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Record W6888984101 · doi:10.25384/sage.c.7183783

Perceptions and Information-Seeking Behavior Regarding COVID-19 Vaccination Among Patients With Chronic Kidney Disease in 2023: A Cross-Sectional Survey

2024· other· en· W6888984101 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsKidney diseaseVaccinationDescriptive statisticsKidney transplantSerologyDiseasePublic health

Abstract

fetched live from OpenAlex

Background:People living with chronic kidney disease (CKD) face an increased risk of severe outcomes such as hospitalization or death from COVID-19. COVID-19 vaccination is a vital approach to mitigate the risk and severity of infection in patients with CKD. Limited information exists regarding the factors that shape COVID-19 vaccine uptake, including health information-seeking behavior and perceptions, within the CKD population.Objective:The objectives were to describe among CKD patients, (1) health information-seeking behavior on COVID-19, (2) their capacity to comprehend and trust COVID-19 information from different sources, and (3) their perceptions concerning COVID-19 infection and vaccination.Design/Setting:Cross-sectional web-based survey administered in British Columbia and Ontario from February 17, 2023, to April 17, 2023.Participants:Chronic kidney disease G3b-5D patients and kidney transplant recipients (CKD G1T-5T) enrolled in a longitudinal COVID-19 vaccine serology study.Methods and Measurements:The survey consisted of a questionnaire that included demographic and clinical data, perceived susceptibility of contracting COVID-19, the ability to collect, understand, and trust information on COVID-19, as well as perceptions regarding COVID-19 vaccination. Descriptive statistics were used to present the data with values expressed as count (%) and chi square tests were performed with a significance level set at P ≤ .05. A content analysis was performed on one open-ended response regarding respondents’ questions surrounding COVID-19 infection and vaccination.Results:Among the 902 patients who received the survey via email, 201 completed the survey, resulting in a response rate of 22%. The median age was 64 years old (IQR 53-74), 48% were male, 51% were university educated, 32% were on kidney replacement therapies, and 57% had received ≥5 COVID-19 vaccine doses. 65% of respondents reported that they had sought out COVID-19-related information in the last 12 months, with 91% and 84% expressing having understood and trusted the information they received, respectively. Those with a higher number of COVID-19 vaccine doses were associated with having sought out (P =.017), comprehended (P < .001), and trusted (P =. 005) COVID-19-related information. Female sex was associated with expressing more concern about contracting COVID-19 (P = .011). Most respondents strongly agreed to statements regarding the benefits of COVID-19 vaccination. Respondents’ questions about COVID-19 infection and vaccination centered on 4 major themes: COVID-19 vaccination strategy, vaccine effectiveness, vaccine safety, and the impact of COVID-19 infection and vaccination on kidney health.Limitations:This survey was administered within the Canadian health care context to patients with CKD who had at least 1 COVID-19 vaccine dose. Race/ethnicity of participants was not captured.Conclusions:In this survey of individuals with CKD, COVID-19 information-seeking behavior was high and almost all respondents understood and trusted the information they received. Perceptions toward the COVID-19 vaccine and booster were mostly favorable.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.217
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.351
Teacher spread0.308 · 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 designObservational
Domainnot available
GenreDataset

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".

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Published2024
Admission routes1
Has abstractyes

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