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Record W3119187406 · doi:10.1111/aogs.14079

Sociodemographic and health‐related determinants of seasonal influenza vaccination in pregnancy: A systematic review and meta‐analysis of the evidence since 2000

2021· review· en· W3119187406 on OpenAlexaff
George N. Okoli, Viraj K. Reddy, Yahya Al‐Yousif, Christine Neilson, Salaheddin M. Mahmud, Ahmed M Abou-Setta

Bibliographic record

VenueActa Obstetricia Et Gynecologica Scandinavica · 2021
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of ManitobaManitoba HealthGeorge & Fay Yee Centre for Healthcare Innovation
Fundersnot available
KeywordsMedicineVaccinationMeta-analysisOdds ratioPregnancyConfidence intervalInfluenza vaccineCINAHLSeasonal influenzaMEDLINEPopulationDemographyPediatricsEnvironmental healthPsychological interventionImmunologyInternal medicineDiseaseCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

INTRODUCTION: Vaccination is considered to be the most practical and effective preventative measure against influenza. It is highly recommended for population subgroups most at risk of developing complications, including pregnant women. However, seasonal influenza vaccine uptake remains suboptimal among pregnant women, even in jurisdictions with universal vaccination. We summarized the evidence on the determinants of seasonal influenza vaccine uptake during pregnancy to better understand factors that influence vaccine uptake among pregnant women. MATERIAL AND METHODS: We systematically searched MEDLINE, Embase and CINAHL from January 2000 to February 2020 for publications in English reporting on sociodemographic and/or health-related determinants of seasonal influenza vaccine uptake during pregnancy. Two reviewers independently included studies. One reviewer extracted data and assessed study quality, and another reviewer checked extracted data and study quality assessments for errors. Disagreements were resolved through consensus, or a third reviewer. We meta-analyzed using the inverse variance, random-effects method, and reported the odds ratios (OR) and 95% confidence intervals (CI). RESULTS: From 1663 retrieved citations, we included 36 studies. The following factors were associated with increased seasonal influenza vaccine uptake: Older age (20 studies: OR 1.13, 95% CI 1.07-1.20), being nulliparous (13 studies: OR 1.26, 95% CI 1.15-1.38), married (8 studies: OR 1.11, 95% CI 1.07-1.15), employed (4 studies: OR 1.13, 95% CI 1.02-1.24), a non-smoker (8 studies: OR 1.25, 95% CI 1.04-1.51) and having prenatal care (3 studies: OR 3.36, 95% CI 2.25-5.02), a chronic condition (6 studies: OR 1.30, 95% CI 1.17-1.44), been previously vaccinated (9 studies: OR 4.88, 95% CI 3.14-7.57) and living in a rural area (9 studies: OR 1.09, 95% CI 1.05-1.14). Compared with being black, being white was also associated with increased seasonal influenza vaccine uptake (11 studies: OR 1.30, 95% CI 1.20-1.41). CONCLUSIONS: The evidence suggests that several sociodemographic and health-related factors may determine seasonal influenza vaccination in pregnancy, and that parity, history of influenza vaccination, prenatal care and comorbidity status may be influential.

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)0.016
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.048
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.030
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.220
GPT teacher head0.458
Teacher spread0.238 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations24
Published2021
Admission routes1
Has abstractyes

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