Objective and Subjective Auditory Effects of Traumatic Brain Injury and Blast Exposure in Service Members and Veterans
Bibliographic record
Abstract
Service members and veterans (SMVs) with a history of traumatic brain injury (TBI) or blast-related injury often report difficulties understanding speech in complex environments that are not captured by clinical tests of auditory function. Little is currently known about the relative contribution of other auditory, cognitive, and symptomological factors to these communication challenges. This study evaluated the influence of these factors on subjective and objective measures of hearing difficulties in SMVs with and without a history of TBI or blast exposure. Analyses included 212 U.S. SMVs who completed auditory and cognitive batteries and surveys of hearing and other symptoms as part of a larger longitudinal study of TBI. Objective speech recognition performance was predicted by TBI status, while subjective hearing complaints were predicted by blast exposure. Bothersome tinnitus was associated with a history of more severe TBI. Speech recognition performance deficits and tinnitus complaints were also associated with poorer cognitive function. Hearing complaints were predicted by high frequency hearing loss and reports of more severe PTSD symptoms. These results suggest that SMVs with a history of blast exposure and/or TBI experience communication deficits that go beyond what would be expected based on standard audiometric assessments of their injuries.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".