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Record W4403484355 · doi:10.3390/jal4040023

Ageism Through the Informational Practices During Health Crisis: A Qualitative Study Among Older Adults in Quebec (Canada)

2024· article· en· W4403484355 on OpenAlexafffundabout
Nicolai Guzun, André Tourigny, Ève Dubé, Alexandre Coutant, Maryline Vivion

Bibliographic record

VenueJournal of Ageing and Longevity · 2024
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversité du Québec à MontréalCentre de Santé et de Services Sociaux de la Vieille-CapitaleCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleUniversité Laval
FundersCanadian Institutes of Health ResearchUniversité Laval
KeywordsThematic analysisQualitative researchPandemicSocial mediaInterpersonal communicationGovernment (linguistics)Content analysisPublic healthPsychologyPublic relationsCoronavirus disease 2019 (COVID-19)GerontologyPolitical scienceSociologyMedicineSocial psychologyNursingSocial science

Abstract

fetched live from OpenAlex

This study explores the health-information-seeking practices of older adults. Conducted in Quebec, Canada, this qualitative research involved semi-structured interviews with 36 participants aged 60 and over, between 19 July and 20 August 2021, during the COVID-19 pandemic. The interviews, carried out via online platforms and telephone, focused on information sources, the method of information retrieval, and participants’ reflections on and use of pandemic-related information. Thematic content analysis was used to identify the presence of ageism. The study showed that participants favored government press conferences and traditional media, while remaining skeptical of social media. The analysis identified the concept of ageism (institutional, interpersonal, and self-directed) in about half of the interviews, with institutional ageism predominating in communications and actions of authorities and in the portrayal of older adults by media. The findings highlight the need for reliable, respectful communications reaching older adults for effective and relevant public health messages.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.424
Teacher spread0.385 · 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 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

Citations0
Published2024
Admission routes3
Has abstractyes

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