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An innovative interactive medical student induction programme in paediatrics

Personal statements are widely used in medical schools alongside academic achievement as predictors of applicants’ performance in order to discriminate who should be selected or invited for interview and who should not. This requires an objective and transparent method for assessing personal statements in order to meet the General Medical Council’s (GMC) requirement that ‘‘selection will be valid, reliable and objective’’ (General Medical Council 2009). The literature does not provide sufficient information about personal statement scoring or the reliability of scoring methods. It has been suggested that ‘‘if personal statements could be systematically targeted at key questions and scored consistently, they might yield more information’’ (Murphy et al. 2009). To achieve a valid, reliable and objective method for scoring personal statements, we constructed an initial tool with 52 items based on a literature review. Each item measured a given component/criterion of the personal statement on a continuum ranging from strongly agree to strongly disagree. Next, we asked experts to review the tool, and to provide comments for each item. In addition, we asked them to add some items to our tool that we failed to include. Based on the experts’ comments, a new tool with 15 items was created on a continuum ranging from 1 to 5. In order to create a standardised tool, we asked experts to review each statement/item and rate how important it is in contributing towards effective medical student selection (1 representing low and 5 representing high). In addition, we asked them to consider two questions: (1) ‘‘Is the statement/item important?’’ (2) ‘‘Can this information be reliably scored from the personal statement?’’ We analysed the data of the new tool using the Rasch model in order to create a single-dimensional tool. After conducting iterative Rasch analyses and the examination of item characteristic curves, seven items were removed because they were either a misfit or they deviated away from the model curve. Following this, the remaining eight items showed that the tool fitted a unidimensional model. The reliability of eight items was 0.75, indicating that the tool worked satisfactorily. The functioning of response categories were investigated to obtain more information from the items. To ensure the final tool would be useful and functional, the content of eight items were reviewed and then finalised. In order to reduce cost for analysis, errors and the tedious task of data entry, an online version of the tool was developed.