Treating latent tuberculosis infection (LTBI) with isoniazid and rifapentine (3HP) in an inner-city population with psychosocial barriers to treatment adherence: A qualitative descriptive study
Bibliographic record
Abstract
In Canada, preventive therapy for latent tuberculosis infection (LTBI) has required multiple doses of medication over an extended period of time. Such regimens are associated with poor adherence and completion rates. A shortened treatment regimen of once weekly isoniazid plus rifapentine for 3 months (3HP), is now available, and holds promise in populations facing challenges to treatment adherence. Although many factors impact treatment adherence, a knowledge gap exists in describing these factors in the context of this regimen. We present findings from a qualitative descriptive study, involving semi-structured interviews with unstably housed or homeless individuals in Edmonton and Fort McMurray, Alberta, Canada who were offered directly-observed preventive therapy (DOPT) with 3HP, and their health care providers. Latent content analysis revealed incomplete understandings of LTBI and about the need for preventive therapy. Clients' motivation to be healthy, alongside education, health care outreach, relationships developed in the context of DOPT, ease of treatment regimen, incentives, and collaboration were all described as supporting treatment completion. Competing priorities, difficulty in reaching clients, undesirable aspects of the regimen and difficulties obtaining and initiating 3HP were identified as barriers. Perceptions of stigma related to LTBI and TB were described by clients in addition to feelings of shame related to their diagnosis. Our study provides insight into LTBI and indicates that multiple interacting psychosocial factors influence preventive therapy access, uptake, and adherence. Findings from this study of both client and provider perspectives can be used to inform and address inequities among individuals experiencing homelessness, and ultimately contribute to a diminished reservoir of LTBI.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".