MétaCan
Menu
Back to cohort
Record W4223490554 · doi:10.1080/21645515.2022.2048623

Exploring the impact of media and information on self-reported intentions to vaccinate against COVID-19: A qualitative interview-based study

2022· article· en· W4223490554 on OpenAlexafffund
Jeanna Parsons Leigh, Beth Halperin, Sara J. Mizen, Emily A. FitzGerald, Stephana J. Moss, Kirsten M. Fiest, Antonia M. Di Castri, Henry T. Stelfox, Scott A. Halperin

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversity of CalgaryAlberta Health ServicesSt. Francis Xavier UniversityDalhousie University
FundersCanadian Institutes of Health Research
KeywordsThematic analysisVaccinationMisinformationMedicineQualitative researchMeaslesSocial mediaPublic healthPsychological interventionPopulationFamily medicinePsychologyEnvironmental healthImmunologyNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The World Health Organization declared vaccine hesitancy a top threat to global health following resurgence of vaccine-preventable diseases close to eradication in many countries (e.g. measles). Vaccines are effective in preventing severe illness, hospitalization, and death from COVID-19, yet there remains a small proportion of the eligible population who choose not to vaccinate. Social media and online news sources are opportunities for targeted public health interventions to improve vaccine uptake. This study reports the results of a semi-structured interview study that explored the influence of media and information on individuals' self-reported intentions to vaccinate against COVID-19. METHODS: A qualitative descriptive study was employed to gain insight from a diverse group of individuals. Adult participants were recruited through a related COVID-19 study; we used a maximum variation sampling technique and purposively sampled participants based on demographics. Interviews were conducted from February 2021 to May 2021. Themes from interviews were summarized with representative quotations according to the 3C Theoretical Framework (Confidence, Complacency, Convenience). RESULTS: Key themes identified following thematic analysis from 60 participants included: vaccine safety, choice of vaccine, fear mongering, trust in authority, belief in vaccinations (Confidence); delaying vaccination (Complacency); confusing information, access to vaccines and information (Convenience). While most participants intended to vaccinate, many expressed concerns and hesitancy. CONCLUSIONS: COVID-19 vaccine hesitancy prevents universal immunization and contradictory messages in media are a source of concern and fear. The success of future vaccine campaigns will depend upon authorities' ability to disseminate accessible, detailed, and consistent information promoting public confidence.

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)0.015
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.199
GPT teacher head0.423
Teacher spread0.223 · 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 designQualitative
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

Citations11
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueHuman Vaccines & ImmunotherapeuticsSame topicVaccine Coverage and HesitancyFrench-language works237,207