Perceptions and Aspirations Toward Peer Mentoring in Social Media–Based Electronic Cigarette Cessation Interventions for Adolescents and Young Adults: Focus Group Study
Notice bibliographique
Résumé
BACKGROUND: Social media offer a promising channel to deliver e-cigarette cessation interventions to adolescents and young adults (AYAs); however, interventions delivered on social media face challenges of low participant retention and decreased engagement over time. Peer mentoring has the potential to ameliorate these challenges. OBJECTIVE: The aim of this study was to understand, from both the mentee and potential mentor perspective, the needs, expectations, and concerns of AYAs regarding peer mentoring to inform the development of social media-based peer mentoring interventions for e-cigarette cessation among AYAs. METHODS: Seven focus groups, including four mentee groups and three potential mentor groups, were conducted with 26 AYAs who had prior experience with e-cigarette use and attempts to quit in the context of a social media-based e-cigarette cessation intervention. Discussion focused on preferred characteristics of peer mentors, expectations about peer mentoring, mentoring mode, mentor training, incentives for peer mentors, preferred social media platforms for intervention delivery, supervision, and concerns. Focus group transcripts were coded and analyzed using a thematic analysis approach. RESULTS: Overall, participants were receptive to peer mentoring in social media-based cessation interventions and believed they could be helpful in assisting e-cigarette cessation. Participants identified the most important characteristics of peer mentors to be of similar age and to be abstinent from e-cigarette use. Participants expected peer mentors would share personal experiences, provide emotional support, and send check-ins and reminders. Peer mentors supporting a group of mentees in combination with one-on-one mentoring as needed was the preferred mentoring mode. A group of 10 mentees with a mentor:mentee ratio of 1:3-5 was deemed acceptable for most participants. Participants expressed that mentor training should include emotional intelligence, communication skills, and the scientific evidence about e-cigarettes. Although monetary incentives were not the main motivating factor for being a peer mentor, they were viewed as a good way to compensate mentors' time. Instagram was considered an appropriate social media platform to deliver a peer-mentored intervention due to its functionality. Participants did not express many privacy concerns about social media-based peer mentoring, but mentioned that boundaries and community agreements should be set to keep relationships professional. CONCLUSIONS: This study reflects the needs and preferences of young people for a peer mentoring intervention to complement a social media program to support e-cigarette cessation. The next step will be to establish the feasibility, acceptability, and preliminary efficacy of such a peer mentoring program.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».