Bibliographic record
Abstract
Introduction: Osteosynthesis materials (OSM) are raising concerns among patients and medical staff, influencing attitudes and practices related to their use. Research in sociology and anthropology on these materials is limited, justifying a study of the knowledge, attitudes, and practices (KAP) of users of the surgical department at the Regional Hospital Center (CHR) of Dédougou (Burkina Faso).Methods: This is a descriptive cross-sectional mixed-methods study. A sample of 310 users was selected for the administration of a digital questionnaire. Semi-structured interviews with 51 individuals explored detailed perceptions and experiences concerning osteosynthesis materials (OSM). The data were analyzed using QDA Miner, with strict adherence to ethical principles.Results: The majority of users (63%) had heard of OSM, mainly from informal sources, but only 53% understood its advantages and disadvantages. Attitudes were predominantly positive, with 82% willing to use OSM if necessary, although 18% expressed reluctance due to high costs and cultural prejudices. Nearly 29% of users had experienced a fracture, with 50% having been offered OSM. Effective communication between caregivers and patients is crucial to improving the understanding and acceptance of OSM.Conclusion: The study highlights the need to strengthen communication and education strategies for better understanding of OSM. Efforts should include policies to make OSM financially accessible, integrate cultural concerns into care planning, and improve the training of healthcare professionals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.282 | 0.093 |
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".