Perceptions and attitudes toward clinical trials in adolescent and young adults with cancer: a systematic review
Bibliographic record
Abstract
Victoria Forcina,1 Branavan Vakeesan,1 Chelsea Paulo,1 Laura Mitchell,1 Jennifer AH Bell,2 Seline Tam,1 Kate Wang,1 Abha A Gupta,1,3,4 Jeremy Lewin1,3,5 1Adolescent and Young Adult Program, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada; 2Joint Center for Bioethics, University of Toronto, Toronto, ON, Canada; 3Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON, Canada; 4Division of Hematology/Oncology, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada; 5ONTrac, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia Purpose: Although cancer clinical trials (CT) offer opportunities for novel treatments that may lead to improved outcomes, adolescents and young adults (AYA) are less likely to participate in these trials as compared to younger children and older adults. We aimed to identify the perceptions and attitudes toward CT in AYA that influence trial participation. Materials and methods: A systematic review of cancer literature was conducted that assessed perceptions and attitudes toward CT enrollment limited to AYA patients (defined as age 15–39). We estimated the frequency of identified themes by pooling identified studies. Results: In total, six original research articles were identified that specifically addressed perceptions or attitudes that influenced CT participation in AYA patients. Three studies were conducted at pediatric centers – one at an AYA unit, one at an adult cancer hospital, and one was registry based. Major themes identified for CT acceptability included: hope for positive clinical affect, altruism, and having autonomy. Potential deterrents included: prolonged hospitalization, worry of side effects, and discomfort with experimentation. Conclusion: Limited information is available with regard to the perceptions and attitudes toward CT acceptability among AYA patients, especially those treated at adult cancer centers, which prevents generalization of data and themes. Future research assessing strategies for understanding and supporting CT decision-making processes among AYA represents a key focus for future funding to improve CT enrollment. Keywords: adolescent and young adult, clinical trials, barriers, psychosocial, cancer
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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 | 0.039 | 0.216 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| 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".