Children’s assent within clinical care: A concept analysis
Bibliographic record
Abstract
Seeking children's assent has been put forward as a way to foster children's involvement in the healthcare decision-making process. However, the functions of the concept of assent within clinical care are manifold, and methods used to recognize children's capacities and promote their involvement in their care remain debated. We performed an instrumentalist concept analysis of assent, with 58 included articles. Final themes were jointly identified through a deliberative process. Two distinct perspectives of assent were predominant: as an affirmative agreement for a specific decision and as part of a continuous, interactive process of care. Differing standards were provided as to how and when to apply the concept of assent. The concept of dissent was largely omitted from conceptions of assent, especially in situations for which children's refusal would lead to severe health consequences. Ethical implications included fostering autonomy, reducing physical/psychological harm to the child, respecting the child as a human being, and fulfilling the universal rights of the child. There remain important gaps in the theory of assent and its desirable and possible practical implications. Practical standards are largely missing, and evidence supporting the claims made in the literature requires further investigation.
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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 | 0.059 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".