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Record W4386984337 · doi:10.1093/pch/pxad055.041

41 Evaluating Immunization Status and Barriers to Immunization for Patients Admitted to the Stollery Children's Hospital

2023· article· en· W4386984337 on OpenAlexaboutno aff
Brittany Lissinna, Chelsea Gilbert, Calla Isaac, Qaasim Mian, Karen Forbes

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImmunizationFamily medicinePediatricsPublic healthNursingImmunology

Abstract

fetched live from OpenAlex

Abstract Introduction/Background Routine immunization is an effective public health intervention. Despite this, immunization coverage in Alberta remains below national targets. While vaccine hesitancy is a frequently cited barrier, underimmunization is likely multifactorial. Previous research has shown that hospitalization presents an opportunity to “catch-up” children who are underimmunized. Unfortunately, this is not readily available at the Stollery Children’s Hospital (SCH), a paediatric tertiary care facility serving a large catchment area. Objectives The primary objective of this study was to assess the immunization status of children admitted to paediatric clinical teaching units (CTUs) at SCH. Our secondary objective was to assess potential barriers caregivers face while attempting to immunize their children. Design/Methods Between July 2021 and October 2022, we prospectively gathered the immunization status of children aged 2 months to 18 years admitted to paediatric clinical teaching units (CTUs) at SCH. Two hundred and fifty children and their caregivers were enrolled in the research study. Demographic data and immunization records were documented, and immunization status of each participant was classified as up-to-date or not-up-to-date based on the Alberta Routine Childhood Immunization Schedule. Caregivers completed a standardized survey, Searching for Hardships and Obstacles to Shots (SHOTS), to assess potential barriers they face while attempting to immunize their children, including three subscales (access to shots, concerns about shots and importance of shots). Results Of the 250 children enrolled, immunization data was available for 240 children. Of these, 142 (59%) were up-to-date on their immunizations. Assessment of demographic data revealed no difference in immunization status between urban and rural addresses. When evaluating barriers that families face when approaching immunization, concerns about immunization were most commonly cited as barriers for all patients. However, caregivers whose children were not up-to-date on immunizations scored higher on all subscales compared to those whose children were up-to-date. Conclusion The immunization status of children admitted to paediatric CTUs at SCH falls far below national targets. Due to logistical issues, it is challenging to access routine immunizations during hospitalization. Caregivers of children who are underimmunized also identify a higher rate of barriers to immunization. These underimmunized patients represent a missed opportunity, and improving access to routine immunization while in hospital could improve the overall immunization rates for both hospitalized children and the broader community.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.309
Teacher spread0.296 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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