Prevalence and Perception of Intimate Partner Violence-Related Traumatic Brain Injury
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) is a serious and often undiagnosed consequence of intimate partner violence (IPV). Data on prevalence of TBI among IPV survivors are emerging, but prevalence of IPV among patients presenting to TBI clinics is unknown. Identification of IPV is important to ensure patients with TBI receive appropriate intervention and referrals. OBJECTIVE: To determine the proportion of women 18 years and older presenting to an acquired brain injury (ABI) clinic with confirmed or suspected concussion who reported experiencing IPV in the last 12 months or their lifetime. METHODS: Single-center cross-sectional cohort study. Proportion of IPV-related TBI or head, neck, or facial) injuries were determined using a modified HELPS Brain Injury Screening Tool and the Neurobehavioral Symptom Inventory. RESULTS: Of the 97 women approached, 50 were enrolled in the study. The average age was 46.1 years and 32 women (64.0%) reported a relationship history with a violent partner; 12-month prevalence of IPV was 26.5% and lifetime prevalence was 44.0%. Within their lifetime, all (44.0%) who reported an IPV history reported emotional abuse, 24.0% reported physical abuse, and 18.0% sexual abuse. HELPS responses indicated a high potential of lifetime IPV-related TBI for 29.2%, most commonly from being hit in the face or head (20.8%). CONCLUSION: Implementation of IPV screening in community-based ABI clinics is a pivotal step toward understanding the potential scope of TBI and addressing the wide range of somatic, cognitive, and affective symptoms experienced by IPV survivors. IPV screening also will lead to timely referral and follow-up and increase patient safety after discharge from rehabilitation.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".