MétaCan
Menu
Back to cohort
Record W2017189900 · doi:10.1016/j.vaccine.2015.04.041

Strategies intended to address vaccine hesitancy: Review of published reviews

2015· review· en· W2017189900 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueVaccine · 2015
Typereview
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsDalhousie UniversityIzaak Walton Killam Health CentreInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsPsychological interventionPublic health interventionsMedicinePublic healthSystematic reviewIntervention (counseling)MEDLINEFamily medicinePolitical scienceNursing

Abstract

fetched live from OpenAlex

When faced with vaccine hesitancy, public health authorities are looking for effective strategies to address this issue. In this paper, the findings of 15 published literature reviews or meta-analysis that have examined the effectiveness of different interventions to reduce vaccine hesitancy and/or to enhance vaccine acceptance are presented and discussed. From the literature, there is no strong evidence to recommend any specific intervention to address vaccine hesitancy/refusal. The reviewed studies included interventions with diverse content and approaches that were implemented in different settings and targeted various populations. Few interventions were directly targeted to vaccine hesitant individuals. Given the paucity of information on effective strategies to address vaccine hesitancy, when interventions are implemented, planning a rigorous evaluation of their impact on vaccine hesitancy/vaccine acceptance will be essential.

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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.082
GPT teacher head0.400
Teacher spread0.318 · 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