Clinical Utility and Psychometric Properties of the Traumatic Brain Injury Quality of Life Scale (TBI-QOL) in US Military Service Members
Bibliographic record
Abstract
OBJECTIVE: To examine the clinical utility and psychometric properties of the Traumatic Brain Injury Quality of Life (TBI-QOL) scale in a US military population. PARTICIPANTS: One hundred fifty-two US military service members (age: M = 34.3, SD = 9.4; 89.5% men) prospectively enrolled from the Walter Reed National Military Medical Center and other nationwide community outreach initiatives. Participants included 99 service members who had sustained a mild traumatic brain injury (TBI) and 53 injured or noninjured controls without TBI (n = 29 and n = 24, respectively). PROCEDURE: Participants completed the TBI-QOL scale and 5 other behavioral measures, on average, 33.8 months postinjury (SD = 37.9). MAIN OUTCOME MEASURES: Fourteen TBI-QOL subscales; Neurobehavioral Symptom Inventory; Posttraumatic Stress Disorder Checklist-Civilian version; Alcohol Use Disorders Identification Test; Combat Exposure Scale. RESULTS: The internal consistency reliability of the TBI-QOL scales ranged from α = .91 to α = .98. The convergent and discriminant validity of the 14 TBI-QOL subscales was high. The mild TBI group had significantly worse scores on 10 of the 14 TBI-QOL subscales than the control group (range, P < .001 to P = .043). Effect sizes ranged from medium to very large (d = 0.35 to d = 1.13). The largest differences were found on the Cognition-General Concerns (d = 1.13), Executive Function (d = 0.94), Grief-Loss (d = 0.88), Pain Interference (d = 0.83), and Headache Pain (d = 0.83) subscales. CONCLUSION: These results support the use of the TBI-QOL scale as a measure of health-related quality of life in a mild TBI military sample. Additional research is recommended to further evaluate the clinical utility of the TBI-QOL scale in both military and civilian settings.
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How this classification was reachedexpand
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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".