Perceptions of and decision making about clinical trials in adolescent and young adults with Cancer: a qualitative analysis
Bibliographic record
Abstract
BACKGROUND: Adolescent and young adults (AYA) enrolment rates into cancer clinical trials (CCT) are the lowest of any age group globally. As AYA have distinct biological, psychosocial and relational needs, we aimed to explore any unique factors influencing their CCT decision-making process, including AYA-specific perceptions or attitudes towards CCT. METHODS: Qualitative interpretive descriptive methodology was used to explore AYA perceptions and decision-making related to CCT. An analytic approach conducive to inductive imagining and exploratory questioning was used in order to generate insights and interpret data. RESULTS: A total of 21 AYA were interviewed (median age: 31 (18-39)). Twelve (57%) participants had previously been approached to participate in CCT. Major themes influencing trial enrolment decisions were: 1) severity of illness/urgency for new treatment 2) side effect profile of investigational drug in the short and long term (e.g., impact on future quality of life) 3) who approached patient for trial participation (oncologist vs. other) 4) additional information found on-line about the trial and investigators, and 5) family, friends and peer group opinion regarding the CCT. CONCLUSIONS: Several psychosocial and relational factors were identified as influencing AYA CCT decisions, some of which are unique to this demographic. Specific strategies to address barriers to CCT and enable supportive decision-making include: 1) involving family in decision-making and 2) helping AYA appreciate short- and long-term implications of trial participation. Finally, exploring social networking and general education about CCT that AYA can independently access may increase participation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".