“Living with dying”: The evolution of family membersʼ experience of mechanical ventilation
Bibliographic record
Abstract
BACKGROUND: Communication with families about mechanical ventilation may be more effective once we gain a better understanding of what families experience and understand about this life support technology when their loved ones are admitted to the intensive care unit (ICU). METHODS: We conducted in-depth interviews with family members of 27 critically ill patients who required mechanical ventilation for > or = 7 days and had an estimated ICU mortality of > or = 50%. Team members reviewed transcripts independently and used grounded theory analysis. RESULTS: The central theme of family members' experience with mechanical ventilation was "living with dying." Initial reactions to the ventilator were of shock and surprise. Family members perceived no option except mechanical ventilation. Although the ventilator kept the patient alive, it also symbolized proximity to death. In time, families became accustomed to images of the ICU as ventilation became more familiar and routine. Their shock and horror were replaced by hope that the ventilator would allow the body to rest, heal, and recover. However, ongoing exposure to their loved one's critical illness and the new role as family spokesperson were traumatizing. CONCLUSIONS: Family members' experiences and their understanding of mechanical ventilation change over time, influenced by their habituation to the ICU environment and its routines. They face uncertainty about death, but maintain hope. Understanding these experiences may engender more respectful, meaningful communication about life support with families.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".