A national survey of children’s experiences and needs when attending Canadian pediatric emergency departments
Bibliographic record
Abstract
BACKGROUND: Optimizing a child's emergency department (ED) experience positively impacts their memories and future healthcare interactions. Our objectives were to describe children's perspectives of their needs and experiences during their ED visit and relate this to their understanding of their condition. METHODS: 514 children, aged 7-17 years, and their caregivers presenting to 10 Canadian pediatric EDs completed a descriptive cross-sectional survey from 2018-2020. RESULTS: Median child age was 12.0 years (IQR 9.0-14.0); 56.5% (290/513) were female. 78.8% (398/505) reported adequate privacy during healthcare conversations and 78.3% (395/504) during examination. 69.5% (348/501) understood their diagnosis, 89.4% (355/397) the rationale for performed tests, and 67.2% (338/503) their treatment plan. Children felt well taken care of by nurses (90.9%, 457/503) and doctors (90.8%, 444/489). Overall, 94.8% (475/501) of children were happy with their ED visit. Predictors of a child better understanding their diagnosis included doctors talking directly to them (OR 2.21 [1.15, 4.28]), having someone answer questions and worries (OR 2.51 [1.26, 5.01]), and older age (OR 1.08 [1.01, 1.16]). Direct communication with a doctor (OR 2.08 [1.09, 3.99]) was associated with children better understanding their treatment, while greater fear/ 'being scared' at baseline (OR 0.59 [0.39, 0.89]) or at discharge (OR 0.46 [0.22, 0.96]) had the opposite effect. INTERPRETATION: While almost all children felt well taken care of and were happy with their visit, close to 1/3 did not understand their diagnosis or its management. Children's reported satisfaction in the ED should not be equated with understanding of their medical condition. Further, caution should be employed in using caregiver satisfaction as a proxy for children's satisfaction with their ED visit, as caregiver satisfaction is highly linked to having their own needs being met.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".