Children’s understanding of the risks and benefits associated with research
Bibliographic record
Abstract
OBJECTIVE: The objective of the current study was to maximise the amount of information children and adolescents understand about the risks and benefits associated with participation in a biomedical research study. DESIGN: Participants were presented with one of six hypothetical research protocols describing how to fix a fractured thigh using either a "standard" cast or "new" pins procedure. Risks and benefits associated with each of the treatment options were manipulated so that for each one of the six protocols there was either a correct or ambiguous choice. PARTICIPANTS AND SETTING: Two hundred and fifty one children, ages 6-15 (53% boys), and 237 adults (30% men) were interviewed while waiting for a clinic appointment at the Hospital for Sick Children. RESULTS: Using standardised procedures and questionnaires, it was determined that most participants, regardless of age group, were able to understand the basic purpose and procedures involved in the research, and most were able to choose the "correct" operation. The younger children, however, showed an overall preference for a cast operation, whereas the older participants were more likely to choose the pins. CONCLUSIONS: By creating age appropriate modules of information, children as young as six years can understand potentially difficult and complex concepts such as the risks and benefits associated with participation in biomedical research. It appears, however, that different criteria were used for treatment preference, regardless of associated risks; older participants tended to opt for mobility (the pins procedure) whereas younger participants stayed with the more familiar cast operation.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".