Current knowledge and attitudes toward antibiotic use among community pharmacy personnel in a rural province in South Africa and the implications
Bibliographic record
Abstract
Background Antimicrobial resistance (AMR) is an appreciable threat to public health, especially among low- and middle-income countries (LMICs), exacerbated by high levels of inappropriate prescribing and dispensing of antibiotics in these countries. There have been variable levels of dispensing of antibiotics without a prescription among community pharmacies in South Africa. Given the importance of community pharmacies, especially in rural South Africa, there is a need to assess their knowledge and attitudes towards antibiotics, AMR, and antibiotic stewardship. This was the aim of this study. Methods A previously piloted questionnaire was administered to pharmacy personnel currently operating community pharmacies in a rural province in South Africa, where dispensing of antibiotics without a prescription is likely to be greatest. The questionnaire included key knowledge questions regarding antibiotics and AMR, as well as ways to reduce AMR. Community pharmacies were divided into three categories: Independent, chain, and franchise pharmacies. Results A total of 128 pharmacies participated (75.7%), with independent pharmacies representing the majority (60.9%). A total of 313 completed questionnaires were returned (78.3% response rate), including responses from 106 pharmacists (33.9%) and 207 pharmacist assistants (66.1%). Overall, there was very good knowledge among both community pharmacists and pharmacist assistants concerning antibiotics and AMR. However, there was a significant misconception regarding the potential role of antibiotics in relieving pain. Encouragingly, attitudes regarding the risks associated with obtaining antibiotics without a prescription among both community pharmacists and pharmacist assistants were high. There was also strong agreement among both community pharmacists and pharmacist assistants for potential solutions to AMR. Conclusion Overall, the findings showed that most pharmacists and pharmacist assistants in this rural province demonstrated a strong understanding of the effectiveness of antibiotics in bacterial infections and their lack of effectiveness to treat viral infections. They also demonstrated considerable knowledge regarding the risks associated with the inappropriate dispensing of antibiotics without a prescription, as well as ways to address rising AMR rates.
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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 | 0.000 | 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".