202: Sibling Superhero Day – Honouring Siblings of Medically Complex Children at the Alberta Children's Hospital
Bibliographic record
Abstract
Medically complex children are becoming a larger proportion of the inpatient population at pediatric tertiary care centers. With increasingly lengthy stays, the families of these children feel significant effects. Notably, siblings of medically complex and chronically unwell children are often not the primary focus of most families. There is a body of qualitative research that shows regardless of the underlying etiology of pathology, many siblings feel overlooked and demonstrate compromised psychosocial wellbeing. ‘Sibling Superhero Day’ at the Alberta Children's Hospital was established to recognize and celebrate the siblings of chronically ill children. Review literature surroundings the needs of siblings of medically complex children Review reported outcomes of siblings in a variety of medical environments Describe the execution of Sibling Superhero Day at the Alberta Children's Hospital as a resident advocacy project Review findings of a needs assessment survey completed by parents at the event A survey was provided to all families who attended the event. Sample size was limited by the families attending Sibling Superhero Day. 21 families completed the survey – Siblings participating in the event ranged from three mos to 22 years – Families attending the event had between 0 and four siblings - some families did have more than one child they considered “sick” – 19 of 21 (90%) of respondents reported moderate to significant impact on the well sibling – 18 of 21 (86%) felt that their family would benefit from additional programs for siblings while another child is admitted to hospital – 8 of 21 (86%) felt that their family would benefit from additional programs for siblings in the community – None of the respondents are accessing community therapy programs for siblings – All respondents found Sibling Superhero Day “helpful” Sibling Superhero Day was a great success and many families appreciated the hospital community acknowledging the well siblings in these families. None of the families that participated in the event were accessing any outside resources to provide support to siblings and these families rely on in-hospital programming, though the majority felt their family would benefit from such programs.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".