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Record W2738000783 · doi:10.2196/publichealth.6870

Facebook Recruitment of Vaccine-Hesitant Canadian Parents: Cross-Sectional Study

2017· article· en· W2738000783 on OpenAlexaffvenueabout
Jordan Tustin, Natasha S. Crowcroft, Dionne Gesink, Ian Johnson, Jennifer Keelan, Barbara Lachapelle

Bibliographic record

VenueJMIR Public Health and Surveillance · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsToronto Public HealthConcordia University of EdmontonToronto Metropolitan UniversityPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsHerd immunityRandom digit dialingSocial mediaImmunizationCross-sectional studyInternet privacyEnvironmental healthPsychologyFamily medicineMedicinePopulationImmunologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: There is concern over the increase in the number of "vaccine-hesitant" parents, which contributes to under-vaccinated populations and reduced herd immunity. Traditional studies investigating parental immunization beliefs and practices have relied on random digit dialing (RDD); however, this method presents increasing limitations. Facebook is the most used social media platform in Canada and presents an opportunity to recruit vaccine-hesitant parents in a novel manner. OBJECTIVE: The study aimed to explore the use of Facebook as a tool to reach vaccine-hesitant parents, as compared with RDD methods. METHODS: We recruited Canadian parents over 4 weeks in 2013-14 via targeted Facebook advertisements linked to a Web-based survey. We compared methodological parameters, key parental demographics, and three vaccine hesitancy indicators to an RDD sample of Canadian parents. Two raters categorized respondent reasons for difficulties in deciding to vaccinate, according to the model of determinants of vaccine hesitancy developed by the World Health Organization's Strategic Advisory Group of Experts on Immunization. RESULTS: The Facebook campaign received a total of 4792 clicks from unique users, of whom 1696 started the Web-based survey. The total response rate of fully completed unique Web-based surveys was 22.89% (1097/4792) and the survey completion rate was 64.68% (1097/1696). The total cost including incentives was reasonable (Can $4861.19). The Web-based sample yielded younger parents, with 85.69% (940/1097) under the age of 40 years as compared with 23.38% (408/1745) in the RDD sample; 91.43% (1003/1097) of the Facebook respondents were female as compared with 59.26% (1034/1745) in the RDD sample. Facebook respondents had a lower median age of their youngest child (1 year vs 8 years for RDD). When compared with the RDD sample, the Web-based sample yielded a significantly higher proportion of respondents reporting vaccines as moderately safe to not safe (26.62% [292/1097] vs 18.57% [324/1745]), partially or not at all up-to-date vaccination status of youngest child (22.06% [242/1097] vs 9.57% [167/1745]), and difficulty in making the decision to vaccinate their youngest child (21.06% [231/1097] vs 10.09% [176/1745]). Out of the Web-based respondents who reported reasons for the difficulties in deciding to vaccinate, 37.2% (83/223) reported lack of knowledge or trust due to conflicting information and 23.8% (53/223) reported the perception of the risk of the adverse effects of vaccines being higher than the risk of disease acquisition. CONCLUSIONS: We successfully recruited a large sample of our target population at low cost and achieved a high survey completion rate using Facebook. When compared with the RDD sampling strategy, we reached more vaccine-hesitant parents and younger parents with younger children-a population more likely to be making decisions on childhood immunizations. Facebook is a promising economical modality for reaching vaccine-hesitant parents for studies on the determinants of vaccine 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.121
GPT teacher head0.408
Teacher spread0.287 · 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.

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

Citations24
Published2017
Admission routes3
Has abstractyes

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