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Multicenter Study
. 2019 Feb;27(2):240-247.
doi: 10.1016/j.joca.2018.10.002. Epub 2018 Oct 15.

Preferences for physical activity: a conjoint analysis involving people with chronic knee pain

D Pinto  1 , U Bockenholt  2 , J Lee  3 , R W Chang  4 , L Sharma  5 , D J Finn  6 , A W Heinemann  7 , J L Holl  8 , P Hansen  9
Affiliations
Multicenter Study

Preferences for physical activity: a conjoint analysis involving people with chronic knee pain

D Pinto et al. Osteoarthritis Cartilage. 2019 Feb.

Abstract

Objective: To investigate individual preferences for physical activity (PA) attributes in adults with chronic knee pain, to identify clusters of individuals with similar preferences, and to identify whether individuals in these clusters differ by their demographic and health characteristics.

Design: An adaptive conjoint analysis (ACA) was conducted using the Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) method to determine preference weights representing the relative importance of six PA attributes. Cluster analysis was performed to identify clusters of participants with similar weights. Chi-square and ANOVA were used to assess differences in individual characteristics by cluster. Multinomial logistic regression was used to assess associations between individual characteristics and cluster assignment.

Results: The study sample included 146 participants; mean age 65, 72% female, 47% white, non-Hispanic. The six attributes (mean weights in parentheses) are: health benefit (0.26), enjoyment (0.24), convenience (0.16), financial cost (0.13), effort (0.11) and time cost (0.10). Three clusters were identified: Cluster 1 (n = 33): for whom enjoyment (0.35) is twice as important as health benefit; Cluster 2 (n = 63): for whom health benefit (0.38) is most important; and Cluster 3 (n = 50): for whom cost (0.18), effort (0.18), health benefit (0.17) and enjoyment (0.18) are equally important. Cluster 1 was healthiest, Cluster 2 most self-efficacious, and Cluster 3 was in poorest health.

Conclusions: Patients with chronic knee pain have preferences for PA that can be distinguished effectively using ACA methods. Adults with chronic knee pain, clustered by PA preferences, share distinguishing characteristics. Understanding preferences may help clinicians and researchers to better tailor PA interventions.

Keywords: Conjoint analysis; Knee; Osteoarthritis; Physical activity; Preferences; Stated choice.

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Conflict of interest statement

Conflict of interest:

PH is a co-inventor of 1000minds conjoint analysis software. All other authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1
Example of a pairwise-ranking question from 1000minds conjoint analysis software
Figure 2
Figure 2
Preference weights* for physical activity attributes by cluster * Preference weights – higher values represent greater importance related to physical activity choice
See this image and copyright information in PMC

References

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