Prevention and control of tuberculosis in workplaces: how knowledgeable are the workers in Bangladesh?
Bibliographic record
Abstract
BACKGROUND: The National Tuberculosis (TB) Control Programme (NTP) of Bangladesh succeeded in achieving the dual targets of 70 % case detection and 85 % treatment completion as set by the World Health Organization. However, TB prevention and control in work places remained largely an uncharted area for NTP. There is dearth of information regarding manufacturing workers' current knowledge, attitudes and practices (KAP) on pulmonary TB which is essential for designing a TB prevention and control programme in the workplaces. This study aimed to fill-in this knowledge gap. METHODS: This cross-sectional survey was done in multiple workplaces like garment factories, jute mills, bidi/tobacco factories, flour mills, and steel mills using a multi-stage sampling procedure. Data on workers' KAP related to pulmonary TB were collected from 4800 workers in face-to-face interview. RESULTS: The workers were quite knowledgeable about symptoms of pulmonary TB (72 %) and free- of-cost sputum test (86 %) and drug treatment (88 %), but possessed superficial knowledge regarding causation (4 %) and mode of transmission (48 %). Only 11 % knew about preventive measures e.g., taking BCG vaccine and/or refraining from spitting here and there. Knowledge about treatment duration (43 %) and consequences of incomplete treatment (11 %) was poor. Thirty-one percent were afraid of the disease, 21 % would feel embarrassed (and less dignified) if they would have TB, and 50 % were afraid of isolation if neighbours would come to know about it. Workers with formal education (AOR 1.92; 95 % CI 1.61, 2.29) and exposure to community health workers (CHW) (AOR 31.60; 95 % CI 18.75, 53.35) were more likely to have TB knowledge score ≥ mean. Workers with knowledge score ≥ mean (AOR = 1.91; 95 % CI:1.44, 2.53) and exposure to CHWs either alone (AOR = 42.4; 95 % CI: 9.94, 180.5) or in combination with print media (AOR = 37.35; 95 % CI: 9.1, 180.5) were more likely to go to DOTS centre for treatment . Only around 43 % had sputum examination despite having chronic cough of ≥ 3 weeks duration. CONCLUSION: The workers had inadequate knowledge regarding its causation, transmission and prevention which may interfere with appropriate treatment-seeking for chronic cough including sputum test. NTP needs to be cognizant of these factors while designing a workplace TB prevention and control programme for Bangladesh.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".