Navigating choice in the face of uncertainty: using a theory informed qualitative approach to identifying potential patient barriers and enablers to participating in an early phase chimeric antigen receptor T (CAR-T) cell therapy trial
Bibliographic record
Abstract
OBJECTIVES: Bench to bedside translation of groundbreaking treatments like chimeric antigen receptor T (CAR-T) cell therapy depends on patient participation in early phase trials. Unfortunately, many novel therapies fail to be adequately evaluated due to low recruitment rates, which slows patient access to emerging treatments. Using the Theoretical Domains Framework (TDF), we sought to identify potential patient barriers and enablers to participating in an early phase CAR-T cell therapy trial. DESIGN: We used qualitative semistructured interviews to identify potential barriers and enablers to patients' hypothetical participation in an early phase CAR-T cell therapy trial. We used the TDF and directed content analysis to identify relevant domains based on frequency, relevance and the presence of conflicting beliefs. PARTICIPANTS: Canadian adult patients diagnosed with haematological malignancies. RESULTS: In total, we interviewed 13 participants (8 women, 5 men). Participants ranged in age from 18 to 73 (median=56) and had been living with haematological cancer from a few months to several years. We found participants were unfamiliar with CAR-T cell therapy but wished to know more about treatment safety, efficacy and trial logistics (domains: knowledge, beliefs about consequences). They were motivated by altruistic considerations, though many prioritised personal health benefits despite recognising the goals (ie, establishing safety) of early phase clinical trials (domains: goals, intentions). Every participant valued receiving medical advice from their haematologists and oncologists, though some preferred impartial medical experts to inform their decision making (domain: social influences). Finally, participants indicated that improving access to financial and social supports would improve their trial participation experience (domain: environmental context and resources). CONCLUSION: NCT03765177; Pre-results.
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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 | 0.038 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| 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".