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2013, Number 4

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Gac Med Mex 2013; 149 (4)

Clinical learning environments|Medical specialties|Reliability|Construct validity|

Hamui SA, Anzarut CM , de la Cruz FG, Ramírez ROF , Lavalle MC, Vilar PP

Language: Spanish
References: 20
Page: 394-405
PDF size: 107.25 Kb.


ABSTRACT

Introduction: Clinical education is an essential component of medical training and takes place in relatively adequate learning environments. Objective: Build and validate an instrument specific for the assessment of factors influencing a clinical learning environment. Material and methods: A Likert-type questionnaire was designed and its content was validated, while statistical trials were applied to it to determine its psychometric properties. The instrument was refined and assessed twice (a pilot of 122 cases on October 2011 and the study of 4,189 PUEM residents on March 2012). It consists of 28 items, distributed in four dimensions: interpersonal relations (IR), teaching processes (TP), institutional culture (IC), and service dynamics (SD). Results: Cronbach’s α of the whole pilot questionnaire after item refinement and 4,189 case study was 0.94 and 0.96, respectively. The percentage of total variance explained by the first component was 48 and 46%, respectively. Conclusions: The reliability and validity of the whole questionnaire and by dimension was adjusted to assess clinical learning environments in Mexican contexts and allows ranking specialized medical departments.


REFERENCES

  1. Isba R, Boor K. Creating a learning environment. In: Dornan T, Mann KI, Scherpbier A, Spencer J, eds. Medical education. Theory and practice. China: Churchill Livingstone - Elsevier. 2011. p. 99-114.

  2. Frenk J, Chen L, Bhutta ZA, et al. Health professionals for a new century: transforming education to strengthen health systems in an interdependent world. The Lancet Commissions. Lancet. 2010;29:1- 36 (on line).

  3. Cassar K. Development of an instrument to measure the surgical operating theatre learning environment as perceived by basic surgical trainees. Med Teach. 2004;26(3):260-4.

  4. Felleti GI, Clarke RM. Construct validity of a learning environment survey for medical schools. Educ Psychol Meas. 1981;41:875-82.

  5. Pololi L, Price J. Validation and use of an instrument to measure the learning environment as perceived by medical students. Teach Learn Med. 2000;12(4):201-7.

  6. Roff S, McAleer S, Skinner A. Development and validation of an instrument to measure the postgraduate clinical learning and teaching educational environments for hospital-based junior doctors in the UK. Med Teach. 2005;27(4):326-31.

  7. Boor K, Scheele F, Van der Vleuten CPM, Scherpbier AJJ, Teunissen PW, Sijtsma K. Psychometric properties of an instrument to measure clinical learning environments. Med Educ. 2007;41:92-9.

  8. Tojuda Y, Goto E, Otaki J, et al. Educational environment of university and non university hospitals in Japan. Int J Med Educ. 2010;1:10-4.

  9. Van der Hem-Stokroos HH, Daelmans HEM, Van der Vleuten CPM, Haarman JHTHM, Scherpbier AJJA. A qualitative study of constructive clinical learning experiences. Med Teach. 2003;25(2):120-6.

  10. Boor K, Scheele F, Van der Vleuten CPM, Teunissen PW, Der Breejen EME, Scherpbier AJJA. How undergraduate clinical learning climates differ: a multi-method case study. Med Educ. 2008;42:1029-36.

  11. Dornan T, Boshuizen H, King N, Scherpbier A. Experience-based learning: a model linking the processes and outcomes of medical students’ workplace learning. Med Educ. 2007;41(1):84-91.

  12. Fuller A, Unwin L, Learning as apprentices in the contemporary UK workplace: creating and managing expansive and restrictive participation. J Educ Work. 2003;16(4):407-26.

  13. Boor K. The clinical learning climate. Amsterdam: VU Medical Center; 2009.

  14. Tryfos P. Methods for business analysis and forecasting: text and cases. Vol 4. Toronto: John Wiley & Sons; 1998. p. 592. http://www.yorku.ca/ ptryfos/f1400.pdf.

  15. Efron B, Tibshirani R. Boostrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Statistical Science. 1986;1(1):54-77. http://matthieucheminresearch.mcgill.ca/ECON742/paper/ efron.pdf.

  16. Efron BA. The Jackknife, the Bootstrap, and other resampling plans. CBMSNSF Regional Conference Series in Applied Mathematics; 1982; p. 96.

  17. Chernick MR. Bootstrap methods: a guide for practitioners and researchers. John Wiley & Sons; 2007. p. 400.

  18. Flury B. Common principal components and related multivariate models. Wiley; 1988. p. 258.

  19. Mulaik SA. Foundations of factor analysis. Chapman & Hall/CRC; 2009. p. 548.

  20. Jolliffe IT. Principal component analysis. Springer; 2002. p. 487.




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