Perceptions of Occupational Risk and Adherence to Tuberculosis Prevention Among Health Care Workers: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) is a major public health problem around the world. Health care workers (HCWs) are at a much higher risk of contracting TB because they are often working around sick people in clinical settings. Even though HCWs play a key role in controlling TB, we still do not fully understand how they see this risk and how it affects their willingness to follow preventive measures. OBJECTIVE: This study aims to examine the existing body of knowledge on HCWs' perceived risks of TB and how these perceptions impact their adherence to TB prevention measures. The results of this scoping review will identify gaps in the current literature that should inform policy and practice and guide future research studies to optimize TB prevention among HCWs. METHODS: This scoping review will be conducted following the framework proposed by Arksey and O'Malley, incorporating the recent advancements. This approach involves 6 key stages: identifying the research question; identifying relevant studies; selecting studies; charting the data; collating, summarizing, and reporting the results; and consulting with stakeholders. RESULTS: As of June 2024, 1345 records were identified (1234 from databases and 111 from other sources), and 667 duplicates were removed. The remaining 678 records were screened by title and abstract, with 216 progressing to full-text review. After applying the eligibility criteria, 42 studies were included in the final analysis. Screening and full-text assessments were conducted between September and October 2024. Data extraction and thematic analysis were performed in winter 2024. The final data synthesis stage is expected to be completed by 2025. CONCLUSIONS: HCWs' perceptions of risk have a considerable effect on how well they follow TB prevention measures such as using personal protective equipment and undergoing health screenings. Lack of resources, lack of training, and the stigma around TB are some of the main barriers to TB prevention adherence. The thematic analysis showed that adherence levels were different depending on the support offered by the institution and the TB knowledge level and perception of each HCW. Although TB treatment has become more effective, nosocomial infections are still a big concern, especially in low- and middle-income countries like Indonesia, where HCWs are more likely to have latent TB infections. This review shows how important it is for HCWs to understand how TB prevention behaviors work. To improve HCW adherence, the gaps in institutional support, stigma, and training must be filled. Future interventions should be based on the specific problems found in low- and middle-income countries. This will make health care safer for everyone around the world. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64037.
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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 | 0.086 | 0.076 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.066 | 0.011 |
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".