An attachment-based intervention for patients with cardiovascular disease and their partners: A proof-of-concept study.
Bibliographic record
Abstract
Couple distress is associated with cardiovascular disease (CVD) risk factors, whereas support is associated with heart-healthy behaviors and better CVD outcomes. OBJECTIVE: To assess the clinical benefit of the Healing Hearts Together (HHT) intervention, an attachment-based relationship enhancement program for couples in which 1 partner has CVD, on relationship quality, mental health, and quality of life (QoL). METHOD: Patients from a tertiary cardiac care center and their partners (N = 78; 39 couples) attended the 8-session HHT group. Participants completed validated, self-report questionnaires pre- and postintervention, including the Dyadic Adjustment Scale (DAS), Couple Satisfaction Index (CSI), Hospital Anxiety and Depression Scale (HADS), and the SF-36 (QoL). At intervention completion, participants completed a satisfaction survey. Between-groups comparisons (patient/partner) were examined with analysis of variance. Paired-sample t tests were used to assess changes over time with HHT participation for the complete sample and for patients and partners separately. RESULTS: Many participants reported relationship and psychological distress at baseline. Clinically and statistically significant changes from pre to postintervention were observed for relationship distress (DAS: +7.8 points; p < .001; CSI changes [+3.6] were clinically significant) and depression (-1.8; p < .001), whereas statistically significant changes occurred for anxiety (-1.5; p < .001), and physical (+2.1; p = .047) and mental (+3.3; p < .001) QoL. Patients, but not partners, reported statistically significant changes in QoL-mental component summary. Clinically and statistically significant changes were observed for anxiety for partners, but not patients. CONCLUSIONS: The HHT intervention was beneficial for patients' and partners' relationship quality, mental health, and QoL. A larger randomized controlled trial evaluating the impact of this intervention on relationship quality, mental health and QoL is warranted. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".