Assessing the Feasibility of Studying Awareness of a Digital Health Campaign on Facebook: Pilot Study Comparing Young Adult Subsamples
Notice bibliographique
Résumé
BACKGROUND: Mass media campaigns for preventive health messaging have been shown to be effective through years of research. However, few studies have assessed the effectiveness of campaigns on digital media, which is currently how youths and young adults are primarily consuming media. In particular, a platform that can accurately assess exposure to digital messaging in a real-life setting has yet to be developed. OBJECTIVE: This study examines the feasibility of a unique survey platform, Virtual Lab, to conduct a study on exposure to a media campaign within Facebook using a chatbot-style survey administration technique. METHODS: Virtual Lab is a survey platform that was used to recruit and survey participants within Facebook and Facebook Messenger, respectively. We created a Facebook business account with 2 Facebook pages: one for recruitment and disseminating the survey and the other one for serving the target advertisements. Pre- and postexposure surveys were administered via Facebook Messenger using a chatbot-style questionnaire 1 week apart. During this time, the target advertisements were shown to participants who completed the pre-exposure survey. The total time from recruitment to completion of the postexposure survey was 13 days, and incentive costs were US $10 per participant. Survey data were compared between those who completed both pre- and postexposure surveys and those who only completed the pre-exposure survey; that is, those who were lost to follow-up. The demographics of the complete cases were also compared to the US census data. RESULTS: A total of 375 Facebook users aged between 18 and 24 years met eligibility requirements and consented to the study, which consisted of complete cases (n=234) and participants lost to follow-up (n=141). A few differences between complete cases and participants lost to follow-up were observed. Regarding gender, complete cases comprised 40.2% males and 59.4% females, and among participants lost to follow-up, 44.0% were male and 50.4% were female (P=.003). Differences were also observed for e-cigarette use status, where a greater number of current users and fewer past and never users were lost to follow-up than complete cases (P=.01). CONCLUSIONS: The use of Virtual Lab yielded a diverse sample quickly and cost-effectively. Demographic characteristics of participants who completed the study and those who were lost to follow-up were similar, indicating that no biases were caused by the platform during recruitment or testing. This study suggests the feasibility of the Virtual Lab survey platform for studies of media campaign exposure within Facebook. This platform can advance health campaign research by providing more accurate data to inform digital messaging.
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 | 0,007 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».