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dc.contributor.authorStagg, Helen R.en
dc.contributor.authorFlook, Maryen
dc.contributor.authorMartinecz, Antalen
dc.contributor.authorKielmann, Karinaen
dc.contributor.authorAbel Zur Wiesch, Piaen
dc.contributor.authorKarat, Aaron S.en
dc.contributor.authorLipman, Marcen
dc.contributor.authorSloan, Derek J.en
dc.contributor.authorWalker, Elizabeth F.en
dc.contributor.authorFielding, Katherine L.en
dc.date.accessioned2020-07-17T08:37:08Z
dc.date.available2020-07-17T08:37:08Z
dc.date.issued2020
dc.identifierhttps://eresearch.qmu.ac.uk/bitstream/handle/20.500.12289/10646/10646.pdf
dc.identifier.citationStagg, H. R., Flook, M., Martinecz, A., Kielmann, K., Abel Zur Wiesch, P., Karat, A. S., Lipman, M., Sloan, D. J., Walker, E. F. & Fielding, K. L. (2020) All non-adherence is equal, but is some more equal than others? TB in the digital era. ERJ Open Research (In Press).en
dc.identifier.issn2312-0541en
dc.identifier.urihttps://openres.ersjournals.com/
dc.identifier.urihttps://eresearch.qmu.ac.uk/handle/20.500.12289/10646
dc.descriptionKarina Kielmann - ORCID 0000-0001-5519-1658 https://orcid.org/0000-0001-5519-1658en
dc.descriptionAaron S. Karat - ORCID 0000-0001-9643-664X https://orcid.org/0000-0001-9643-664X
dc.description.abstractAdherence to treatment for tuberculosis (TB) has been a concern for many decades, resulting in the World Health Organization’s recommendation of the direct observation of treatment in the 1990s. Recent advances in digital adherence technologies (DATs) have renewed discussion on how to best address non-adherence, as well as offering important information on dose-by-dose adherence patterns and their variability between countries and settings. Previous studies have largely focussed on percentage thresholds to delineate sufficient adherence, but this is misleading and limited, given the complex and dynamic nature of adherence over the treatment course. Instead, we apply a standardised taxonomy- as adopted by the international adherence community- to dose-by-dose medication-taking data, which divides missed doses into a) late/non-initiation (starting treatment later than expected/not starting), b) discontinuation (ending treatment early), and c) suboptimal implementation (intermittent missed doses). Using this taxonomy, we can consider the implications of different forms of non-adherence for intervention and regimen design. For example, can treatment regimens be adapted to increase the ‘forgiveness’ of common patterns of suboptimal implementation to protect against treatment failure and the development of drug resistance? Is it reasonable to treat all missed doses of treatment as equally problematic and equally common when deploying DATs? Can DAT data be used to indicate the patients that need enhanced levels of support during their treatment course? Critically, we pinpoint key areas where knowledge regarding treatment adherence is sparse and impeding scientific progress.en
dc.description.urihttps://openres.ersjournals.com/en
dc.language.isoenen
dc.publisherEuropean Respiratory Societyen
dc.relation.ispartofERJ Open Researchen
dc.titleAll non-adherence is equal, but is some more equal than others? TB in the digital eraen
dc.typeArticleen
dcterms.accessRightsrestricted
dcterms.dateAccepted2020-07-16
dc.description.ispublishedinpress
rioxxterms.typeJournal Article/Reviewen
rioxxterms.publicationdate2020
refterms.dateFCD2020-07-17
refterms.depositExceptionpublishedGoldOAen
refterms.accessExceptionNAen
refterms.technicalExceptionNAen
refterms.panelUnspecifieden
qmu.authorKielmann, Karinaen
qmu.authorKarat, Aaron S.en
qmu.centreInstitute for Global Health and Developmenten
dc.description.statusinpress
refterms.versionAMen
refterms.dateDeposit2020-07-17


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