PREDICTIVE ABILITY AND STAKEHOLDERS’ PERCEPTIONS OF THE SELECTION TOOLS FOR MBBS IN WOMEN MEDICAL COLLEGE: A MIXED METHODS STUDY - Qazi, Muhammad Abdullah; Anwar, Jasim; Moffat, Mandy (Journal of Ayub Medical College Abbottabad, 2020)
Background: The selection criteria for entry into the MBBS programme used by Women Medical College (WMC) includes previous academic achievements, namely Secondary School Certificate (SSC) and Higher Secondary Certificate (HSC), and the Medical and Dental College Admission Test (MDCAT). This study determined the predictive validity of these selection tools and explored the perceptions of stakeholders regarding the selection process and the use of selection tools in WMC. Methods: This study utilized both quantitative and qualitative methods. Quantitative methods involved a retrospective cohort study design to determine the statistical correlation between the performance of candidates in the selection tools and their subsequent academic achievements at medical college. This consisted of data collected from three cohorts (n=186) of students who graduated in 2014, 2015 and 2016. Qualitative methods of the study explored the perceptions of stakeholders through purposive sampling using face-to-face semi-structured interviews, which were analysed using thematic analysis. Results: The study showed very weak correlations of SSC with performance in the fourth professional examination undertaken by the students and HSC with performance inthe first andsecond professional examinations. MDCAT did not correlate with any professional examination. Qualitative analysis identified three emerging themes; a) lack of standardization, b) fairness of selection criteria, and c) assessment of non-cognitive attributes. Conclusion: The selection tools showed poor predictive ability for the performance of students in the medical college. Standardizing the selection tools and including an assessment of non-cognitive attributes in the selection criteria is suggested. Keywords: Medical College; Admission Criteria; Selection Tools; Predictive Validity; Perceptions