The use, adherence, and evaluation of interactive text-messaging among women admitted to prevention of mother-to-child transmission of HIV care in Kenya (WelTel PMTCT)
Notice bibliographique
Résumé
Abstract Background To improve future mobile health (mHealth) interventions in resource-limited settings, knowledge of participants’ adherence to interactive interventions is needed, but previous studies are limited. We aimed to investigate how women in prevention of mother-to-child transmission of HIV (PMTCT) care in Kenya used, adhered to, and evaluated an interactive text-messaging intervention. Methods We conducted a cohort study nested within the WelTel PMTCT trial among 299 pregnant women living with HIV aged ≥ 18 years. They received weekly text messages from their first antenatal care visit until 24 months postpartum asking “How are you?”. They were instructed to text within 48 h stating that they were “okay” or had a “problem”. Healthcare workers phoned non-responders and problem-responders to manage any issue. We used multivariable-adjusted logistic and negative binomial regression to estimate adjusted odds ratios (aORs), rate ratios (aRRs) and 95% confidence intervals (CIs) to assess associations between baseline characteristics and text responses. Perceptions of the intervention were evaluated through interviewer-administered follow-up questionnaires at 24 months postpartum. Results The 299 participants sent 15,183 (48%) okay-responses and 438 (1%) problem-responses. There were 16,017 (51%) instances of non-response. The proportion of non-responses increased with time and exceeded 50% around 14 months from enrolment. Most reported problems were health related (84%). Having secondary education was associated with reporting a problem (aOR:1.88; 95%CI: 1.08–3.27) compared to having primary education or less. Younger age (18–24 years) was associated with responding to < 50% of messages (aOR:2.20; 95%CI: 1.03–4.72), compared to being 35–44 years. Women with higher than secondary education were less likely (aOR:0.28; 95%CI: 0.13–0.64), to respond to < 50% of messages compared to women with primary education or less. Women who had disclosed their HIV status had a lower rate of non-response (aRR:0.77; 95%CI: 0.60–0.97). In interviews with 176 women, 167 (95%) agreed or strongly agreed that the intervention had been helpful, mainly by improving access to and communication with their healthcare providers (43%). Conclusion In this observational study, women of younger age, lower education, and who had not disclosed their HIV status were less likely to adhere to interactive text-messaging. The majority of those still enrolled at the end of the intervention reported that text-messaging had been helpful, mainly by improving access to healthcare providers. Future mHealth interventions aiming to improve PMTCT care need to be targeted to attract the attention of women with lower education and younger age.
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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 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,002 | 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 ».