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Record W4324274079 · doi:10.1136/ebm-2022-ebmlive.44

149 Factors relating to nonpublication and publication bias in clinical trials in Canada: a qualitative interview study

2022· article· en· W4324274079 on OpenAlex
Richard A. Morrow, Barbara Mintzes, Garry Gray, Michael R. Law, Scott Garrison, Colin R. Dormuth

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAbstracts · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsUniversity of AlbertaUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsClinical trialQualitative researchAlternative medicineNonprobability samplingDrug trialFamily medicineGrounded theoryMedicineCoding (social sciences)PsychologyMedical educationSocial sciencePathologyEnvironmental healthSociology

Abstract

fetched live from OpenAlex

<h3>Objectives</h3> Clinical trials are essential for informing drug development and clinical practice, but many clinical trials are not published and positive trials are more likely to be published than negative trials. Systematic reviews have examined factors contributing to nonpublication of biomedical and health-related studies, based on reasons provided by investigators. However, the ambiguity of reasons commonly given for nonpublication, such as a lack of time or the low priority of a study, make these studies difficult to interpret. We conducted a qualitative interview study to investigate factors related to clinical trial reporting in Canada. The analysis reported in this abstract aimed to understand factors contributing to nonpublication and publication bias in clinical trials in Canada. We have separately published findings from these interviews relating to industry sponsor influence in clinical trial reporting. <h3>Method</h3> Our study used a qualitative research design involving semi-structured, in-depth interviews. We conducted the interviews between March 2019 and April 2021 with participants in the Canadian provinces of Alberta, British Columbia and Ontario. We used purposive sampling to include clinical trial investigators from a range of fields, past trial participants from trials of treatments for a variety of medical conditions, and others involved in the conduct, administration or ethical review of clinical trials. Analysis of interview transcripts was informed by grounded theory. Initial coding involved developing provisional codes to characterize processes relating to clinical trial reporting. Focused coding and memo-writing were used to identify key themes. <h3>Results</h3> The study included 17 clinical trial investigators, 1 clinical research coordinator, 3 research administrators, 3 research ethics board members, and 10 clinical trial participants. Several factors contribute to nonpublication and publication bias in trial research. A core theme was that reporting practices are shaped by incentives within the research system which favour publication of positive over negative trials. Investigators are discouraged from reporting by experiences or perceptions of difficulty in publishing negative findings but rewarded for publishing positive findings in various ways. Publication of positive trials may be more likely to lead to funding from industry sponsors and nonindustry funders. Research institutions play a role in incentivizing publication of positive trials, by rewarding researchers who attract funding and publish in prestigious journals, through promotion, bonuses, and recognition. Policies to promote trial reporting have been too weak and inconsistent to counterbalance the prevailing incentives that lead to nonpublication and publication bias. <h3>Conclusions</h3> While a range of factors contribute to nonpublication and publication bias, our study suggests that clinical trial reporting practices in Canada are shaped by incentives which favour publication of positive over negative trials. Canadian universities and research institutions could help change incentives by more widely adopting performance metrics that emphasize full reporting of trial results in journals or registries. It may also be valuable for research institutions to implement programs to support researchers to report results in trial registries in a timely manner, which could be modelled on strategies used at some US medical schools to improve compliance with regulatory requirements to report clinical trials. Health Canada could also play a central role in changing incentives by adopting regulatory measures to require timely reporting of results within a recognized clinical trial registry.

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)0.196
metaresearch head score (Gemma)0.292
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1960.292
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.691
GPT teacher head0.591
Teacher spread0.100 · 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