Development and Examination of the Reactive Attachment Disorder and Disinhibited Social Engagement Disorder Assessment Interview
Bibliographic record
Abstract
The fifth edition of the Diagnostic and Statistical Manual ( DSM) categorizes reactive attachment disorder (RAD) and disinhibited social engagement disorder (DSED) as two separate disorders, and their criteria are revised. For DSED, the core symptoms focus on abnormal social disinhibition, and symptoms regarding lack of selective attachment have been removed. The core symptoms of RAD are the absence of attachment behaviors and emotional dysregulation. In this study, an international team of researchers modified the Child and Adolescent Psychiatric Assessment for RAD to update it from DSM-IV to DSM-5 criteria for RAD and DSED. We renamed the interview the reactive attachment disorder and disinhibited social engagement disorder assessment (RADA). Foster parents of 320 young people aged 11 to 17 years completed the RADA online. Confirmatory factor analysis of RADA items identified good fit for a three-factor model, with one factor comprising DSED items (indiscriminate behaviors with strangers) and two factors comprising RAD items (RAD1: failure to seek/accept comfort, and RAD2: withdrawal/hypervigilance). The three factors showed differential associations with clinical symptoms of emotional and social impairment. Time in foster care was not associated with scores on RAD1, RAD2, or DSED. Higher age was associated with lower scores on DSED, and higher scores on RAD1.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".