100 How accurate are argentine main on-line newspapers when they inform about breast cancer screening? cross-sectional study
Notice bibliographique
Résumé
Introduction Mass media have a key role in the communication of breast cancer screening strategy to the population. Misinformation and erroneous information, as well as the spreading of medical publications that are outdated or fail to be supported by any scientific evidence, serve as a barrier and prevent the implementation of adequate preventive practices from being carried out by the population. In furtherance of its early detection, the National Cancer Institute of Argentina (‘Instituto Nacional del Cáncer de Argentina’ -INC-, by its Spanish acronym), an agency of the Argentine Ministry of Health, following the recommendations issued by the U.S. Preventive Services Task Force (2016) and the Canadian Task Force on Preventive Health Care (2011), recommends healthy women to have a mammography once every two years after they turn 50, until they turn 70 years old. Objectives To document the agreement between the breast cancer prevention information published on the Internet sites of the main Argentine newspapers and the INC recommendations. To describe and quantify the main messages that fail to agree with the recommendations of the INC. Method Design A cross-sectional documentary study was carried out. Context Two researchers looked for news articles related to breast cancer that were published between 01/Jan/2015 and 31/Dec/2015, on the websites of the five newspapers with the most digital traffic in the country -Clarín, Infobae, La Nación, Página/12 and Perfil. Inclusion criteria Digital content promoting secondary preventive strategies for breast cancer in women. Variables Two independent researchers determined whether such contents had information which followed the recommendations of the INC regarding secondary preventive strategies for breast cancer. Whenever there was disagreement between them, a third researcher studied the disagreeing contents, not knowing the findings of the other two researchers. All contents which recommended healthy women between 50 and 70 years old (with no personal or family breast cancer history) to have a mammography every two years were considered concordant with the recommendations of the INC. Results 135 news articles were identified, 95 of them were excluded because they failed to meet the inclusion criteria. 40 articles were included in the analysis. 95% of them (38/40) disagree with the INC recommendations on breast cancer screening in low risk general population (with no personal or family breast cancer history). Among the recommendations which failed to agree with those of the INC, the most frequently identified (33/40; 82.5%) was the one related to having a mammography once a year after turning 40; followed by the ones related to the promotion of periodical breast self-examinations (20/40; 50%) and the promotion of other periodical tests, such as breast scans or magnetic resonance imaging (6/40; 15%). Conclusions During the term under analysis, the mass media, which can create and consolidate conducts, beliefs and values in the population, as well as provide information that is taken into consideration for health-related decisions, provided incomplete, confusing information which failed to agree with the recommendations made by the INC. This may probably result in the population being confused and in the demand for studies, such as mammographies, being performed at younger ages or at inappropriate intervals, with all the risks involved. In order to prevent or minimize the damage caused by health activities, it is necessary to make current scientifically supported recommendations on this issue even more visible, which will help dispel erroneous beliefs in relation to breast cancer and clarify information on the benefits, risks, and effectiveness of the different breast cancer tests, thus improving health outcomes, and at the same time minimizing harm and unnecessary interventions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».