Novel Methods for Screening: Contributions from Attachment and Biobehavioral Catch-up

• Published in: Prevention science Vol. 19; no. 7; pp. 894 - 903
• Main Authors: Caron, EB, Roben, Caroline K. P., Yarger, Heather A., Dozier, Mary
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-10-2018; Springer Nature B.V
• Subjects: Adult; Allocation; Attachment; Babies; Child; Child abuse & neglect; Child Abuse - prevention & control; Child Abuse - psychology; Child and School Psychology; Child Behavior; Clinical research; Clinical trials; Female; Fidelity; Health Psychology; Humans; Implementation; Infant; Infants; Intervention; Male; Mass Screening - methods; Medical screening; Medicine; Medicine & Public Health; Methods; Openness; Process Assessment, Health Care; Public Health; Resource allocation; Tests; Training; Vignettes; Training; Provider characteristics; Screening interviews; Fidelity; Implementation science
• ISSN: 1389-4986; 1573-6695
• DOI: 10.1007/s11121-018-0894-5

Preventative interventions are needed across the lifespan, including for children who have experienced maltreatment. However, interventions’ effect sizes are typically smaller in real-world settings than in clinical trials. Identifying providers who are likely to implement interventions with fidelity could promote implementation outcomes through targeted allocation of training resources. This study tested two pre-training screening measures as predictors of provider fidelity to Attachment and Biobehavioral Catch-up (ABC), a preventative intervention for maltreated infants. One measure assessed valuing of attachment/openness, and the other used vignettes to assess initial skill in a key intervention component. In a sample of 42 providers across 197 sessions, both screening measures predicted future ABC fidelity, even when controlling for experience and education. These results support the development of screening measures for other interventions, suggesting approaches that target specific qualities and behaviors are likely to predict implementation fidelity.