Prevalence, Assessment, and Treatment of Mild Traumatic Brain Injury and Posttraumatic Stress Disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Iraq and Afghanistan war veterans are returning from combat having sustained traumatic brain injury, mostcommonly mild traumatic brain injury (mTBI), and experiencing posttraumatic stress disorder (PTSD). Clinical guidelines for mTBI and PTSDdo not focus on the co-occurrence of these conditions (mTBI/PTSD). A synthesis of the evidence on prevalence, diagnostic accuracy, andtreatment effectiveness for mTBI/PTSD would be of use to clinicians, researchers, and policymakers. METHODS: We conducteda systematic review of studies identified through PubMed, PsycINFO, REHABDATA, Cochrane Library, pearling, and expert recommendations. Peer-reviewed English language studies published between 1980 and June, 2009 were included if they reported frequencies of traumatic braininjury and PTSD, or diagnostic accuracy or treatment effectiveness specific to mTBI/PTSD. RESULTS: Thirty-four studies metinclusion criteria. None evaluated diagnostic accuracy or treatment effectiveness. Studies varied considerably in design. Frequency ofmTBI/PTSD ranged from 0% to 89%. However, in 3 large studies evaluating Iraq and Afghanistan war veterans, frequencies ofprobable mTBI/PTSD were from 5% to 7%; among those with probable mTBI, frequencies of probable PTSD were from 33% to 39%. DISCUSSION: The wide range of mTBI/PTSD frequency levels was likely due to variation across studyparameters, including aims and assessment methods. Studies using consistent, validated methods to define and measure mTBI history andPTSD are needed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it