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Record W2993885906 · doi:10.1186/s13063-019-3957-4

Comparison of randomized controlled trials discontinued or revised for poor recruitment and completed trials with the same research question: a matched qualitative study

2019· article· en· W2993885906 on OpenAlex
Matthias Briel, Benjamin Speich, Erik von Elm, Viktoria Gloy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTrials · 2019
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMcMaster University
FundersUniversitätsspital BaselSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsRandomized controlled trialMedicineContext (archaeology)Patient recruitmentPopulationResearch designSample size determinationConsolidated Standards of Reporting TrialsAlternative medicineMEDLINEFamily medicinePhysical therapySurgeryPathologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: More than a quarter of randomized controlled trials (RCTs) are prematurely discontinued, mostly due to poor recruitment of patients. In this study, we systematically compared RCTs discontinued or revised for poor recruitment and completed RCTs with the same underlying research question to better understand the causes of poor recruitment, particularly related to methodological aspects and context-specific study settings. METHODS: We compared RCTs that were discontinued or revised for poor recruitment to RCTs that were completed as planned, matching in terms of population and intervention. Based on an existing sample of RCTs discontinued or revised due to poor recruitment, we identified matching RCTs through a literature search for systematic reviews that cited the discontinued or revised RCT and matching completed RCTs without poor recruitment. Based on extracted data, we explored differences in the design, conduct, and study settings between RCTs with and without poor recruitment, separately for each research question using semi-structured discussions. RESULTS: We identified 15 separate research questions with a total of 29 RCTs discontinued or revised for poor recruitment and 48 RCTs completed as planned. Prominent research areas in the sample were cancer and acute care. The mean number of RCTs with poor recruitment per research question was 1.9 ranging from 1 to 4 suggesting clusters of research questions or settings prone to recruitment problems. The reporting quality of the recruitment process in RCT publications was generally low. We found that RCTs with poor recruitment often had narrower eligibility criteria, were investigator- rather than industry-sponsored, were associated with a higher burden for patients and recruiters, sometimes used outdated control interventions, and were often launched later in time than RCTs without poor recruitment compromising uncertainty about tested interventions through emerging evidence. Whether a multi- or single-center setting was advantageous for patient recruitment seemed to depend on the research context. CONCLUSIONS: Our study confirmed previously identified causes for poor recruitment, i.e., narrow eligibility criteria, investigator sponsorship, and a reduced motivation of patients and recruiters. Newly identified aspects were that researchers need to be aware of all other RCTs on a research question so that compromising effects on the recruitment can be minimized and that a larger number of centers is not always advantageous.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.774
metaresearch head score (Gemma)0.829
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.7740.829
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0290.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.924
GPT teacher head0.756
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it