Test-Retest Reliability of the Short-Form McGill Pain Questionnaire
Bibliographic record
Abstract
OBJECTIVES: No previous study has adequately demonstrated the test-retest reliability of the Short-Form McGill Pain Questionnaire, yet it is increasingly being used as a measure of pain. This study evaluates the test-retest reliability in patients with osteoarthritis. METHODS: A prospective, observational cohort study was undertaken using serial evaluation of 57 patients at 2 time points. A sample of patients awaiting primary hip or knee joint replacement surgery were recruited in clinic or via mail (mean age 64.8 years). Short-Form McGill Pain Questionnaires were delivered by mail 5 days apart, and a supplementary questionnaire was completed on the second occasion to explore if the patients' pain report had remained stable. RESULTS: The intraclass correlation coefficient was used as an estimate of reliability. For the total, sensory, affective, and average pain scores, high intra-class correlations were demonstrated (0.96, 0.95, 0.88, and 0.89, respectively). The current pain component demonstrated a lower intraclass correlation of 0.75. The coefficient of repeatability was calculated as an estimation of the minimum metrically detectable change. The coefficients of repeatability for the total, sensory, affective, average, and current pain components were 5.2, 4.5, 2.8, 1.4 cm, and 1.4, respectively. DISCUSSION: Problems of adequate completion of the Short-Form McGill Pain Questionnaire were highlighted in this sample, and supervision via telephone contact was required. Patients recruited in clinic who had practiced completing the Short-Form McGill Pain Questionnaire demonstrated fewer errors than those recruited by mail. The Short-Form McGill Pain Questionnaire was demonstrated to be a highly reliable measure of pain. These results should not be generalized to a more elderly population, as increasing age was correlated with greater variability of the sensory component scores.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".