BMC Musculoskeletal Disorders (May 2024)

Cross-cultural adaption, validity, and reliability of the Japanese version of the Central Aspects of Pain in the Knee (CAP-Knee-J) questionnaire in patients with knee pain: a validation study

  • Tomohiro Oka,
  • Osamu Wada,
  • Shun Matsuda,
  • Katsuyoshi Tanaka,
  • Kiyonori Mizuno

DOI
https://doi.org/10.1186/s12891-024-07471-5
Journal volume & issue
Vol. 25, no. 1
pp. 1 – 7

Abstract

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Abstract Background Knee pain is a prominent concern among older individuals, influenced by the central nervous system. This study aimed to translate the Central Aspects of Pain in the Knee (CAP-Knee) questionnaire into Japanese and investigate its reliability and validity in older Japanese individuals with knee pain. Methods Using a forward–backward method, CAP-Knee was translated into Japanese, and data from 110 patients at an orthopedic clinic were analyzed. The Japanese version (CAP-Knee-J) was evaluated regarding pain intensity during walking, central sensitization inventory, and pain catastrophizing scale. Statistical analyses confirmed internal validity and test–retest reliability. Concurrent validity was assessed through a single correlation analysis between CAP-Knee-J and the aforementioned measures. Exploratory factor analysis was employed on each CAP-Knee-J item to examine structural validity. Results CAP-Knee-J showed good internal consistency (Cronbach’s α = 0.86) and excellent test–retest reliability (intraclass correlation coefficient = 0.77). It correlated significantly with pain intensity while walking, central sensitization inventory scores, and pain catastrophizing scale scores. Exploratory factor analysis produced a three-factor model. Conclusions CAP-Knee-J is a reliable and valid questionnaire for assessing central pain mechanisms specific to knee pain in older Japanese individuals, with moderate correlations with the CSI and weak with the PCS, thus indicating construct validity. This study supports the development of effective knee pain treatments and prognosis predictions.

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