The Therapeutic Misconception: A Threat to Valid Parental Consent for Paediatric Neuroimaging Research
Bibliographic record
Abstract
Neuroimaging research has brought major advances to child health and well-being. However, because of the vulnerabilities associated with neurological and developmental conditions, the parental need for hope, and the expectation of parents that new medical advances can benefit their child, pediatric neuroimaging research presents significant challenges to the general problem of consent in the context of research involving children. A particular challenge in this domain is created by the presence of therapeutic misconception on the part of parents and other key research stakeholders. This article reviews the concept of therapeutic misconception and its role in pediatric neuroimaging research. It argues that this misconception can compromise consent given by parents for the involvement of their children in research as healthy controls or as persons with neurological and developmental conditions. The article further contends that therapeutic misconception can undermine the research ethics review process for proposed and ongoing neuroimaging studies. Against this backdrop, the article concludes with recommendations for mitigating the effects of therapeutic misconception in pediatric neuroimaging 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 | 0.402 | 0.490 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.058 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.027 | 0.046 |
| 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".