MétaCan
Menu
Back to cohort
Record W1970657318 · doi:10.5539/gjhs.v6n4p42

Skin Cancer Prevention Coverage in Popular US Women’s Health and Fitness Magazines: An Analysis of Advertisements and Articles

2014· article· en· W1970657318 on OpenAlexvenueno aff
Corey H. Basch, Danna Ethan, Grace Clarke Hillyer, Alyssa Berdnik

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSkin cancerMedicineAdvertisingHealth communicationHealth educationHealth literacyCancer preventionPublic healthHealth promotionGerontologyCancerEnvironmental healthFamily medicinePsychologyHealth carePublic relationsNursingBusinessPolitical science

Abstract

fetched live from OpenAlex

The desire to be tan is a phenomenon that public health researchers have investigated, as exposure to UV radiation increases the chances of developing skin cancer. Media messages in women's magazines have been shown to contribute to this problem. Much less is known about the prevalence of skin cancer prevention messages in these magazines. This study's aim was to identify the number and type of articles and advertised products devoted to skin health (sun protection and skin cancer prevention in particular) within five popular U.S. greater than women's health and fitness magazines. We analyzed articles and advertisements over seven months of issues of the following popular women's health and fitness magazines: Fitness, Health, Self, Shape, and Women's Health, March 2013 through September 2013. Overall, 31 issues of the five magazines with a total of 780 articles and 1,986 advertisements were analyzed. Of the 780 articles, a mere 2.9% (n=23) were devoted to skin. Of the 258 skin product advertisements, less than 20% of the products contained sun protection factor (SPF). These findings suggest that women's health and fitness magazines can improve their efforts in informing women of skin cancer risks and preventive measures to minimize these risks. The role of these magazines in building health literacy among their readers is also discussed.

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 score0.127
Threshold uncertainty score0.199

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 head0.019
GPT teacher head0.365
Teacher spread0.346 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicSkin Protection and AgingFrench-language works237,207