Mapping evidence-based interventions to the care of unaccompanied minor refugees using a group formulation approach

Abstract

Background: How we adapt treatment algorithms to complex, clinically untested, difficult-to-engage patient groups without losing evidence base in everyday practice is a clinical challenge. Here we describe process and reasoning for fast, pragmatic, context-relevant and service-based adaptations of a group intervention for unaccompanied minor asylum seekers (UASC) arriving in Europe. We employed a distillation-matching model and deployment-focused process in a mixed-method, top-down (theory-driven) and bottom-up (participant-informed) approach. Prevalence of mental disorders amongst UASC is extremely high. They also represent a marginalised and hard-to-engage group with limited evidence for effective treatments. Method: Content and process adaptations followed four steps: (1) descriptive local group characterisation and theoretical formulation of problems; (2) initial adaptation of evidenced treatment, based on problem-to-component grid; (3) iterative adaptation using triangulated feedback; and (4) small-scale pilot evaluation. Results: Based on evidence and participant feedback, adaptations included minimising verbal demands, facilitating in-session inductive learning, fostering social connectedness via games, enhancing problem-solving skills, accounting for multi-traumatisation, uncertainty and deportation. Quantitative evaluation suggested improved feasibility, with increased attendance, low drop-out and symptom improvement on depression and trauma scores. Conclusions: By describing the principles under-pinning development of a group intervention for severely traumatised UASC, we contribute to the literature supporting dynamic adaptations of psychological interventions, without losing reference to evidence base. Complex and difficult-to-reach clinical groups are often those in most need of care, yet least researched and most affected by inequality of care. Pragmatic adaptations of proven programs are often necessary to increase feasibility.