Universal Child Mental Health Screening for Parents: a Systematic Review of the Evidence

Shona K Brinley1, Lucy A Tully2, Talia Carl2

  • 1The School of Psychology, The Faculty of Science, The University of Sydney, Sydney, NSW, Australia. shona.brinley@anu.edu.au.

Insights

Parent reported universal mental health screening (UMHS) is generally accepted by parents for early identification of child mental health risks. However, more research is needed to confirm its effectiveness and address barriers like stigma.

Area of Science:

  • Child and Adolescent Psychiatry
  • Public Health
  • Mental Health Services Research

Background:

  • Early identification of child mental health disorders is crucial, but many cases are missed or diagnosed late.
  • Parent reported universal mental health screening (UMHS) aims to improve early detection and intervention for at-risk children.
  • Existing research on the effectiveness and parental engagement with UMHS is limited.

Approach:

  • A systematic review was conducted by searching six databases for peer-reviewed primary research on parent-reported UMHS.
  • Ten studies involving 3,464 parents of children aged 0-18 years were included, focusing on effectiveness, acceptability, barriers, and enablers.
  • Studies were assessed for quality using the Mixed Methods Appraisal Tool, revealing varied quality across the included research.

Key Points:

  • Parents generally express support and acceptance for UMHS.
  • Limited evidence suggests UMHS may increase referrals and adherence to follow-up care.
  • Common barriers to UMHS implementation include concerns about confidentiality and social stigma.

Conclusions:

  • Parental attitudes towards UMHS are vital for successful implementation and improved child mental health outcomes.
  • There is a significant need for more high-quality research, including randomized controlled trials, to establish the effectiveness and acceptability of UMHS.
  • Addressing parental concerns and understanding contextual factors are essential for optimizing UMHS in diverse settings.