The structure, reliability and validity of pain expression: Evidence from patients with shoulder pain
Bibliographic record
Abstract
The present study examined psychometric properties of facial expressions of pain. A diverse sample of 129 people suffering from shoulder pain underwent a battery of active and passive range-of-motion tests to their affected and unaffected limbs. The same tests were repeated on a second occasion. Participants rated the maximum pain induced by each test on three self-report scales. Facial actions were measured with the Facial Action Coding System. Several facial actions discriminated painful from non-painful movements; however, brow-lowering, orbit tightening, levator contraction and eye closing appeared to constitute a distinct, unitary action. An index of pain expression based on these actions demonstrated test-retest reliability and concurrent validity with self-reports of pain. The findings support the concept of a core pain expression with desirable psychometric properties. They are also consistent with the suggestion of individual differences in pain expressiveness. Reasons for varying reports of relations between pain expression and self-reports in previous studies are discussed.
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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 | 0.004 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".