Face and Content Validity of an Artificial Eye Model for Secondary IOL Fixation
Bibliographic record
Abstract
Purpose: To evaluate the face and content validity of the use of artificial eye models (SimulEYE Iris Suturing & IOL model, InsEYEt, Westlake Village, CA) in training physicians the techniques required for secondary intraocular lens (IOL) fixation.Secondary IOL fixation, or secondary IOL implantation, is a common yet technically challenging skill useful in the treatment of primary IOL implantation failure, zonular instability, or aphakia related to trauma or surgery. Materials and Methods: Twenty-eight ophthalmologists at the 2019 Canadian Ophthalmology Society annual meeting underwent a secondary IOL fixation wet-lab using artificial eye models. The technique was scleral suturing of a single piece IOL with via 4 closed-loop haptics. All of the ophthalmologists were given an 18-response survey immediately following the training session which were composed of statements which addressed the face and content validity of the artificial eyes. Responses were recorded on a 5-point Likert-type scale ranging from (5) strongly agree to (1) strongly disagree. Mann-Whitney U analysis compared instructor versus non-instructor and expert versus non-expert respondent responses.Results: Respondents rated all statements regarding the model with a median response of 3 (Neither Agree or Disagree) to 5 (Strongly Agree).Mann-Whitney U analysis did not show a significant difference in responses for expert versus non-expert and instructor vs non-instructor respondents for any of the survey statements.The artificial eye received highest ratings for its usefulness for training residents, ease of set-up and clean-up compared to cadaveric models and how using the model is a better way to learn the procedure than discussion or observation and will likely result in future surgical success.The lowest survey ratings were for the model's realism when compared to human cadaveric models.Conclusions: The artificial eye model was generally regarded highly by ophthalmologists with all levels of experience performing secondary IOL fixation.These results suggest that this artificial eye may be a valuable tool for teaching secondary IOL fixation in competency-based ophthalmology education programs.
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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 | 0.026 | 0.114 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".