Family Caregiver Perspectives on Caring for Ventilator-Assisted Individuals at Home
Bibliographic record
Abstract
BACKGROUND: The trend of patients who are invasively ventilated to prefer home care is one that benefits both the patient and the health care system. However, this assumes a role for patients' family members to become informal caregivers. OBJECTIVE: To explore the impact of caring for a ventilator-assisted individual on informal caregivers. METHODS: A descriptive design with semistructured caregiver interviews and the Caregiver Burden Inventory were used. Participants were informal caregivers of a family member with a progressive neuromuscular disease on invasive ventilation for at least six months. Transcript coding was performed and regularly reviewed, and recruitment continued until data saturation. Qualitative analysis was based on 'thematic analysis'. RESULTS: A total of 21 caregivers were interviewed. Five themes developed: a sense of duty; restriction of day-to-day life; physical and emotional burden; training and education; and the need for more paid support. Caregivers described a sense of duty to take care of loved ones, but suffered a significant restriction of their own time with a negative impact on their physical and mental health. The initial transfer home was highlighted as the most stressful part of the process. The Caregiver Burden Inventory scores supported a high level of burden: median 49 (interquartile range 39.5 to 53.0) of a maximum 96. CONCLUSION: Homecare for ventilator-assisted individuals with progressive neuromuscular disease causes significant burden to informal caregivers. Approaches to lessen this burden, such as increased paid care, improved professional support and respite care, may enable home ventilation to be a more sustainable modality of care.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".