Delayed access to mental health services for children and adolescents has been linked to an increased risk of harm and nonattendance to scheduled appointments. While studies suggest that the lack of standardized assessments for prioritizing individuals has contributed to long wait times, the inconsistent use of assessments across service sectors in Ontario continues to persist. This has contributed to a paucity of information surrounding which children and adolescents may require urgent mental health services. Using a large secondary data set, this study examined whether service sector (e.g., school), and other individual client characteristics (e.g., age, sex, legal guardianship, interpersonal and school conflict) predicted greater mental health service urgency in 61,448 children and adolescents assessed using the interRAI Child and Youth Mental Health Screener. Binary logistic regression revealed that all predictors, except for sector, showed a significant effect on service urgency. Findings are instrumental in prioritization, reducing the likelihood that children with acute needs remain on waitlists.
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This study was partially funded by the London Community Foundation (RES001102).
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. This study was approved by the Research Ethics Board at The University of Western Ontario.
Informed consent was obtained from all individual participants included in the study.
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Semovski, V., King, C.B. & Stewart, S.L. Mental Health Service Urgency in Children’s Mental Health: Factors Impacting the Need for Expedited Services. Child Psychiatry Hum Dev (2021). https://doi.org/10.1007/s10578-021-01161-2
- Binary logistic regression