J Orthop Sports Phys Ther. 2022 Sep;52(9):620-629. doi: 10.2519/jospt.2022.11133. Epub 2022 Jul 8.
To explore the person-level predictors of adherence to a step count intervention following total knee replacement (TKR).
Prospective cohort study, nested within the PATHway trial.
Participants who had recently undergone TKR were recruited from 3 rehabilitation hospitals in Sydney, Australia, for the main trial. Only data from participants who were randomized to the TKR intervention group were analyzed. Participants in the intervention group (n = 51) received a wearable tracker to monitor the number of steps taken per day. Step count adherence was objectively measured at 3 months as the number of steps completed divided by the number prescribed and multiplied by 100 to express adherence as a percentage. Participants were classified into 4 groups: withdrawal, low adherence (0%-79%), adherent (80%-100%), and >100% adherent. Ordinal logistic regression was used to identify which factors predicted adherence to the prescribed step count.
Of the 51 participants enrolled, nine (18% of 51) withdrew from the study before 3 months. Half of participants were classified as >100% adherent (n = 24%, 47%). Ten were classified as low adherence (20%), and 8 participants were classified as adherent (16%). In the univariable model, lower age (OR 0.90; 95% CI 0.83-0.97), higher patient activation (OR 1.03; 95% CI 1.00-1.06), and higher technology self-efficacy (OR 1.03; 95% CI 1.00-1.06) were associated with higher adherence. After adjusting for age in the multivariable model, patient activation and technology self-efficacy were not significant.
Younger age, higher patient activation, and higher technology self-efficacy were associated with higher adherence to a step count intervention following TKR in the univariable model. Patient activation and technology self-efficacy were not associated with higher adherence following adjustment for age. .
探索全膝关节置换（TKR）后，影响步数干预依从性的个体因素。
前瞻性队列研究，嵌套于 PATHway 试验中。
主要试验从澳大利亚悉尼的 3 家康复医院招募了近期接受 TKR 的患者。仅分析了随机分配到 TKR 干预组的参与者的数据。干预组（n=51）参与者佩戴可穿戴追踪器来监测每天的步数。3 个月时通过实际完成步数除以规定步数并乘以 100，将依从性表示为百分比，对步数依从性进行客观测量。参与者分为 4 组：退出组、低依从组（0%-79%）、依从组（80%-100%）和＞100%依从组。采用有序逻辑回归来确定哪些因素可预测对规定步数的依从性。
在 51 名入组的参与者中，有 9 名（51 名中的 18%）在 3 个月前退出了研究。一半的参与者被归类为＞100%依从组（n=24%，47%）。10 名被归类为低依从组（20%），8 名被归类为依从组（16%）。在单变量模型中，年龄较低（OR 0.90；95%CI 0.83-0.97）、患者激活度较高（OR 1.03；95%CI 1.00-1.06）和技术自我效能感较高（OR 1.03；95%CI 1.00-1.06）与更高的依从性相关。在多变量模型中调整年龄后，患者激活和技术自我效能不再具有统计学意义。
在单变量模型中，年龄较小、患者激活度较高和技术自我效能感较高与 TKR 后对步数干预的更高依从性相关。在调整年龄后，患者激活和技术自我效能与更高的依从性无关。
