Digital Adherence Technologies and Mobile Money Incentives for Management of Tuberculosis Medication Among People Living With Tuberculosis: Mixed Methods Formative Study
Notice bibliographique
Résumé
BACKGROUND: Although there is an increasing use of digital adherence technologies (DATs), such as real-time monitors and SMS reminders in tuberculosis medication adherence, suboptimal patient engagement with various DATs has been reported. Additionally, financial constraints can limit DAT's utility. The perceived usefulness and the design mechanisms of DATs linked to mobile money financial incentives for tuberculosis medication management remain unclear. OBJECTIVE: The aim of this study is to describe the perceived usefulness and design mechanisms for a DAT intervention called My Mobile Wallet, which is composed of real-time adherence monitors, SMS reminders, and mobile money incentives to support tuberculosis medication adherence in a low-income setting. METHODS: This study used mixed methods approaches among persons with tuberculosis recruited from the Tuberculosis Clinic in the Mbarara Regional Referral Hospital. We purposively sampled 21 persons with tuberculosis aged 18 years and older, who owned cell phones and were able to use SMS text messaging interventions. We also enrolled 9 participants who used DATs in our previous study. We used focus group discussions with the 30 participants to solicit perceptions about the initial version of the My Mobile Wallet intervention, and then iteratively refined subsequent versions of the intervention following a user-centered design approach until the beta version of the intervention that suited their needs was developed. Surveys eliciting information about participants' cell phone use and perceptions of the intervention were also administered. Content analysis was used to inductively analyze qualitative data to derive categories describing the perceived usefulness of the intervention, concerns, and design mechanisms. Stata (version 13; StataCorp) was used to analyze survey data. RESULTS: Participants expressed the perceived usefulness of the My Mobile Wallet intervention in terms of being reminded to take medication, supported with transport to the clinic, and money to meet other tuberculosis medication-related costs, all of which were perceived to imply care, which could create a sense of connectedness to health care workers. This could consequently cause participants to develop a self-perceived need to prove their commitment to adherence to health care workers who care for them, thereby motivating medication adherence. For fear of unintended tuberculosis status disclosure, 20 (67%) participants suggested using SMS language that is confidential-not easily related to tuberculosis. To reduce the possibilities of using the money for other competing demands, 25 (83%) participants preferred sending the money 1-2 days before the appointment to limit the time lag between receiving the money and visiting the clinic. CONCLUSIONS: DATs complemented with mobile money financial incentives could potentially provide acceptable approaches to remind, support, and motivate patients to adhere to taking their tuberculosis medication. TRIAL REGISTRATION: ClinicalTrials.gov NCT05656287; https://clinicaltrials.gov/ct2/show/NCT05656287.
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 | 0,047 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».