Population-Level Dissemination of a Smoking Cessation Smartphone App: Quasi-Experimental Comparison of Values-Based Messages in Social Media Advertisements
Notice bibliographique
Résumé
Background: Cigarette smoking is prevalent in many countries worldwide, especially in low- and middle-income countries (LMICs), presenting an urgent public health challenge. Disseminating freely available smoking cessation treatments that effectively decrease cigarette smoking globally is urgently needed. Objective: Identify the highest impact and most cost-effective values-based social media advertisements to disseminate our smoking cessation smartphone app, "iCanQuit", among adults living in 7 major cities of India. Values represented in the advertisements included family, relationships, self-care, health, and self-control. Using a quasi-experimental design, we aimed to determine (1) which values-based advertisements had the highest smoking cessation app dissemination reach, as measured by click-through rate (CTR), app installs, and app usage metrics; and (2) which values-based message advertisements were more cost-effective as measured by cost-per-impression, cost-per-click, and cost-per-install. The study population included a selected media market of individuals living in 7 metro cities of India - Delhi, Mumbai, Kolkata, Chennai, Bengaluru, Hyderabad, and Pune - who were exposed to one of 6 social media advertisements from January 16 to May 5, 2024. Methods: The advertisement campaign design for each of the identified values, based on previous smoking cessation trial data, followed a collaborative iterative process. Advertisements ran sequentially for 16 weeks. Advertisement exposure and app usage data were objectively collected via Google's Display & Video 360 advertisements campaign management and Firebase app development platforms. Advertisement exposure impact on app engagement was measured via several metrics, including click-through rate (CTR, ie, the likelihood of user clicks on an advertisement after seeing it), the number of app installs (ie, a user opening the app for the first time after downloading it), and the number of app sessions (ie, app usage). Cost efficiency was measured via cost per click and cost per install for each ad. Results: Overall, the CTR was 5%. The app was installed 5111 times. The average cost per click and cost per app install across all advertisements were US $ 0.006 and US $ 6.43, respectively. The advertisements with the lowest cost per install (range: US $4.83-US $5.16) and highest CTR (between 6% and 9%) focused on the values of family, health, and self-control. Advertisements focused on the values of relationships and self-care had modestly higher levels of engagement. Conclusions: Advertisements focusing on the values of family, health, and self-control had the highest potential reach at the lowest cost. Overall, these findings provide insights into the reach and cost-effectiveness of values-based messages in social media advertisements, guiding future outreach efforts for population-level dissemination of smoking cessation apps.
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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 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».