title: A taxometric study of the Adult Attachment Interview.
abstract: This study is the first to examine the latent structure of individual differences reflected in the Adult Attachment Interview (AAI; C. George, N. Kaplan, & M. Main, 1985), a commonly used and well-validated measure designed to assess an adult's current state of mind regarding childhood experiences with caregivers. P. E. Meehl's (1995) taxometric methods (i.e., MAXCOV-HITMAX) were applied to data from 504 AAIs. Analyses revealed that the variation underlying secure versus dismissing states of mind was more consistent with a dimensional than a taxonic model. (Taxometric analyses of preoccupation were indeterminate.) In addition, variation in secure adults' (n=278) reports about their early experiences revealed little evidence for qualitative groups of earned- and continuous-secures. Rather, the inferred life experiences of secure adults appeared to be distributed continuously. Findings are discussed in terms of their theoretical implications regarding the phenomenon of earned-security specifically and variation underlying secure and insecure states of mind more generally. The consequences of these analyses for AAI reliability training and coding are also explored.
authors.affiliation: Department of Psychology.
authors.forename: Glenn I
authors.initials: GI
authors.lastname: Roisman
authors.affiliation: Department of Psychology.
authors.forename: R Chris
authors.initials: RC
authors.lastname: Fraley
authors.affiliation: Institute for the Study of Children, Families and Social Issues.
authors.forename: Jay
authors.identifier: 0000-0003-2191-2503
authors.initials: J
authors.lastname: Belsky
mesh_terms: D000328:Adult; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007206:Individuality; D007223:Infant; D007406:Interview, Psychological; D008016:Life Change Events; D008297:Male; D009769:Object Attachment; D010287:Parent-Child Relations; D010552:Personality Assessment / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data; D015203:Reproducibility of Results