Assessing the relationship between pain catastrophizing and early physical, psychological and cognitive symptoms following a mild traumatic brain injury
Bibliographic record
Abstract
L'identification de facteurs influençant le rétablissement suite à un traumatisme crânien cérébral léger (TCCL) s'avère cliniquement pertinent compte tenu du fardeau imposé au système santé. Cette étude visait à établir si la dramatisation envers la douleur (DD) influence le rétablissement précoce suite à un TCCL, en étant possiblement associée à plus de douleur, symptômes aigus, détresse psychologique, et, à une réduction du niveau de fonctionnalité. Cette recherche prospective auprès de 58 patients fut basée sur les questionnaires Rivermead, Inventaire Multidimensionnel de la douleur, et Échelle de DD. Des corrélations de Pearson positives et significatives furent observées entre la DD et la sévérité de douleur, les symptômes post-TCCL, et la détresse psychologique. Les analyses corrélationnelles ont aussi illustré une relation négative entre la DD et le niveau de fonctionnalité. En somme, la DD semble affecter défavorablement le rétablissement précoce suite à un TCCL, et pourrait être un facteur de risque pour le développement d'un syndrome post-commotionnel.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".