Youth Study Recruitment Using Paid Advertising on Instagram, Snapchat, and Facebook: Cross-Sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: The use of paid social media advertising for targeted study recruitment is an effective strategy in health research and evaluation, specifically to reach diverse youth participants. Although the literature adequately describes the utility of Facebook in recruitment, limited information exists for social media platforms that are more popular with youth, specifically Instagram and Snapchat. OBJECTIVE: This paper outlines a paid advertising approach using Instagram, Snapchat, and Facebook to evaluate a statewide youth marijuana prevention campaign. The objective of this study was to compare recruitment metrics across Instagram, Snapchat, and Facebook for two surveys documenting youth knowledge, attitudes, and behaviors related to retail marijuana in Colorado post legalization. In addition, the study assessed the feasibility of using Instagram and Snapchat as effective additions to Facebook for youth study recruitment. METHODS: A social media recruitment strategy was used to conduct two cross-sectional surveys of youth, aged 13 to 20 years, in Colorado. Geographically targeted ads across 3 social media platforms encouraged the completion of a Web-based self-administered survey. Ad Words and Snap Ads were used to deploy and manage advertising campaigns, including ad design, placement, and analysis. Ad costs and recruitment metrics (ie, impressions, link clicks, and conversion rates) were calculated across the three social media platforms. RESULTS: Over two 1-month periods, 763,613 youth were reached (ie, impressions), 6089 of them clicked survey links (ie, clicks), and 828 eligible youth completed surveys about knowledge, attitudes, and behaviors related to retail marijuana. Instagram converted 36.13% (803/2222) of impressions to clicks (ie, conversion rate) in the first survey and 0.87% (864/98982) in the second survey. Snapchat generated the most impressions and link clicks, but it did so with the lowest conversion rate for both surveys, with a 1.40% (1600/114,200) conversion rate in the first survey and a 0.36% (1818/504700) conversion rate in the second survey. Facebook maintained a consistent conversion rate of roughly 2% across both surveys, despite reductions in budget for the second survey. The cost-per-click ranged between US $0.25 and $0.37 across the three platforms, with Snapchat as both the most cost-effective platform in the first survey and the most expensive platform in the second survey. CONCLUSIONS: Recruitment and enrollment outcomes indicate the use of Instagram and Snapchat, in addition to Facebook, may be a modern, useful, and cost-effective approach to reach youth with surveys on sensitive health topics. As the use of Facebook declines among youth, the use of more popular social media platforms can augment study recruitment for health research and evaluation efforts.
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 | 0,011 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,000 |
| 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 ».