Perception and preferences of the doctors from the Health Centers towards the use of antibiotics in Prishtina, Kosovo
Bibliographic record
Abstract
Background: Resistance to antibiotics is a global public health problem with economic, social and political implications, especially in underdeveloped countries. Over the last few years, this challenge has been of particular importance at the global level seriously endangering the effective treatment of many diseases. Purpose: The purpose of this study is to assess the level of use of antibiotics and practices followed by Pristina primary doctors in Kosovo and to educate and educate as many as possible the population of Pristina regarding the use of antibiotics in order to ensure the quality of their lives. Method: A survey was conducted with a random sampling, attended by about 120 doctors of KPSH to indicate whether they have antibiotics with whom they are familiar, as well as antibiotic access and preference, which is the same regardless of the type of specialization staff at the KPSH. Participants were recruited into one of the 12 Main Family Medicine Centers (KPSH) in Prishtina for the period June - July - August 2017. Results: Of the 120 doctors surveyed at KPSH, on the question of whether you have antibiotics with whom you are familiar with, more than half (55%) do not have any favorite antibiotics, while 40% of them have some antibiotics with whom they are familiar. Though 6 (8.1%) of family doctors have reported that they are familiar with many of the antibiotics, there is no significant difference between Chi-square = 4.76; Df = 4; p = 0.313 after testing. About a quarter of the respondents describe antibiotics without antibiograms, and over half of them sometimes and only 10.8% do not prescribe antibiotics without antibiograms, regardless of the type of specialization of staff at SPC. Patient advise on side effects has been performed by most doctors of SCC and only 5 doctors or 4.2% do not give advice to their patients for side effects, but without significant difference depending on the type of specialization. Over 80% of respondents in their daily practice have encountered a known case of resistance to any antibiotic, but without significant difference depending on the type of specialization
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".