MétaCan
Menu
Back to cohort
Record W4391994776 · doi:10.2196/48134

Newspaper Coverage of Hospitals During a Prolonged Health Crisis: Longitudinal Mixed Methods Study

2024· article· en· W4391994776 on OpenAlexvenueno aff
Frank van de Baan, Rachel Gifford, Dirk Ruwaard, Bram Fleuren, Daan Westra

Bibliographic record

VenueJMIR Public Health and Surveillance · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
FundersZonMw
KeywordsNewspaperThematic analysisPreparednessContent analysisPublic healthPandemicMedicineHealth carePublic relationsPolitical scienceCoronavirus disease 2019 (COVID-19)Qualitative researchBusinessSociologyNursingAdvertisingSocial sciencePathology

Abstract

fetched live from OpenAlex

BACKGROUND: It is important for health organizations to communicate with the public through newspapers during health crises. Although hospitals were a main source of information for the public during the COVID-19 pandemic, little is known about how this information was presented to the public through (web-based) newspaper articles. OBJECTIVE: This study aims to examine newspaper reporting on the situation in hospitals during the first year of the COVID-19 pandemic in the Netherlands and to assess the degree to which the reporting in newspapers aligned with what occurred in practice. METHODS: We used a mixed methods longitudinal design to compare internal data from all hospitals (n=5) located in one of the most heavily affected regions of the Netherlands with the information reported by a newspaper covering the same region. The internal data comprised 763 pages of crisis meeting documents and 635 minutes of video communications. A total of 14,401 newspaper articles were retrieved from the LexisNexis Academic (RELX Group) database, of which 194 (1.3%) articles were included for data analysis. For qualitative analysis, we used content and thematic analyses. For quantitative analysis, we used chi-square tests. RESULTS: The content of the internal data was categorized into 12 themes: COVID-19 capacity; regular care capacity; regional, national, and international collaboration; human resources; well-being; public support; material resources; innovation; policies and protocols; finance; preparedness; and ethics. Compared with the internal documents, the newspaper articles focused significantly more on the themes COVID-19 capacity (P<.001), regular care capacity (P<.001), and public support (P<.001) during the first year of the pandemic, whereas they focused significantly less on the themes material resources (P=.004) and policies and protocols (P<.001). Differences in attention toward themes were mainly observed between the first and second waves of the pandemic and at the end of the third wave. For some themes, the attention in the newspaper articles preceded the attention given to these themes in the internal documents. Reporting was done through various forms, including diary articles written from the perspective of the hospital staff. No indication of the presence of misinformation was found in the newspaper articles. CONCLUSIONS: Throughout the first year of the pandemic, newspaper articles provided coverage on the situation of hospitals and experiences of staff. The focus on themes within newspaper articles compared with internal hospital data differed significantly for 5 (42%) of the 12 identified themes. The discrepancies between newspapers and hospitals in their focus on themes could be attributed to their gatekeeping roles. Both parties should be aware of their gatekeeping role and how this may affect information distribution. During health crises, newspapers can be a credible source of information for the public. The information can also be valuable for hospitals themselves, as it allows them to anticipate internal and external developments.

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)0.009
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 score0.371
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.422
Teacher spread0.378 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Public Health and SurveillanceSame topicPublic Relations and Crisis CommunicationFrench-language works237,207