Marquette University, Walter Schroeder Complex, Suite 346, P.O. Box 1881, Milwaukee, WI 53201-1881, USA.
Northwestern University, Kellogg School of Management, Evanston, IL, USA.
Osteoarthritis Cartilage. 2019 Feb;27(2):240-247. doi: 10.1016/j.joca.2018.10.002. Epub 2018 Oct 15.
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.
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.
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.
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.
调查慢性膝痛成年人对身体活动(PA)属性的个体偏好,确定具有相似偏好的个体群集,并确定这些群集中的个体是否在人口统计学和健康特征上存在差异。
使用潜在全对排列等级(PAPRIKA)方法进行适应性联合分析(ACA),以确定代表六个 PA 属性相对重要性的偏好权重。聚类分析用于确定具有相似权重的参与者群集。卡方检验和方差分析用于评估按群集划分的个体特征差异。多变量逻辑回归用于评估个体特征与群集分配之间的关联。
研究样本包括 146 名参与者;平均年龄 65 岁,72%为女性,47%为白人,非西班牙裔。六个属性(括号内为平均值权重)为:健康效益(0.26)、享受(0.24)、便利(0.16)、经济成本(0.13)、努力(0.11)和时间成本(0.10)。确定了三个群集:群集 1(n=33):对他们来说,享受(0.35)是健康效益的两倍重要;群集 2(n=63):对他们来说,健康效益(0.38)最重要;群集 3(n=50):对他们来说,成本(0.18)、努力(0.18)、健康效益(0.17)和享受(0.18)同样重要。群集 1 健康状况最佳,群集 2 自我效能感最强,群集 3 健康状况最差。
慢性膝痛患者对 PA 有偏好,使用 ACA 方法可以有效地进行区分。根据 PA 偏好聚类的慢性膝痛成年人具有区别特征。了解偏好可能有助于临床医生和研究人员更好地调整 PA 干预措施。