Knowledge and attitude towards ankle sprain management among primary care physicians in the department of family medicine, King Fahad Armed Forces Hospital, Jeddah, Saudi Arabia
Bibliographic record
Abstract
Introduction: Family doctors are the primary care providers for ankle sprains, which are a prevalent condition that they treat with great care. Family physicians' differing management styles and levels of knowledge about established recommendations may have a substantial influence on patient outcomes. Aims: The current study aimed to assess the level of awareness among family physicians regarding established guidelines for ankle sprain management. Materials and Methods: A cross-sectional study was conducted targeting all available and accessible primary care physicians within the Department of Family Medicine at King Fahad Armed Forces Hospital, Jeddah, Saudi Arabia during the period from 2023 to May 2024. Data were collected using an online questionnaire that was initiated by the study researchers after comprehensive review of similar articles in the literature. Results: A total of 88 primary care physicians were included. Physicians' ages ranged from 25 to 60 years with a mean age of 33.4 ± 7.4 years old. A total of 47 (53.4%) were males, 29 (33%) were residents, 28 (31.8%) were consultants, 16 (18.2%) were senior Registrar, and 9 (10.2%) were GPs. A total of 41 (46.6%) of the study physicians had an overall good knowledge level about ankle sprain while most of them (53.4%) had poor knowledge level. A total of 55 (62.5%) of the study physicians utilize the Ottawa Ankle Rules to guide the need for X-ray imaging in ankle sprains, and 52 (59.1%) routinely provide information on preventive measures to patients diagnosed with an ankle sprain. Conclusion: The study found that primary care physicians have average knowledge about ankle sprains, diagnosis, classification, and treatment, with lower knowledge of follow-up plans. They need training and educational programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 | 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".