Evidence map›Paper›PMID 42008452›Full record

ArticlePloS one2026

Multi-level determinants of tuberculosis treatment completion in rural Uganda: A cross-sectional study.

Munanura Turyasiima, Daniel Muliika, Gaston Turinawe, Miriam Acheng, Antony Ikiriza, Agnes Alinde, Precious Natureeba, Amon Nkwansiibwe, Balbina Gillian Akot, Susan Wendy Wandera Kayizzi and 6 more

Abstract readMulticenter Study
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Munanura TuryasiimaDepartment of Standards Accreditation and Patient Protection, Ministry of Health, Kampala, Uganda.ORCID https://orcid.org/0000-0002-2598-5593
Daniel MuliikaFaculty of Health Sciences, Uganda Martyrs University, Kampala, Uganda.
Gaston TurinaweDivision of STD/AIDs Control, Ministry of Health, Kampala, Uganda.
Miriam AchengDivision of STD/AIDs Control, Ministry of Health, Kampala, Uganda.
Antony IkirizaFaculty of Health Sciences, Uganda Martyrs University, Kampala, Uganda.
Agnes AlindeFaculty of Health Sciences, Uganda Martyrs University, Kampala, Uganda.
Precious NatureebaDepartment of Educational Foundations and Psychology, Mbarara University of Science and Technology, Mbarara, Uganda.
Amon NkwansiibweFaculty of Clinical Medicine and Dentistry, Kampala International University, Kampala, Uganda.
Balbina Gillian AkotFaculty of Clinical Medicine and Dentistry, Kampala International University, Kampala, Uganda.
Susan Wendy Wandera KayizziDivision of STD/AIDs Control, Ministry of Health, Kampala, Uganda.
Derrick AsaasiraDepartment of Health Sciences, Faculty of Science and Technology, Cavendish University Uganda, Kampala, Uganda.
Shamim NantegeDepartment of Health Sciences, Faculty of Science and Technology, Cavendish University Uganda, Kampala, Uganda.
Iloit Daniel OodeFaculty of Clinical Medicine and Dentistry, Kampala International University, Kampala, Uganda.
Hilda Barbara WesongaDivision of STD/AIDs Control, Ministry of Health, Kampala, Uganda.
Raymond Kamara AtuhaireDepartment of Epidemiology, Baylor Foundation, Kampala, Uganda.
Ronald KookoDepartment of Epidemiology, Africa CDC, Kampala, Uganda.ORCID https://orcid.org/0000-0003-4872-7017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB) treatment completion rates in high-burden countries like Uganda often fall short of the WHO End TB Strategy target of ≥90%. This study evaluated multilevel determinants of treatment completion to guide evidence-based improvement strategies in rural Western Uganda.

methodsWe conducted a cross-sectional, multi-center analytical study of 224 patients with drug-susceptible TB across four public health facilities in Kakumiro District. Eligible participants had been on treatment for at least six months. Data collected via structured questionnaires were validated against facility TB registers. Multivariable logistic regression identified independent predictors, reported as adjusted odds ratios (AOR) with 95% confidence intervals (CI).

resultsThe treatment completion rate was 82.6% (185/224), with a 30.4% TB-HIV co-infection rate. Significant positive predictors included high TB knowledge (AOR = 14.0; 95% CI: 3.06-24.5), high economic status (AOR = 7.2; 95% CI: 1.63-31.5), belief in treatment efficacy (AOR = 6.2; 95% CI: 2.02-18.8), and respectful health worker behavior (AOR = 5.0; 95% CI: 2.15-11.83). Community-level support was critical, specifically religious/community leader advocacy (AOR = 4.2; 95% CI: 1.84-9.51) and community health worker (CHW) home visits (AOR = 3.5; 95% CI: 1.64-7.72). Waiting time less than 30 minutes (AOR = 6.3, 95% CI: 1.91-20.96) also positively impacted TB treatment completion. Major negative predictors were male gender (AOR = 0.3; 95% CI: 0.11-0.86), drug stockouts (AOR = 0.3; 95% CI: 0.11-0.70), belief in traditional cures (AOR = 0.3; 95% CI: 0.13-0.71), and stigma (AOR = 0.4; 95% CI: 0.16-0.80).

conclusionAchieving the WHO End TB targets requires integrated, multilevel interventions. Efforts should focus on male-targeted engagement, strengthening supply chains to eliminate drug stockouts, enhancing CHW-led community outreach, and reducing stigma to ensure equitable treatment success.

Indexed as

Antitubercular AgentsTuberculosisAdolescentAdultCross-Sectional StudiesFemaleHIV InfectionsHumansMaleMiddle AgedRural PopulationUgandaYoung AdultAntitubercular Agents

Identifiers

PMID42008452
PMCPMC13094977

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.