Mobile Text Messaging for Tobacco Risk Communication Among Young Adult Community College Students: Randomized Trial of Project Debunk
Notice bibliographique
Résumé
BACKGROUND: The use of new and emerging tobacco products (NETPs) and conventional tobacco products (CTPs) has been linked to several alarming medical conditions among young adults (YAs). Considering that 96% of YAs own mobile phones, SMS text messaging may be an effective strategy for tobacco risk communication. OBJECTIVE: Project Debunk is a community-based randomized trial aiming to identify specific types of messages that effectively improve perceived NETP and CTP risk among YAs in community colleges. METHODS: With YAs recruited offline from 3 campuses at the Houston Community College (September 2016 to July 2017), we conducted a 6-month randomized trial with 8 arms based on the combination of 3 message categories: framing (gain-framed vs loss-framed), depth (simple vs complex), and appeal (emotional vs rational). Participants received fully automated web-based SMS text messages in two 30-day campaigns (2 messages per day). We conducted repeated-measures mixed-effect models stratified by message type received, predicting perceived CTP and NETP risks. Owing to multiple testing with 7 models, an association was deemed significant for P<.007 (.05 divided by 7). RESULTS: A total of 636 participants completed the baseline survey, were randomized to 1 of 8 conditions (between 73 and 86 participants per condition), and received messages from both campaigns. By the 2-month post campaign 2 assessment point, 70.1% (446/636) completed all outcome measures. By the end of both campaigns, participants had a significant increase in perceived NETP risk over time (P<.001); however, participants had a marginal increase in perceived CTP risk (P=.008). Separately for each group, there was a significant increase in perceived NETP risk among participants who received rational messages (P=.005), those who received emotional messages (P=.006), those who received simple messages (P=.003), and those who received gain-framed messages (P=.003). CONCLUSIONS: In this trial, YAs had an increase in perceived NETP risk. However, with stratification, we observed a significant increase in perceived NETP risk upon exposure to rational, emotional, simple, and gain-framed messages. In addition, YAs generally had an increase in perceived CTP risk and presented nonsignificant but observable improvement upon exposure to emotional, complex, and loss-framed messages. With the results of this study, researchers and practitioners implementing mobile health programs may take advantage of our tailored messages through larger technology-based programs such as smartphone apps and social media campaigns. TRIAL REGISTRATION: ClinicalTrials.gov NCT03457480; https://clinicaltrials.gov/ct2/show/NCT03457480. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/10977.
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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 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 ».