MétaCan
Menu
Back to cohort
Record W4392582103 · doi:10.1371/journal.pgph.0002610

Impact of vaccination education in cardiac rehabilitation on attitudes and knowledge

2024· article· en· W4392582103 on OpenAlexaff
Andrea Rivera Solera, Marta Supervía, José R. Medina‐Inojosa, David Bedos Senon, Francisco López-Jiménez, Sherry L. Grace

Bibliographic record

VenuePLOS Global Public Health · 2024
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsToronto Rehabilitation InstituteYork UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsVaccinationMisinformationMedicineIntervention (counseling)Patient educationRehabilitationFamily medicinePhysical therapyNursingImmunology

Abstract

fetched live from OpenAlex

Clinical guidelines recommend influenza vaccination for cardiac patients, and COVID-19 vaccination is also beneficial given their increased risk. Patient education regarding vaccination was developed for cardiac rehabilitation (CR); impact on knowledge and attitudes were evaluated. A single-group pre-post design was applied at a Spanish CR program in early 2022. After baseline assessment, a nurse delivered the 40-minute group education. Knowledge and attitudes were re-assessed. Sixty-one (72%) of the 85 participants were vaccinated for influenza, and 40 (47%) for pneumococcus. Most participants perceived vaccines were important, and that the COVID-19 vaccine specifically was important, with three-quarters not influenced by vaccine myths/misinformation. The education intervention resulted in significant improvements in perceptions of the importance of vaccines (Hake's index 69%), understanding of myths (48%), knowledge of the different types of COVID vaccines (92%), and when they should be vaccinated. Vaccination rates are low despite their importance; while further research is needed, education in the CR setting could promote greater uptake.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.330
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.490
Teacher spread0.406 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePLOS Global Public HealthSame topicInfluenza Virus Research StudiesFrench-language works237,207