Computer-administered bath ankylosing spondylitis and Quebec Scale outcome questionnaires for low back pain: agreement with traditional paper format.
Bibliographic record
Abstract
OBJECTIVE: To measure the agreement between computer and paper-administered versions of Bath ankylosing spondylitis (AS) questionnaires and the Quebec Scale for low back pain (LBP). METHODS: Fifty patients with LBP completed the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Functional Index (BASFI), Global Score (BAS-G), and the Quebec Scale. Outcome measures were administered both in traditional paper format and by computerized touch-screen system. The order of completion was randomly assigned to each participant. The length of time required to complete each set of questionnaires was recorded and a "washout" period of at least 40 minutes was ensured between completion of the first and second set of outcome measures. RESULTS: There was no statistically significant difference in completion time between the 2 methods of administration. A small systematic difference between computer and paper-administered versions was observed in the Quebec Scale and in the BAS-G results. However, there was a high degree of agreement between paper and computer-administered versions of the Quebec Scale, the BASDAI, BASFI, and BAS-G. Out of the 50 subjects, 84% indicated a preference for the computer-administered method. CONCLUSION: The Bath AS questionnaires and the Quebec Scale can be reliably administered by a computerized touch-screen system. Given the ease of data integration and analysis supported by computer-administered versions of these outcome measures, their excellent reliability, and their popularity among study participants, the computerized versions of the BASDAI, BASFI, BAS-G, and Quebec Scale seem preferable to the traditional paper format.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".