Varför ”icke-farmakologisk förskrivning av antibiotika?” : Fenomenologisk undersökning av allmänläkares attityder och åsikter
Bibliographic record
Abstract
BACKGROUND: Concern has increased worldwide with regard to the over-prescribing of antibiotics, as well as the fact that more bacteria strains are developing resistance to antibiotics. According to research, a great deal of this use is for what has been called “non-pharmacological” reasons. The reduction of unnecessary antibiotic use and exploration of the reasons for ”irrational prescribing” has become a public health priority. OBJECTIVE: To study the reasons cited by Icelandic general practitioners for their “non-pharmacological” prescribing of antibiotics. DESIGN: A qualitative interview-study with research dialogues guided by the Vancouver School of doing phenomenology. SETTING: General practice. PARTICIPANTS: 16 general practitioners: 11 in the maximum variety sample and 5 in the theoretical sample. RESULTS: The most important reasons for prescribing antibiotics in situations with low pharmacological indications (non-pharmacological prescribing) were an unstable doctor-patient relationship due to lack of continuity of care, patient pressure in a stress-loaded society, the doctor’s personal characteristics, particularly zeal and readiness to serve, and finally, the insecurity and uncertainty of the doctor who falls back upon the prescription as a coping strategy in a difficult situation. CONCLUSION:The causes of non-pharmacological prescribing of antibiotics are highly varied, and relational factors in the interplay between the doctor and the patient are often a key factor. Therefore, it is of great importance for the general practitioner to know the patient and to become better equipped to resist patient pressure, in order to avoid the need to use the prescription as a coping strategy. Continuity of medical care and a stable doctor-patient relationship may be seen as the core concepts in this study and the most important task for the GPs is to promote the patients’ trust.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".