Validation of a Translated Version of the Modified Japanese Orthopaedic Association Score to Assess Outcomes in Cervical Spondylotic Myelopathy
Bibliographic record
Abstract
BACKGROUND: Although the Japanese Orthopaedic Association (JOA) originally developed in Japan, the modified English version (mJOA) has become widely used and is arguably now the accepted standard. OBJECTIVE: In order to apply the mJOA successfully at an international level, we have translated it with a validated approach into Dutch to pave the way for other translated versions. METHODS: After a thorough forward and backward translation procedure, a final Dutch version of the mJOA was developed. This translated version was used to assess the interobserver reliability among 2 independent examiners by using a cohort of patients with neurological impairment due to spinal pathology. RESULTS: The mJOA grading scale was used by 2 independent examiners in 25 patients with a variety of spinal diseases. Initially, the interobserver reliability expressed as kappa was 0.56 +/- 0.11. Then, instructions were given to the instructors to refrain from providing patients with an interpretation of the symptoms. Patients were asked to restrict themselves to the questionnaire and select the most appropriate score without bias from the examiner. Kappa increased to 0.78 +/- 0.05. This difference reached statistical significance (P < .001). CONCLUSION: We present a streamlined approach to translate the mJOA into a language other than English. The approach resulted in a Dutch version of the mJOA that had a high degree of interobserver reliability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".