Constrains Faced by Tb Patients Leading to Non-Compliance: A Cross Sectional Study in Mardan, Kpk, Pakistan
Bibliographic record
Abstract
Background: Pakistan is among the high endemic countries for TB and ranked 5th in the high TB burden countries with estimated 4th highest prevalence of multidrug resistance (MDR) TB. TB patients in Pakistan are facing different socio-economic and cultural constraints. TB patients are stigmatized and have been affected negatively due to poor knowledge about the disease dynamics, wrong socio-cultural myths and misapprehensions in general public. Objective: The study conducted by active TB patients to explore and evaluate different constraints that TB patients are facing in Mardan, Pakistan. Methods: A cross sectional study was conducted in district Mardan during March to June 2015. From 350 selected patients 210 were enrolled in study after informed consents. Data were collected though structured questionnaire and statistically analyzed by Epi-info/SPSS. Results: Overcrowding (P=.001, CI, 95%), unawareness of disease (86%), low educational status (P<.002, CI 95%), poverty and access to healthcare facilities were directly related to poor compliance. Attitude of family members, colleagues, society and even healthcare staff (P=.002, CI 95%) were also found significant. Age groups, marital status and treatment duration were found to be highly significant (P<.002). 85% patients were unaware with the risk factors and precautions during the treatment. 42% patients were unemployed, 58% employed less than 200 USD/month (P=.001, CI 95%). 59% patients complained worst behavior of their colleagues (P=.001) and 41.7% complained worst behavior of healthcare staff (P=.003, CI 95%). Conclusions: TB patients were found stigmatized due to poor economic conditions and bad attitude of family, colleagues and healthcare staff. Unemployment, malnutrition and overcrowding were among the worst constraints. Sensitization of medical staff and doctors to diagnose the disease in time and behave properly with patients is recommended. Dedicated patients and family education sessions must be conducted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".