The structured interview as a tool for predicting premature withdrawal from medical school

Abstract

A 1:1 matched case-control study was carried out to assess whether comments written about a candidate during a semi-structured interview can identify students likely to withdraw from a medical course better than global numerical scores. Fifty-nine students who withdrew from the undergraduate medical course at the University of Newcastle prior to completion were matched for sex, year and mode of entry into the course, prior academic qualifications and age at entry, with 59 students who had not discontinued or been excluded from the course. No significant differences were found between the numerical scores allocated for personal attributes to students who later withdrew from the course and those who continued. However, students who withdrew had statistically significantly more negative comments made about them at interview with respect to their supportive and encouraging behaviour (p = 0.04) and their motivation to become doctors (p = 0.05). Although no other comparisons reached statistical significance, students who withdrew consistently received more negative comments and fewer positive comments than their continuing peers. A stepwise logistic regression procedure identified the number of negative comments made by interviewers about a candidate on their supportive and encouraging behaviour as the only statistically significant predictor of later withdrawal (odds ratio 1.65 95% confidence interval 1.01-2.70).

Can we Improve on how we Select Medical Students?

“…There are some reports of association between clinical performance and admission interviews 55,56,60,61 , although others reveal no correlation 54,58 . In a school that carefully evaluates applicants, empathy and motivation to be a doctor were found particularly important in predicting both clinical and academic success 62 .…”

Medical school dropout - testing at admission versus selection by highest grades as predictors

“…2 The number of negative comments assigned by interviewers to the subscale for supportive and encouraging behaviour was found to be associated with dropout (OR = 1.65, 95% confidence interval [CI] 1.01-2.70). 2 This result was statistically significant at 0.05%, although it may have occurred purely by chance. By contrast, Urlings-Strop et al presented a more optimistic case for the protective effect of non-grade-based admission tests on student dropout.…”

“…1 Only two studies included in the review examined the association between non-grade-based admission criteria and dropout. 2,3 Powis et al examined 21 different admission interview subscales and subscores as predictors of dropout in a case-control study, and found only one of these to be significantly associated with dropout. 2 The number of negative comments assigned by interviewers to the subscale for supportive and encouraging behaviour was found to be associated with dropout (OR = 1.65, 95% confidence interval [CI] 1.01-2.70).…”

“…2,3 Powis et al examined 21 different admission interview subscales and subscores as predictors of dropout in a case-control study, and found only one of these to be significantly associated with dropout. 2 The number of negative comments assigned by interviewers to the subscale for supportive and encouraging behaviour was found to be associated with dropout (OR = 1.65, 95% confidence interval [CI] 1.01-2.70). 2 This result was statistically significant at 0.05%, although it may have occurred purely by chance.…”

An analysis of an admissions system: can performance in the first year of the dental course be predicted?

“…Researching the structured interview Powis et al 11 and Chapman 12 found no differences in interview numerical scores between those who completed the course and those who dropped-out but, those with negative written comments were more likely to drop-out. In this present study it appears that those with high interview scores, with better leadership experience, perform better at the end of Year 1.…”