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Record W2768651471 · doi:10.1136/bmjopen-2017-017425

Interpretation of health news items reported with or without spin: protocol for a prospective meta-analysis of 16 randomised controlled trials

2017· article· en· W2768651471 on OpenAlexfundno aff
Romana Haneef, Amélie Yavchitz, Philippe Ravaud, Gabriel Baron, Ivan Oranksy, Gary Schwitzer, Isabelle Boutron

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
FundersYork University
KeywordsMedicineMisrepresentationHeadlineObservational studyRandomized controlled trialInterpretation (philosophy)PopulationPublic healthFamily medicineClinical trialProtocol (science)Sample size determinationAlternative medicineAdvertisingLinguisticsSurgeryNursingInternal medicineLawPathologyStatistics

Abstract

fetched live from OpenAlex

INTRODUCTION: We aim to compare the interpretation of health news items reported with or without spin. 'Spin' is defined as a misrepresentation of study results, regardless of motive (intentionally or unintentionally) that overemphasises the beneficial effects of the intervention and overstates safety compared with that shown by the results. METHODS AND ANALYSIS: We have planned a series of 16 randomised controlled trials (RCTs) to perform a prospective meta-analysis. We will select a sample of health news items reporting the results of four types of study designs, evaluating the effect of pharmacological treatment and containing the highest amount of spin in the headline and text. News items reporting four types of studies will be included: (1) preclinical studies; (2) phase I/II (non-randomised) trials; (3) RCTs and (4) observational studies. We will rewrite the selected news items and remove the spin. The original news and rewritten news will be appraised by four types of populations: (1) French-speaking patients; (2) French-speaking general public; (3) English-speaking patients and (4) English-speaking general public. Each RCT will explore the interpretation of news items reporting one of the four study designs by each type of population and will include a sample size of 300 participants. The primary outcome will be participants' interpretation of the benefit of treatment after reading the news items: (What do you think is the probability that treatment X would be beneficial to patients? (scale, 0 (very unlikely) to 10 (very likely)).This study will evaluate the impact of spin on the interpretation of health news reporting results of studies by patients and the general public. ETHICS AND DISSEMINATION: This study has obtained ethics approval from the Institutional Review Board of the Institut national de la santé et de la recherche médicale (INSERM) (registration no: IRB00003888). The description of all the steps and the results of this prospective meta-analysis will be available online and will be disseminated as a published article. On the completion of this study, the results will be sent to all participants. PROSPERO REGISTRATION NUMBER: CRD42017058941.

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)0.230
metaresearch head score (Gemma)0.335
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.980
Threshold uncertainty score0.950

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2300.335
Meta-epidemiology (narrow)0.0100.008
Meta-epidemiology (broad)0.0200.032
Bibliometrics0.0100.012
Science and technology studies0.0040.007
Scholarly communication0.0090.007
Open science0.0050.006
Research integrity0.0130.014
Insufficient payload (model declined to judge)0.0530.012

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 head0.907
GPT teacher head0.691
Teacher spread0.216 · 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 designMeta-analysis
DomainMethods
GenreProtocol

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

Citations25
Published2017
Admission routes1
Has abstractyes

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