Impact of WHO AWaRe Antibiotic Handbook training on antibiotics prescribing knowledge among primary care providers: A vignette-based, pre-post pilot study in Patna, India
Bibliographic record
Abstract
Abstract Introduction Inappropriate antibiotic prescribing is a major concern in low– and middle-income countries (LMICs), particularly at the primary care level. The WHO AWaRe Antibiotic Handbook was introduced to promote rational antibiotic use, yet its real-world feasibility and potential impact remain underexplored. Our study evaluated the effectiveness and usefulness of the WHO AWaRe Handbook training among primary care providers (PCPs) in Patna, India. Methods We conducted a pre-post interventional study among 145 PCPs (40 formal providers (FPs) and 105 informal providers (IPs), 98% male) in Patna, India. Participants received training from an infectious disease physician on the WHO AWaRe Antibiotic Handbook. Antibiotic prescribing knowledge was assessed before and after the intervention using clinical vignettes for four conditions: acute diarrhea, urinary tract infection (UTI), cellulitis, and community-acquired pneumonia (CAP). An endline survey evaluated the perceived usefulness of the training. Changes in prescribing were analyzed using McNemar’s test for paired data. Results The intervention significantly reduced overall antibiotic prescribing for acute diarrhea (p=0.0003) and UTI (p=0.0113), with greater reductions among IPs. No significant changes were observed for cellulitis (p=0.3692) or CAP (p=0.7150). Watch-category antibiotic prescribing significantly decreased for acute diarrhea (p<0.0001), with no significant changes for other conditions. IPs showed greater improvements overall compared to FPs. The majority of providers (75%; n=107) rated the training as moderately or very useful. Conclusion Training PCPs using the WHO AWaRe Handbook improved antibiotic prescribing knowledge for some common conditions, particularly among IPs. Future research should focus on the impact of ongoing training, tailored interventions, and long-term follow-up. Strengths and limitations of this study – This is the first study to evaluate the effectiveness of WHO AWaRe Handbook training on improving antibiotic prescribing knowledge among primary care providers in India, focusing on both formal and informal healthcare providers. – Using a vignette-based, pre-post study design allowed for standardized assessment of prescribing knowledge across four common clinical conditions: acute diarrhea, cellulitis, pneumonia, and urinary tract infection. – Stratified analysis by provider type offered important insights into the intervention’s differential effects, particularly highlighting knowledge improvements among informal providers. – While the study captures shifts in prescribing knowledge, it does not assess actual prescribing behavior in clinical practice, which may limit the generalizability of the findings. – The study evaluated outcomes over a short follow-up period, which restricts understanding of the sustainability of training effects over time.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".