School Attachment Monitor (SAM)
Scientific Focus
Our aim is to test the feasibility of a ‘whole-school delivery’ approach to SAM, a digital attachment assessment tool. We will explore its acceptability to children, parents and teachers as part of a routine mental health assessment; make technological refinements as required; and finally establish operational protocols for schools.
Overview
SAM was developed as a cross-college collaboration between the Schools of Health and Wellbeing and Computing. It was devised to provide a transformative role in supporting children’s mental health assessment, uniquely using computer games and machine learning technologies to provide real-time feedback on attachment patterns in children. It seeks to enhance existing attachment measurement tools by reducing the clinical time required to make an assessment.
Attachment patterns draw together biological, social and environmental factors.
During the next phase of SAM we will be working collaboratively with children to best understand how a school-wide delivery model may be achieved.
Principal Investigator: Professor Helen Minnis
Research Assistants: Yara Aleid and Michael Saiger
