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The Use of Multi-Criteria Decision Analysis Weight Elicitation Techniques in Patients with Mild Cognitive Impairment

A Pilot Study

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Abstract

Objective: To test the applicability of multi-criteria decision analysis preference elicitation techniques in cognitively impaired individuals.

Method: A convenience sample of 16 cognitively impaired subjects and 12 healthy controls was asked to participate in a small pilot study. The subjects determined the relative importance of four decision criteria using five different weight elicitation techniques, namely simple multi-attribute rating technique, simple multi-attribute rating technique using swing weights, Kepner-Tregoe weighting, the analytical hierarchical process, and conjoint analysis.

Results: Conjoint analysis was judged to be the easiest method for weight elicitation in the control group (Z = 10.00; p = 0.04), while no significant differences in difficulty rating between methods was found in cognitively impaired subjects. Conjoint analysis elicitates weights and rankings significantly different from other methods. Subjectively, cognitively impaired subjects were positive about the use of the weight elicitation techniques. However, it seems the use of swing weights can result in the employment of shortcut strategies.

Conclusion: The results of this pilot study suggest that individuals with mild cognitive impairment are willing and able to use multi-criteria elicitation methods to determine criteria weights in a decision context, although no preference for a method was found. The same methodologic and practical issues can be identified in cognitively impaired individuals as in healthy controls and the choice of method is mostly determined by the decision context.

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Notes

  1. A rank reversal is when a criterion is ranked differently, depending on the weight elicitation method. For instance when result is ranked first (most important) using AHP, but is ranked second (2nd important) using CA a rank reversal occurs.

References

  1. Bishop AJ, Marteau TM, Armstrong D, et al. Women and health care professionals’ preferences for Down’s syndrome screening tests: a conjoint analysis study. BJOG 2004; 111: 775–9

    Article  PubMed  Google Scholar 

  2. Spencer K, Aitken D. Factors affecting women’s preference for type of prenatal screening test for chromosomal anomalies. Ultrasound Obstet Gynecol 2004; 24: 735–9

    Article  PubMed  CAS  Google Scholar 

  3. Aristides M, Chen J, Schulz M, et al. Conjoint analysis of a new chemotherapy: willingness to pay and preference for the features of raltitrexed versus standard therapy in advanced colorectal cancer. Pharmacoeconomics 2002; 20: 775–84

    Article  PubMed  Google Scholar 

  4. Fallowfield L, McGurk R, Dixon M. Same gain, less pain: potential patient preferences for adjuvant treatment in preme-nopausal women with early breast cancer. Eur J Cancer 2004; 40: 2403–10

    Article  PubMed  Google Scholar 

  5. Hummel JM, Snoek GJ, van Til JA, et al. A multicriteria decision analysis of augmentative treatment of upper limbs in persons with tetraplegia. J Rehabil Res Dev 2005; 42: 635–44

    Article  PubMed  Google Scholar 

  6. Robinson A, Thomson R. Variability in patient preferences for participating in medical decision making: implication for the use of decision support tools. Qual Health Care 2001; 10Suppl. 1: i34–8

    PubMed  Google Scholar 

  7. Frosch DL, Kaplan RM. Shared decision making in clinical medicine: past research and future directions. Am J Prev Med 1999; 17: 285–94

    Article  PubMed  CAS  Google Scholar 

  8. Coulter A. Partnerships with patients: the pros and cons of shared clinical decision-making. J Health Serv Res Policy 1997; 2: 112

    PubMed  CAS  Google Scholar 

  9. Ryan M, Scott DA, Reeves C, et al. Eliciting public preferences for healthcare: a systematic review of techniques. Health Technol Assess 2001; 5: 1–186

    PubMed  CAS  Google Scholar 

  10. Trevena L, Barratt A. Integrated decision making: definitions for a new discipline. Patient Educ Couns 2003; 50: 265–8

    Article  PubMed  Google Scholar 

  11. Edwards W, Barren FH. SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organ Behav Human Decis Process 1994; 60: 306–25

    Article  Google Scholar 

  12. Ryan M. Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation. Soc Sci Med 1999; 48: 535–46

    Article  PubMed  CAS  Google Scholar 

  13. Belton V, Stewart TJ. Multiple criteria decision analysis: an integrated approach. London: Kluwer Academic Publishers, 2003

    Google Scholar 

  14. von Nitzsch R, Weber M. The effect of attribute ranges on weights in multiattribute utility measurements. Manage Sci 1993; 39: 937–43

    Article  Google Scholar 

  15. Weber M, Borcherding K. Behavioral influences on weight judgments in multiattribute decision making. Eur J Operat Res 1993; 67: 1–12

    Article  Google Scholar 

  16. Williams ML, Dennis AR, Stam A, et al. The impact of DSS use and information load on errors and decision quality. Eur J Operat Res 2007; 176: 468–81

    Article  Google Scholar 

  17. Barry MJ. Health decision aids to facilitate shared decision making in office practice. Ann Intern Med 2002; 136: 127–35

    PubMed  Google Scholar 

  18. Feldman-Stewart D, Brundage MD. Challenges for designing and implementing decision aids. Patient Educ Couns 2004; 54: 265–73

    Article  PubMed  Google Scholar 

  19. Dolan JG. Are patients capable of using the analytic hierarchy process and willing to use it to help make clinical decisions? Med Decis Making 1995; 15: 76–80

    Article  PubMed  CAS  Google Scholar 

  20. Kepner CH, Tregoe BB. The new rational manager. Skillman (NJ): Princeton Research Press, 1981

    Google Scholar 

  21. Saaty TL. How to make a decision: the analytic hierarchy process. Eur J Operat Res 1990; 48: 9–26

    Article  Google Scholar 

  22. Ryan M, Farrar S. Using conjoint analysis to elicit preferences for health care. BMJ 2000; 320: 1530–3

    Article  PubMed  CAS  Google Scholar 

  23. Seymour DG, Ball AE, Russell EM, et al. Problems in using health survey questionnaires in older patients with physical disabilities: the reliability and validity of the SF-36 and the effect of cognitive impairment. J Eval Clin Prac 2001; 7: 411–8

    Article  CAS  Google Scholar 

  24. Chibnall JT, Tait RC. Pain assessment in cognitively impaired and unimpaired older adults: a comparison of four scales. Pain 2001; 92: 173–86

    Article  PubMed  CAS  Google Scholar 

  25. Dyer RF, Forman EH. Group decision support with the analytic hierarchy process. Decision Support Systems 1992; 8: 99–124

    Article  Google Scholar 

  26. Shoemaker PJH, Waid CC. An experimental comparison of different approaches to determining weights in additive utility models. Manage Sci 1982; 28: 182–96

    Article  Google Scholar 

  27. Pöyhönen M, Hämäläinen RP. On the convergence of multiattribute weighting methods. Eur J Operat Res 2001; 129: 569–85

    Article  Google Scholar 

  28. Srivastava J, Connolly T, Beach LR. Do ranks suffice? A comparison of alternative weighting approaches in value elicitation. Organ Behav Human Decis Process 1995; 63: 112–6

    Article  Google Scholar 

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Acknowledgments

This research was committed under a grant assigned by the Dutch organization for health research and health innovation, ZONMW. The authors have no conflicts of interest to declare.

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Correspondence to Janine A. van Til.

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van Til, J.A., Dolan, J.G., Stiggelbout, A.M. et al. The Use of Multi-Criteria Decision Analysis Weight Elicitation Techniques in Patients with Mild Cognitive Impairment. Patient-Patient-Centered-Outcome-Res 1, 127–135 (2008). https://doi.org/10.2165/01312067-200801020-00008

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