MULTIDISCIPLINARY APPROACH TO PREVENTION OF CHILDREN'S EYE HEALTH IN OPHTHALMOLOGICAL PRACTICE
Bibliographic record
Abstract
Children's eye health is a prerequisite for normal development and good quality of life of the child. In our country, preventive activities for children's eye health are regulated and delegated to general practitioners and pediatricians. Activities are limited and not up to date with the European directives. In recent years, after the opening of new specialties at the Medical University of Varna, the range of eye health specialists (ophthalmologists, ophthalmological nurses, medical opticians and optometrists), which can collaborate in a multidisciplinary team and facilitate comprehensive prevention measures. The purpose of the work is to study and analyze the readiness of ophthalmologists to conduct the prevention activities in a multidisciplinary team at regional level. Methods include: documentary, sociological and statistical. An empirical sociological study was conducted using a direct, individual, anonymous questionnaire for the period January - June 2019 in the region of Varna, Bulgaria. During the study 53 ophthalmologists were approached. Results: For the half of the ophthalmologists (53.5%) the prevention of children's eye health should be the professional activity of various specialists united in a multidisciplinary team. The majority of respondents (65.1%) believe that other specialists (ophthalmological nurses, medical opticians and optometrists) should be involved in all team activities, and a quarter of them (25.6%) still prefer the traditional model – results registration and doctor‘s assistance. Most of the ophthalmologists (93%) trust the results of the activities of other specialists in the team if they are familiar with their professional skills and competence. According to ophthalmologists, there are three main barriers for the preventive measures: limited preventive activities of the NHIF, lack of financial resources on annual basis and a declining number of medical specialists working with children. Conclusions: Ophthalmologists have a positive attitude towards team activities and appreciate the multidisciplinary team approach for prevention related to eye health in young age. The ophthalmopediatric specialists include not only ophthalmologists, but also ophthalmological nurses, medical opticians and optometrists. Integrating the professional competence of different eye health specialists in the field of prevention will contribute to improved access to ophthalmic care and better perspective for children‘s eye health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".