Perception and Challenges of Time Management for Caregivers of People with Heart Failure
Bibliographic record
Abstract
BACKGROUND: Informal caregivers contribute substantially to the self-care of people with heart failure (HF) by helping with concrete and interpersonal tasks. Time perception and management are essential issues among caregivers. However, investigators have not explored this topic in caregivers of people with HF. OBJECTIVES: The aim of this study was to describe the perceptions and challenges of the time management experience among caregivers who support the self-care efforts of their relatives with HF. METHODS: Adult informal caregivers of patients with HF, taking care of the patient for at least 3 months and without cognitive limitations, were recruited from Spain, Italy, and the Netherlands. Data were collected using semistructured interviews. Maryring's qualitative content analysis strategy with both a deductive and an inductive approach was used for analysis. RESULTS: We enrolled 50 participants (20 Italians, 19 Spanish, and 11 Dutch). Caregivers had a mean (SD) age of 62.8 (12.8) years and were mostly female (84%). They dedicated 31.2 (SD, 21.7) hours per week to providing caring activities for their patients. After extracting 33 codes from their qualitative interview data, we summarized them into 8 categories and identified 4 main themes: (1) time for yourself, (2) house management, (3) time for the patient (dedicated to directing care), and (4) time for own socialization. CONCLUSION: Caregivers navigate the complexity of time management by balancing dedicated time for supporting patients with HF and their own personal time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".