The Use of Travel as an Appeal to Motivate Millennial Parents on Facebook to Get Vaccinated Against COVID-19: Message Framing Evaluation
Notice bibliographique
Résumé
BACKGROUND: In summer 2021, the Centers for Disease Control and Prevention recommended that people get fully vaccinated against COVID-19 before fall travel to protect themselves and others from getting and spreading COVID-19 and new variants. Only 61% of parents had reported receiving at least 1 dose of the COVID-19 vaccine, according to a Kaiser Family Foundation study. Millennial parents, ages 25 to 40 years, were a particularly important parent population because they were likely to have children aged 12 years or younger (the age cutoff for COVID-19 vaccine eligibility during this time period) and were still planning to travel. Since Facebook has been identified as a popular platform for millennials and parents, the Centers for Disease Control and Prevention's Travelers' Health Branch determined an evaluation of public health messages was needed to identify which message appeals would resonate best with this population on Facebook. OBJECTIVE: The objective was to evaluate which travel-based public health message appeals aimed at addressing parental concerns and sentiments about COVID-19 vaccination would resonate most with Millennial parents (25 to 40 years old) using Facebook Ads Manager and social media metrics. METHODS: Six travel-based public health message appeals on parental concerns and sentiments around COVID-19 were developed and disseminated to millennial parents using Facebook Ads Manager. The messages ran from October 23, 2021, to November 8, 2021. Primary outcomes included the number of people reached and the number of impressions delivered. Secondary outcomes included engagements, clicks, click-through rate, and audience sentiments. A thematic analysis was conducted to analyze comments. The advertisement budget was evaluated by cost-per-mille and cost-per-click metrics. RESULTS: All messages reached a total of 6,619,882 people and garnered 7,748,375 impressions. The Family (n=3,572,140 people reached, 53.96%; 4,515,836 impressions, 58.28%) and Return to normalcy (n=1,639,476 people reached, 24.77%; 1,754,227 impressions, 22.64%) message appeals reached the greatest number of people and garnered the most impressions out of all 6 message appeals. The Family message appeal received 3255 engagements (60.46%), and the Return to normalcy message appeal received 1148 engagements (21.28%). The Family appeal also received the highest number of positive post reactions (n=82, 28.37%). Most of the comments portrayed negative opinions about COVID-19 vaccination (n=46, 68.66%). All 6 message appeals were either on par with or outperformed cost-per-mille benchmarks set by other similar public health campaigns. CONCLUSIONS: Health communicators can use travel, specifically the Family and Return to normalcy message appeals, to successfully reach parents in their future COVID-19 vaccination campaigns and potentially inform health communication messaging efforts for other vaccine-preventable infectious disease campaigns. Public health programs can also utilize the lessons learned from this evaluation to communicate important COVID-19 information to their parent populations through travel messaging.
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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 | 0,006 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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 ».