Emotional Experiences of Caregivers of Patients with a Ventricular Assist Device
Bibliographic record
Abstract
Context Little is known about the stresses experienced by caregivers of patients discharged home with a ventricular assist device. Objective To describe the lived experience of caregivers of patients who were discharged home with a ventricular assist device. Design The study used a phenomenological framework to conduct semistructured interviews guided by 2 psychologists using a focus group setting. Participants Interviews of 13 caregivers of 9 patients discharged to home with a ventricular assist device between March 2004 and June 2007 were recorded, transcribed, and analyzed. Results Four themes emerged during the interviews: anxiety, initially exhibited as profound shock; loss of a loved one, of their lives, of freedom and independence; burden, both the physical burden and the burden of responsibility; and finally coping through faith, acceptance, empathy, and social support. Conclusion Caregivers of patients discharged home with a ventricular assist device experienced significant pressures that changed over the duration of support with the ventricular assist device. Caregivers described their coping mechanisms in dealing with shock, loss, and burden. Understanding the fluctuating needs of caregivers will enable teams to provide interventions based on the situation. Future care guidelines should address the significant stresses placed on caregivers of recipients of a ventricular assist device.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".