Lachman DM, van Kooij YE, Slijper HP, Hovius SER, Selles RW, Wouters RM. Explaining Personalized Activity Limitations in Patients With Hand and Wrist Disorders: Insights from Sociodemographic, Clinical, and Mindset Characteristics.
Arch Phys Med Rehabil 2024;
105:314-325. [PMID:
37604381 DOI:
10.1016/j.apmr.2023.08.003]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 07/31/2023] [Accepted: 08/02/2023] [Indexed: 08/23/2023]
Abstract
OBJECTIVES
To investigate the association of sociodemographic, clinical, and mindset characteristics on outcomes measured with a patient-specific patient-reported outcome measure (PROM); the Patient Specific Functional Scale (PSFS). Secondly, we examined whether these factors differ when a fixed-item PROM, the Michigan Hand Outcome Questionnaire (MHQ), is used as an outcome.
DESIGN
Cohort study, using the aforementioned groups of factors in a hierarchical linear regression.
SETTING
Twenty-six clinics for hand and wrist conditions in the Netherlands.
PARTICIPANTS
Two samples of patients with various hand and wrist conditions and treatments: n=7111 (PSFS) and n=5872 (MHQ).
INTERVENTIONS
NA.
MAIN OUTCOME MEASURES
The PSFS and MHQ at 3 months.
RESULTS
The PSFS exhibited greater between-subject variability in baseline, follow-up, and change scores than the MHQ. Better PSFS outcomes were associated with: no involvement in litigation (β[95% confidence interval=-0.40[-0.54;-0.25]), better treatment expectations (0.09[0.06;0.13]), light workload (0.08[0.03;0.14]), not smoking (-0.07[-0.13;-0.01]), men sex (0.07[0.02;0.12]), better quality of life (0.07[0.05;0.10]), moderate workload (0.06[0.00;0.13]), better hand satisfaction (0.05[0.02; 0.07]), less concern (-0.05[-0.08;-0.02]), less pain at rest (-0.04[-0.08;-0.00]), younger age (-0.04[-0.07;-0.01]), better comprehensibility (0.03[0.01;0.06]), better timeline perception (-0.03[-0.06;-0.01]), and better control (-0.02[-0.04;-0.00]). The MHQ model was highly similar but showed a higher R2 than the PSFS model (0.41 vs 0.15), largely due to the R2 of the baseline scores (0.23 for MHQ vs 0.01 for PSFS).
CONCLUSIONS
Health care professionals can improve personalized activity limitations by addressing treatment expectations and illness perceptions, which affect PSFS outcomes. Similar factors affect the MHQ, but the baseline MHQ score has a stronger association with the outcome score than the PSFS. While the PSFS is better for individual patient evaluation, we found that it is difficult to explain PSFS outcomes based on baseline characteristics compared with the MHQ. Using both patient-specific and fixed-item instruments helps health care professionals develop personalized treatment plans that meet individual needs and goals.
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