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Preadmission schooling context helps to predict examination performance throughout medical school

Stringer, N., Chan, M., Bimpeh, Y., Chan, P. (2017) Preadmission schooling context helps to predict examination performance throughout medical school. Advances in Health Sciences Education, 22 (2). pp. 505-519. ISSN 1382-4996. (doi:10.1007/s10459-016-9714-5) (KAR id:78317)

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This study investigates the effects of socioeconomic status and schooling on the academic attainment of a cohort of students at a single medical school (N = 240). Partial least squares structural equation modelling was used to explore how students’ summative assessment scores over 4 years of medical school were affected by: attainment in secondary school examinations (GCSEs and A-levels); the Income Deprivation Affecting Children Index (IDACI) rank associated with students’ home postcodes; the performance of students’ A-level institutions, measured as the percentage of A-level students achieving 3 A-levels at AAB or higher in two or more facilitating subjects. The effects were consistent across time; the final linear regression model used students’ cumulative scores (the basis of the medical school’s UK Foundation Programme submission) as the dependent variable. The final model fit was quite poor (R2 = .184, n = 178). IDACI Rank was non-significant and excluded from the final model. Both GCSE (.340, p < .001) and A-level (.204, p < .005) scores were associated with increasing Cumulative Score; School Performance was associated with decreasing Cumulative Score (−.159, p < .05). This study confirmed the predictive validity of prior academic attainment and found the same inverse relationship between schooling and medical course performance as previous studies. The study found no evidence that socioeconomic background affects course performance; however, students admitted to medicine from poorly performing schools achieve higher academic attainment throughout the course than students admitted from better-performing schools with the same grades. Schooling could be taken into account for admissions purposes.

Item Type: Article
DOI/Identification number: 10.1007/s10459-016-9714-5
Uncontrolled keywords: Contextual data, Higher education admissions, Medical school admissions, Predictive validity, Widening participation, child, controlled study, dependent variable, education, genetic polymorphism, high school, human, linear regression analysis, major clinical study, medical school, medicine, mental capacity, partial least squares regression, predictive validity, social status, statistical model, student, achievement, education, female, male, medical school, medical student, socioeconomics, statistics and numerical data, Achievement, Educational Measurement, Female, Humans, Male, Schools, Medical, Socioeconomic Factors, Students, Medical
Divisions: Divisions > Division of Natural Sciences > Kent and Medway Medical School
Depositing User: Philip Chan
Date Deposited: 07 Nov 2019 11:09 UTC
Last Modified: 25 Nov 2021 16:06 UTC
Resource URI: (The current URI for this page, for reference purposes)
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