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A multimethods randomized trial found that plain language versions improved adults understanding of health recommendations

2023· article· en· W4389001120 on OpenAlexafffund
Shahab Sayfi, Rana Charide, Sarah A Elliott, Lisa Hartling, Matthew Munan, Lisa Stallwood, Nancy J. Butcher, Dawn P. Richards, Joseph L. Mathew, Jozef Suvada, Elie A. Akl, Tamara Kredo, Lawrence Mbuagbaw, Ashley Motilall, Ami Baba, Shannon D. Scott, Maicon Falavigna, Miloslav Klugar, Tereza Friessová, Tamara Lotfi, Adrienne Stevens, Martin Offringa, Holger J. Schünemann, Kevin Pottie

Bibliographic record

VenueJournal of Clinical Epidemiology · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsSt. Joseph’s Healthcare HamiltonGlycemic Index LaboratoriesWestern UniversityUniversity of TorontoSickKids FoundationHospital for Sick ChildrenAlberta HealthUniversity of AlbertaMcMaster UniversityPublic Health Agency of CanadaUniversity of OttawaInstitute for Clinical Evaluative SciencesImpactCochrane
FundersCanadian Institutes of Health ResearchWorld Health Organization
KeywordsUsabilityRandomized controlled trialPlain languageMedicineGuidelinePopulationMedical educationMEDLINEFamily medicineApplied psychologyPsychologyComputer scienceEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: To make informed decisions, the general population should have access to accessible and understandable health recommendations. To compare understanding, accessibility, usability, satisfaction, intention to implement, and preference of adults provided with a digital "Plain Language Recommendation" (PLR) format vs. the original "Standard Language Version" (SLV). STUDY DESIGN AND SETTING: An allocation-concealed, blinded, controlled superiority trial and a qualitative study to understand participant preferences. An international on-line survey. 488 adults with some English proficiency. 67.8% of participants identified as female, 62.3% were from the Americas, 70.1% identified as white, 32.2% had a bachelor's degree as their highest completed education, and 42% said they were very comfortable reading health information. In collaboration with patient partners, advisors, and the Cochrane Consumer Network, we developed a plain language format of guideline recommendations (PLRs) to compare their effectiveness vs. the original standard language versions (SLVs) as published in the source guideline. We selected two recommendations about COVID-19 vaccine, similar in their content, to compare our versions, one from the World Health Organization (WHO) and one from Centers for Disease Control and Prevention (CDC). The primary outcome was understanding, measured as the proportion of correct responses to seven comprehension questions. Secondary outcomes were accessibility, usability, satisfaction, preference, and intended behavior, measured on a 1-7 scale. RESULTS: Participants randomized to the PLR group had a higher proportion of correct responses to the understanding questions for the WHO recommendation (mean difference [MD] of 19.8%, 95% confidence interval [CI] 14.7-24.9%; P < 0.001) but this difference was smaller and not statistically significant for the CDC recommendation (MD of 3.9%, 95% CI -0.7% to 8.3%; P = 0.096). However, regardless of the recommendation, participants found the PLRs more accessible, (MD of 1.2 on the seven-point scale, 95% CI 0.9-1.4%; P < 0.001) and more satisfying (MD of 1.2, 95% CI 0.9-1.4%; P < 0.001). They were also more likely to follow the recommendation if they had not already followed it (MD of 1.2, 95% CI 0.7-1.8%; P < 0.001) and share it with other people they know (MD of 1.9, 95% CI 0.5-1.2%; P < 0.001). There was no significant difference in the preference between the two formats (MD of -0.3, 95% CI -0.5% to 0.03%; P = 0.078). The qualitative interviews supported and contextualized these findings. CONCLUSION: Health information provided in a PLR format improved understanding, accessibility, usability, and satisfaction and thereby has the potential to shape public decision-making behavior.

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)0.009
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0220.002

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 head0.636
GPT teacher head0.676
Teacher spread0.041 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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".

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Citations17
Published2023
Admission routes2
Has abstractyes

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