The Feasibility of Embedding Data Collection into the Routine Service Delivery of a Multi-Component Program for High-Risk Young People.

BACKGROUND

There is little evidence about how to improve outcomes for high-risk young people, of whom Indigenous young people are disproportionately represented, due to few evaluation studies of interventions. One way to increase the evidence is to have researchers and service providers collaborate to embed evaluation into the routine delivery of services, so program delivery and evaluation occur simultaneously. This study aims to demonstrate the feasibility of integrating best-evidence measures into the routine data collection processes of a service for high-risk young people, and identify the number and nature of risk factors experienced by participants.

METHODS

The youth service is a rural based NGO comprised of multiple program components: (i) engagement activities; (ii) case management; (iii) diversionary activities; (iv) personal development; and (v) learning and skills. A best-evidence assessment tool was developed by staff and researchers and embedded into the service's existing intake procedure. Assessment items were organised into demographic characteristics and four domains of risk: education and employment; health and wellbeing; substance use; and crime. Descriptive data are presented and summary risk variables were created for each domain of risk. A count of these summary variables represented the number of co-occurring risks experienced by each participant. The feasibility of this process was determined by the proportion of participants who completed the intake assessment and provided research consent.

RESULTS

This study shows 85% of participants completed the assessment tool demonstrating that data on participant risk factors can feasibly be collected by embedding a best-evidence assessment tool into the routine data collection processes of a service. The most prevalent risk factors were school absence, unemployment, suicide ideation, mental distress, substance use, low levels of physical activity, low health service utilisation, and involvement in crime or with the juvenile justice system. All but one participant experienced at least two co-occurring domains of risk, and the majority of participants (58%) experienced co-occurring risk across four domains.

CONCLUSIONS

This is the first study to demonstrate that best-evidence measures can feasibly be embedded into the routine data collection processes of a service for high-risk young people. This process allows services to tailor their activities to the most prevalent risks experienced by participants, and monitor these risks over time. Replication of this process in other services would improve the quality of services, facilitate more high quality evaluations of services, and contribute evidence on how to improve outcomes for high-risk young people.