Supporting siblings during the critical illness hospitalization of a child: learning from experience
Bibliographic record
Abstract
Introduction: Childhood critical illness impacts the entire family of the critically ill patient. Disruptions to usual family rhythms and routines, established relationships, physical relocations or shifts in caregivers, and the uncertainty about the patient's well-being can have significant impacts on siblings and other connected children in the family. Promoting and facilitating family interactions and engaging younger family members in the hospital experience have been shown to reduce patient and family anxiety, enhance family adaptation, and improve child and family outcomes. The critical care team can implement evidence-informed approaches to address and mitigate challenges for families and provide developmentally aligned support to impacted siblings. Aim: This conceptual paper describes the potential impacts of a critical illness hospitalization on siblings, approaches to supporting siblings, and practical interventions drawn from a synthesis of the current literature and the author's practice experience caring for critically ill children and their families. Data sources: A traditional review and narrative analysis moderated by the authors and supported by lived experience. Conclusions: There is a range of impacts of a critical illness hospitalization on siblings and young family members of the patient. Providing consistent, transparent, and supportive child, sibling, and whole family-centered care can improve the experience and outcomes for the child and family.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".