Acta Orthopaedica (Jan 2020)

The Forgotten Joint Score-12 in Swedish patients undergoing knee arthroplasty: a validation study with the Knee Injury and Osteoarthritis Outcome Score (KOOS) as comparator

  • Siri Heijbel,
  • Josefine E Naili,
  • Axel Hedin,
  • Annette W-Dahl,
  • Kjell G Nilsson,
  • Margareta Hedström

DOI
https://doi.org/10.1080/17453674.2019.1689327
Journal volume & issue
Vol. 91, no. 1
pp. 88 – 93

Abstract

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Background and purpose — Having patients self-evaluate the outcome is an important part of the follow-up after knee arthroplasty. The Forgotten Joint Score-12 (FJS-12) introduced joint awareness as a new approach, suggested to be sensitive enough to differentiate well-functioning patients. This study evaluated the Swedish translation of the FJS-12 and investigated the validity, reliability, and interpretability in patients undergoing knee arthroplasty Patients and methods — We included 109 consecutive patients 1 year after primary knee arthroplasty to assess construct validity (Pearson’s correlation coefficient, r), internal consistency (Cronbach’s alpha [CA]), floor and ceiling effects, and score distribution. The Knee injury and Osteoarthritis Outcome Score (KOOS) was the comparator instrument for the analyses. Further, 31 patients preoperatively and 22 patients postoperatively were included to assess test–retest reliability (intraclass correlation coefficient [ICC]). Results — Construct validity was moderate to excellent (r = 0.62–0.84). The FJS-12 showed a high degree of internal consistency (CA = 0.96). The ICC was good preoperatively (0.76) and postoperatively (0.87). Ceiling effects were 2.8% in the FJS-12 and ranging between 0.9% and 10% in the KOOS. Interpretation — The Swedish translation of the FJS-12 showed good validity and reliability and can be used to assess outcome after knee arthroplasty. Moreover, the FJS-12 shows promising results in its ability to differentiate well-functioning patients. Future studies on unidimensionality, scale validity, interpretability, and responsiveness are needed for a more explicit analysis of the psychometric properties.