Role of Moderators on Engagement of Adolescents With Depression or Anxiety in a Social Media Intervention: Content Analysis of Web-Based Interactions
Notice bibliographique
Résumé
BACKGROUND: The Supporting Our Valued Adolescents (SOVA) intervention aims to use a moderated social media website to encourage peer discussion about negative health beliefs, which may prevent treatment uptake. Web moderators with a background in behavioral health are used to facilitate peer conversation to promote a sense of community, provide social support, and ensure safety. OBJECTIVE: Although moderation is a core component of this intervention, little is known on best practices for moderators to ensure safety while encouraging engagement. This study sought to describe interactions between moderators and peer users and understand moderator experiences through individual interviews. METHODS: Adolescents and young adults aged 14 to 26 years with depression or anxiety history were recruited for a usability study of the SOVA intervention. During this study, 14 moderators were trained to regularly review comments to blog posts for safety, facilitate conversation, and correct misinformation. A total of 110 blog posts and their associated comments were extracted and coded using a codebook based on items from the supportive accountability model and a peer social support analysis. Closing interviews with 12 moderators assessing their experience of moderating were conducted, recorded, and transcribed. Blog post text and comments as well as transcripts of moderator interviews were assessed using a thematic analysis approach, and blog posts were examined for trends in content of moderator comments comparing blog posts with differences in comment contributor order. RESULTS: There were no safety concerns during the study, and moderators only intervened to remove identifiable information. Web moderators exhibited elements of supportive accountability (such as being perceived as experts and using verbal rewards as well as offering informational and emotional support). When the moderators provided the last comment under a blog post, thereby potentially ending contribution by users, they were at times found to be commenting about their own experiences. Moderators interviewed after completing their role expressed challenges in engaging users. A cohort of moderators who received more extensive training on supportive accountability and peer social support felt their ability to engage users improved because of the training. CONCLUSIONS: Moderators of a Web-based support site for adolescents with depression or anxiety were able to ensure safety while promoting user engagement. Moderators can elicit user engagement by offering gratitude and encouragement to users, asking users follow-up questions, and limiting their own opinions and experiences when responding to comments.
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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 | 0,010 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».