Exploring the Socio-cultural Dynamics of Treatment Adherence amongst Females living with Pulmonary Tuberculosis in Karachi, Pakistan
Bibliographic record
Abstract
Background & Objective: Pakistan ranks fifth amongst thirty high-burden TB countries and fourth-highest in prevalence of multi-drug resistant TB. Despite higher TB rates among men, women disproportionately experience unsuccessful treatment outcomes. The National TB-Control Program despite its contributions has not adequately addressed underlying grassroots factors, particularly those impacting women, that contribute to poor treatment-outcomes. Thus the objective is to explore socio-cultural and grassroots factors influencing treatment non-adherence amongst females living with Pulmonary TB. Methods: A qualitative Phenomenological design was adopted. Twelve in-depth interviews were conducted at a TB Clinic in Karachi (from February to May 2020) with participants including (i) females living with Pulmonary TB and (ii) healthcare providers engaged in TB service-provision. Interviews were semi-structured and conducted in-person. Data was analyzed inductively using thematic analysis. Results: Three themes contributing to treatment non-adherence emerged, which are: A) The burden of home-making with sub-themes of a culture of matriarchy, traditional household norms, and intended non-disclosure of TB status; B) The journey of pursing treatment with subthemes of challenges in accessing diagnostic services, barriers in treatment adherence/continuation, unique treatment-related misconceptions; and C) TB myths with subthemes emphasizing local rumors and an inherent lack of trust in public healthcare services. Conclusion: This study reveals important grassroots, socio-cultural and physical barriers to treatment adherence among women, including gender, social norms and treatment demands. Addressing these requires a holistic approach prioritizing community empowerment with a focus on understanding day-to-day lived experiences of TB and enhancing healthcare provider capacity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".