Psychometric properties of the Italian version of the Experience in Close Relationship Scale 12 (ECR-12): an exploratory structural equation modeling study
Bibliographic record
Abstract
The Experiences in Close Relationship Scale (ECR) is one of the most commonly used self-report instruments of adult attachment and has been widely adopted in psychotherapy research. Composed of two subscales, namely Attachment Avoidance and Anxiety, the ECR was recently shortened to a 12-items version, called the ECR-12. Given the importance of extending knowledge on its applicability in understudied populations, our aim was to validate the ECR-12 in a large sample of Italian native-speakers. A total of 1197 participants (73.2% females; mean age=28.53±11.37 years) completed the ECR-12. Each participant also completed other measures of attachment, psychopathology, interpersonal distress, coping strategies, and well-being. An Exploratory Structural Equation Modeling analysis showed an excellent fit of the data, providing support for the two-dimensional orthogonal structure of the ECR-12. In addition, the measurement model was invariant across genders. Both attachment anxiety and attachment avoidance subscales demonstrated good internal reliability, with McDonald's Omegas and Cronbach's Alphas above the suggested 0.8 cut-off. Finally, the Italian version of ECR-12 showed adequate convergent, concurrent, and divergent validity. Highly anxious individuals reported the highest levels of maladaptive interpersonal functioning and coping strategies, resulting in lower well-being. Interestingly, both attachment insecurity dimensions predicted higher levels of psychopathology, even after controlling for demographic variables and levels of self-reported relational difficulties. Given the good psychometric properties of the ECR-12, researchers and practitioners in Italy are encouraged to adopt the ECR-12 in their future research on adult attachment in psychotherapy.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".