Behavioral Predictors of Intention to Use a Text Messaging Reminder System Among People Living With HIV in Rural Uganda: Survey Study
Notice bibliographique
Résumé
BACKGROUND: The expansion of cellular phones in sub-Saharan Africa spurred the development of SMS text message-based mobile health (mHealth) technology. Numerous SMS text message-based interventions have attempted to increase retention in care for people living with HIV in sub-Saharan Africa. Many of these interventions have failed to scale. Understanding theory-grounded factors leading to mHealth acceptability is needed to create scalable, contextually appropriate, and user-focused interventions to improve longitudinal HIV care for people living with HIV in sub-Saharan Africa. OBJECTIVE: In this study, we aimed to understand the relationship between constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), constructs identified in previous qualitative research, and behavioral intention to use a novel SMS text message-based mHealth intervention designed to improve care retention among people living with HIV initiating treatment in rural Uganda. METHODS: We conducted a survey of people living with HIV who were newly initiating HIV care in Mbarara, Uganda, and had agreed to use a novel SMS text message-based system that notified them of abnormal laboratory results and reminded them to return to the clinic. Survey items assessed behavioral intention to use the SMS text messaging system; constructs from UTAUT; and demographics, literacy, SMS text messaging experience, HIV status disclosure, and social support. We used factor analysis and logistic regression to estimate the relationships between UTAUT constructs and the behavioral intention to use the SMS text messaging system. RESULTS: A total of 249 participants completed the surveys, of whom 115 (46.2%) expressed high behavioral intention to use the SMS text messaging intervention. In a multivariable analysis, we found that performance expectancy (adjusted odds ratio [aOR] of the scaled factor score 5.69, 95% CI 2.64-12.25; P<.001), effort expectancy (aOR of the scaled factor score 4.87, 95% CI 1.75-13.51; P=.002), and social influence (measured as a 1-unit Likert score increase in the perception that clinical staff have been helpful in the use of the SMS text messaging program; aOR 3.03, 95% CI 1.21-7.54; P=.02) were significantly associated with high behavioral intention to use the SMS text messaging program. SMS text messaging experience (aOR/1-unit increase 1.48, 95% CI 1.11-1.96; P=.008) and age (aOR/1-year increase 1.07, 95% CI 1.03-1.13; P=.003) were also significantly associated with increased odds of high intention to use the system. CONCLUSIONS: Performance expectancy, effort expectancy, and social influence, as well as age and SMS experience, were drivers of high behavioral intention to use an SMS text messaging reminder system among people living with HIV initiating treatment in rural Uganda. These findings highlight salient factors associated with SMS intervention acceptability in this population and indicate attributes that are likely to be key to the successful development and scaling of novel mHealth interventions.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».