iCCareD: The Development of an Algorithm to Identify Factors Associated With Distress Among Caregivers of Children and Youth Referred for Mental Health Services

Abstract

Caregiver well-being plays an important role in children's development and a number of factors have been found to impact distress levels among caregivers of children and youth referred for mental health services. Further, caregiver distress impacts youth psychopathology, its acuity as well as related mental health interventions. The purpose of this study was to develop and validate an algorithm for identifying caregivers who are at greatest risk of experiencing caregiver distress. This algorithm was derived from, and will be embedded in, existing comprehensive interRAI child and youth instruments. Ontario data based on the interRAI Child and Youth Mental Health assessment instruments (ChYMH and ChYMH-DD) were analyzed to identify predictors of distress among caregivers of children and youth ages 4–18 years. Starting with proactive aggression, the algorithm uses 40 assessment items to assign one of 30 nodes that are grouped into five levels of risk. The interRAI ChYMH Caregiver Distress (iCCareD) algorithm was validated using longitudinal data from mental health agencies across Ontario and was found to be a good predictor among this sample with a c-statistic of 0.71 for predicting new or ongoing caregiver distress and 65% for both sensitivity and specificity using algorithm values of 3 or greater. This algorithm provides an evidence-based decision-support tool embedded within a comprehensive assessment tool that may be used by clinicians to inform their selection of supports and services for families.