Assessment of Hand Hygiene Knowledge, Attitude, and Practice Among Health Sciences Students in Herat, Afghanistan: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Hand hygiene (HH) is a fundamental practice in preventing hospital-acquired infections (HAIs), yet compliance among healthcare workers, including students, remains suboptimal. This study assesses the knowledge, attitude, and practice (KAP) related to HH among final-year health sciences students in Herat, Afghanistan. Methods: A convenience-based cross-sectional study was conducted in October to December 2023 at public and private health sciences institutions in Herat, using a structured questionnaire to assess KAP on HH. A sample of 427 participated. Data analysis in SPSS 27 included descriptive statistics, chi-square tests, and logistic regression. Results: The overall accuracy of responses was 84.61% (IQR: 76.92, 84.61), reflecting a strong level of awareness. Attitudes toward HH were also largely positive, with a correct rate of 81.25% (IQR: 75.00, 85.41). Additionally, self-reported adherence to proper HH practices was notably high at 92.85% (IQR: 85.71, 98.21). Students assigned to the emergency ward (23.6%) demonstrated significantly higher knowledge compared to those in other wards (p = 0.016). Logistic regression further confirmed that work setting played a crucial role, with students in the internal ward exhibiting significantly higher knowledge levels than their peers (95% CI: 1.001-4.448) (p = 0.050). The study objectives were met, revealing that final-year students possessed strong knowledge, positive attitudes, and high adherence to HH practices. However, the work environment was a key determinant of knowledge variation across wards. Conclusion: Despite high awareness and adherence, misconceptions and barriers to compliance exist. Strengthening educational interventions, institutional policies, and real-time monitoring is crucial to ensuring sustained HH practices among future 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".