Smartphone Ownership and Usage Among Pregnant Women Living With HIV in South Africa: Secondary Analysis of CareConekta Trial Data
Notice bibliographique
Résumé
BACKGROUND: Mobile health (mHealth) initiatives are increasingly common in low-resource settings, but the appropriateness of smartphone interventions in health care settings is uncertain. More research is needed to establish the appropriateness and feasibility of integrating new mHealth modalities (novel apps and social media apps) in the South African context. OBJECTIVE: In this study, to inform future mHealth interventions, we describe smartphone ownership, preferences, and usage patterns among pregnant women living with HIV in Gugulethu, South Africa. METHODS: We screened pregnant women living with HIV from December 2019 to February 2021 for the CareConekta trial. To be enrolled in the trial, respondents were required to be 18 years of age or older, living with HIV, ≥28 weeks pregnant, and own a smartphone that met the technical requirements of the CareConekta app. In this secondary analysis, we describe mobile phone ownership and sociodemographic characteristics of all women screened for eligibility (n=639), and smartphone use patterns among those enrolled in the trial (n=193). RESULTS: Overall, median age was 31 (IQR 27-35) years. Of the 582 women who owned smartphones, 580 responded to the question about whether or not it was a smartphone, 2 did not. Among those with smartphones, 92% (421/458) of them used the Android operating system of version 5.0 or above, 98% (497/506) of phones had a GPS, and 96% (485/506) of individuals charged their phones less than twice a day. Among women who were enrolled in the trial, nearly all (99%, 190/193) owned the smartphone themselves; however, 14% (26/193) shared their smartphone with someone. In this case, 96% (25/26) reported possessing the phone most of the day. Median duration of ownership of the smartphone was 12 (IQR 5-24) months, median duration with current phone number use was 25 (IQR 12-60) months, and median number of cell phone numbers owned 2 years prior to enrollment in the trial was 2 (IQR 1-2). Receiving (192/193, 99.5%) and making (190/193, 99%) phone calls were among the most common smartphone uses. The least used features were GPS (106/193, 55%) and email (91/193, 47%). WhatsApp was most frequently reported as a favorite app (181/193, 94%). CONCLUSIONS: Smartphone ownership is very common among pregnant women living with HIV in this low-resource, periurban setting. Phone sharing was uncommon, nearly all used the Android system, and phones retained sufficient battery life. These results are encouraging to the development of mHealth interventions. Existing messaging platforms-particularly WhatsApp-are exceedingly popular and could be leveraged for interventions. Findings of moderate smartphone ownership turnover and phone number turnover are considerations for mHealth interventions in similar settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT03836625; https://clinicaltrials.gov/ct2/show/NCT03836625?term=NCT03836625.
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 | 0,006 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».