The Impact of Dose in an mHealth Intervention to Support Parents and Carers Via Healthy Beginnings for Hunter New England Kids Program: Pragmatic Randomized Controlled Trial
Notice bibliographique
Résumé
Background: The dose of mobile health (mHealth) interventions can influence participant engagement, acceptability, and overall impact. However, few mHealth interventions have explored this dose-response relationship. Objective: This study aims to explore how dose influences the acceptability, engagement, cost, and impact on infant feeding status of a parent-targeted mHealth text messaging program which aims to enhance child health, including breastfeeding exclusivity and duration. Methods: This pragmatic randomized controlled trial was conducted from October 2021 to May 2024. The Healthy Beginnings for Hunter New England Kids (HB4HNEKids) program provides- text messages aimed to support parents and carers and their children by providing evidence-based preventive health information across the first 2000 days. Participants were enrolled in HB4HNEKids from 5 Child and Family Health Services in the Hunter New England region of New South Wales, Australia, and randomized into either a high-dose or low-dose text message group for the first 2 years of the pilot program. Dose refers to the quantity and frequency of text messages sent to participants. Participants in the high-dose text message group received an average of 111-121 text messages, and the low-dose text message group received 80-82 text messages across the 2 years. Outcomes of interest included acceptability, engagement, cost, and infant feeding status in relation to dose. Engagement with the messages was determined using click rates and program opt-out rates. Participant acceptability was assessed via a brief survey. Impact on infant feeding status (ie, breastfeeding, formula feeding, or mixed feeding) was determined by participants reporting their feeding status at several time points across the program. Cost was determined by assessing the per participant and total cost of sending text messages for each dose group across the 2-year period. Results: There were no statistically significant differences in click rates between high or low-dose text message groups. In the first 6 months, significantly more participants opted out of the high-dose text message group (191/2724; 7%) compared to the low-dose (108/2812; 3.8%; P<.001). In terms of program acceptability, 183 out of 214 (85.5%) participants of the high-dose and 228 out of 252 (90.5%) participants of the low-dose text message group were satisfied with the frequency of text messages. In addition, 188 out of 215 (87%) participants of high-dose and 220 out of 255 (86%) participants of low-dose text message group indicated they would recommend the program to other caregivers. The average per participant and total cost to the health service for sending messages was lower in the low-dose group (A$9.32 per participant and A$15,271.48 total; A$1 is approximately equal to US $0.68) compared to the high-dose text message group (A$12.96 per participant and A$21,241.44 total). Conclusions: The HB4HNEKids program demonstrated positive outcomes including high acceptability across both groups and no impact on infant feeding status, irrespective of dose. Given the higher opt-out rates and message costs in the high-dose text message group, a lower dose is likely more scalable for future use.
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 | 0,008 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 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 ».