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Record W4205857768 · doi:10.3390/vaccines10010105

Vaccine Acceptance and Hesitancy among College Students in Nevada: A State-Wide Cross-Sectional Study

2022· article· en· W4205857768 on OpenAlexaboutno aff
Leslie Elliott, Kanyeemengtiang Yang

Bibliographic record

VenueVaccines · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsResidenceQuarter (Canadian coin)Marital statusFamily medicinePandemicMedicineEthnic groupPopulationPublic healthPsychologyCoronavirus disease 2019 (COVID-19)Environmental healthDemographyGeographyNursingPolitical scienceDiseaseSociology

Abstract

fetched live from OpenAlex

The purpose of this study was to identify factors related to COVID-19 vaccine acceptance and hesitancy in a diverse state-wide population of students. An electronic survey was emailed to students in the Nevada System of Higher Education to assess effects of the pandemic. The survey included questions related to vaccine status, interest in receiving the COVID-19 vaccine, factors influencing these decisions, and sources of health information. Among the 3773 respondents, over half (54%) were accepting of the vaccine, including vaccinated students (18.9%). Nearly one quarter (23.5%) expressed hesitancy to receive the vaccine, citing concerns about side effects and the need for more research. Factors related to hesitancy included female gender, increasing age, place of residence, marital status, and Black or Native American race. Vaccine hesitant respondents were less likely than other respondents to rely on public health agencies or newspapers for health information, and more likely to rely on employers, clinics, or "no one". Culturally appropriate efforts involving COVID-19 vaccine information and distribution should target certain groups, focusing on factors such as side effects, development and testing of the vaccine. Research should investigate sources of health information of people who are hesitant to receive vaccines.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.323
Teacher spread0.305 · 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

Citations25
Published2022
Admission routes1
Has abstractyes

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