The Relationship between Doctor and Patient as an Indicator of the Level of Trust in Medical Care
Bibliographic record
Abstract
Communication between the doctor and the patient is one of the most important elements affecting the treatment process. The trust, which determines the patients’ health attitude and their implementation of medical recommendations, is built by maintaining an appropriate doctor-patient relationship. A trusting patients demonstrate better mental and physical well-being, obtain better diagnostic results, use preventive healthcare services more frequently, and show greater confidence in the overall health system. Nevertheless, in order for the patients to exhibit such behaviors, they must trust the physician, which is influenced by many important issues: the maintenance an appropriate doctor-patient relationship, the patients’ hope, the prevailing opinion about the physician as well as stereotypes about the medical profession (including age, gender, professional experience, professional and scientific title). This paper presents different models of the doctor-patient relationship and how each of them affects the level of trust in the discussed relationship. In addition, it is described how stereotypes about medical personnel influence the trust among patients. All information included in the study are based on the available literature.
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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 | 0.005 | 0.042 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".