Decision-making by Adolescents and Parents of Children With Cancer Regarding Health Research Participation
Bibliographic record
Abstract
BACKGROUND: Low rates of participation of adolescents and young adults (AYAs) in clinical oncology trials may contribute to poorer outcomes. Factors that influence the decision of AYAs to participate in health research and whether these factors are different from those that affect the participation of parents of children with cancer. METHODS: This is a secondary analysis of data from validated questionnaires provided to adolescents (>12 years old) diagnosed with cancer and parents of children with cancer at 3 sites in Canada (Halifax, Vancouver, and Montreal) and 2 in the United States (Atlanta, GA, and Memphis, TN). Respondents reported their own research participation and cited factors that would influence their own decision to participate in, or to provide parental authorization for their child to participate in health research. RESULTS: Completed questionnaire rates for AYAs and parents were 86 (46.5%) of 185 and 409 (65.2%) of 627, respectively. AYAs (n = 86 [67%]) and parents (n = 409 [85%]) cited that they would participate in research because it would help others. AYAs perceived pressure by their family and friends (16%) and their physician (19%). Having too much to think about at the time of accrual was an impediment to both groups (36% AYAs and 47% parents). The main deterrent for AYAs was that research would take up too much time (45%). Nonwhite parents (7 of 56 [12.5%]) were more apt to decline than white parents (12 of 32 [3.7%]; P < .01). CONCLUSIONS: AYAs identified time commitment and having too much to think about as significant impediments to research participation. Addressing these barriers by minimizing time requirements and further supporting decision-making may improve informed consent and impact on enrollment in trials.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".