Insufficient recruitment and premature discontinuation of clinical trials in Switzerland: qualitative study with trialists and other stakeholders
Bibliographic record
Abstract
AIMS OF THE STUDY: Premature discontinuation occurs in about 25% of randomised clinical trials in Switzerland; it mainly affects investigator-initiated trials and is mostly due to problems with recruitment of patients. The aim of this study was to qualitatively investigate reasons for trial discontinuation due to poor patient recruitment and suggestions to address those reasons in the Swiss context. METHODS: We conducted semi-structured interviews with trialists whose trials were discontinued because of recruitment problems, other experienced trialists, and stakeholders in clinical research in Switzerland. Interviews were audio-recorded, transcribed verbatim, and anonymised. We analysed the transcripts using deductive coding and built up themes that were continuously discussed within the research team. RESULTS: Of 65 invited Swiss trialists and stakeholders, 39 (60%) agreed to be interviewed and contributed to this analysis. We identified four main themes of reasons for poor recruitment: (1) Switzerland has a decentralised healthcare system with many small hospitals and few patients per hospital, many research regulations, no standardisation of medical records across hospitals, and a heterogeneous ethics assessment of study protocols. There is little collaboration of different stakeholders in clinical research and a lack of prioritisation of projects. (2) Limited human and financial resources, especially in the academic setting, compromise research questions and size of clinical trials. When funding is used up this typically triggers discontinuation of already delayed clinical trials. (3) Investigators face underdeveloped research networks and a limited collaborative attitude among clinical researchers. They typically embark on clinical studies with a great deal of optimism but insufficient preparation. (4) Swiss patients have universal health coverage and many treatment options. Negative media coverage of clinical research and a lack of accessible information for patients about ongoing clinical studies frequently make participation in clinical trials less attractive. More interactive structures and collaboration across stakeholders were mentioned as potential solutions to tackle the problems. CONCLUSIONS: Recruitment of participants into clinical trials in Switzerland is challenging because of various, often interlinked factors related to the Swiss health system, available funding, investigators, and patients. Common goals and concerted efforts by involved stakeholders appear necessary to achieve improvement.
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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 | 0.046 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".