“It’s Totally Okay to Be Sad, but Never Lose Hope”: Content Analysis of Infertility-Related Videos on YouTube in Relation to Viewer Preferences
Notice bibliographique
Résumé
BACKGROUND: Infertility patients frequently use the internet to find fertility-related information and support from people in similar circumstances. YouTube is increasingly used as a source of health-related information and may influence health decision making. There have been no studies examining the content of infertility-related videos on YouTube. OBJECTIVE: The purpose of this study was to (1) describe the content of highly viewed videos on YouTube related to infertility and (2) identify video characteristics that relate to viewer preference. METHODS: Using the search term "infertility," the 80 top-viewed YouTube videos and their viewing statistics (eg, views, likes, and comments) were collected. Videos that were non-English, unrelated to infertility, or had age restrictions were excluded. Content analysis was used to examine videos, employing a coding rubric that measured the presence or absence of video codes related to purpose, tone, and demographic and fertility characteristics (eg, sex, parity, stage of fertility treatment). RESULTS: A total of 59 videos, with a median of 156,103 views, met the inclusion criteria and were categorized into 35 personal videos (35/59, 59%) and 24 informational-educational videos (24/59, 41%). Personal videos did not differ significantly from informational-educational videos on number of views, dislikes, subscriptions driven, or shares. However, personal videos had significantly more likes (P<.001) and comments (P<.001) than informational-educational videos. The purposes of the videos were treatment outcomes (33/59, 56%), sharing information (30/59, 51%), emotional aspects of infertility (20/59, 34%), and advice to others (6/59, 10%). The tones of the videos were positive (26/59, 44%), neutral (25/59, 42%), and mixed (8/59, 14%); there were no videos with negative tone. No videos contained only male posters. Videos with a positive tone did not differ from neutral videos in number of views, dislikes, subscriptions driven, or shares; however, positive videos had significantly more likes (P<.001) and comments (P<.001) than neutral videos. A majority (21/35, 60%) of posters of personal videos shared a pregnancy announcement. CONCLUSIONS: YouTube is a source of both technical and personal experience-based information about infertility. However, videos that include personal experiences may elicit greater viewer engagement. Positive videos and stories of treatment success may provide hope to viewers but could also create and perpetuate unrealistic expectations about the success rates of fertility treatment.
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 | 0,009 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».