196: Do adverse childhood experiences make teenagers more vulnerable? A study about youth in custodial facilities
Bibliographic record
Abstract
Studies in adults have shown a correlation between the number of adverse childhood experiences (ACE) and an increasing risk of mental health issues, substance abuse, suicide and premature death. However, there are few data on the impact of ACEs on the health status of teenagers. Moreover, youth living in custodial facilities represent an especially at-risk group. To evaluate if there is a correlation between the number ACEs and the health status of teenagers in custodial facilities. This is a secondary analysis from a cross sectional health evaluation study of youth in custodial facilities that took place in 13 facilities in Quebec in 2011 to 2013. A total of 315 teenagers 14 to 17 years of age were evaluated by a nurse/doctor shortly after admission using a comprehensive standardized data collection form/check list. We identified seven ACEs: single parent family, violent death of a family member, family history of incarceration/mental health issues/substance abuse and personal history of physical or sexual abuse before 13 years old. CHI square analysis were performed between the number of ACEs and a number of relevant variables. 94% of girls and 91% of boys had at least one ACE and 39% of girls and 25% of boys had ≥4 ACEs. More youths who had an increased number of ACEs evaluate their health status as being worse (P<0.03), had a history of mental health issues (P<0.00), ADHD (P<0.04), learning disabilities (P<0.2), had at-risk sexual behaviors (girls, P<0.04; boys, P<0.003), had psychosomatic symptoms (P<0.002), respiratory problems (girls, P<0.04; boys, P<0.01) and dental problems (P<0.05). More boys with higher number of ACEs had oral and vaginal sex before 13 years of age (P<0.01), were more prone to engage in violent behavior, ie, frequent threats of harming (P<0.014), frequent threats of taxing (P<0.02); while more girls had personal history of having sex for money (P<0.04), STI (P<0.05), suicidal attempts (P<0.03) and expressed more need for mental health consultation (P<0.01). The results of the study confirm that increased adverse experiences in childhood are associated with increased health problems during adolescence for youth in custodial facilities. This shows the importance of not only asking about ACEs, but to consider their cumulative impact. For teenagers with more than three ACEs, services should be intensified in order to avoid their negative impact.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".