More than words: Computerized text analysis of child welfare professionals' Adult Attachment Interviews

Studying the attachment representations of child welfare workers can benefit workers and the vulnerable populations they serve. The Adult Attachment Interview (AAI) is the most widely used and well-validated measure of adult attachment but is also costly and time-consuming to score. Linguistic Inqui...

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Bibliographic Details
Published inJournal of human behavior in the social environment Vol. 29; no. 6; pp. 804 - 818
Main Authors Call, Casey D., Razuri, Erin Becker, Hiles Howard, Amanda R., DeLuna, Jamie Hurst, Ito-Jaeger, Sachiyo, Cross, David R.
Format Journal Article
LanguageEnglish
Published Abingdon Routledge 18.08.2019
Taylor & Francis Ltd
Subjects
Adult Attachment Interview
Adults
Attachment
Attachment representations
Child welfare
child welfare workers
Children
Classification
Computerization
Labor force
language
linguistic inquiry
Scores
Social workers
Software
Subsets
Vulnerability
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Summary:Studying the attachment representations of child welfare workers can benefit workers and the vulnerable populations they serve. The Adult Attachment Interview (AAI) is the most widely used and well-validated measure of adult attachment but is also costly and time-consuming to score. Linguistic Inquiry Word Count (LIWC), a text-analysis software program, has the potential to lessen the burden of AAI scoring, making it a lower-cost, faster option for providing basic attachment representation information. In the current study, we explore the use of the LIWC in the AAI transcripts of 239 child welfare professionals. Findings indicate that subsets of LIWC categories could distinguish the AAI transcripts of individuals coded as dismissing, preoccupied, and secure-autonomous in attachment. Further, a subset of LIWC categories predicted AAI classification. Specifically, discriminant function analysis revealed two functions, activation and incoherence, that accurately classified 66.2% of AAI transcripts. Implications for the child welfare workforce are discussed.
ISSN:1091-1359
1540-3556
DOI:10.1080/10911359.2019.1617819