Abbiati Milena, Baroffio Anne, Gerbase Margaret W
Faculty of Medicine, Unit of Development and Research in Medical Education, University of Geneva, Geneva, Switzerland.
Faculty of Medicine, Unit of Development and Research in Medical Education, University of Geneva, Geneva, Switzerland;
Med Educ Online. 2016 Apr 12;21:29705. doi: 10.3402/meo.v21.29705. eCollection 2016.
A consistent body of literature highlights the importance of a broader approach to select medical school candidates both assessing cognitive capacity and individual characteristics. However, selection in a great number of medical schools worldwide is still based on knowledge exams, a procedure that might neglect students with needed personal characteristics for future medical practice. We investigated whether the personal profile of students selected through a knowledge-based exam differed from those not selected.
Students applying for medical school (N=311) completed questionnaires assessing motivations for becoming a doctor, learning approaches, personality traits, empathy, and coping styles. Selection was based on the results of MCQ tests. Principal component analysis was used to draw a profile of the students. Differences between selected and non-selected students were examined by Multivariate ANOVAs, and their impact on selection by logistic regression analysis.
Students demonstrating a profile of diligence with higher conscientiousness, deep learning approach, and task-focused coping were more frequently selected (p=0.01). Other personal characteristics such as motivation, sociability, and empathy did not significantly differ, comparing selected and non-selected students.
Selection through a knowledge-based exam privileged diligent students. It did neither advantage nor preclude candidates with a more humane profile.
大量文献一致强调，采用更广泛的方法来选拔医学院校候选人具有重要意义，这种方法既要评估认知能力，也要考量个人特质。然而，全球众多医学院校的选拔仍基于知识考试，这一过程可能会忽视那些具备未来医疗实践所需个人特质的学生。我们调查了通过基于知识的考试选拔出来的学生的个人概况与未被选拔的学生是否存在差异。
申请医学院校的学生（N = 311）完成了问卷调查，评估他们成为医生的动机、学习方法、性格特质、同理心和应对方式。选拔基于多项选择题测试的结果。主成分分析用于勾勒学生的概况。通过多变量方差分析检验入选学生和未入选学生之间的差异，并通过逻辑回归分析检验这些差异对选拔的影响。
展现出勤奋特质、具有更高尽责性、采用深度学习方法且以任务为导向应对的学生更常被选中（p = 0.01）。将入选学生和未入选学生进行比较，其他个人特质，如动机、社交能力和同理心，并无显著差异。
通过基于知识的考试进行选拔使勤奋的学生具有优势。它既没有使具有更具人文特质的候选人受益，也没有将他们排除在外。
