PURPOSE: To investigate the incremental effects of selected psychosocial measures--beyond the effects of conventional admission measures--in predicting students' academic performances in medical school. METHODS: In 1989-90, 210 second-year students at Jefferson Medical College were each asked to complete 11 psychosocial questionnaires that were then used as predictors of performance measures in medical school. The students' scores on three subtests of the Medical College Admission Test (MCAT) were also used as predictors. Three composite measures of performance were used as the criterion measures: basic science examination grades, clinical examination grades, and ratings of clinical competence. A multiple regression algorithm (general linear model) was used for statistical analysis. RESULTS: The response rate was 83% (175 students). When the psychosocial measures were added to the statistical models in which the common variances of the MCAT scores were already determined, significant increments in the common variances were observed for two of the three performance measures: basic science grades and clinical examination grades. Whereas only 4% of the common variance in the ratings of clinical competence could be accounted for by the MCAT scores, 14% could be accounted for by the psychosocial measures. CONCLUSION: The "noncognitive," or psychosocial, measures increased the magnitude of the relationships between the predictive and criterion measures of the students' academic performances, beyond the magnitude attained when only the conventional admission measures were used. Therefore, psychosocial measures should be considered as significant and unique predictors of performance in medical school.
PURPOSE: To investigate the incremental effects of selected psychosocial measures--beyond the effects of conventional admission measures--in predicting students' academic performances in medical school. METHODS: In 1989-90, 210 second-year students at Jefferson Medical College were each asked to complete 11 psychosocial questionnaires that were then used as predictors of performance measures in medical school. The students' scores on three subtests of the Medical College Admission Test (MCAT) were also used as predictors. Three composite measures of performance were used as the criterion measures: basic science examination grades, clinical examination grades, and ratings of clinical competence. A multiple regression algorithm (general linear model) was used for statistical analysis. RESULTS: The response rate was 83% (175 students). When the psychosocial measures were added to the statistical models in which the common variances of the MCAT scores were already determined, significant increments in the common variances were observed for two of the three performance measures: basic science grades and clinical examination grades. Whereas only 4% of the common variance in the ratings of clinical competence could be accounted for by the MCAT scores, 14% could be accounted for by the psychosocial measures. CONCLUSION: The "noncognitive," or psychosocial, measures increased the magnitude of the relationships between the predictive and criterion measures of the students' academic performances, beyond the magnitude attained when only the conventional admission measures were used. Therefore, psychosocial measures should be considered as significant and unique predictors of performance in medical school.
Authors: Marie A Chisholm-Burns; Christina A Spivey; Erin Sherwin; Jennifer Williams; Stephanie Phelps Journal: Am J Pharm Educ Date: 2019-08 Impact factor: 2.047
Authors: Aubree Worobetz; Petrus J Retief; Sinead Loughran; Jane Walsh; Monica Casey; Peter Hayes; Enrique García Bengoechea; Andrew O'Regan; Catherine Woods; Dervla Kelly; Raymond O Connor; Deirdre Mc Grath; Liam G Glynn Journal: BMC Med Educ Date: 2020-06-03 Impact factor: 2.463