Caregiver needs in and after the ICU: A call to action for critical care nurses
Bibliographic record
Abstract
Despite increasing illness severity and patient complexity, intensive care unit (ICU) and hospital mortality continue to decline (Prescott et al., 2024). At the same time, the long-term physical, cognitive, and mental health challenges experienced by ICU survivors are becoming better understood and more frequently recognized as post-intensive care syndrome (PICS; Needham et al., 2012; Schwitzer et al., 2023). In contrast, the experiences and needs of family members, who often transition into unpaid caregiving roles after discharge, remain underrecognized in the ICU setting. These family caregivers frequently experience post-intensive care syndrome–family (PICS-F), a cluster of emotional, psychological, physical, and social symptoms that can impair their health and caregiving capacity (Davidson et al., 2012).
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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 | 0.020 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.006 | 0.017 |
| Research integrity | 0.030 | 0.041 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".