Knowledge, Attitude, and Practice and service barriers in a tuberculosis programme in Lakes State, South Sudan: a qualitative study
Bibliographic record
Abstract
Background: The World Health Organisation (WHO) estimates the incidence of tuberculosis (TB) in South Sudan to be 79 per 100,000 for new sputum smear positive TB and 140 per 100,000 for all forms of TB cases. The case detection rate of 53% for all forms of TB in South Sudan is below the WHO target of 70%. Objective: To explore knowledge, attitude, and practice barriers as well as service barriers to implementing TB programme in Lakes State, South Sudan. Method: This was a qualitative study conducted in May 2015. Results: Despite some understanding of the symptoms, causes, and consequences of TB, the stigma for TB and lack of disclosure of the disease, is very high among the local community. The limited network of TB facilities for case detection, lack of community distribution of TB drugs and lack of food at hospitals when patients were admitted for treatment, are key barriers to TB service delivery. Conclusion: To overcome barriers it is recommended that the local community worldview should be incorporated into TB awareness, testing, and treatment, and attention should be paid to areas where traditional practices, such as elimination of maize, clash with modern treatments.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 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".