Translation of the Neck Disability Index and validation of the Greek version in a sample of neck pain patients
Bibliographic record
Abstract
BACKGROUND: Neck pain is a highly prevalent condition resulting in major disability. Standard scales for measuring disability in patients with neck pain have a pivotal role in research and clinical settings. The Neck Disability Index (NDI) is a valid and reliable tool, designed to measure disability in activities of daily living due to neck pain. The purpose of our study was the translation and validation of the NDI in a Greek primary care population with neck complaints. METHODS: The original version of the questionnaire was used. Based on international standards, the translation strategy comprised forward translations, reconciliation, backward translation and pre-testing steps. The validation procedure concerned the exploration of internal consistency (Cronbach alpha), test-retest reliability (Intraclass Correlation Coefficient, Bland and Altman method), construct validity (exploratory factor analysis) and responsiveness (Spearman correlation coefficient, Standard Error of Measurement and Minimal Detectable Change) of the questionnaire. Data quality was also assessed through completeness of data and floor/ceiling effects. RESULTS: The translation procedure resulted in the Greek modified version of the NDI. The latter was culturally adapted through the pre-testing phase. The validation procedure raised a large amount of missing data due to low applicability, which were assessed with two methods. Floor or ceiling effects were not observed. Cronbach alpha was calculated as 0.85, which was interpreted as good internal consistency. Intraclass correlation coefficient was found to be 0.93 (95% CI 0.84-0.97), which was considered as very good test-retest reliability. Factor analysis yielded one factor with Eigenvalue 4.48 explaining 44.77% of variance. The Spearman correlation coefficient (0.3; P = 0.02) revealed some relation between the change score in the NDI and Global Rating of Change (GROC). The SEM and MDC were calculated as 0.64 and 1.78 respectively. CONCLUSION: The Greek version of the NDI measures disability in patients with neck pain in a reliable, valid and responsive manner. It is considered a useful tool for research and clinical settings in Greek Primary Health Care.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".