Conjoint Analysis of Treatment Preferences for Osteoarthritis
Condition: Osteoarthritis
MeSH terms: Osteoarthritis
Study type: Observational

Summary: 
      The purpose of this study is to develop a conjoint analysis-based questionnaire and decision
      aid for patients with osteoarthritis of the knee and to compare the responses of two groups
      of subjects, one receiving only printed information about knee osteoarthritis, the other
      participating in a computer-based adaptive conjoint analysis program.
    

Detailed description: 
      Osteoarthritis (OA) is a major cause of disability in the elderly, second only to
      cardiovascular disease. The medical treatment of OA alleviates symptoms, but does not halt
      disease progression. Exercise is an effective intervention but for patients who do not get
      adequate relief from exercise and whose disease is not so severe as to warrant joint
      replacement, there are a variety of intermediate steps including medication and joint
      injection. There are nontrivial tradeoffs between these choices.

      This project explores the choices made by patients who have significant osteoarthritis of the
      knee using specialized computer software as a decision aid. Traditional decision aids present
      information in ways that help patients make decisions that are consistent with their values.
      However, this sort of decision aid usually provides no feedback for the clinician or
      researcher about the patient's thoughts, preferences, or reasoning. We propose to use
      conjoint analysis, an analytic tool for assessing preferences that has been used extensively
      in marketing but has only recently been introduced into medical decision making.

      In conjoint analysis, the consumer (in the marketing context) or subject (in the medical
      research context) is presented with pairs of choices. The marketing researcher might ask, for
      instance, if the consumer would rather have a $1000 laptop with 250 MB of RAM, or a $1200
      laptop with 500 MB of RAM. The answer allows the accurate calculation of the subject's
      utilities for both money and RAM. Extending the questions to other elements allows utilities
      for the laptop's speed, weight, battery life, and screen size to be calculated and allows the
      computer maker to optimize its product lines. Instead of one sweet spot where price and
      features are at a happy medium, every laptop offered can be perceived by potential consumers
      as offering reasonable value for the money.

      Fraenkel and others have used conjoint analysis in the study of osteoarthritis and rheumatoid
      arthritis. Conjoint analysis presents choice pairs to subjects; for instance, how would you
      feel about a cream that offered an extremely low risk of complications with only moderate
      relief in symptoms, versus a medication that offered a moderate risk of major complications
      and better symptom relief? As a result of this process, utilities are generated
      mathematically for each of the preferences.

      Because we know relatively little about how patients feel about using conjoint analysis, and
      about making tradeoffs among the factors that conjoint analysis permits us to assess, this
      project will also utilize patient focus groups to explore these issues.
    

Intervention name(s): Standard of care for osteoarthritis treatment; Conjoint Analysis for Osteoarthritis
Intervention type(s): Behavioral; Behavioral
Intervention description(s): Standard of care educational materials to inform patients about choices for knee pain.; Conjoint Analysis computer software to inform patients about choices for knee pain.
Other intervention name(s): Osteoarthritis usual care; Computer-assisted decision aid
Sampling method: Non-Probability Sample
Study population: 
        People aged 65-95 with knee pain
      
Keywords: Knee pain, osteoarthritis, non-surgical treatment, age 65+