SynthesisBMC public health2024
Barriers and facilitators of tuberculosis treatment among immigrants: an integrative review.
Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07609264 (Making Sense of Tuberculosis), which is not on this map. Cited by 5 papers.
What it found
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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.
Making Sense of Tuberculosis (TB) Related Stigma in a Low-incidence Area of the UK: Patients Experiences and Everyday Responses
Who cites it
5 citing papers in PubMed.
- Tuberculosis epidemiology and programmatic progress in the WHO Western Pacific Region, 2010-2024: an analysis of surveillance data.Tropical medicine and health · 2026Article
- AI-Driven Tuberculosis Hotspot Mapping to Optimize Active Case-Finding: Implementing the Epi-Control Platform in Uganda.Tropical medicine and infectious disease · 2026Article
- Community-based strategies for tuberculosis control in migrant communities: how to integrate determinants of vulnerability into decision-making.BMC public health · 2025Article
- Determinants of the lost to follow-up status among patients with tuberculosis who emigrated to the Republic of Korea: a mixed-method study.Frontiers in public health · 2025Article
- Geographic mapping and spatiotemporal patterns of tuberculosis in Libya within ten years' period (2015 to 2024).Frontiers in epidemiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesMigration, as an important social determinant in the field of health, plays a crucial role in the non-eradication of tuberculosis worldwide. Therefore, it is essential to identify the factors related to tuberculosis treatment in immigrants to effectively combat this disease. However no comprehensive study has focused on this issue. Therefore, this study was conducted using an ecological approach to identify the barriers and facilitators of tuberculosis treatment in immigrants.
methodsThis qualitative study utilized an integrative literature review. Studies were searched without time restrictions in database such as MEDLINE, Institute for Scientific Information (ISI), Google Scholar, Scopus, and EMBAS, as well as internal databases like Scientific Information Database and Magiran. The findings of 100 studies that met the inclusion criteria were analyzed using the conventional content analysis method based on the ecological approach.
resultsIn general, the aforementioned codes were placed into four main categories, including individual factors (i.e., biological factors, psychological factors, behavioral factors, patient knowledge, factors related to tuberculosis, and economic factors), interpersonal factors (i.e., communication with the treatment team and family-related factors), factors related to health service provider centers (i.e., medical facilities), and extra-organizational factors (i.e., social factors and health policies).
conclusionThe findings of the present study show that treating tuberculosis in immigrants is a complex phenomenon influenced by several factors. Therefore policymakers and healthcare providers should take a more comprehensive look at the factors affecting treatment in this group of patients to plan and implement more effective interventions.
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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.