Patterns of antibiotic use, knowledge, and perceptions among different population categories: A comprehensive study based in Arabic countries
Bibliographic record
Abstract
Background: Antibiotics are essential for the treatment of bacterial infections and are considered among the most commonly sold drug classes from the community pharmacy in the developing countries without a prescription in most cases. Purpose: This study aims to explore the knowledge, practices, and attitudes regarding antibiotic use. Materials and methods: This study employs a cross-sectional descriptive design that used a pre-validated survey. The participants were classified into three main mutually exclusive groups: healthcare professionals, medical students, and other adults in the community. Results: Of the 10,226 participants, 1157 (11%) were healthcare professionals; 2322 (23%) were medical students and 6747 (66%) were other adults in community. The majority of participants used antibiotic at least once during the past year. A total of 838 (72.4%) healthcare professionals and 800 (34.5%) medical students had prescribed an antibiotic during the last 6 months.Almost half of the medical students and adults in the community and almost one-third of healthcare professionals reported that the aim of antibiotics use is for fever. Furthermore, around one-quarter of participants reported that the aim of antibiotics use is for viral infection. Around one-quarter of respondents stated that the antibiotic will always be effective in the treatment of the same infection in the future. Around one-quarter of participants stated that 21 to 50% of antibiotics are considered to be unnecessary or inappropriate prescriptions. Different factors were perceived as being very important causes of antibiotic resistance among the participants. Conclusions: These findings indicated that this study participants showed unsatisfactory knowledge and perceptions of proper antibiotic use. Therefore, there is a requirement for a comprehensive and effective antibiotic-stewardship program to promote rational antibiotics use, and compensate for knowledge and perceptions gaps to prevent antibiotic resistance development.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".