Using mHealth to Support Postabortion Contraceptive Use: Results From a Feasibility Study in Urban Bangladesh
Notice bibliographique
Résumé
BACKGROUND: As access to mobile technology improves in low- and middle-income countries, it becomes easier to provide information about sensitive issues, such as contraception and abortion. In Bangladesh, 97% of the population has access to a mobile signal, and the equity gap is closing in mobile phone ownership. Bangladesh has a high pregnancy termination rate and improving effective use of contraception after abortion is essential to reducing subsequent unwanted pregnancies. OBJECTIVE: This study examines the feasibility and acceptability of implementing a short message service (SMS) text message-based mHealth intervention to support postabortion contraceptive use among abortion clients in Bangladesh, including women's interest in the intervention, intervention preferences, and privacy concerns. METHODS: This feasibility study was conducted in four urban, high abortion caseload facilities. Women enrolled in the study were randomized into an intervention (n=60) or control group (n=60) using block randomization. Women completed a baseline interview on the day of their abortion procedure and a follow-up interview 4 months later (retention rate: 89.1%, 107/120). Women in the intervention group received text message reminders to use their selected postabortion contraceptive methods and reminders to contact the facility if they had problems or concerns with their method. Women who did not select a method received weekly messages that they could visit the clinic if they would like to start a method. Women in the control group did not receive any messages. RESULTS: Almost all women in the feasibility study reported using their mobile phones at least once per day (98.3%, 118/120) and 77.5% (93/120) used their phones for text messaging. In the intervention group, 87% (48/55) of women were using modern contraception at the 4-month follow-up, whereas 90% (47/52) were using contraception in the control group (P=.61). The intervention was not effective in increasing modern contraceptive use at follow-up, but 93% (51/55) of women reported at follow-up that the text reminders helped them use their method correctly and 76% (42/55) said they would sign up for this service again. Approximately half of the participants (53%, 29/55) said that someone they did not want to know about the text message reminders found out, mostly their husbands or children. CONCLUSIONS: In this small-scale feasibility study, text reminders did not increase postabortion contraceptive use. Despite the ineffectiveness of the text reminder intervention, implementation of a mHealth intervention among abortion clients in urban Bangladesh was feasible in that women were interested in receiving follow-up messages after their abortion and mobile phone use was common. Text messages may not be the best modality for a mHealth intervention due to relatively low baseline SMS text message use and privacy concerns.
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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 | 0,005 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| 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) | 0,004 | 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 ».