Tuberculosis related barriers and facilitators among immigrants in Atlantic Canada: A qualitative study
Bibliographic record
Abstract
Tuberculosis (TB) is a disease caused by the bacterium Mycobacterium tuberculosis and affects approximately one-quarter of the world's population. Immigrant populations in Canada are disproportionately affected by TB. Canada's immigration medical examinations include screening for active TB but not latent TB infection (LTBI). In LTBI, the bacterium remains dormant within the host but can reactivate and cause disease. Once active, TB can be transmitted to close contacts sharing confined spaces leading to the possibility of outbreaks in the broader community. This study aimed to 1) assess the current TB knowledge, perceived risk, and risk behaviors of immigrants in Atlantic Canada as well as 2) identify barriers and facilitators to testing and treatment of TB among this population. Three focus group discussions were conducted with a total of 14 non-Canadian born residents of New Brunswick aged 19 years and older. Data were analyzed using inductive thematic analysis. Four themes were identified from the data relating to barriers to testing and treatment of LTBI: 1) Need for education, 2) stigma, 3) fear of testing, treatment, and healthcare system, and 4) complacency. Results included reasons individuals would not receive TB testing, treatment, or seek help, as well as facilitators to testing and treatment. These findings may inform the implemention of an LTBI screening program in Atlantic Canada and more broadly across the country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".