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Does coding internal working models of attachment have to be so hard?

Amanda C VentaVeronica McLarenCarla SharpAnna AbateMadeleine AllmanBreana CervantesSophie KerrJessica Hernandez OrtizEric SumlinJesse WalkerKiana Wall
Published in: Child psychiatry and human development (2022)
The Child Attachment Interview (CAI) has demonstrated promise in youth, yet widespread use is thwarted by the need for interview transcription, face-to-face training, and reliability certification. The present study sought to examine the empirical basis for these barriers. Thirty-five archival CAIs were re-coded by: (1) expert coders (i.e., trained and reliable) without access to transcripts, (2) trained coders who had not completed reliability training, and (3) novice coders who had no formal training. Agreement with consensus classifications was computed with the expectation of moderate agreement. Results supported coding by experts without transcription of the interview. Near-moderate agreement preliminarily supported the use of trained coders who have not attempted reliability certification with appropriate caveats. While moderate agreement was not achieved for novice raters, findings suggest that self-paced training options for the CAI may hold future promise. These contributions erode a number of significant barriers to the current use of the CAI.
Keyphrases
  • virtual reality
  • high intensity
  • resistance training
  • mental health
  • big data
  • magnetic resonance imaging
  • machine learning
  • computed tomography
  • current status
  • artificial intelligence