Factors Contributing to Medication Noncompliance of Newly Diagnosed Smear-Positive Pulmonary Tuberculosis Patients in the District of Colombo, Sri Lanka
Bibliographic record
Abstract
Medication noncompliance hinders effective tuberculosis control. This descriptive study investigates the factors contributing to medication noncompliance among new patients with smear-positive pulmonary tuberculosis on treatment at government health institutions in Colombo, Sri Lanka. In a cohort of patients aged > or =15 years (n = 326), 23% were found to be noncompliers (n = 74) on follow-up. The median age of noncompliers (50 years) was significantly higher than the compliers (45 years). In multivariate logistic regression analysis, factors associated with noncompliance are as follows: being a male, living alone or with extended family, experiencing side effects to medication, perceiving nonsusceptibility to adverse effects of illness, and perceiving no benefit in regular treatment. The participants of a focus group discussion on service factors opined that the reception at treatment facilities and the interaction with certain categories of staff were poor. Noncompliance is related to a multiplicity of factors involving patients and healthcare services.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".