What Do Patients Expect of Health Care Providers? Patient Perceptions and Expectations of Professionalism in Optometry Practice in KwaZulu-Natal, South Africa
Bibliographic record
Abstract
BACKGROUND: Professionalism, which includes factors such as attire, hygiene, communication skills, compassion and empathy; has not been previously investigated in the discipline of Optometry and yet is known to be influential in building patient-practitioner relationships. METHODS: This study was conducted at public and private eye care facilities in KwaZulu-Natal (KZN), South Africa. Convenience sampling was used to select 600 participants and data collected with a self-administered questionnaire. Data was analyzed using SPSS version 25. RESULTS: Attire was considered a competency indicator by the majority of participants (70.1%). Practitioners who exercised good hygiene were regarded as being more competent (73.3%). More than half (57.4%) of the respondents perceived an optometrist who wears glasses as more professional and likely to better understand their condition. A practitioner who smelled of cigarette smoke was considered unprofessional (67.3%). The use of simple terms was preferred by 88.5%, while 75.6% respondents felt that an optometrist who introduces themselves and maintained eye contact is more reliable. Most respondents (65%) believed that an optometrist who considers their lifestyle and finance was more trustworthy. CONCLUSIONS: Overall, physical appearance and other factors such as hygienic practices, communication skills and empathy appear to be important contributors to patient perspectives of professionalism in optometrists. Health care practitioners would therefore do well to consider these factors and soft skills in advancing the public’s perception of them and apply them to routine practice to build trust with patients.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".