Barriers to effective communication between family physicians and pa-tients in Georgia
Bibliographic record
Abstract
Search, G -Funds CollectionBackground.Effective doctor-patient communication is one of the most significant parts of medicine since it has a huge influence on the outcome of treatment, patient satisfaction and quality of health care.Objectives.The purpose of the research was to identify the main barriers to effective communication between patients and family physicians.Material and methods.Quantitative, cross-sectional studies were conducted.230 patients and 36 family physicians participated in the study. Results.The study showed that the main barriers to doctor-patient communication were limited time during consultation (35.2%), the extensive amount of information being delivered by the family physicians (31%), patients mispresenting their health problems (77.8%),insufficient meeting time (72.2%),inconsistent information being delivered by the patients (47.2%), patients complying with the treatment strategy (38.9%) and patients having difficulty in understanding the outcomes of the diagnosis (33.3%). Conclusions.Active communication between family physicians and patients stimulates patients' motivation and self-confidence, which has a positive impact on their treatment.Patients would like to have doctors who can conduct effective communication, diagnose the disease correctly and treat it successfully.Family physicians must pay attention to patients' social and personal problems.Particular attention should be paid to effective communication with patients whose involvement in treatment is low.In this regard, it is necessary to undertake various measures to enhance communication between the family physician and the patient.
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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 | 0.009 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".