Ethics of Involving Children in Health-Related Research: Applying a Decision-Making Framework to a Clinical Trial
Bibliographic record
Abstract
PURPOSE: This paper explores ethical issues related to the involvement of children in health-related research through the application of a conceptual model (the Miller and Kenny framework) to a current clinical trial on casting protocols for equinus gait of children with cerebral palsy (CP). SUMMARY OF KEY POINTS: The direct involvement of children in health-related research is important for maintaining and improving standards of paediatric clinical care. Ethical considerations around investigations involving this highly vulnerable population are complex, however, requiring the involvement of many levels of decision makers-government, research ethics boards (REBs), health care providers, parents, and children. The Miller and Kenny framework is useful in distinguishing these levels and heightening awareness of the complexities of the issues around engaging children in research. Considerations include the role of parents/caregivers in decision making, individual assessment of the child's decisional capacities, close attention to the child's context and life experience, provision of developmentally appropriate information about the research study, and careful assessment of dissent prior to withdrawing the child from the study. RECOMMENDATIONS: Physical therapists involved in paediatric clinical practice and/or research must be knowledgeable about ethical principles, policies, and REB requirements. The Miller and Kenny framework is a helpful guide to clarify decision-making roles around children's participation in research.
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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 | 0.677 | 0.476 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.093 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.007 | 0.017 |
| Research integrity | 0.029 | 0.033 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".