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Record W2931901908 · doi:10.1093/pch/pxz025

Overview of a Knowledge Translation (KT) Project to improve the vaccination experience at school: The CARD™ System

2019· article· en· W2931901908 on OpenAlexafffund
Anna Taddio, C. Meghan McMurtry, Lucie M. Bucci, Noni E. MacDonald, Anthony N T Ilersich, Angelo L T Ilersich, Angela Alfieri-Maiolo, Christene deVlaming-Kot, Leslie Alderman, Tamlyn Freedman, T. W. McDowall, Horace Wong, Kate Robson, Christine Halpert, Evelyn Wilson, Jocelyn Cortes, M Mustafa Hirji, Cathryn Schmidt, Srdjana Filipovic, Melanie Badali

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsMinistry of Health and Long Term CareBC Centre for Disease ControlHospital for Sick ChildrenUniversity of GuelphRegional Municipality of NiagaraDalhousie UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsKnowledge translationPsychological interventionFocus groupStakeholderMedical educationIntervention (counseling)Stakeholder engagementMedicineVaccinationPsychologyNursingKnowledge managementComputer sciencePublic relationsBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: Students experience fear, pain, and fainting during vaccinations at school. While evidence-based interventions exist, no Knowledge Translation (KT) interventions have been developed to mitigate these symptoms. A multidisciplinary team-the Pain Pain Go Away Team-was assembled to address this knowledge-to-care gap. This manuscript provides an overview of the methodology, knowledge products, and impact of an evidence-based KT program developed and implemented to improve the vaccination experience at school. METHODS: We adapted knowledge and assessed the barriers to knowledge use via focus group interviews with key stakeholder groups involved in school-based vaccinations: students, nurses, school staff, and parents. Next, we developed project-specific goals and data collection tools and collected baseline data. We then created a multifaceted KT intervention called The CARD™ System (C-Comfort, A-Ask, R-Relax, D-Distract) to provide a framework for planning and delivering vaccinations using a student-centred approach. Selected KT tools from this framework were reviewed in additional focus groups held in all stakeholder groups. The multifaceted KT intervention was then finalized and implemented in stages in two projects including grade 7 students undergoing school vaccinations and impact on student outcomes (e.g., symptoms of fear, pain, dizziness) and process outcomes (e.g., utilization of interventions that reduce student symptoms, vaccination rate) were assessed. RESULTS: Participants reported that improving the vaccination experience is important. Based on participant feedback, an evidence-based multifaceted KT intervention called The CARD™ System was developed that addresses user needs and preferences. Selected KT tools of this intervention were demonstrated to be acceptable and to improve knowledge and attitudes about vaccination in the stakeholder groups. In two separate implementation projects, CARD™ helped grade 7 students prepare for vaccinations and positively impacted on their vaccination experiences. CARD™ improved vaccination experiences for other stakeholder groups as well. There was no evidence of an impact on school vaccination rates. CONCLUSION: We developed and implemented a promising multifaceted KT intervention called The CARD™ System to address vaccination-associated pain, fear, and fainting. Future research is recommended to determine impact in students of different ages and in different geographical regions and clinical contexts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.042
GPT teacher head0.347
Teacher spread0.304 · 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.

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".

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Citations43
Published2019
Admission routes2
Has abstractyes

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