Development and Validation of the Shared Decision Making Questionnaire Using Rasch Model
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Abstract
Objective: To develop and validate the questionnaire measuring shared decision making (SDM) between patients and healthcare professional from patient’s perspective. Methods: The first draft of the SDM questionnaire was developed based on steps of SDM process and its face validity was assessed using experts’ opinion. Index of item objective congruence ranged 0.67-1.00. The final version with 17 items was administered in 240 patients from 4 medical clinics including 1) outpatient department 2) inpatient department 3) accident and emergency department and 4) chronic non-communicable disease clinic. Subsequently, data were analyzed using the Rasch model. Results: The questionnaire showed unidimensionality and local independence. The reliability tests unveiled that person reliability, person separation index, and alpha reliability were 0.86, 2.45 and 0.92 respectively, which were regarded as acceptable. Item reliability was 0.86 and item separation was 2.52. Test of item fit statistics revealed that 15 items (88.24%) had item fit statistics ranged between 0.60-1.40. After combining 5 response categories to 3 categories and excluding 28 mis-fitted persons (11.67%) from the Rasch model, the reliability tests unveiled item reliability and item separation increased, but were marginally below the acceptable cut-off value. Person reliability, person separation index, and alpha reliability were 0.85, 2.39 and 0.92 respectively. Item reliability was 0.88 and item separation was 2.74. Item fit statistics of 12 items (70.59%) ranged between 0.60-1.27. Conclusion: The SDM questionnaire has unidimensionality and local independence with high validity and reliability. However, it should be further tested in a larger number of patients.
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ผลการวิจัยและความคิดเห็นที่ปรากฏในบทความถือเป็นความคิดเห็นและอยู่ในความรับผิดชอบของผู้นิพนธ์ มิใช่ความเห็นหรือความรับผิดชอบของกองบรรณาธิการ หรือคณะเภสัชศาสตร์ มหาวิทยาลัยสงขลานครินทร์ ทั้งนี้ไม่รวมความผิดพลาดอันเกิดจากการพิมพ์ บทความที่ได้รับการเผยแพร่โดยวารสารเภสัชกรรมไทยถือเป็นสิทธิ์ของวารสารฯ
References
2. Charles C, Gafni A, Whelan T. Shared decision-making in the medical encounter: What does it mean? (or it takes at least two to tango). Soc Sci Med 1997; 44: 681-92.
3. Brennan B, Holly M. Interprofessional collaboration in health care: Lessons to be learned from competitive sports. Can Pharm J 2015; 148: 176-9.
4. Haggerty JL, Reid RJ, Freeman GK, Starfield BH, Adair CE, McKendry R. Continuity of care: a multidisciplinary review. BMJ 2003; 327: 1219-21.
5. Scholl I, Koelewijn-van Loon M, Sepucha K, Elwyn G, Légaré F, Härter M, et al. Measurement of shared decision making–a review of instruments. Z Evid Fortbild Qual Gesundhwes 2011; 105: 313-24.
6. Elwyn G, Edwards A, Wensing M, Hood K, Atwell C, Grol R. Shared decision-making: developing the OPTION scale for measuring patient involvement. Qual Saf Health Care 2003; 12: 93-9.
7. Lerman CE, Brody DS, Caputo GC, Smith DG, Lazaro CG, Wolfson HG. Patient’s perceived involvement in care scale: Relationship to attitudes about illness and medical care. J Gen Intern Med 1990; 5: 29-33.
8. Kriston L, Scholl I, Hölzel L, Simon D, Loh A, Härter M. The 9-item Shared Decision Making Questionnaire (SDM-Q-9): Development and psy chometric properties in a primary care sample. Patient Educ Couns 2010; 80: 94-9.
9. Elwyn G, Miron-Shatz T. Deliberation before determination: The definition and evaluation of good decision making. Health Expect 2010 Jun; 13: 139-47.
10. NHS Organisations. Measuring shared decision making: A review of research evidence [online]. 2012 (cited Apr 1, 2015). Available from: www.eng land.nhs.uk/wp-content/uploads/2013/08/7sdm-rep ort.pdf.
11. Linacre JM. Understanding Rasch measurement: Optimizing rating scale category effectiveness. J Appl Meas 2002; 3: 85-106.
12. Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns 2006; 60: 301-12.
13. Guntayoung C, Chinchai S. The content validity and test-retest reliability of the developmental visual perception test (DTVP-2) in Thai children. International Journal of
Medicine and Pharmaceuti cal Sciences 2013; 3: 1-6.
14. Meijer RR, Sijtsma K. Methodology review: Evalua ting person fit. Appl Psychol Meas 2001; 25: 107-35.
15. DeMars C. Measuring higher education outcomes with a multidimensional Rasch model. J Appl Meas 2004; 5: 350-61.
16. Linacre JM. Fit diagnosis: Infit outfit mean-square standardized [online]. 1999 (cited Apr 1, 2018).
17. Bond T, Fox C. Applying the Rasch model: Fundamental measurement in the human sciences. 2nd ed. Mahwah: Lawrence Erlbaum Associates; 2007.
18. Linacre JM. Reliability and separation of measures [online]. 1999 (cited May 12, 2016). Available from: www.winsteps.com/winman/reliability.htm.
19. Smith EV. Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. J Appl Meas 2002; 3: 205-31.
20. Linacre JM. Data variance explained by Rasch measures. Rasch Measurement Transactions 2006 ; 20: 1045.
21. Embetson SE, Reise SP. Item response theory for psychologists. Mahwah: New Jersey, L. Erlbaum Associates, 2000.
22. Wang Z, Zhou J, Luo X, Xu Y, She X, Chen L, et al. Rasch analysis of the Adult Strabismus Quality of Life Questionnaire (AS-20) among Chinese adult patients with strabismus. PLOS ONE 2015; 10: e0142188. doi:10.1371/journal.pone.0142188.
23. Tellez A, Cadena CHG, Corral-Verdugo V. Effect size, confidence intervals and statistical power in psychological research. Psychology in Russia: State of the Art 2015; 8: 27-46.
24. Fox CM, Jones JA. Uses of Rasch modeling in counseling psychology research. J Couns Psychol 1998; 45: 30-45.
25. Linacre JM. Small sample size, sample size and item calibration (or person measure) stability [online]. 1998 (cited Sep 1, 2018). Available from: www.rasch.org/rmt/rmt74m.htm.
