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What impacts students’ satisfaction the most from Medicine Student Experience Questionnaire in Australia: a validity study
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Pin-Hsiang Huang
, Gary Velan , Greg Smith , Melanie Fentoullis , Sean Edward Kennedy , Karen Jane Gibson , Kerry Uebel , Boaz Shulruf
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J Educ Eval Health Prof. 2023;20:2. Published online January 18, 2023
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DOI: https://doi.org/10.3352/jeehp.2023.20.2
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Abstract
PDF Supplementary Material
- Purpose
This study evaluated the validity of student feedback derived from Medicine Student Experience Questionnaire (MedSEQ), as well as the predictors of students’ satisfaction in the Medicine program.
Methods Data from MedSEQ applying to the University of New South Wales Medicine program in 2017, 2019, and 2021 were analyzed. Confirmatory factor analysis (CFA) and Cronbach’s α were used to assess the construct validity and reliability of MedSEQ respectively. Hierarchical multiple linear regressions were used to identify the factors that most impact students’ overall satisfaction with the program.
Results A total of 1,719 students (34.50%) responded to MedSEQ. CFA showed good fit indices (root mean square error of approximation=0.051; comparative fit index=0.939; chi-square/degrees of freedom=6.429). All factors yielded good (α>0.7) or very good (α>0.8) levels of reliability, except the “online resources” factor, which had acceptable reliability (α=0.687). A multiple linear regression model with only demographic characteristics explained 3.8% of the variance in students’ overall satisfaction, whereas the model adding 8 domains from MedSEQ explained 40%, indicating that 36.2% of the variance was attributable to students’ experience across the 8 domains. Three domains had the strongest impact on overall satisfaction: “being cared for,” “satisfaction with teaching,” and “satisfaction with assessment” (β=0.327, 0.148, 0.148, respectively; all with P<0.001).
Conclusion MedSEQ has good construct validity and high reliability, reflecting students’ satisfaction with the Medicine program. Key factors impacting students’ satisfaction are the perception of being cared for, quality teaching irrespective of the mode of delivery and fair assessment tasks which enhance learning.
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- Mental health and quality of life across 6 years of medical training: A year-by-year analysis
Natalia de Castro Pecci Maddalena, Alessandra Lamas Granero Lucchetti, Ivana Lucia Damasio Moutinho, Oscarina da Silva Ezequiel, Giancarlo Lucchetti International Journal of Social Psychiatry.2024; 70(2): 298. CrossRef
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Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study
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Boaz Shulruf
, Gary Mayer Velan , Sean Edward Kennedy
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J Educ Eval Health Prof. 2022;19:31. Published online November 28, 2022
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DOI: https://doi.org/10.3352/jeehp.2022.19.31
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2,774
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156
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1
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Abstract
PDF Supplementary Material
- Purpose
The study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Tertiary Admission Rank; (2) structured interview focusing on interpersonal interaction and concerns should the applicants become students; and (3) embracing interviewers’ diverse perspectives.
Methods Data from 5 cohorts of students were analyzed, comparing outcomes of the second year in the medicine program of 4 cohorts of the old selection process and 1 of the new process. The main analysis comprised multiple linear regression models for predicting academic, clinical, and professional outcomes, by section tools and demographic variables.
Results Selection interview marks from the new interview (512 applicants, 2 interviewers each) were analyzed for inter-rater reliability, which identified a high level of agreement (kappa=0.639). No such analysis was possible for the old interview since it required interviewers to reach a consensus. Multivariate linear regression models utilizing outcomes for 5 cohorts (N=905) revealed that the new selection process was much more effective in predicting academic and clinical achievement in the program (R2=9.4%–17.8% vs. R2=1.5%–8.4%).
Conclusion The results suggest that the medical student selection process can be significantly enhanced by employing a non-compensatory selection algorithm; and using a structured interview focusing on interpersonal interaction and concerns should the applicants become students; as well as embracing interviewers’ diverse perspectives.
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Citations
Citations to this article as recorded by 
- Insights into undergraduate medical student selection tools: a systematic review and meta-analysis
Pin-Hsiang Huang, Arash Arianpoor, Silas Taylor, Jenzel Gonzales, Boaz Shulruf Journal of Educational Evaluation for Health Professions.2024; 21: 22. CrossRef
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