Examination of Text Message Plans and Baseline Usage of Families Enrolled in a Text Message Influenza Vaccine Reminder Trial: Survey Study
Notice bibliographique
Résumé
BACKGROUND: Mobile health (mHealth) is quickly expanding as a method of health promotion, but some interventions may not be familiar or comfortable for potential users. SMS text messaging has been investigated as a low-cost, accessible way to provide vaccine reminders. Most (97%) US adults own a cellphone and of those adults most use SMS text messaging. However, understanding patterns of SMS text message plan type and use in diverse primary care populations needs more investigation. OBJECTIVE: We sought to use a survey to examine baseline SMS text messaging and data plan patterns among families willing to accept SMS text message vaccine reminders. METHODS: As part of a National Institutes of Health (NIH)-funded national study (Flu2Text) conducted during the 2017-2018 and 2018-2019 influenza seasons, families of children needing a second seasonal influenza vaccine dose were recruited in pediatric primary care offices at the time of their first dose. Practices were from the American Academy of Pediatrics' (AAP) Pediatric Research in Office Settings (PROS) research network, the Children's Hospital of Philadelphia, and Columbia University. A survey was administered via telephone (Season 1) or electronically (Season 2) at enrollment. Standardized (adjusted) proportions for SMS text message plan type and texting frequency were calculated using logistic regression that was adjusted for child and caregiver demographics. RESULTS: Responses were collected from 1439 participants (69% of enrolled). The mean caregiver age was 32 (SD 6) years, and most children (n=1355, 94.2%) were aged 6-23 months. Most (n=1357, 94.3%) families were English-speaking. Most (n=1331, 92.8%) but not all participants had an unlimited SMS text messaging plan and sent or received texts at least once daily (n=1313, 91.5%). SMS text messaging plan type and use at baseline was uniform across most but not all subgroups. However, there were some differences in the study population's SMS text messaging plan type and usage. Caregivers who wanted Spanish SMS text messages were less likely than those who chose English to have an unlimited SMS text messaging plan (n=61, 86.7% vs n=1270, 94%; risk difference -7.2%, 95% CI -27.1 to -1.8). There were no significant differences in having an unlimited plan associated with child's race, ethnicity, age, health status, insurance type, or caregiver education level. SMS text messaging use at baseline was not uniform across all subgroups. Nearly three-quarters (n=1030, 71.9%) of participants had received some form of SMS text message from their doctor's office; most common were appointment reminders (n=1014, 98.4%), prescription (n=300, 29.1%), and laboratory notifications (n=117, 11.4%). Even the majority (n=64, 61.5%) of those who did not have unlimited plans and who texted less than daily (n=72, 59%) reported receipt of these SMS text messages. CONCLUSIONS: In this study, most participants had access to unlimited SMS text messaging plans and texted at least once daily. However, infrequent texting and lack of access to an unlimited SMS text messaging plan did not preclude enrolling to receive SMS text message reminders in pediatric primary care settings.
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 | 0,010 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».