2 Mental Health Presentations and Referral Appointment Outcomes at a School Based Health Centre Program
Bibliographic record
Abstract
According to WHO, mental health conditions are one of the leading causes of disability worldwide. In Ontario, 20% of children have a mental health condition. Growing evidence demonstrates that early intervention improves a child’s ability to function, prevents illness from worsening, and reduces morbidity and mortality. However, many parents face barriers including long wait times, accessibility issues and not knowing where to seek out help. In an effort to remedy this problem, The Model Schools Pediatric Health Initiative was established to open School Based Health Centres (SBHCs) in inner-city elementary schools. Students with health concerns, including mental health, can be referred to the SBHC by school staff or caregivers. Each SBHC is staffed by family doctors and developmental and general pediatricians who assess students and arrange for interventions and follow-up. The aims of this study were to 1) examine the characteristics of children presenting with mental health conditions to the SBHCs, with a focus on demographics and reason for choosing the SBHC and 2) review the referrals made by the SBHCs and assess attendance rate. A retrospective chart review was conducted, specifically examining a cohort of children who presented with a mental health concern(s) to SBHCs. Study data was collected from September 2012 to August 2016 and included all consented children enrolled in the clinics. Frequencies and means were used to summarize outcomes. 270 (28%) of 979 SBHC patients presented with a mental health concern, including but not limited to depression, anxiety, psychosocial trauma and emotional dysregulation. 85% of referrals were initiated by a teacher. The average age at presentation was 7.5 years old. A significant majority of patients and their families were immigrants to Canada. 63% of patients had an annual family income of <$30,000. Patients’ caregivers reported choosing the SBHC due to 1) teacher recommendation, 2) convenience factors and 3) lacking a family doctor. 273 referrals to other health care providers were made, including psychologists, occupational and physical therapists and developmental pediatricians. Of these referrals, 32% were attended, 30% were unattended, 10% were waitlisted and 28% were lost to follow up. Inner-city SBHCs address the need for timely and easily accessible services for children with mental health concerns. Future research will focus on referral appointments and barriers to attendance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".