98 10 year prospective healthcare data on child maltreatment cases assessed at a tertiary care pediatric centre in Canada
Bibliographic record
Abstract
Abstract Background Child maltreatment is common with a reported prevalence of 32.1%. Physical abuse (PA), sexual abuse (SA), and exposure to intimate partner violence (IPV) are reported by 26%, 10%, and 7.9% of Canadian adults, respectively. While many child maltreatment cases require health evaluation, there is little data on the medical assessment of these cases. The Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-2008) reviewed child welfare cases but not data on their medical aspects, despite 5% of substantiated PA cases being sufficiently severe to require need for medical assessment. There is no published data describing the type, breadth, or outcomes of cases seen in the Canadian healthcare system. Objectives 1 - To describe 10 years of institutional data of children and youth seen for concerns of maltreatment. 2- To use this information to provide recommendations for resource allocation and highlight need for services. Design/Methods Secondary data was analyzed using descriptive statistics from a preexisting quality improvement database where information was collected from the CHEO Child and Youth Protection Review Committee (CYP RC) over 10 years (April 2009-April 2019). The project was approved by the CHEO REB. Results There were a total of 2651 cases reviewed at the CYP RC. Fifty-seven percent (n=1658) of child maltreatment cases were substantiated. The most common types of substantiated child maltreatment were caregiver capacity 29% (n=481), emotional abuse 19% (n=321), PA 18% (n=304), neglect 16% (n=259), SA 14% (n=227), sexual assault with CYP concerns 2% (n=36), and abandonment 2% (n=30). For PA, soft tissue injuries (e.g., bruising) and fractures were the most common injuries seen in medical evaluations for maltreatment. The most frequently ordered tests are skeletal survey, coagulation screening blood work, and CT head. In SA, most cases of substantiated sexual abuse cases were intra-familial (75%). Most physical examinations in SA cases were normal (83%). Forty one percent (1100/2651) of cases were alerted in the medical record for child protection purposes. Conclusion Our findings expand our knowledge of the different types of child maltreatment by linking child welfare and medical assessment information. In cases identified and/or assessed by hospital staff for child maltreatment, 54% were substantiated by child welfare and 41% were “alerted” in the electronic medical record (EMR). The most common type of child maltreatment was “concern for caregiver capacity” which highlights the need for parental education and supports.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".