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Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback

Digital adherence technologies (DATs) have emerged as an alternative to directly observed therapy (DOT) for supervisions of tuberculosis (TB) treatment. We conducted a meta-analysis of implementation feedback obtained from people with TB and health care workers (HCWs) involved in TB REACH Wave 6-fun...

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Autores principales: Guzman, Kevin, Crowder, Rebecca, Leddy, Anna, Maraba, Noriah, Jennings, Lauren, Ahmed, Shahriar, Sultana, Sonia, Onjare, Baraka, Shilugu, Lucas, Alacapa, Jason, Levy, Jens, Katamba, Achilles, Kityamuwesi, Alex, Bogdanov, Aleksey, Gamazina, Kateryna, Cattamanchi, Adithya, Khan, Amera
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10426983/
https://www.ncbi.nlm.nih.gov/pubmed/37582066
http://dx.doi.org/10.1371/journal.pdig.0000322
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author Guzman, Kevin
Crowder, Rebecca
Leddy, Anna
Maraba, Noriah
Jennings, Lauren
Ahmed, Shahriar
Sultana, Sonia
Onjare, Baraka
Shilugu, Lucas
Alacapa, Jason
Levy, Jens
Katamba, Achilles
Kityamuwesi, Alex
Bogdanov, Aleksey
Gamazina, Kateryna
Cattamanchi, Adithya
Khan, Amera
author_facet Guzman, Kevin
Crowder, Rebecca
Leddy, Anna
Maraba, Noriah
Jennings, Lauren
Ahmed, Shahriar
Sultana, Sonia
Onjare, Baraka
Shilugu, Lucas
Alacapa, Jason
Levy, Jens
Katamba, Achilles
Kityamuwesi, Alex
Bogdanov, Aleksey
Gamazina, Kateryna
Cattamanchi, Adithya
Khan, Amera
author_sort Guzman, Kevin
collection PubMed
description Digital adherence technologies (DATs) have emerged as an alternative to directly observed therapy (DOT) for supervisions of tuberculosis (TB) treatment. We conducted a meta-analysis of implementation feedback obtained from people with TB and health care workers (HCWs) involved in TB REACH Wave 6-funded DAT evaluation projects. Projects administered standardized post-implementation surveys based on the Capability, Opportunity, Motivation, Behavior (COM-B) model to people with TB and their health care workers. The surveys included questions on demographics and technology use, Likert scale questions to assess capability, opportunity, and motivation to use DAT and open-ended feedback. We summarized demographic and technology use data descriptively, generated pooled estimates of responses to Likert scale questions within each COM-B category for people with TB and health care workers using random effects models, and performed qualitative analysis of open-ended feedback using a modified framework analysis approach. The analysis included surveys administered to 1290 people with TB and 90 HCWs across 6 TB REACH-funded projects. People with TB and HCWs had an overall positive impression of DATs with pooled estimates between 4·0 to 4·8 out of 5 across COM-B categories. However, 44% of people with TB reported taking TB medications without reporting dosing via DATs and 23% reported missing a dose of medication. Common reasons included problems with electricity, network coverage, and technical issues with the DAT platform. DATs were overall perceived to reduce visits to clinics, decrease cost, increase social support, and decrease workload of HCWs. DATs were acceptable in a wide variety of settings. However, there were challenges related to the feasibility of using current DAT platforms. Implementation efforts should concentrate on ensuring access, anticipating, and addressing technical challenges, and minimizing additional cost to people with TB.
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spelling pubmed-104269832023-08-16 Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback Guzman, Kevin Crowder, Rebecca Leddy, Anna Maraba, Noriah Jennings, Lauren Ahmed, Shahriar Sultana, Sonia Onjare, Baraka Shilugu, Lucas Alacapa, Jason Levy, Jens Katamba, Achilles Kityamuwesi, Alex Bogdanov, Aleksey Gamazina, Kateryna Cattamanchi, Adithya Khan, Amera PLOS Digit Health Research Article Digital adherence technologies (DATs) have emerged as an alternative to directly observed therapy (DOT) for supervisions of tuberculosis (TB) treatment. We conducted a meta-analysis of implementation feedback obtained from people with TB and health care workers (HCWs) involved in TB REACH Wave 6-funded DAT evaluation projects. Projects administered standardized post-implementation surveys based on the Capability, Opportunity, Motivation, Behavior (COM-B) model to people with TB and their health care workers. The surveys included questions on demographics and technology use, Likert scale questions to assess capability, opportunity, and motivation to use DAT and open-ended feedback. We summarized demographic and technology use data descriptively, generated pooled estimates of responses to Likert scale questions within each COM-B category for people with TB and health care workers using random effects models, and performed qualitative analysis of open-ended feedback using a modified framework analysis approach. The analysis included surveys administered to 1290 people with TB and 90 HCWs across 6 TB REACH-funded projects. People with TB and HCWs had an overall positive impression of DATs with pooled estimates between 4·0 to 4·8 out of 5 across COM-B categories. However, 44% of people with TB reported taking TB medications without reporting dosing via DATs and 23% reported missing a dose of medication. Common reasons included problems with electricity, network coverage, and technical issues with the DAT platform. DATs were overall perceived to reduce visits to clinics, decrease cost, increase social support, and decrease workload of HCWs. DATs were acceptable in a wide variety of settings. However, there were challenges related to the feasibility of using current DAT platforms. Implementation efforts should concentrate on ensuring access, anticipating, and addressing technical challenges, and minimizing additional cost to people with TB. Public Library of Science 2023-08-15 /pmc/articles/PMC10426983/ /pubmed/37582066 http://dx.doi.org/10.1371/journal.pdig.0000322 Text en © 2023 Guzman et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Guzman, Kevin
Crowder, Rebecca
Leddy, Anna
Maraba, Noriah
Jennings, Lauren
Ahmed, Shahriar
Sultana, Sonia
Onjare, Baraka
Shilugu, Lucas
Alacapa, Jason
Levy, Jens
Katamba, Achilles
Kityamuwesi, Alex
Bogdanov, Aleksey
Gamazina, Kateryna
Cattamanchi, Adithya
Khan, Amera
Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback
title Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback
title_full Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback
title_fullStr Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback
title_full_unstemmed Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback
title_short Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback
title_sort acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: a meta-analysis of implementation feedback
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10426983/
https://www.ncbi.nlm.nih.gov/pubmed/37582066
http://dx.doi.org/10.1371/journal.pdig.0000322
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