The influence of communication goals and physical demands on different dimensions of pain behavior
Bibliographic record
Abstract
The purpose of the present research was to examine the influence of communication goals and physical demands on the expression of communicative (e.g., facial grimaces) and protective (e.g., guarding) pain behaviors. Participants with musculoskeletal conditions (N=50) were asked to lift a series of weights under two communication goal conditions. In one condition, participants were asked to estimate the weight of the object they lifted. In a second condition, participants were asked to rate their pain while lifting the same objects. The display of communicative pain behaviors varied as a function of the communication goal manipulation; participants displayed more communicative pain behavior when asked to rate their pain while lifting objects than when they estimated the weight of the object. Protective pain behaviors varied with the physical demands of the task, but not as a function of the communication goals manipulation. Pain ratings and self-reported disability were significantly correlated with protective pain behaviors but not with communicative pain behaviors. The results of this study support the functional distinctiveness of different forms of pain behavior. Findings are discussed in terms of evolutionary and learning theory models of pain behavior. Clinical implications of the findings are addressed.
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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 | 0.002 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".