154 A demographic look at Adverse Childhood Experiences in Behavioural Referrals to Consultant Pediatrics
Bibliographic record
Abstract
Consultant pediatricians are commonly asked to see children regarding behavior and the potential of a diagnosis of ADHD. If left untreated and children unsupported over the long-term, the overall prognosis is poor, especially in terms of academic achievement and social functioning. Social inequities can create significant barriers to accessing timely and appropriate assessment and care (e.g., difficulty making appointments due to inconsistent contact information; decreased access to transportation to and from appointments). Adverse childhood experiences (ACEs) (exposure to mental illness, addiction and violence in the home to name a few) can influence child behaviour and function, complicating accurate diagnosis and effective treatment. There is evidence that children who are exposed to addiction, mental illness and violence will suffer long-term negative health outcomes and have increased rates of ADHD diagnosis. This study aims to describe the family history and social conditions of children receiving behaviour-related referrals in a consultant pediatric clinic of five pediatricians in a catchment area of approximately 300,000 people, one urban city and including several rural communities. This area reports one of the highest child poverty rates in Canada. Family history of mental illness, learning, addiction, and anger issues, parental education level and employment status, and child demographics will be reported. By better understanding the needs of our referral base, we can make interventions to decrease barriers to care and match care plans to patient needs. Data was collected via phone intake interviews of children being referred to pediatricians for behaviour-related referrals. Interview questions pertained to the child’s medical, academic and family history and other factors. Descriptive statistics were conducted to look at the frequency of potential risk factors that may impact children referred for behavioural assessments in terms of access to care, accurate diagnosis and treatment. These were referenced against the ACE score screening questionnaire. The sample was composed of 483 families, where the referred child was most often male (70.8%). Results indicate that a family history of mental illness (including, but not limited to: anxiety, depression, manic depression, schizophrenia, and bipolar disorder) was common among these families at 69.8%, and that 37.7% of families had at least one parent who reported a learning issue. Also common was a family history of addiction (43.5%) and anger issues (36%). Only 12.5% of mothers and 17.1% of fathers reported not having a high school education. This study demonstrates that many of the children being referred for behavioral referrals are at high-risk for ACEs such as exposure to mental illness, physical or emotional abuse, and addiction in the home. It is important to know these risk factors to inform the approach and considerations of diagnosis, treatment interventions and how to involve the family in a community centred, needs-based approach.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.007 | 0.001 |
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".