THE PATIENT-PHYSICIAN RELATIONSHIP AND ROLE OF EMPATHIC COMMUNICATION IN CONTACT LENS PRACTICE
Bibliographic record
Abstract
Purpose: To assess the relationship between eye care practitioners and contact lens patients and todetermine how empathy is associated with patients’ overall satisfaction. Methods: Multilingual electronic surveys shared by email and on social media in patients’ and practitioners’ groups. Ratings were converted to a numerical scale. The scores were compared using Wilcoxon rank sum tests. Results: The survey had 804 responses: 68.4% were over 46 years old, and 58.1% were female. Only 770 reported the type of contact lens worn. Of all patients, 10.6% would not recommend their physician due to feeling excluded from decisions (55.3%), lack of personal interest (63.5%), no written recommendations (84%), and unmet expectations (77%). Scleral lens wearers were highly satisfied. Optometrists excelled in care, ratings, relationships, communication, symptom relief, and prevention. Discussion: The findings highlight the importance of empathy in eye care and its impact on patient experiences. Factors such as contact lens type, physician recommendation, and physician type can influence the level of empathy perceived by patients. Satisfaction varied based on contact lens type, with soft and scleral lens wearers reporting better experiences. Patients valued physicians who listened, explained treatments, showed empathy, and had patient-centered communication and open-ended questions. Optometrists were scored higher than ophthalmologists in several aspects. Conclusion: Patients, especially scleral lens patients, were generally satisfied with the services and care. Optometrists scored higher than ophthalmologists. Patients would not recommend their physicians mainly because of a lack of empathy.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.007 | 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".