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Record W4382021781 · doi:10.24095/hpcdp.43.6.05

“I just got tired of their healthy tips”: health promotion during public health crises

2023· article· en· W4382021781 on OpenAlexafffundvenueabout
Julia Dabravolskaj, Noreen D. Willows, Laena Maunula, Boshra A. Mandour, Shannon Sim, Paul J. Veugelers, Katerina Maximova

Bibliographic record

VenueHealth Promotion and Chronic Disease Prevention in Canada · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsPublic Health OntarioUniversity of TorontoMemorial University of NewfoundlandSt. Michael's HospitalWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCanadian Institutes of Health ResearchPublic Health AgencyPublic Health Agency of Canada
KeywordsHealth promotionHumanitiesPublic healthPolitical scienceSociologyMedicineArtNursing

Abstract

fetched live from OpenAlex

This qualitative study highlights parents' perspectives on pandemic-related changes to health promotion programming. We conducted 60-minute, semi-structured telephone interviews with 15 parents (all mothers) of children in Grades 4 to 6 between December 2020 and February 2021 in two western Canadian provinces. Transcripts were analyzed through thematic analysis. While some parents found the health promotion materials helpful, most were overwhelmed and did not access the materials, finding them intrusive, being preoccupied with other things and facing their own personal stressors. This study highlights key factors to be addressed and further investigated to ensure the successful delivery of health promotion programming during future crises.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.007
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
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 head0.163
GPT teacher head0.435
Teacher spread0.272 · 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 designQualitative
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

Citations1
Published2023
Admission routes4
Has abstractyes

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