Kamperman, Astrid M., Cornelis G. Kooiman, Nicolas Lorenzini, Jurate Aleknaviciute, Jon G. Allen, & Peter Fonagy (2020, September). Using the attachment network Q-sort for profiling one’s attachment style with different attachment-figures. PLoS ONE, 15(9), e0237576. 22 pp. (doi: 10.1371/journal.pone.0237576) (Link: https://doi.org/10.1371/journal.pone.0237576) (Open Access: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0237576)

Abstract: Attachment instruments vary substantially in practicability of administration, employment of categorical versus dimensional scoring, quality of scales, and applicability to different attachment figures. The Attachment Network Q-sort (ANQ) is a self-report, quasi-qualitative instrument that discriminates relationship-specific attachment styles for multiple attachment figures. The current study assesses the properties of the ANQ in psychotherapy patients and in non-patient respondents, using mother, father and romantic partner as possible attachment figures. Analyzing the ANQ-data with latent class analysis, we found four types or classes of participants: a group with an overall secure profile, a group only insecure for father, a group only insecure for mother, and a group insecure for mother as well as father but not for partner (if available). These profiles proved to have good concurrent, discriminant and construct validity. We conclude that the ANQ is potentially a useful alternative clinical self-report instrument to assess combinations of attachment styles for a range of attachment figures such as parents and a romantic partner.

Cornelis G Kooiman <kees.kooiman@deviersprong.nl> and <kooiman@cgkooiman.nl> is in the Department of Psychiatry, Erasmus Medical Center, Rotterdam, and the Viersprong Institute for Studies on Personality Disorder (VISPD), Halsteren, The Netherlands.

Leave a Reply

Please log in using one of these methods to post your comment:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.