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Record W2780417658 · doi:10.2196/publichealth.8237

Characteristics of Articles About Human Papillomavirus Vaccination in Japanese Newspapers: Time-Series Analysis Study

2017· article· en· W2780417658 on OpenAlexvenueno aff
Nao Ueda, Ryoki Yokouchi, Taro Onoda, Atsushi Ogihara

Bibliographic record

VenueJMIR Public Health and Surveillance · 2017
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperCervical cancerVaccinationMedicineHuman papillomavirusFamily medicineHealth informationPublic healthCancerAdvertisingHealth careVirologyPathologyPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Media coverage and reports have a major influence on individual vaccination and other health-related activities. People use the media to seek information and knowledge on health-related behaviors. They obtain health-related information from media such as television and newspapers, and they trust such information. While several studies have examined the relation between media coverage and individual health, there is a lack of studies that have analyzed media reports of health information. In particular, we have found no analyses related to cervical cancer (human papillomavirus [HPV]) vaccine. OBJECTIVE: This study aimed to identify mentions of cervical cancer vaccine in Japan's printed news media and to determine their characteristics. METHODS: We used the archival databases of 2 Japanese newspapers, Yomiuri Shimbun (Yomidasu Rekishikan) and Asahi Shimbun (Kikuzo II Visual), for text mining. First, we created a database by extracting articles published between January 1, 2007, and December 31, 2014, that matched the terms "cervical cancer" AND "vaccination" in a keyword search. Then, we tallied the extracted articles based on the month of publication and number of characters in order to conduct a time-series analysis. RESULTS: We extracted a total of 219 articles. Of these, 154 (70.3%) were positive and 51 (23.3%) were negative toward HPV vaccination. Of the 51 negative articles, 4 (7.8%) were published before June 2013, when routine vaccination was temporarily discontinued due to concerns regarding side effects, and 47 (92.2%) were published since then. The negative reports commonly cited side effects, although prior to June 2013, these issues were hardly mentioned. Although foreign media reports mentioned side effects before routine vaccination was temporarily discontinued, fewer articles mentioned side effects than recommendations for vaccination. Furthermore, on June 13, 2013, the World Health Organization's advisory body Global Advisory Committee on Vaccine Safety issued a statement regarding the safety of HPV vaccines, but hardly any articles reported this statement. Rather, several articles were published about the side effects after June 2013. CONCLUSIONS: Since we consider media coverage to be a factor affecting human health behavior, the media should extensively report on the cost of not receiving cervical cancer vaccination, global trends concerning cervical cancer vaccination, and statements released by various agencies on the subject.

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)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.014
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.052
GPT teacher head0.391
Teacher spread0.339 · 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.

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

Citations10
Published2017
Admission routes1
Has abstractyes

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