Exploring the Practice Elements of Attachment-Based Interventions: A Distillation-and-Matching Review
摘要
Attachment-based interventions enjoy a growing evidence-base for their effectiveness. These interventions may be decomposed into practice elements and studied for how they may cluster differentially for different children. Exploring this could reshape how attachment-based interventions are applied, potentially enhancing their utility.
ObjectivesTo apply the Distillation and Matching Model to the empirical literature on attachment-based interventions to identify practice elements common across these interventions and to describe their occurrence for target populations.
MethodsIn this systematic review, across 60 studies, 23 practice elements were extracted from 45 intervention protocols that were tested in trials to be effective on attachment, sensitivity, and/or parent–child interaction outcomes.
ResultsFindings show that practice elements were most differentiated for child age (≤ 6 months; 7 months to 11 years; 12–18 years) although further differentiations were found for location, ethnicity, and risk status. While there is similarity across practice element profiles regarding the use of relationship-building, video-feedback, psychoeducation, and home-based approaches, some distinctions were observed. Interventions for younger infants frequently involved direct demonstration and modelling, while those for older infants and young children consisted of feedback-based approaches. Interventions for vulnerable, at-risk parents consisted of intensive guidance, while those for groups indigenous to North America benefitted from a comprehensive, multifaceted package of practice elements. Interventions for adolescent-aged children were frequently implemented in parent-group format, involving role-plays and discussions between parents, with limited direct involvement of the child.
ConclusionsThese distinctions may inform differential clinical applications of attachment-based interventions informed by the needs of specific populations.