Challenges and management of venomous bites and scorpion stings in Lebanon: a qualitative study
Bibliographic record
Abstract
Background: Snakebites and scorpion stings are significant public health issues globally, particularly in the Middle East. This qualitative study investigates the management of these incidents in Lebanon by exploring the perceptions of healthcare providers and public health experts. Methods: Thematic analysis, guided by sociocultural theory, examined qualitative data from 17 interviews with healthcare providers, including emergency physicians, paramedics, pharmaceutical providers, and ministry workers. Transcripts were coded to identify recurring themes related to the management of snakebites and scorpion stings, focusing on availability, accessibility, inequity, healthcare access disparities, and cultural influences on treatment-seeking behavior. Results: The analysis revealed significant disparities in antivenom availability and accessibility, particularly in rural areas and among low socioeconomic groups. Healthcare providers often resorted to illicit channels to secure antivenom due to stock shortages, while victims sometimes relied on traditional treatment methods. The lack of standardized treatment protocols and inadequate clinician training resulted in inconsistent antivenom usage and unsafe practices. The study also highlighted insufficient documentation and reporting mechanisms and inadequate networking among stakeholders, alongside a notable knowledge gap among victims. Conclusion: This study emphasizes the urgent need for targeted interventions to address systemic challenges in managing snakebites and scorpion stings in Lebanon. Collaborative efforts are essential to enhance awareness, improve antivenom access, standardize treatment protocols, and promote effective management practices.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".