Attachment assessment in clinical practice: Factor structure of the attachment questionnaire
Bibliographic record
Abstract
OBJECTIVE: Attachment theory is of great relevance to psychotherapy process and outcome. The labor-intensive and time-consuming nature of attachment codification impedes its widespread use in clinical practice. The Attachment Questionnaire (AQ), a clinician-rated instrument, was developed to address these limitations. However, the status of validation of the AQ remains preliminary. The objective of this study is to further validate the AQ by evaluating its factor structure and convergent validity. METHODS: To this end, 389 psychotherapists completed the AQ and assessed patients' personality disorders and level of functioning. RESULTS: Factor analyses revealed that a five-factor solution provided a better fit than the original four-factor solution. The additional factor, inhibited exploration, captured difficulties in open, nondefensive, exploration of memories and their effects. Correlations between AQ factors and criterion variables support the convergent validity of the AQ. CONCLUSIONS: These results are discussed in light of patients' characteristics and recent advances in attachment research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 teacher head, 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".