A brief 5-item version of the Neck Disability Index shows good psychometric properties
Bibliographic record
Abstract
BACKGROUND: The purpose of this secondary analysis of clinical databases of people with neck pain was to use a mixed unique conceptual and statistical approach to develop a brief version of the Neck Disability Index (NDI). METHODS: An a priori framework of neck-related function based on the International Classification of Functioning, Disability and Health was used to identify items from the original 10-item NDI that do not conceptually fit. Remaining items were subject to Rasch analysis to identify items that did not statistically fit with axioms of quantitative measurement. Finally, approaches drawn from classical test theory were used to compare stability, responsiveness and concurrent validity of the original NDI, the new brief NDI and the linearly-transformed brief NDI. RESULTS: Conceptual analysis identified 3 items that did not fit with the construct of self-reported ability to perform activity: pain intensity, headache, and sleeping. These items were removed, and responses to the remaining 7 items drawn from an assembled database of 316 physiotherapy patients with neck pain were subject to Rasch analysis. Two items were removed due to either considerable differential item functioning (reading) or statistical redundancy (lifting). The remaining items were considered the NDI-5. Test-retest reliability, responsiveness, sensitivity to change, and concurrent validity were all comparable across the original NDI, NDI-5 and linearly-transformed NDI-5. Sensitivity to change over a 1-month period of physiotherapy was the notable exception, where the linearly-transformed NDI-5 showed superiority over the other two forms. CONCLUSIONS: A shortened version of the NDI, the NDI-5, has been constructed that is conceptually and statistically sound. Implications for research and clinical practice are discussed. Comparison with the NDI-8 is provided that suggests overall similar function across the forms, although the latter may be more sensitive to change.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".