Does prospective acceptability of an intervention influence refusal to participate in a randomised controlled trial? An interview study
Bibliographic record
Abstract
BACKGROUND: The generalizability of findings of Randomised Controlled Trials (RCTs) is undermined by low or biased recruitment. Reasons for participant refusal are infrequently reported in published literature. AIMS: To apply the Theoretical Framework of Acceptability (TFA) to: (1) explore patient-reported reasons for declining to participate in a RCT comparing a new service model (patient-initiated appointments) with standard care (appointments scheduled by clinician) for managing blepharospasm and hemifacial spasm; (2) to explore associations between decliners' perceptions of acceptability and non-participation. METHOD: Eligible patients (n = 242) were approached to participate in the trial. Phase 1: decliners provided a brief reason for refusal. Reasons were analysed descriptively and reviewed against TFA constructs. PHASE 2: Consecutive decliners participated in short semi-structured interviews, to explore their reasons for refusal in more depth. Interviews were transcribed and analysed, with the TFA as a coding framework. RESULTS: Eighty-seven (36%) eligible patients refused trial participation; all provided a reason. From interviews with 15 decliners (17%), four key beliefs about acceptability were identified: happy with standard care (n = 41) (49%), anticipated burden of patient-initiated service, lack of confidence in ability to engage with new service and uncertainties about effectiveness of new service. Two themes reflected non-TFA factors: trial participation a low priority and burden of completing trial documentation. CONCLUSION: Reasons for refusal trial participation included: (a) reasons directly associated with intervention acceptability, and (b) reasons associated with trial participation more broadly. The TFA facilitated identification of problematic aspects of the new appointment booking system which could be addressed to enhance acceptability.
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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 | 0.579 | 0.738 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".