RESEARCH PAPER
Validation of a Self-report Tool to Measure Self-study in Medical School – Applying the Triads Method
 
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1
Department of Public Health and Forensic Sciences and Medical Education, Faculty of Medicine, University of Porto, PORTUGAL
2
Undergraduate Education Department, Institute of Biomedical Sciences Abel Salazar, University of Porto, PORTUGAL
Publish date: 2018-07-12
 
EURASIA J. Math., Sci Tech. Ed 2018;14(10):em1592
KEYWORDS
ABSTRACT
Many students have difficulty mastering the demands of medical courses. Applying the Triads method, the present research compares the validity of three self-reported methods that measure self-study hours in a medical course. Thirty randomly selected students participated in this study. Three surveys were developed: continuous weekly records (WR) and two end-course retrospective self-reported surveys, AR (asking average hours/week during academic year) and FR (asking study frequency throughout academic year and mean hours of studying on a given day). Validity coefficients (VCs), which measure the correlation between observed and “true” self-study, were estimated using the Triads method. The estimated VC was 0.86, 0.94 and 0.87 for WR, FR and AR, respectively. Therefore, given the demands of WR and, since FR showed more accuracy than AR, we propose a novel method, FR, to retrospectively estimate self-study in a medical course.
 
REFERENCES (26)
1.
Aherne, D., Farrant, K., Hickey, L., Hickey, E., McGrath, L., & McGrath, D. (2016). Mindfulness based stress reduction for medical students: optimising student satisfaction and engagement. BMC Medical Education, 16(1), 209. https://doi.org/10.1186/s12909....
 
2.
Barbosa, J., Silva, Á., Ferreira, M. A., & Severo, M. (2016). Transition from Secondary School to Medical School: The Role of Self-Study and Self-Regulated Learning Skills in Freshman Burnout. Acta Médica Portuguesa, 29(12), 803-808. https://doi.org/10.20344/amp.8....
 
3.
Bologna Declaration. (1999). The Bologna Declaration of 19 June 1999. Joint declaration of the European Ministers of Education.
 
4.
Bowyer, K. (2012). A model of student workload. Journal of Higher Education Policy and Management, 34(3), 239-258. https://doi.org/10.1080/136008....
 
5.
Cohen-Schotanus, J. (1999). Student assessment and examination rules. Medical Teacher, 21(3), 318-321. https://doi.org/10.1080/014215....
 
6.
Cope, C., & Staehr, L. (2005). Improving students’ learning approaches through intervention in an information systems learning environment. Studies in Higher Education, 30(2), 181-197. https://doi.org/10.1080/030750....
 
7.
Dolmans, D., Wolfhagen, H., Essed, G., Scherpbier, A., & Van Der Vleuten, C. (2001). Students’ perceptions of time spent during clinical rotations. Medical teacher, 23(5), 471-475. https://doi.org/10.1080/014215....
 
8.
González, J., & Wagenaar, R. (2003). Tuning educational structures in Europe: University of Deusto Final report. Phase one. Bilbao.
 
9.
Guillaume, D. W., & Khachikian, C. S. (2011). The effect of time‐on‐task on student grades and grade expectations. Assessment & Evaluation in Higher Education, 36(3), 251-261. https://doi.org/10.1080/026029....
 
10.
Jacobs, S. R., & Dodd, D. (2003). Student burnout as a function of personality, social support, and workload. Journal of College Student Development, 44(3), 291-303. https://doi.org/10.1353/csd.20....
 
11.
Kaaks, R. (1997). Biochemical markers as additional measurements in studies of the accuracy of dietary questionnaire measurements: conceptual issues. The American Journal of Clinical Nutrition, 65(4), 1232S-1239S. https://doi.org/10.1093/ajcn/6....
 
12.
Karjalainen, A., Alha, K., & Jutila, S. (2006). Give me time to think: determining student workload in higher education: Oulu, Finland: Oulu University Press.
 
