RESUMO
Background: Academic performance is an important issue for universities. Andrés Bello University's academic risk factors identification system focuses on performance variables, such as scores on university entrance examinations and scores in high school. Since medical students have high entrance scores, their academic risk is not detected. Aim: To create an academic risk predictive model for medical students using neuro-didactic variables. Material and Methods: Prospective cohort study with 189 first-year medical students. After signing the informed consent, questionnaires were applied to measure variables related to executive functions and reward system. These were analyzed with logistic regression models and classification trees. Results: The variables that modified the probability of academic risk were identified by the logistic regression model with a global accuracy of 0.74 and by the algorithm of the classification tree, with a sensitivity and specificity of 68 and 79% respectively. The identified variables for executive functions, were the scores obtained in the science, mathematics, and emotional intelligence tests of the university entrance examination. Family pressure and who they live with, were variables associated with the reward system. Conclusions: A low score in the science test of the university entrance examination is the variable that initially determines the probability of academic risk. It is modulated by variables related to reward system. In the most complex branch, the terminal node is represented by the emotional intelligence variable of executive functions.
RESUMO
BACKGROUND: Academic performance is an important issue for universities. Andrés Bello University's academic risk factors identification system focuses on performance variables, such as scores on university entrance examinations and scores in high school. Since medical students have high entrance scores, their academic risk is not detected. AIM: To create an academic risk predictive model for medical students using neuro-didactic variables. MATERIAL AND METHODS: Prospective cohort study with 189 first-year medical students. After signing the informed consent, questionnaires were applied to measure variables related to executive functions and reward system. These were analyzed with logistic regression models and classification trees. RESULTS: The variables that modified the probability of academic risk were identified by the logistic regression model with a global accuracy of 0.74 and by the algorithm of the classification tree, with a sensitivity and specificity of 68 and 79% respectively. The identified variables for executive functions, were the scores obtained in the science, mathematics, and emotional intelligence tests of the university entrance examination. Family pressure and who they live with, were variables associated with the reward system. CONCLUSIONS: A low score in the science test of the university entrance examination is the variable that initially determines the probability of academic risk. It is modulated by variables related to reward system. In the most complex branch, the terminal node is represented by the emotional intelligence variable of executive functions.
Assuntos
Desempenho Acadêmico , Estudantes de Medicina , Avaliação Educacional , Humanos , Estudos Prospectivos , Fatores de Risco , Faculdades de Medicina , Estudantes de Medicina/psicologiaRESUMO
Background Educational inclusion, a concept that has changed over time, is becoming relevant. It initially considered only disability and now contemplates education for all people. Educational inclusion has special relevance in health care workers' training, who will have direct contact with heterogeneous populations, where diversity-oriented treatments are required. Aim To describe how diversity is integrated into health care training in a clinical context. Material and Methods qualitative study, based on Grounded Theory. Two group interviews and thirteen semi-structured interviews were conducted among 11 teachers and 25 students of health careers. Data was analyzed using Atlas-ti 7.5.2. A constant comparison method, reaching an axial coding level, was used. Results The category of training in health careers in the context of diversity emerged. It is a process that operates in cognitive, affective and behavioral dimensions. It accounts for the diversity of system actors and the model of a health professional and teacher facing diversity. Conclusions These dimensions should be understood during clinical training. Socio-cultural diversity encompassing gender, sex, ethnicity, religion and disability should be considered. Therefore, educational inclusion is an important issue to be considered by universities.
