Cross‐Cultural Adaptation and Psychometric Properties of Low Back Pain Core Outcome Measures: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: The purpose of this systematic review was to identify and evaluate the quality of cross-cultural adaptations of the six core outcome measures (NRS, SF-12, PROMIS, ODI, RMDQ and VAS) for low back pain (LBP) and assess their psychometric properties. METHODS: Medline, EMBASE, Emcare and CINAHL databases were searched from inception to August 2024. Eligible studies included those assessing core LBP outcome measures in adults with LBP. The COSMIN checklist was used to assess the quality of cross-cultural adaptations and evaluate the psychometric properties. Additionally, the COSMIN risk of bias tool and GRADE approach were employed to assess study quality and provide levels of evidence. RESULTS: A total of 82 studies were included. Among them, 35 studies examined the cross-cultural adaptations of the ODI, 25 for the RMDQ, 4 for PROMIS, 1 for SF-12 and 2 for NRS/VAS. The quality of cross-cultural adaptations was generally poor or fair due to inadequate reporting of pre-testing processes and small sample sizes. Most psychometric properties were rated as having an inadequate risk of bias, with evidence quality ranging from very low to low. CONCLUSION: This review highlights that the cross-cultural adaptations of the five core LBP outcome measures have generally been conducted with low quality. To improve the adaptation process, studies should employ larger sample sizes and standardised pre-testing procedures. Additional research is needed to explore a broader range of psychometric properties of cross-cultural adaptations, ensuring better validity, reliability and comparability across adapted versions. SIGNIFICANCE STATEMENT: Improving the quality of cross-cultural adaptations of LBP outcome measures is crucial to ensuring that assessments are culturally relevant and accurate across diverse populations, leading to better-informed clinical decisions and equitable care for patients with LBP globally. TRIAL REGISTRATION: CRD42023413077.
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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 | 0.035 | 0.155 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".