Using Text Messaging to Improve Access to Prenatal Health Information in Urban African American and Afro-Caribbean Immigrant Pregnant Women: Mixed Methods Analysis of Text4baby Usage
Notice bibliographique
Résumé
BACKGROUND: The Text4baby (T4B) mobile health (mHealth) program is acclaimed to provide pregnant women with greater access to prenatal health care, resources, and information. However, little is known about whether urban African American and Afro-Caribbean immigrant pregnant women in the United States are receptive users of innovative health communication methods or of the cultural and systematic barriers that inhibit their behavioral intent to use T4B. OBJECTIVE: This study aimed to understand the lived experiences of urban African American and Afro-Caribbean immigrant pregnant women with accessing quality prenatal health care and health information; to assess usage of mHealth for seeking prenatal health information; and to measure changes in participants' knowledge, perceptions, and behavioral intent to use the T4B mHealth educational intervention. METHODS: An exploratory sequential mixed methods study was conducted among pregnant women and clinical professionals for a phenomenological exploration with focus groups, key informants, interviews, and observations. Qualitative themes were aligned with behavioral and information technology communications theoretical constructs to develop a survey instrument used. repeated-measures pre- and post-test design to evaluate changes in participants' knowledge, attitudes, and beliefs, of mHealth and T4B after a minimum of 4 weeks' exposure to the text message-based intervention. Triangulation and mixing of both qualitative and quantitative data occurred primarily during the survey development and also during final analysis. RESULTS: A total of 9 women participated in phase 1, and 49 patients signed up for T4B and completed a 31-item survey at baseline and again during follow-up. Three themes were identified: (1) patient-provider engagement, (2) social support, and (3) acculturation. With time as a barrier to quality care, inadequate patient-provider engagement left participants feeling indifferent about the prenatal care and information they received in the clinical setting. Of 49 survey participants, 63% (31/49) strongly agreed that T4B would provide them with extra support during their pregnancy. On a Likert scale of 1 to 5, participants' perception of the usefulness of T4B ranked at 4.26, and their perception of the compatibility and relative advantage of using T4B ranked at 4.41 and 4.15, respectively. At follow-up, there was a 14% increase in participants reporting their intent to use T4B and a 28% increase from pretest and posttest in pregnant women strongly agreeing to speak more with their doctor about the information learned through T4B. CONCLUSIONS: Urban African American and Afro-Caribbean immigrant pregnant women in Brooklyn endure a number of social and ecological determinants like low health literacy, income, and language that serve as barriers to accessing quality prenatal health care and information, which negatively impacts prenatal health behaviors and outcomes. Our study indicates a number of systematic, political, and other microsystem-level factors that perpetuate health inequities in our study population.
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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 | 0,009 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».