Mental health Profiles of Sexually Abused Youth: Comorbidity, Resilience and Complex Trauma
Bibliographic record
Abstract
Objectives: The current study’s objectives were to 1) determine if sexually abused youth in child protective agencies (CPA) were given more psychiatric diagnoses and exhibited more comorbidity than youth from the general population, 2) examine the comorbidity profiles of sexually abused youth over 10 years of medical consultations and hospitalizations. Method: Diagnoses of 882 youth with a substantiated sexual abuse report between 2001 and 2010 at a participating CPA were compared to those of 882 matched controls (n = 1764). Results: Results of generalized linear mixed models showed that sexually abused youth presented higher rates of all diagnostic categories and were up to four times more likely to present comorbid diagnoses. Latent class analyses among abused youth revealed four different comorbidity profiles; two more severe groups named complex trauma (11%) and dissociation (14%); and two less severe groups named depression (10%) and low or no comorbidity/resilience (65%). Youth with more cumulative maltreatment and greater number of years of data following CSA report were more at risk of presenting a comorbidity profile, while females were more likely to present a depression profile. Profiles of youth in the highest comorbidity class were similar to what is defined as complex trauma or complex post-traumatic stress disorder. Implications: Sexually abused youth's varied profiles warrant varied interventions. Integrated trauma informed interventions are needed to address the cumulative maltreatment experienced and the psychiatric comorbidity some youth exhibit.
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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 | 0.000 | 0.000 |
| 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".