Health Impact of Suspected Interpersonal Violence Against Adults: Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Interpersonal violence (IV) has an extensive and profound impact on health, representing a public health concern. Different health outcomes have been identified based on the characteristics of the survivor and the abuser, their relationship, the type of violence perpetrated, and the cumulative effect of multiple violent experiences. OBJECTIVE: The main objective of this study was to estimate the likelihood of negative health outcomes, such as substance abuse, mental health, and somatic disorders, occurring in adults presenting a clinical suspicion of IV. METHODS: We performed a retrospective, observational cohort study, using secondary data from electronic health records of adult patients of the Local Health Unit of Matosinhos (ULSM). The control cohort included all patients aged between 18 and 59 years followed at ULSM between January 1, 2008, and May 9, 2024, while the violence cohort included patients within the same age range who were suspected survivors of IV within the same time period. Exposure was defined by the presence of one or more of the IV text expressions or codes in the patient's electronic health record. Data regarding violence suspicion, comorbidities, and health outcomes were obtained by conducting a text search on clinical notes, as well as ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10 (International Statistical Classification of Diseases, Tenth Revision) and International Classification of Primary Care 2 codes. The follow-up period was 10 years. To estimate the risk of developing health outcomes, we constructed a cohort model using a Cox proportional hazards model adjusted at baseline for age and sex. RESULTS: The control cohort included 154,145 patients, and the violence cohort included 36,835 patients. Suspected survivors of IV had a higher hazard ratio of developing alcohol abuse (3.05, 95% CI 2.87-3.24), drug abuse (6.03, 95% CI 4.5-8.06), suicidal ideation (5.50, 95% CI 4.78-6.32), major psychiatric disorder (4.46, 95% CI 4.38-4.53), chronic pain (3.70, 95% CI 3.60-3.81), sleep disorders (3.57, 95% CI 3.46-3.68), use of antidepressants (3.57, 95% CI 3.51-3.64), use of anxiolytics (2.98, 95% CI 2.93-3.03), and eating disorder (2.72, 95% CI 2.06-3.59). Regarding somatic health conditions, suspected violence exposure was linked to a higher hazard ratio for metabolic dysfunction-associated steatotic liver disease (6.91, 95% CI 6.37-7.50), chronic immune inflammatory disorder (3.68, 95% CI 3.93-3.44), asthma (2.64, 95% CI 2.53-2.74), chronic kidney disease (2.49, 95% CI 2.39-2.59), hypercholesterolemia (2.16, 95% CI 2.12-2.20), and early heart disease (2.01, 95% CI 1.93-2.10). CONCLUSIONS: Exposure to violence was linked to a higher likelihood of developing adverse events related to substance abuse, mental, and somatic health. Our findings lead to a deeper understanding of the complex burden of violence on health, uncovering new relationships between IV and health outcomes while validating those already explored.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".