Qualitative Assessment of Knowledge, Perception and Experience of Physicians about Antimicrobial Stewardship in Nigeria during COVID-19 Pandemic
Bibliographic record
Abstract
Background: The critical role of antimicrobial stewardship (AMS) in mitigating antimicrobial resistance cannot be overemphasized, especially during COVID-19 pandemic. This study aimed to understand the perception of physicians about AMS as it relates to their training and practice experience. Method: A phenomenological qualitative study design was employed, and data was collected using a semi-structured questionnaire-based interview of a purposive sample of practicing physicians in the federal capital territory of Nigeria. Eighteen physicians completed the interview and responded based on their perceptions and practice experience. Thematic analysis and coding of the data were performed through an iterative process. Results: 56% of the respondents were female physicians, 67% worked in a private hospital/clinic, and 44% have been practicing for 11 – 15 years. 83% of the respondents think auditing clinicians would promote antibiotics stewardship. 44% of the respondents were unaware of clinical guidelines for an empirical antibiotics prescription. 56% felt doctors were not provided thorough training on AMS. The participants suggest that AMS in Nigeria could be promoted through training of personnel, establishing antibiotics policy and protocol, cessation of over-the-counter sales of antibiotics, creating awareness, access to prompt laboratory investigation and inter-professional collaboration between physicians and pharmacists. They also believed inter-professional collaboration is necessary to achieve AMS. Conclusion: Physicians perceived a knowledge gap in AMS as a result of inadequate training and lack of clinical guidelines on antimicrobial stewardship in the healthcare system of Nigeria. Intensive education of healthcare providers and inter-professional collaboration are plausible approaches to improving antibiotic stewardship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".