ArticleGlobal public health2018
Surveillance or support: The experience of direct observation during tuberculosis treatment.
Article in Global public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Manualised package intervention to achieve treatment adherence in people with tuberculosis: the IMPACT pilot cluster-RCT.Health technology assessment (Winchester, England) · 2026Trial
- An assessment of video-observed treatment as an adherence support tool for patients with drug-resistant TB.IJTLD open · 2025Article
- Perceptions and experiences of directly observed treatment in tuberculosis: insights from a mixed-methods cross-sectional study.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2025Article
- Machine learning model to predict the adherence of tuberculosis patients experiencing increased levels of liver enzymes in Indonesia.PloS one · 2025Article
- Improving Tuberculosis Medication Adherence: The Potential of Integrating Digital Technology and Health Belief Model.Tuberculosis and respiratory diseases · 2023Article
- A scoping review of patient-centred tuberculosis care interventions: Gaps and opportunities.PLOS global public health · 2023Article
- Bioethical Implications of Vulnerability and Politics for Healthcare in Ethiopia and The Ways Forward.Journal of bioethical inquiry · 2022Article
- "Journal of clinical tuberculosis and other mycobacterial diseases · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
Directly observed therapy (DOT) is a cornerstone of tuberculosis (TB) control. DOT has been criticised as paternalistic, but it has also been argued that the interaction with healthcare workers (HWs) can be a source of support for patients. We explored the experience of patients in antituberculosis treatment, with the aim of understanding the balance between surveillance and support from the recipient's point of view. We interviewed 27 patients in Tijuana, Mexico, employing narrative analysis to understand how participants made sense of their illness and their experience of DOT. We found a core narrative of biographic disruption and self-reconstruction, in which HWs helped participants to attribute a less negative meaning to TB. Interviewees accepted DOT's as necessary for other people to avoid treatment abandonment, but felt that in their case it was unnecessary. Only a few felt that DOT represented mistrust on the part of the HWs. We conclude that DOT can be a source of support when it is enacted in a patient-centred way. We discuss whether participants' lack of criticism of DOT is a case of adaptive preference, in the context of a power differential between patient and health system.
Indexed as
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What OpenQuestion holds
Registered trials
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.