Characteristics Assessment of Online YouTube Videos on Radiotherapy for Lung Cancer
Notice bibliographique
Résumé
Introduction The internet has become a mainstay source of health information for cancer patients. Online patient education videos are common; however, there have been no studies examining the quality of publicly available videos on radiotherapy for lung cancer (one of the most common forms of cancer). To fill this knowledge gap, we aim to systematically map and objectively assess videos discussing radiotherapy for lung cancer on YouTube. Methods The terms "radiotherapy for lung cancer," "radiation for lung cancer," "radiation therapy for lung cancer," and "radiation treatment for lung cancer" were searched on YouTube using a clear-cache browser. Results were sorted by relevance and the top 50 English-language results for each search were recorded. After removing duplicates, each video was assessed for length, Video Power Index (VPI, which is the product of a video's average daily views and like and dislike ratio), source, content, comment moderation, and misinformation. Two raters were used to ensure consistency. Results were evaluated using descriptive and inferential statistics. Results A total of 88 unique videos resulted from the search. The median video length was 4 minutes and 5 seconds. The average VPI was 10.9 (95% CI: 1.5-20.4) and the median number of views was 954.5. All videos were published between July 8, 2009 and November 18, 2020. Of the videos, 44% were published within the past two years. A total of 61% of the videos were from the USA, 14% were from the UK, 6% from Australia, 5% each from Canada and India, and other countries make up the remaining 10%. Most of the videos were published by healthcare facilities (39%) and non-profit organizations (31%). Content-wise, 95% of videos contain information specific to lung cancer. A total of 46 videos (52%) were targeted toward patient education. Of which, 37 covered radiotherapy for lung cancer, 12 covered side effects for radiotherapy, and 11 covered both. The other 42 videos (48%) were designed for a professional audience. Stereotactic body radiation therapy (SBRT)/stereotactic ablative radiotherapy (SABR) was the most commonly described radiotherapy modality (42%), and the physician interview was the most common format, being used in 59% of videos. Out of the 38 videos with at least one comment, only two (5%) were moderated by the host channel. None of the videos featured misleading information. Conclusions This study comprehensively surveyed YouTube videos pertaining to radiotherapy for lung cancer to provide a high-level overview of the information that patients may find online. Although nearly half of the videos describe lung cancer radiotherapy for patients, only a small proportion comprehensively cover both radiotherapy and its side effects. The results of our study can help guide the development of patient education tools and encourage healthcare providers to recognize the limitations of online health information and proactively address patient questions regarding radiotherapy. Future research could examine videos on other lung cancer treatment options or radiotherapy for other cancers.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».