Evidence-based medicine among Jordanian family physicians
Bibliographic record
Abstract
OBJECTIVE To assess family practitioners’ attitudes toward and awareness of evidence-based medicine (EBM). DESIGN A cross-sectional study from a questionnaire distributed between January and March 2007. SETTING Rural and urban family medicine centres throughout Jordan that are affiliated with the Ministry of Health, military centres, university medical centres, and the private sector. PARTICIPANTS Two hundred family physicians. MAIN OUTCOME MEASURES Family physicians’ attitudes toward EBM; training in EBM; barriers to practising EBM; level of awareness of and access to EBM journals and databases; and knowledge and understanding of related technical terms. RESULTS The response rate was 70.5%. Among those who responded, 56.7% were women and 42.6% were between the ages of 40 and 49 years. More than 50% of the respondents were working in mixed urban and rural practice settings. Most of the respondents had a positive attitude toward EBM: 63.5% welcomed the concept of EBM; more than 40% used EBM in their daily practices; and 90% agreed that practising EBM improved patient care. Of the respondents, 42.6% thought that the best way to move from opinion-based medicine to EBM was through learning the skills of EBM. Fifty percent of the respondents had access to MEDLINE, while only 20.4% of them had received formal training in research and critical appraisal. Lack of personal time was the main perceived barrier to practising EBM. Participants reported a low level of awareness of some of the technical terms. CONCLUSION Jordanian family physicians showed eagerness to learn and implement EBM in their daily practices. Nevertheless, they need more guidance and training to ensure the correct application of EBM ideals.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Research integrity | 0.000 | 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".