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Record W3135532508 · doi:10.3390/ijerph18052611

French Public Familiarity and Attitudes toward Clinical Research during the COVID-19 Pandemic

2021· article· en· W3135532508 on OpenAlexaboutno aff
Émilien Schultz, Jeremy K. Ward, Laëtitia Atlani-Duault, Seth M. Holmes, Julien Mancini

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsPandemicPharmaceutical industryClinical trialCoronavirus disease 2019 (COVID-19)PopulationDistancingHealth literacyMedicineQuarter (Canadian coin)Public healthLiteracyPsychologyFamily medicinePublic relationsNursingHealth carePolitical scienceEnvironmental healthGeographyPathologyPharmacology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic put clinical research in the media spotlight globally. This article proposes a first measure of familiarity with and attitude toward clinical research in France. Drawing from the "Health Literacy Survey 2019" (HLS19) conducted online between 27 May and 5 June 2020 on a sample of the French adult population (N = 1003), we show that a significant proportion of the French population claimed some familiarity with clinical trials (64.8%) and had positive attitudes (72%) toward them. One of the important findings of this study is that positive attitudes toward clinical research exist side by side with a strong distancing from the pharmaceutical industry. While respondents acknowledged that the pharmaceutical industry plays an important role in clinical research (68.3%), only one-quarter indicated that they trust the industry (25.7%). Positive attitudes toward clinical trials were associated with familiarity with clinical trials (Odds Ratio, OR 2.97 [1.90-4.63]), financial difficulties (OR 0.63 [0.46-0.85]), as well as mistrust of doctors (0.48 [0.27-0.85]) and of scientists (OR 0.62 [0.38-0.99]). Although the French media provided a great deal of information on how clinical research works during the first months of the pandemic, there remains profound mistrust of the pharmaceutical industry in France. This suspicion can undermine crisis management, especially in the areas of vaccine development and preparation for future pandemics.

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 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)0.021
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.408
GPT teacher head0.543
Teacher spread0.135 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
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

Citations12
Published2021
Admission routes1
Has abstractyes

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