Use of the WelTel mobile health intervention at a tuberculosis clinic in British Columbia: a pilot study
Notice bibliographique
Résumé
Successful treatment of latent tuberculosis infection (LTBI) is critical to reduce the impact of TB; however, treatment completion in North America is less than 50%. Evidence has shown that weekly text messages can improve treatment adherence in HIV. One of these evidence-based interventions is WelTel, a service involving weekly text-message ‘‘check-ins’’ with patients. The aim of this study was to determine the feasibility of adopting the WelTel intervention, originally developed and tested in Kenya, for use in the context of TB care in British Columbia (BC). (1) Determine prevalence of mobile phone ownership, text-message use, and patient attitudes towards receiving text messages from the clinic. (2) Determine the technological feasibility of the WelTel mobile health intervention, and patient and healthcare provider acceptability of the service. A descriptive cross-sectional survey was undertaken at a provincial TB control clinic in BC. A clinician administered a questionnaire focused on demographics, mobile phone ownership and use, and attitudes towards receiving text messages from the clinic. The WelTel intervention was then implemented in a small group of LTBI patients for 12 weeks. On Monday morning, an SMS gateway sent ‘‘How are you?’’ text messages to patients, to which they were to respond either ‘‘OK’’ or ‘‘Not OK’’ within 48 hours. A clinician phoned those who responded ‘Not OK’’ and those who did not respond. Participants completed baseline and follow-up questionnaires, and semi-structured interviews. Of 82 participants who completed the survey between September 2011 and December 2011, 68 owned a mobile phone and 58 used text messaging weekly. Participants were receptive to receiving treatment-related communication from the clinic via text messaging (n 80) but preferred not to have language relating to TB in the message content. Of 16 patients who received the intervention, 14 completed the study. After overcoming initial difficulties, the technological platform was an efficient way to deliver the intervention. The greatest participant-perceived benefits were that it enabled them to report side effects quickly (n 6), reminded them to take their medication (n 4), and imparted a feeling that their healthcare providers cared (n 2). Interview data supported these findings. Barriers included cost (n 3) and network coverage (n 2). Patients have the means to communicate with their healthcare providers via text-messaging and were receptive to doing so. The intervention was well-received by participants and the healthcare provider; however, research on its effectiveness to improve TB treatment adherence is required. MHIMSS 2013 ABSTRACT #JOURNAL OF MOBILE TECHNOLOGY IN MEDICINE VOL. 2 | ISSUE 4S | DECEMBER 2013 5
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 tête enseignante, 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 ».