Inter-rater agreement of the Pain and Disability Drivers Management rating scale
Bibliographic record
Abstract
BACKGROUND: A framework to establish the biopsychosocial patient profile for persons with low back pain has been recently proposed and validated: The Pain and Disability Drivers Management model (PDDM). In order to facilitate its clinical integration, we developed the PDDM rating scale. OBJECTIVES: To determine the inter-rater agreement of the PDDM rating scale. A second objective was to determine if this inter-rater agreement varies according to the complexity of patients' clinical presentation. METHODS: We recruited physiotherapists during one-day workshops on the PDDM. We asked each participant to assess two clinical vignettes using the rating scale. One vignette presented a typical clinical presentation (moderate level of difficulty) and one presented an atypical presentation (complex level of difficulty). We determined inter-rater agreement with the proportion of participants who gave the same answer for each PDDM domain. RESULTS: For the typical vignette, the inter-rater agreement per domain was moderate to good (between 0.54 and 0.97). For the complex vignette, the inter-rater agreement per domain was poor to good (between 0.49 and 0.81). The comparison between the two vignettes showed a significant difference (p< 0.01) for nociceptive and cognitive-emotional domains. CONCLUSION: Overall performance indicates that the rating scale present adequate agreement for clinical use, but specific domains require further development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".