The Effects of Litigation on Symptom Expression: A Prospective Study following Mild Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: To prospectively assess the association between litigation and neurobehavioural symptoms following mild Traumatic Brain Injury (TBI). DESIGN: a prospective study with the inception cohort assessed on average 42.2(17.2) days after injury. SETTING: an outpatient clinic within a large general hospital. PATIENTS: a consecutive sample of 100 clinic attenders with mild TBI. OUTCOME MEASURES: A cognitive screen (Mini-Mental State Examination (MMSE), Galveston Orientation and Amnesia Test (GOAT), a measure of psychological distress (the 28 item General Health Questionnaire (GHQ)) and two head injury outcome measures, the Glasgow Outcome Scale (GOS) and the Rivermead Head Injury Follow-up Questionnaire (RHFUQ). RESULTS: Demographic characteristics, TBI severity ratings and premorbid risk factors for poor outcome did not differ between litigants (27.8 per cent of the sample) and non-litigants. However, litigants were significantly more anxious (p<0.0001), depressed (p<0.01), had greater social dysfunction (p<0.0001) and had poorer outcome on the GOS (p<0.002) and RHFUQ (p<0.002). There were no cognitive differences between the groups. CONCLUSIONS: the data demonstrate an association between litigation and increased psychological distress at the outset of the litigation process. While association is not synonymous with causality, the absence of demographic, premorbid and TBI related differences between litigants and non-litigants suggests that the pursuit of compensation may influence the subjective expression of symptoms following mild traumatic brain injury.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".