Children's participation rights and the role of pediatric healthcare teams: A critical review
Bibliographic record
Abstract
AIM: A critical review examined how childrens participation rights as represented in the United Nations Convention on the Rights of the Child inform the work of pediatric teams in healthcare settings. METHODS: We systematically searched peer-reviewed literature on the enactment of child participation rights, within the context of pediatric teams. Articles were evaluated using the LEGEND (Let Evidence Guide Every New Decision) tool. Data extraction and analysis highlighted themes and disparities between articles, as well as gaps. A total of 25 studies were selected. RESULTS: We reviewed studies from around the globe, with the majority of papers from the UK. Qualitative and mixed methods approaches were administered. The following observations were made: (1) limited language of children's rights exists in the literature, (2) lack of information regarding the composition of pediatric healthcare teams and how they work with children, (3) children's perspectives on what constitutes good interactions with healthcare providers are replicated, (4) minimal references to theory or philosophical underpinnings that can guide practice. CONCLUSION: Explicit references to children's participation rights are lacking in the literature which may reflect the absence of rights language that could inform pediatric practice. Descriptive understandings of the tenets of pediatric interprofessional team composition and collaboration are necessary if we are to imagine the child as part of the team along with their family. Despite these shortcomings, the literature alludes to children's ability to discern desirable interactions with healthcare providers.
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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 | 0.036 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| 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".