Using the Adult Attachment Interview to understand Reactive Attachment Disorder: Findings from a 10-case adolescent sample
Bibliographic record
Abstract
A feasibility study was conducted to examine the usability of the Adult Attachment Interview (AAI) and its coding system with 10 adolescents presenting with Reactive Attachment Disorder (RAD). Given that the measure was deemed usable with all 10 participants, the study then sought to identify the attachment status of the sample. Three transcripts were subjected to inter-rater reliability checks. All transcripts indicated a high level of insecurity, with five participants classified as organized-insecure and five assigned to the cannot classify category. However, a number of issues were raised in the administration and coding of the transcripts concerning participant distress, coding of inferred carer behaviour and experiences of unresolved loss or trauma. We also identified two new phenomena, namely extreme derogation and extreme detachment, and discuss possible development of the existing classification system. Our data indicates that cannot classify attachment status in this population may represent a transitional stage to becoming organized, and that organized insecurity may offer a route to future security. Further minimal adaptations to the AAI may promote the validity of its use with this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".