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Record W3199985912 · doi:10.21203/rs.3.rs-102043/v1

Patient and public involvement prior to trial initiation: lessons learnt for rapid partnership in the COVID-19 era.

2020· preprint· en· W3199985912 on OpenAlexaff
Zahra Jamal, Alexander Perkins, Christopher Allen, Research Group, Richard D. Evans, Joanna Sturgess, Claire Snowdon, Tim Clayton, Diana Elbourne

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsClinical trialMedicinePandemicTimelineProtocol (science)Medical educationAlternative medicineCoronavirus disease 2019 (COVID-19)Family medicinePublic relationsPolitical sciencePathologyDisease

Abstract

fetched live from OpenAlex

Abstract Background: Clinical trials are playing a critical role in the global public health response to the COVID-19 pandemic. Despite the increasing recognition of the value of PPI in clinical trials, just 20% of the COVID-19 research proposals reviewed by Research Ethics Committees in the UK at the start of the pandemic reported PPI. There is a perception that PPI might result in delays in delivering research and therefore delays in obtaining important results. In this paper, we report our experience of rapid PPI for a COVID-19 clinical trial. Methods: RAPID-19 is a COVID-19 clinical trial which was planned to be submitted for fast-track ethics review in the United Kingdom. During the development of the trial protocol, the PPI Panel at the London School of Hygiene & Tropical Medicine Clinical Trials Unit was involved in the design of the study. The meeting with the PPI Panel lasted just over one hour and was conducted by teleconference.Results: Although we only had a short period of time to explore the study with the PPI Panel, we were able to gain valuable insight into how the trial would be perceived by potential trial participants. Substantive changes were made to the trial to improve the acceptability of the research without compromising the study timelines. Having access to public contributors with relevant lived experience is an important resource for a Clinical Trials Unit and is critical for rapid PPI. The move to remote working due to lockdown required virtual discussions which helped to overcome some of the barriers to organising face-to-face meetings at short notice.Conclusions: PPI for clinical trials can be conducted in a time-efficient manner within the pressured environment of a pandemic. Involving PPI contributors at an early stage in protocol development maximised the opportunity to shape and influence the trial as well as limited potential delays which could occur if changes to the protocol had to be made at a later stage

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.359
metaresearch head score (Gemma)0.506
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.641
Threshold uncertainty score0.790

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3590.506
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0120.012
Scholarly communication0.0260.036
Open science0.0080.042
Research integrity0.0200.042
Insufficient payload (model declined to judge)0.0280.009

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 head0.776
GPT teacher head0.603
Teacher spread0.173 · 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

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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