Lean on me: attachment and mental health in couples facing cardiovascular disease
Bibliographic record
Abstract
Elevated symptoms of depression and anxiety are common after the onset of cardiovascular disease in both patients and their spouses. Attachment anxiety, attachment avoidance, and the degree to which couples cope jointly with the stress of cardiovascular disease may help to explain why some of them experience worsening psychological distress. The aim of this study was to investigate the link between insecure attachment and the mental health of patients with cardiovascular disease and their spouses, along with the potential mediating role of common dyadic coping (CDC). Patients with cardiovascular disease and their spouses completed validated questionnaires measuring romantic attachment, common dyadic coping, depression, and anxiety. A structural equation modeling framework was used to test an actor-partner interdependence mediation model. Patients’ and spouses’ ( N = 181 couples; M age = 63.15 years; 79% male patients) romantic attachment anxiety was related to their own symptoms of depression and anxiety; the more attachment anxiety they reported, the higher their scores on measures of depression and anxiety were. Patients’ and spouses’ romantic attachment avoidance was related to their own and their spouses’ common dyadic coping, with greater avoidance linked to less common dyadic coping for both. There was no significant relation between common dyadic coping and romantic partners’ mental health. The results suggest that romantic attachment anxiety is related to psychological distress in couples facing cardiovascular disease, and that attachment avoidance is related to low levels of common dyadic coping. Consideration of attachment orientations may be important in the treatment of anxiety and depression among patients and their spouses.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".