The relationship between childhood sexual abuse and mental health outcomes among males: Results from a nationally representative United States sample
Bibliographic record
Abstract
BACKGROUND: Few studies have examined the associations between childhood sexual abuse (CSA), co-occurrence with other types of maltreatment and adult mental health outcomes, specifically among males. The objectives of this study were to: 1) determine the prevalence of males who have experienced a) childhood maltreatment without CSA; b) CSA without other forms of childhood maltreatment; and c) CSA along with other forms of childhood maltreatment; and 2) determine the relationship between CSA among males and mood, anxiety, substance and personality disorders and suicide attempts. METHODS: Data were drawn from the 2004-2005 National Epidemiological Survey on Alcohol and Related Conditions (NESARC) and limited to males age 20 years old and older (n=14,564). Child maltreatment included harsh physical punishment, physical abuse, sexual abuse, emotional abuse, emotional neglect, physical neglect and exposure to intimate partner violence (IPV). RESULTS: Emotional abuse, physical abuse, and exposure to IPV were the most common forms of maltreatment that co-occurred with CSA among males. A history of CSA only, and CSA co-occurring with other types of child maltreatment, resulted in higher odds for many mental disorders and suicide attempts compared to a history of child maltreatment without CSA. CONCLUSIONS: Child maltreatment is associated with increased odds of mental disorders among males. Larger effects were noted for many mental disorders and suicide attempts for males who experienced CSA with or without other child maltreatment types compared to those who did not experience CSA. These results are important for understanding the significant long-term effects of CSA among males.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".