Using the DRS-8 to measure unresolved/disorganized attachment: Associations with states of mind on the adult attachment interview, psychopathology, and offspring social-emotional development
Bibliographic record
Abstract
BACKGROUND: Unresolved/disorganized (U/d) attachment states of mind are associated with poor outcomes across numerous domains of functioning. However, the validity of existing self-report instruments measuring this construct remains questionable. OBJECTIVES: The aim of the current study was to validate the DRS-8, an alternative version of the Disorganized Response Scale (DRS), by assessing its construct validity, internal consistency, and criterion validity with the U/d attachment scales on the Adult Attachment Interview (AAI). PARTICIPANTS AND SETTING: Date were collected from 222 expectant parents (78 % women) at T1 and from 67 of them at 12 months postpartum (T2). METHODS: Participants completed the DRS-8 and questionnaires assessing childhood trauma, romantic attachment, and psychological symptoms during pregnancy (T1). Seventy-four of them participated in the AAI at T1. At T2, parents completed a questionnaire assessing their infants' social-emotional development. RESULTS: The DRS-8 has two highly correlated dimensions, i.e., lapses in the monitoring of reasoning (four items) and discourse (four items). A confirmatory factor analysis supported a bifactor structure of the instrument, showing good fit indices and internal consistency (ω = 0.87). The DRS-8 was significantly correlated with U/d states of mind on the AAI, r(72) = 0.28, p = .016, and demonstrated excellent construct validity. Significant indirect effects of the DRS-8 were found in the associations between childhood trauma and psychological symptoms, and between parental trauma and infant social-emotional development. CONCLUSIONS: The DRS-8 appears to be a promising self-report measure of U/d states of mind showing criterion validity with the AAI.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".