Physiotherapy · 2017
Identifying factors that predict attrition among first year physiotherapy students: a retrospective analysis.
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Ryan Jennifer M, Potier Tara, Sherwin Alison, Cassidy Elizabeth
Аннотация
BACKGROUND: A number of first year students leave physiotherapy programmes every year. A high attrition rate has implications for the student and the academic institution.
OBJECTIVES: To report the rate of attrition among first year physiotherapy students, and to identify contributing factor.
DESIGN: Retrospective analysis.
SETTING: University.
PARTICIPANTS: Electronic student records for enrolled students 2010 to 2013.
MEASURES: Independent variables; gender, age at entry, mode of admission, place of residence, ethnicity, fee status, level of education, disability, whether a student obtained a B in A level Biology, and whether a student repeated A level examinations. Logistic regression analysis was conducted to identify the relationship between independent variables and drop-out (failure to continue to the second year).
RESULTS: Data from 338 students were included in the analysis. The percentage drop-out was 17%; 38 students (11%) failed, and 20 students (6%) withdrew voluntarily. Black and Asian students had greater odds of drop-out for any reason (Odds Ratio (OR): 6.23; 95% Confidence Interval (CI) 1.79 to 21.63, and OR: 6.43; 95% CI: 3.03 to 13.68 respectively), and due to failure (OR: 5.50, 95% CI: 1.27 to 23.70, and OR: 7.19; 95% CI: 3.02 to 17.08, respectively) compared to white British students. Students who lived off-campus were more likely to withdraw from the programme irrespective of ethnicity (OR: 4.65; 95% CI: 1.41 to 15.34).
CONCLUSION: A significant number of students from ethnic minority backgrounds failed to progress. Specific strategies to retain students from ethnic minority backgrounds should be implemented. Students who live off-campus may be at high risk of drop-out; reasons for this should be investigated.
OBJECTIVES: To report the rate of attrition among first year physiotherapy students, and to identify contributing factor.
DESIGN: Retrospective analysis.
SETTING: University.
PARTICIPANTS: Electronic student records for enrolled students 2010 to 2013.
MEASURES: Independent variables; gender, age at entry, mode of admission, place of residence, ethnicity, fee status, level of education, disability, whether a student obtained a B in A level Biology, and whether a student repeated A level examinations. Logistic regression analysis was conducted to identify the relationship between independent variables and drop-out (failure to continue to the second year).
RESULTS: Data from 338 students were included in the analysis. The percentage drop-out was 17%; 38 students (11%) failed, and 20 students (6%) withdrew voluntarily. Black and Asian students had greater odds of drop-out for any reason (Odds Ratio (OR): 6.23; 95% Confidence Interval (CI) 1.79 to 21.63, and OR: 6.43; 95% CI: 3.03 to 13.68 respectively), and due to failure (OR: 5.50, 95% CI: 1.27 to 23.70, and OR: 7.19; 95% CI: 3.02 to 17.08, respectively) compared to white British students. Students who lived off-campus were more likely to withdraw from the programme irrespective of ethnicity (OR: 4.65; 95% CI: 1.41 to 15.34).
CONCLUSION: A significant number of students from ethnic minority backgrounds failed to progress. Specific strategies to retain students from ethnic minority backgrounds should be implemented. Students who live off-campus may be at high risk of drop-out; reasons for this should be investigated.