Volume 17, Issue 6 pp. 840-851
Original Article

Elderly patients' experiences using adaptive conjoint analysis software as a decision aid for osteoarthritis of the knee

Donna Rochon PhD

Corresponding Author

Donna Rochon PhD

Unaffiliated

Correspondence

Donna Rochon PhD

5247 Wigton Dr.

Houston

TX 77096

USA

E-mail: [email protected]

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Jan M. Eberth PhD

Jan M. Eberth PhD

Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

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Liana Fraenkel MD, MPH

Liana Fraenkel MD, MPH

Yale University School of Medicine, VA Connecticut Healthcare System, New Haven, CT, USA

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Robert J. Volk PhD

Robert J. Volk PhD

Department of General Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

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Simon N. Whitney MD, JD

Simon N. Whitney MD, JD

Department of Family and Community Medicine, Baylor College of Medicine, Houston, TX, USA

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First published: 20 September 2012
Citations: 13
The authors have no conflict of interest to report.

Abstract

Background

Decision making in knee osteoarthritis, with many treatment options, challenges patients and physicians alike. Unfortunately, physicians cannot describe in detail each treatment's benefits and risks. One promising adjunct to decision making in osteoarthritis is adaptive conjoint analysis (ACA).

Objective

To obtain insight into the experiences of elderly patients who use adaptive conjoint analysis to explore treatment options for their osteoarthritis.

Design

Participants, all 65 and older, completed an ACA decision aid exploring their preferences with regard to the underlying attributes of osteoarthritis interventions. We used focus groups to obtain insight into their experiences using this software.

Results

Content analysis distributed our participants' concerns into five areas. The predicted preferred treatment usually agreed with the individual's preference, but our participants experienced difficulty in four other domains: the choices presented by the software were sometimes confusing, the treatments presented were not the treatments of most interest, the researchers' claims about treatment characteristics were unpersuasive and cumulative overload sometimes developed.

Conclusion

Adaptive conjoint analysis presented special challenges to our elderly participants; we believe that their relatively low level of computer comfort was a significant contributor to these problems. We suggest that other researchers choose the software's treatments and present the treatment attributes with care. The next and equally vital step is to educate participants about what to expect, including the limitations in choice and apparent arbitrariness of the trade-offs presented by the software. Providing participants with a sample ACA task before undertaking the study task may further improve participant understanding and engagement.

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