Psychological interventions targeting mental health and stress among females with cardiac disease: a scoping review
Bibliographic record
Abstract
Interventions that target mental health symptoms and stress among those with established cardiac disease have included predominately male samples despite female patients reporting greater severity of these symptoms. The aim of this scoping review was to synthesize the published literature on psychological interventions for females with cardiac disease. We conducted a systematic search of peer-reviewed randomized clinical trials (RCTs) published in the English language from 2003 to 2023, in three databases: Medline (Ovid), PsycInfo (Ovid), and CINAHL (EBSCO). Articles that included female samples, a control or comparison group, implemented psychological interventions, and measured depression, anxiety, or stress as an outcome were included in the review. Nine articles describing eight RCTs of psychological interventions, with a total of 1587 female patients with cardiac disease, were included. Interventions were most successful at reducing stress (75% of studies measuring stress reported efficacy), while symptoms of depression and anxiety were less responsive to intervention (∼30% of studies targeting these symptoms reported improvements) in comparison to a control condition. This scoping review highlights that further advancement in knowledge is required to better address the needs of females with cardiac disease and distress, particularly depression and anxiety.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".