Project.

Authors:  John M Westfall; Catarina I Kiefe; Norman W Weissman; Anthony Goudie; Robert M Centor; O Dale Williams; Jeroan J Allison
Journal:  BMC Cardiovasc Disord       Date:  2008-09-09       Impact factor: 2.298

  7 in total

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