Exploring How Youth Use TikTok for Mental Health Information in British Columbia: Semistructured Interview Study With Youth
Notice bibliographique
Résumé
BACKGROUND: TikTok (ByteDance) experienced a surge in popularity during the COVID-19 pandemic as a way for people to interact with others, share experiences and thoughts related to the pandemic, and cope with ongoing mental health challenges. However, few studies have explored how youth use TikTok to learn about mental health. OBJECTIVE: This study aims to understand how youth used TikTok during the COVID-19 pandemic to learn about mental health and mental health support. METHODS: Semistructured interviews were conducted with 21 youths (aged 12-24 years) living in British Columbia, Canada, who had accessed TikTok for mental health information during the COVID-19 pandemic. Interviews were audio-recorded, transcribed verbatim, coded, and analyzed using an inductive, data-driven approach. RESULTS: A total of 3 overarching themes were identified describing youth's experiences. The first theme centered on how TikTok gave youth easy access to mental health information and support, which was particularly helpful during the COVID-19 pandemic to curb the effects of social isolation and the additional challenges of accessing mental health services. The second theme described how the platform provided youth with connection, as it gave youth a safe space to talk about mental health and allowed them to feel seen by others going through similar experiences. This helped normalize and destigmatize conversations about mental health and brought awareness to various mental health conditions. Finally, the last theme focused on how this information led to action, such as trying different coping strategies, discussing mental health with peers and family, accessing mental health services, and advocating for themselves during medical appointments. Across the 3 themes, youth expressed having to be mindful of bias and misinformation, highlighting the barriers to identifying and reporting misinformation and providing individualized advice on the platform. CONCLUSIONS: Findings suggest that TikTok can be a useful tool to increase mental health awareness, reduce stigma, and encourage youth to learn and address their mental health challenges while providing a source of peer connection and support. Simultaneously, TikTok can adversely impact mental health through repetitive exposure to mentally distressing content and misleading diagnosis and treatment information. Regulations against harmful content are needed to mitigate these risks and make TikTok safer for youth. Efforts should also be made to increase media and health literacy among youth so that they can better assess the information they consume online.
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 | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,013 | 0,004 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 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 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 ».