Educational needs of informal caregivers in cardiac rehabilitation: a mixed-methods study
Bibliographic record
Abstract
AIMS: Informal caregivers play a crucial role in supporting individuals with cardiovascular disease (CVD) during cardiac rehabilitation (CR), yet their specific educational needs are often overlooked. Understanding these needs is essential for developing targeted interventions that enhance informal caregiver support and improve patient outcomes in CR. This study aimed to explore the educational needs of informal caregivers supporting individuals with CVD attending CR. METHODS AND RESULTS: A mixed-methods approach was used to explore the educational needs of informal caregivers. Quantitative data were collected through an online cross-sectional survey completed by 86 informal caregivers. The survey assessed sociodemographic characteristics, quality of life (WHOQOL-BREF), and educational needs. Most respondents had not received formal education or training related to caregiving, although their knowledge of CVD was rated as moderate to high. Many reported difficulties accessing reliable information and resources. Qualitative data were gathered through semi-structured interviews with 16 informal caregivers, and four key themes were determined: Helpful Resources, Empowerment, Lived Experience Network, and Psychological Support. Informal caregivers expressed a desire for practical resources, more direct access to healthcare professionals, and both emotional and peer support. They also highlighted the importance of managing stress and balancing their well-being alongside caregiving responsibilities. CONCLUSION: The findings suggest that educational interventions for informal caregivers should be comprehensive and flexible, incorporating practical caregiving strategies as well as social and emotional support. Such programmes could enhance the effectiveness of CR by better equipping informal caregivers to support patient recovery while maintaining their own health.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".