Show simple item record

dc.contributor.authorStagg, Helen
dc.contributor.authorFlook, Mary
dc.contributor.authorMartinecz, Antal
dc.contributor.authorKielmann, Karina
dc.contributor.authorAbel zur Wiesch, Pia
dc.contributor.authorKarat, Aaron
dc.contributor.authorLipman, Marc
dc.contributor.authorSloan, Derek
dc.contributor.authorWalker, Elizabeth
dc.contributor.authorFielding, Katherine L
dc.date.accessioned2021-01-23T15:26:24Z
dc.date.available2021-01-23T15:26:24Z
dc.date.issued2020-11-02
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 nonadherence, 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 1) late/noninitiation (starting treatment later than expected/not starting), 2) discontinuation (ending treatment early), and 3) suboptimal implementation (intermittent missed doses). Using this taxonomy, we can consider the implications of different forms of nonadherence 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_US
dc.identifier.citationStagg, Flook, Martinecz A, Kielmann, Abel zur Wiesch P, Karat, Lipman, Sloan, Walker, Fielding. All non-adherence is equal, but is some more equal than others? TB in the digital era.. European Respiratory Journal Open Research (ERJ Open Research). 2020en_US
dc.identifier.cristinIDFRIDAID 1836164
dc.identifier.doi10.1183/23120541.00315-2020
dc.identifier.issn2312-0541
dc.identifier.urihttps://hdl.handle.net/10037/20437
dc.language.isoengen_US
dc.publisherEuropean Respiratory Societyen_US
dc.relation.journalEuropean Respiratory Journal Open Research (ERJ Open Research)
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 The Author(s)en_US
dc.subjectVDP::Medical disciplines: 700::Health sciences: 800::Epidemiology medical and dental statistics: 803en_US
dc.subjectVDP::Medisinske Fag: 700::Helsefag: 800::Epidemiologi medisinsk og odontologisk statistikk: 803en_US
dc.titleAll non-adherence is equal, but is some more equal than others? TB in the digital eraen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


File(s) in this item

Thumbnail

This item appears in the following collection(s)

Show simple item record