04 Children and youth in alternate care
Bibliographic record
Abstract
Abstract Background Children in alternate care often face unmet medical, emotional, and developmental needs due to a range of factors, including poverty, prenatal drug exposure, parental mental illness, and domestic violence, which are compounded by inconsistent supervision and care. While the overall paediatric population is declining, the number of children in out-of-home care is increasing in our province. In response to this, the CAYAC clinic was established in September 2019 and, as part of the provincial government’s healthcare strategy, was expanded to full-time operation in 2024. This multidisciplinary clinic, staffed by paediatricians, allied health professionals, and in-care social workers, provides trauma-informed care for children and youth referred by social workers, family doctors, and paediatricians. The clinic is also supported by ongoing research, evaluation, and paediatric resident training. Objectives The aim of this study was to describe the demographic characteristics, quantify the medical, developmental, and mental health conditions and analyze risk factors associated with children/youth in alternate care who are referred to this new outpatient service. Design/Methods A cross-sectional study was conducted involving children and youth aged 0 to 17 years who attended their first appointment at the CAYAC clinic between September 2019 and September 2021. Results Data from the first 103 patient charts revealed that all the children experienced at least one type of abuse, with neglect and emotional abuse being the most common (68.9%). Care types included interim (24.3%), temporary (25.2%), continuous (29.1%), and other (21.4%). Placement types were non-relatives (50.5%), relatives (26.2%), group homes (17.5%), and other (5.8%). Most children attended school (70.9%) or daycare (88% for children under 5 years old). Common identified conditions and issues included sleep disturbances (60.7%), nutritional problems (37.9%), gastrointestinal/neurologic issues (25.2% each), aggression/behavioral challenges (45.6%), ADHD (43.7%), and developmental delays/intellectual disabilities (30.1%). Medication use ranged from none (24%) to three or more medications (26%), with stimulants being the most common. Risk factors associated with increased time in placement were older age (p=0.0003), increased number of ACE’s (p=0.0271), type of placement (living in a group home; p=0.0042) and higher BMI percentile (p=0.0446). Going to school was associated with shorter time in care (p=0.0331). Conclusion The clinic has received approximately 500 new referrals and has attended approximately 5,000 appointments with children and youth presenting with complex needs and developmental trauma. As service demand grows, the clinic plans to expand provincially and improve facilities. Future steps include securing funding for additional staff and expanding services to meet the increasing need.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".