13.
Kember, D. (2004). Interpreting student workload and the factors which shape students’ perceptions of their workload. Studies in Higher Education, 29(2), 165-184. https://doi.org/10.1080/030750....
 
14.
Kember, D., Ng, S., Tse, H., Wong, E. T., & Pomfret, M. (1996). An examination of the interrelationships between workload, study time, learning approaches and academic outcomes. Studies in Higher Education, 21(3), 347-358. https://doi.org/10.1080/030750....
 
15.
Kerdijk, W., Cohen‐Schotanus, J., Mulder, B., Muntinghe, F. L., & Tio, R. A. (2015). Cumulative versus end‐of‐course assessment: effects on self‐study time and test performance. Medical Education, 49(7), 709-716. https://doi.org/10.1111/medu.1....
 
16.
Kerdijk, W., Tio, R. A., Mulder, B. F., & Cohen-Schotanus, J. (2013). Cumulative assessment: strategic choices to influence students’ study effort. BMC Medical Education, 13(1), 172. https://doi.org/10.1186/1472-6....
 
17.
Lemanski, C. (2011). Access and assessment? Incentives for independent study. Assessment & Evaluation in Higher Education, 36(5), 565-581. https://doi.org/10.1080/026029....
 
18.
McNaughton, S., Marks, G., Gaffney, P., Williams, G., & Green, A. (2005). Validation of a food-frequency questionnaire assessment of carotenoid and vitamin E intake using weighed food records and plasma biomarkers: the method of triads model. European Journal of Clinical Nutrition, 59(2), 211-218. https://doi.org/10.1038/sj.ejc....
 
19.
Mueller, S., Weichert, N., Stoecklein, V., Hammitzsch, A., Pascuito, G., Krug, C., . . . Schmidmaier, R. (2011). Evaluation of effectiveness of instruction and study habits in two consecutive clinical semesters of the medical curriculum munich (MeCuM) reveals the need for more time for self study and higher frequency of assessment. BMC Medical Education, 11(1), 62. https://doi.org/10.1186/1472-6....
 
20.
Ocke, M., & Kaaks, R. J. (1997). Biochemical markers as additional measurements in dietary validity studies: application of the method of triads with examples from the European Prospective Investigation into Cancer and Nutrition. The American Journal of Clinical Nutrition, 65(4), 1240S-1245S. https://doi.org/10.1093/ajcn/6....
 
21.
Pogacnik, M., Juznic, P., Kosorok-Drobnic, M., Pogacnik, A., Cestnik, V., Kogovsek, J., . . . Fernandes, T. (2004). An attempt to estimate students’ workload. Journal of Veterinary Medical Education, 31, 255-260. https://doi.org/10.3138/jvme.3....
 
22.
Spiegelman, D., Schneeweiss, S., & McDermott, A. (1997). Measurement error correction for logistic regression models with an “alloyed gold standard”. American Journal of Epidemiology, 145(2), 184-196. https://doi.org/10.1093/oxford....
 
23.
Van den Hurk, M., Wolfhagen, H., Dolmans, D., & Van der Vleuten, C. (1998). The relation between time spent on individual study and academic achievement in a problem-based curriculum. Advances in Health Sciences Education, 3(1), 43-49. https://doi.org/10.1023/A:1009....
 
24.
Wilkinson, T. J., Wells, J. E., & Bushnell, J. A. (2005). Using a diary to quantify learning activities. Medical Education, 39(7), 657-664. https://doi.org/10.1111/j.1365....
 
25.
Woodley, A., & Parlett, M. (1983). Student Drop-Out. Teaching at a Distance, 24, 2-23.
 
26.
Yokota, R. T. d. C., Miyazaki, E. S., & Ito, M. K. (2010). Applying the triads method in the validation of dietary intake using biomarkers. Cadernos de Saude Publica, 26(11), 2027-2037. https://doi.org/10.1590/S0102-....
 
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