Antibiotic resistance: is knowledge the only driver for awareness and appropriate use of antibiotics?
Bibliographic record
Abstract
BACKGROUND: The fight against antibiotic resistance (AR) is nowadays a world priority. Antibiotic resistance is largely associated with the overuse of antibiotics and a lack of awareness of the problem. Considering the large use of antibiotics in the paediatric age, the aim of this study was to investigate the knowledge and perception of antibiotic resistance in a sample of parents. METHODS: A cross-sectional study was conducted on a sample of parents of children aged 0-14. Data on antibiotic use and awareness of antibiotic resistance were collected by a self-administrated questionnaire. The potential predictors of the antibiotic resistance awareness were evaluated using a multivariate logistic regression model. RESULTS: The questionnaire was completed by 610 parents of which 91% (n=553) used antibiotics for their children. Summarizing the answers related to antibiotic resistance knowledge and perception, 36% of parents gave a correct answers to at least 9 of 12 questions. Fever seemed to represent a reason of anxiety in parents. Using a 10-point scale, the perceived anxiety by parents was measured based on a situation when the child wakes up in the morning with a fever at 38°C and the doctor suggests to wait at least 48 hours before administering the antibiotic. Almost half of parents (49%) indicated a low degree of anxiety (1-4), 31% medium (5-6), and 20% high (7-10). Multivariate analysis showed that a good level of education, healthcare occupation and low grade of anxiety are associated with antibiotic resistance awareness. CONCLUSIONS: The awareness of antibiotic resistance is not strong. The study highlights the need to put effort on tailored education programs aimed to improve knowledge of antibiotic resistance and guide mainly anxious parents to appropriate management of disease of their children.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".