Depression in cancer: An evaluation of patient education resources.
Notice bibliographique
Résumé
e24194 Background: In recent years, there has been increasing awareness surrounding mental health and depression among cancer patients. Concurrently, the internet has cemented its role as a mainstay source of health information for the general public. However, little is known about the quality of online resources addressing depression specifically in cancer patients. Therefore, we aim to systematically evaluate the quality of such information. Methods: The term "depression in cancer patients" was searched online using the search engine Google and the meta-search engines Dogpile and Yippy. A set of predetermined inclusion and exclusion criteria was applied to all search results, which yielded 48 websites for inclusion. An evidence-based rating tool was then used to score the websites based on the six domains of Affiliation, Accountability, Interactivity, Structure & Organization, Readability, and Content Quality. The results were analyzed using descriptive statistics. Results: Of the 48 websites evaluated, 50% were commercial. In terms of accountability measures, 63% of websites disclosed authorship, 54% cited one or more reliable sources, and 38% were updated within the last two years. Although in-site search engines and video support were found in 94% and 52% of websites respectively, the presence of other interactive features were considerably lower. The average readability was at a grade 12.3 level using the Flesch-Kincaid scale and 11.3 using the SMOG Index, both of which were significantly higher than the traditionally recommended grade-six level ( p < 0.0001 for both). The most commonly covered topics were symptoms and treatment – found on 87% and 83% of websites respectively. Prevention and prognosis were not covered by any of the websites. Content accuracy was generally high among covered topics. Conclusions: Many websites addressing depression in cancer have poor authorship disclosure, attribution, and currency. Additional interactive features should be encouraged to facilitate user-friendliness. Poor readability may pose a barrier for patient comprehension, indicating a need for health care providers to proactively guide patients to suitable resources. Despite high content accuracy in other topics, prevention and prognosis are seldom covered. Our results could help guide the development of new patient education materials and better inform health care providers about the limitations of available online resources. Future research should aim to elucidate reasons contributing to difficult readability levels and identify topics that patients need additional information in.
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 | 0,011 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».