Evidence map›Paper›PMID 37838677›Full record

ArticleBMC public health2023

Risk factors for poor engagement with a smart pillbox adherence intervention among persons on tuberculosis treatment in Ethiopia.

Amare Worku Tadesse, Martina Cusinato, Gedion Teferra Weldemichael, Tofik Abdurhman, Demelash Assefa, Hiwot Yazew, Demekech Gadissa, Amanuel Shiferaw, Mahilet Belachew, Mamush Sahile and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 3 institutions in 2 countries.

Amare Worku TadesseTB Centre, Department of Infectious Disease Epidemiology, London, School of Hygiene & Tropical Medicine (LSHTM) , London, UK. amare.tadesse@lshtm.ac.uk.ORCID http://orcid.org/0000-0002-7805-3191
Martina CusinatoTB Centre, Department of Infectious Disease Epidemiology, London, School of Hygiene & Tropical Medicine (LSHTM) , London, UK.
Gedion Teferra WeldemichaelKNCV Tuberculosis Plus, The Hague, Ethiopia.
Tofik AbdurhmanKNCV Tuberculosis Plus, The Hague, Ethiopia.
Demelash AssefaKNCV Tuberculosis Plus, The Hague, Ethiopia.
Hiwot YazewKNCV Tuberculosis Plus, The Hague, Ethiopia.
Demekech GadissaKNCV Tuberculosis Plus, The Hague, Ethiopia.
Amanuel ShiferawKNCV Tuberculosis Plus, The Hague, Ethiopia.
Mahilet BelachewKNCV Tuberculosis Plus, The Hague, Ethiopia.
Mamush SahileKNCV Tuberculosis Plus, The Hague, Ethiopia.
Job van RestKNCV Tuberculosis Plus, The Hague, Netherlands.
Ahmed BedruKNCV Tuberculosis Plus, The Hague, Ethiopia.
Nicola FosterTB Centre, Department of Infectious Disease Epidemiology, London, School of Hygiene & Tropical Medicine (LSHTM) , London, UK.
Degu JereneKNCV Tuberculosis Plus, The Hague, Netherlands.
Katherine Linda FieldingTB Centre, Department of Infectious Disease Epidemiology, London, School of Hygiene & Tropical Medicine (LSHTM) , London, UK.
London School of Hygiene & Tropical Medicine · GBAt Bristol · GBUniversity of the Witwatersrand · ZA

Funding

Medical Research Council MR/R010161/1
6 · The paper itself

Abstract

backgroundNon-adherence to tuberculosis treatment increases the risk of poor treatment outcomes. Digital adherence technologies (DATs), including the smart pillbox (EvriMED), aim to improve treatment adherence and are being widely evaluated. As part of the Adherence Support Coalition to End TB (ASCENT) project we analysed data from a cluster-randomised trial of DATs and differentiated care in Ethiopia to examine individual-factors for poor engagement with the smart pillbox.

methodsData were obtained from a cohort of trial participants with drug-sensitive tuberculosis (DS-TB) whose treatment started between 1 December 2020 and 1 May 2022, and who were using the smart pillbox. Poor engagement with the pillbox was defined as (i) > 20% days with no digital confirmation and (ii) the count of days with no digital confirmation, and calculated over a two evaluation periods (56-days and 168-days). Logistic random effects regression was used to model > 20% days with no digital confirmation and negative binomial random effects regression to model counts of days with no digital confirmation, both accounting for clustering of individuals at the facility-level.

resultsAmong 1262 participants, 10.8% (133/1262) over 56-days and 15.8% (200/1262) over 168-days had > 20% days with no digital confirmation. The odds of poor engagement was less among participants in the higher stratum of socio-economic position (SEP) over 56-days. Overall, 4,689/67,315 expected doses over 56-days and 18,042/199,133 expected doses over 168-days were not digitally confirmed. Compared to participants in the poorest SEP stratum, participants in the wealthiest stratum had lower rates of days not digitally confirmed over 168-days (adjusted rate ratio [RR

conclusionPoorest SEP stratum, HIV-positive status, single/living independent and separated/ widowed were associated with poor engagement with smart pillbox among people with DS-TB in Ethiopia. Differentiated care for these sub-groups may reduce risk of non-adherence to TB treatment.

Indexed as

HIV InfectionsTuberculosisAntitubercular AgentsEthiopiaHumansMedication AdherenceRandomized Controlled Trials as TopicRisk FactorsTreatment OutcomeAntitubercular AgentsDigital adherence technologiesDrug-sensitive tuberculosisEthiopiaPoor engagementSmart pillbox

Identifiers

PMID37838677
PMCPMC10576388
OpenAlexW4387640281

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.