Measuring attachment security in patients with advanced cancer: psychometric properties of a modified and brief Experiences in Close Relationships scale
Bibliographic record
Abstract
OBJECTIVE: Attachment security has been identified as an important buffer of distress in patients with cancer and other medical illnesses but current measures have not been adapted for this population who may be older, in long-term stable relationships, and suffering from considerable disease burden. This study reports on (1) the psychometric properties of a modified 36-item Experiences in Close Relationships scale (ECR), adapted for this population; and (2) the validity of a brief 16-item version of our modified scale. METHODS: A modified ECR (ECR-M36) was constructed by rephrasing relevant items to refer more generally to people with whom one feels close, instead of specifically in relation to one's romantic partner(s). Patients with metastatic gastrointestinal (GI) and lung cancer completed the ECR-M36 and other scales tapping self-esteem, social support, and depressive symptoms on two occasions within a period of 4-6 months. Based on factor analyses of the ECR-M36, 16 items were selected to form a brief measure (ECR-M16). RESULTS: Factor analyses of both ECR forms revealed a higher-order factor structure in which four first-order factors (Worrying about Relationships, Frustration about Unavailability, Discomfort with Closeness, Turning Away from Others) loaded onto two second-order factors tapping Attachment Anxiety and Avoidance. Both ECR forms were reliable and valid. CONCLUSION: The ECR-M36 and ECR-M16 are good measures of attachment orientations for use with medically ill, older populations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".