Brief Report: Pathways From Childhood Abuse History to Adulthood Mental Health Among Women Living With HIV in Canada: Longitudinal Cohort Findings
Bibliographic record
Abstract
INTRODUCTION: Experiencing childhood abuse elevates risks for long-term mental health challenges (MHC); this complex relationship is underexplored among women with HIV. Informed by the 'chains of risk' life-course approach, we examined pathways from childhood abuse to mental health among women with HIV. METHODS: Using longitudinal data from the Canadian HIV Women's Sexual & Reproductive Health Cohort Study [CHIWOS], we examined associations between childhood abuse history (sexual, physical, verbal) and current poverty (income, food insecurity, housing insecurity) at time 1 (T1, August 2013-May 2015), substance use and past 3-month violence at time 2 (T2, June 2015-January 2017), and MHC (depression, PTSD, mental functioning) at time 3 (T3, February 2017-December 2018). We conducted path analysis to examine direct and indirect effects from childhood abuse to adult MHC via poverty, substance abuse, and violence. FINDINGS: Most (68%) participants with reported data (n=1,315) experienced childhood abuse. Childhood abuse was associated with adulthood poverty, violence, substance use, and MHC. T1 poverty was associated with T2 substance use and violence, and T3 MHC. Violence was associated with T3 MHC. The total standardized effect of childhood abuse on T3 MHC was 0.27 ( p <0.001). Half of this effect was indirect (β=0.13, p <0.001), with poverty accounting for 43% of the total indirect effect (β=0.06, p =0.003). CONCLUSIONS: Among women with HIV in Canada, childhood abuse was associated with poorer adulthood mental health; this association was mediated by poverty, violence, and substance use in adulthood. Findings emphasize the need for life-course approaches in women-centred violence and trauma-aware HIV care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".