The Disorganized Response Scale: Construct validity of a potential self-report measure of disorganized attachment.
Bibliographic record
Abstract
OBJECTIVE: Based on the paucity of self-report measures of disorganized attachment (DA), we developed and tested a scale examining adults' self-reported disorganized verbalizations, cognitions, and behaviors when discussing their childhoods. METHOD: The Disorganized Response Scale (DRS) was created and administered to 640 university students, and its associations with variables known to covary with DA, such as childhood maltreatment, insecure attachment, and psychological symptoms, were examined. RESULTS: Factor analysis of DRS items revealed a single 15-item dimension that reflected participants' self-reported disorganized responses when discussing their childhoods. Structural equation modeling indicated a good fit to a model in which fearful caretaking and childhood abuse and neglect were associated with the DRS. In turn, the DRS, along with anxious and avoidant attachment, was independently related to symptoms and partially mediated the relationship between child maltreatment and symptomatology. Hierarchical multiple regression indicated that the DRS accounted for significant additional variance in posttraumatic stress, externalization, somatization, and, especially, dissociation, even after demographics and both anxious and avoidant attachment were taken into account. CONCLUSIONS: Analyses support the construct validity of the DRS as a measure of disorganized attachment-related responses in adults. Further research is indicated to replicate these findings and to evaluate their convergence with interview measures of DA. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".