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Record W4220915955 · doi:10.2196/36928

Adult Vaccine Hesitancy Scale in Arabic and French: Protocol for Translation and Validation in the World Health Organization Eastern Mediterranean Region

2022· article· en· W4220915955 on OpenAlexvenueno aff
Radwa Nour, Leigh Powell, Wafa K. Alnakhi, Heba Mamdouh, Youness Zidoun, Hamid Y. Hussain, Hanan Al Suwaidi, Nabil Zary

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
FundersAl Jalila FoundationPfizer
KeywordsArabicProtocol (science)Scale (ratio)GeographyMedicineFamily medicineLinguisticsAlternative medicineCartography

Abstract

fetched live from OpenAlex

BACKGROUND: The world as we know it changed during the COVID-19 pandemic. Hope has emerged with the development of new vaccines against the disease. However, many factors hinder vaccine uptake and lead to vaccine hesitancy. Understanding the factors affecting vaccine hesitancy and how to assess its prevalence have become imperative amid the COVID-19 pandemic. The vaccine hesitancy scale (VHS), developed by the World Health Organization (WHO) Strategic Advisory Group of Experts on Immunization, has been modified to the adult VHS (aVHS) and validated in English and Chinese. To our knowledge, no available aVHS has been designed or validated in Arabic or French. OBJECTIVE: The aim of this research is to translate the aVHS from its original English language to Arabic and French and validate the translations in the WHO Eastern Mediterranean region. METHODS: The study will follow a cross-sectional design divided into 5 phases. In phase 1, the original aVHS will be forward-translated to Arabic and French, followed by backward translation to English. An expert committee will review and rate all versions of the translations. Expert agreement will then be measured using the Cohen kappa coefficient (k). In phase 2, the translated aVHS will be pilot-tested with 2 samples of participants (n=100): a group that speaks both Arabic and English and another that speaks French and English. Participants' responses to the English version will also be collected. In phase 3, responses will then be compared. Descriptive statistics and paired t tests or one-way analyses of variance (ANOVA) and Pearson correlation coefficient will be used in the preliminary validation. In phase 4, prefinal versions (Arabic and French) will be tested with larger sample sizes of Arabic speakers (n=1000) and French speakers (n=1000). Sociodemographic information and vaccination status will be collected and used for further analysis. In phase 5, the scale's statistical reliability and internal consistency will be measured using Cronbach alpha. An exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) will be used to examine the model fit resulting from the EFA. ANOVA and regression models will be constructed to control for confounders. All data will be electronically collected. RESULTS: As of January 2022, the scale had been translated to Arabic and French and was undergoing the process of back translation. All data collection tools have been prepared (ie, sociodemographics, vaccination status, and open-ended questions) and are ready to go into their electronic formats. We expect to reach the desired sample size in this phase by June 2022. CONCLUSIONS: This study will provide researchers with a validated tool to assess adult vaccine hesitancy within populations that speak Arabic and/or French and provide a road map to scale translation and ensure cross-cultural adaptation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/36928.

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)0.039
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.039
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.029
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0360.011

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 head0.249
GPT teacher head0.514
Teacher spread0.264 · 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 designNot applicable
Domainnot available
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

Citations9
Published2022
Admission routes1
Has abstractyes

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