Feasibility of School-Based Identification of Children and Adolescents Experiencing, or At-risk of Developing, Mental Health Difficulties: a Systematic Review
Soneson E., Howarth E., Ford T., Humphrey A., Jones PB., Thompson Coon J., Rogers M., Anderson JK.
AbstractUnder-identification of mental health difficulties (MHD) in children and young people contributes to the significant unmet need for mental health care. School-based programmes have the potential to improve identification rates. This systematic review aimed to determine the feasibility of various models of school-based identification of MHD. We conducted systematic searches in Medline, Embase, PsycINFO, ERIC, British Education Index, and ASSIA using terms for mental health combined with terms for school-based identification. We included studies that assessed feasibility of school-based identification of students in formal education aged 3–18 with MHD, symptomatology of MHD, or exposed to risks for MHD. Feasibility was defined in terms of (1) intervention fit, (2) cost and resource implications, (3) intervention complexity, flexibility, manualisation, and time concerns, and (4) adverse events. Thirty-three studies met inclusion criteria. The majority focused on behavioural and socioemotional problems or suicide risk, examined universal screening models, and used cross-sectional designs. In general, school-based programmes for identifying MHD aligned with schools’ priorities, but their appropriateness for students varied by condition. Time, resource, and cost concerns were the most common barriers to feasibility across models and conditions. The evidence base regarding feasibility is limited, and study heterogeneity prohibits definitive conclusions about the feasibility of different identification models. Education, health, and government agencies must determine how to allocate available resources to make the widespread adoption of school-based identification programmes more feasible. Furthermore, the definition and measurement of feasibility must be standardised to promote any future comparison between models and conditions.