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Readability and Quality Assessment of Online Patient Education Materials for Spinal and Epidural Anesthesia

2025· article· en· W4410947900 on OpenAlexaff
Reena Rai, JJ Wiseman, Anthony Chau, Sam M. Wiseman

Bibliographic record

VenueObstetric Anesthesia Digest · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsSt. Paul's HospitalProvidence Health Care
Fundersnot available
KeywordsMedicineReadabilityAnesthesiaSpinal anesthesiaQuality (philosophy)Medical physicsComputer science

Abstract

fetched live from OpenAlex

(Can J Anesth/J Can Anesth. 2024;71(8):1092–1102. doi: 10.1007/s12630-024-02771-9) A study assessed the readability and quality of online patient education materials about spinal and epidural anesthesia, focusing on whether they align with recommended guidelines for accessibility. The American Medical Association suggests health-related materials should be written at or below a sixth-grade reading level to ensure comprehension by a broad audience. The researchers utilized Google Search to evaluate 261 webpages found through 11 relevant search terms. Seven readability formulas were used, including the Flesch-Kincaid Grade Level (FKGL), Coleman–Liau Index (CLI), Gunning Fog Index (GFI), Simple Measure of Gobbledygook (SMOG), Flesch Reading Ease (FRE), New Dale–Chall (NDC), and Automated Readability Index (ARI).

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)0.011
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.003
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.081
GPT teacher head0.441
Teacher spread0.360 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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