EVALUATING THE LEARNING CURVE OF A NOVICE OPTOMETRY STUDENT IN SCLERAL LENS FITTING: A PROSPECTIVE QUANTITATIVE STUDY USING DELIBERATE PRACTICE AND CUMULATIVE SUMMATION (LC-CUSUM)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background and Objective: To evaluate the learning curve of a novice optometry student in scleral lens fitting through deliberate practice and to objectively quantify the learning process using the LearningCurve-Cumulative Summation (LC-CUSUM) test, ensuring accurate and unbiased results. Method: The complexity of scleral contact lens fittings was assessed by categorizing subjects into regular and irregular cornea groups. A student enrolled in the Master of Optometry program conducted the fittings using a dedicated scleral lens record form (rubrics) designed to quantify the lens management approach. Prior to performing fittings independently, the student received four weeks of training from a contact lens expert, who also served as her guide for the study. This training period and the subsequent fittings were structured based on the principles of deliberate practice, with the student performing repeated diagnostic trials. A maximum of three diagnostic trials were performed for each subject to achieve the optimal fit. After each trial, the student completed a self-efficacy scale questionnaire to assess her perceived diffi-culty and clinical judgement skills, recording “FIRST trial scores” following the initial trial and ‘LAST trial scores’ after achieving the optimal fit. The guide consistently provided verbal feedback after each case throughout the fitting process as part of the deliberate practice methodology to enhance the student’s understanding of the fitting procedure while keeping the scores confidential to ensure unbiased self-as-sessment. Following the complete supervision of the fitting procedure, the guide evaluated the student’s clinical skills using a specially designed observation scale questionnaire, referred to as the ‘GUIDE scores.’ A seven-point Likert scale was used to rate the judgement for both the self-efficacy scale and observation scale questionnaire. The student’s LAST trial scores were subsequently compared with the GUIDE scores. Results: A total of 80 scleral lens fittings were evaluated. The Intraclass Correlation Coefficient (ICC) demonstrated excellent agreement between student-reported self-efficacy scores and guide-reported observation scores. The difference in self-efficacy scores between the initial and final lens fittings was statistically significant (p < 0.05), as determined by the Wilcoxon signed-rank test. The Learning Curve-Cumulative Summation (LC-CUSUM) chart revealed that learning stabilized after 26 fittings, marking a consolidation phase where minimal further improvement was observed beyond this point, and additional practice primarily helped to maintain proficiency. The average number of trials required per eye was higher in patients with irregular corneas than those with regular corneas. Conclusion: This study evaluated the learning curve of a novice optometry student in scleral lens fitting through deliberate practice, utilizing the LC-CUSUM test to quantify progress and assess skill acquisition objectively. Proficiency was achieved after 26 fittings, with additional trials needed for irregular corneas, underscoring the influence of patient characteristics on learning. These findings emphasize the importance of structured training, personalized feedback, and self-assessment in developing clinical competence. The insights contribute to advancing education and research in contact lens science by providing practical guid-ance for designing effective programs focused on planning, teaching, and learning about scleral lens fittings.
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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 | 0.031 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it