An assessment of the knowledge of medical students about lymphedema – a survey-based study
Bibliographic record
Abstract
Introduction: Lymphoedema is a dysfunction of the lymphatic system and a chronic disease.Knowledge about lymphedema is crucial for avoiding risk factors and for early recognition of the first lymphoedema signs.In the study, the authors assess both the knowledge and attitude towards lymphoedema among medical students of the Medical University of Silesia in Katowice.This study aimed to discuss the importance of spreading knowledge about lymphoedema. Material and methods:The study assessed the knowledge of medical students about lymphoedema by using a dedicated questionnaire.The survey study was conducted from February 2022 to April 2022 and included medical students from the Medical University of Silesia in Katowice.Results: The questionnaire was completed by 138 medical students in years 1-6.Most students (48.2%) stated that their knowledge was average, and a significant number of students claimed that they had never heard about lymphoedema during their university classes.Statistical analysis revealed that subjective assessment of knowledge and college level were dependent on each other, but there was no correlation with the objective assessment.The results showed that there was no relationship between gender and calculated body mass index (BMI) with either subjective or objective evaluation of knowledge about lymphoedema themed.Conclusions: Knowledge about lymphoedema among the study participants is insufficient.Appropriate education of medical students is essential, which is crucial for early recognition of the first signs of lymphoedema among students and their future patients.Females and individuals with high BMI with higher risk of developing lymphoedema do not have greater awareness about lymphoedema, which can delay its recognition and early treatment.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".