Experiences in Close Relationships Revised Child version (ECR-RC): Psychometric evidence in support of a Security factor

Abstract

Attachment refers to the innate tendency to form strong and close interpersonal bonds, from infancy through adulthood. Many different ways to assess attachment have been developed, one of them being the use of self-report questionnaires. The Experiences in Close Relationships-Revised is one of the most commonly used instruments to assess adult and late adolescent attachment. Recently, a new and brief child version of this instrument has been published, the 12-item ECR-RC short form. The purpose of the current study was threefold: (1) to test the factorial structure of this form in a sample of Italian adolescents, (2) to test the loadings overlap between the mother and the father forms, and (3) to investigate factors reliability. Using a sample of 961 adolescents (M_age = 14.25, SD_age = 1.57), a series of Confirmatory Factor Analyses were performed. The Avoidance – Anxiety structure was not supported, whereas a factor structure including Anxiety, Avoidance, and Security, had a very good fit. Item loadings on these factors were largely equal across mother and father, and internal reliability was high. The results of this study show that the ECR-RC short form is a quick and reliable way to assess attachment in early adolescents. This study also initiates the proposal of an ECR-RC Security factor, to be further validated in future studies.

Keywords:

• ECR-RC
• attachment
• adolescents
• Italian sample
• confirmatory factor analysis
• psychometric proprieties

Acknowledgments

The authors would like to thank the Early Researchers Union of the European Association for Developmental Psychology, the European Association for Developmental Psychology and Jacobs Foundation. Also, the authors would like to thank the schools and the personnel for their help and support; the students, who kindly participated, and their parents. We also thank Robert Heller for the English language editing, Massimiliano Pastore for his statistical advice on the overlapping procedure, and Valentina Zambuto for her help with data collection.