Contact lens education for the practitioners of the future
Bibliographic record
Abstract
The World Health Organization has identified a shortage of trained human resources as one of the greatest challenges to increasing the availability of eye care services and reducing preventable visual impairment around the world. Increased prevalence of myopia and new strategies for myopia management have raised the prospect of various interventions, including contact lenses for therapeutic use as well as for refractive correction. More personnel skilled in contact lens fitting will be needed to address potential worldwide demand for these interventions. This review investigates the current status and future requirements of global contact lens education in light of these developments. The COVD-19 pandemic led educational institutions worldwide to move towards online delivery. An online survey among 546 educators, conducted in May 2020, investigated changes to contact lens education delivery before and after the onset of the pandemic. A total of 214 responses were received from 32 countries. Prior to COVID-19 restrictions, 23% of educators had conducted more than 50% of their total teaching online; however, 69% expected to conduct more than half of their teaching online by the end of 2020 and 12% anticipated 90% or more of their teaching would be online. Some 76% of educators expected to provide more online lectures after the pandemic and 63% anticipated new methods to deliver practical education. Around half were planning to introduce new teaching online platforms (54%) and more online assessment methods (53%). The global need for increasing numbers of skilled personnel points to a crucial role for educators in teaching the contact lens practitioners of the future. Contact lens education delivery was already evolving prior to COVID-19, and changes that are currently occurring may lead to permanent differences in the way contact lenses are taught in future. The International Association of Contact Lens Educators (IACLE) provides educators with a standardised global curriculum, online resources and teaching technology that could also serve as a model for wider ophthalmic education in future.
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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 | 0.008 |
| 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 | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".