The Past and Present of Breast Cancer Resources: A Re-evaluation of the Quality of Online Resources After Eight Years
Notice bibliographique
Résumé
Background and objective The internet has become a major resource of information for cancer patients. However, the quality of these resources is variable, and a better understanding is needed to guide physicians as to how to best support patients in their online searches. We previously evaluated the quality of online breast cancer resources in 2011. Nearly a decade later, we aimed to assess the present quality of online breast cancer-related information and to compare our current analysis with data collected in 2011. Methods A list of 100 breast cancer websites was systematically compiled using meta-search engines Yippy and Dogpile and the search engine Google using the search term "breast cancer". Content accuracy and quality markers, including authorship, attribu-tion, currency, site organization, and readability were assessed by using a previously validated standardized rating tool. Results were analyzed using descriptive statistics and Fisher's exact test. The same strategy was used in both 2011 and 2019. Results When comparing 2011 data to the current one, 27% of websites had been updated in the previous two years in 2011 compared to 65% in 2019 (p<0.00001). Both data sets remained similar in terms of website disclosures and objectivity. Only 30% of websites analyzed in 2019 used two or more reliable sources, while 63% had no reliable sources or no sources cited. From 2011 to 2019, resources with readability above grade 12 increased from 4% to 30% (p<0.0001), while websites offering educational support rose from 8% to 35% (p<0.0001). In 2019, treatment and etiology/risk factors were the most accurately covered areas (64% and 63% of websites, respectively). In 2011, 63% of websites were found to be globally accurate. Prognosis coverage increased from 18% to 33% from 2011 to 2019 (p=0.02). In 2019, survivorship was also evaluated and found to be covered in only 24% of resources. Conclusion Over the past eight years, there have been variable changes in the quality of online breast cancer resources. Promisingly, websites are being updated more frequently and the educational support offered is expanding. Furthermore, there has been significant improvement in the coverage of prognosis, although this requires further progress. Unfortunately, websites are becoming increasingly challenging to understand for the average patient, and coverage of survivorship is lacking. Our study provides vital information to healthcare providers on these trends in online breast cancer resources and how to best support patients in their internet searches.
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 | 0,021 | 0,101 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,020 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,006 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».