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)

Main Article Content

Anjali Ahuja
Usman Memon

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 Learning
Curve-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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1.
Ahuja A, Memon U. 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). JCLRS [Internet]. 2024 Oct. 30 [cited 2024 Nov. 21];8(1):e47-e58. Available from: https://jclrs.org/index.php/JCLRS/article/view/63
Section
Original Article
Author Biography

Anjali Ahuja, Professional Service Executive, Menicon India Private Limited

Anjali Ahuja is a dedicated Optometrist with an extensive experience across clinical, corporate, and academic settings. As a Professional Service Executive at Menicon India Pvt, Ltd., she leads impactful training initiatives for eye care professionals, collaborating with key educators to deliver high-quality education across India. Anjali’s background includes establishing a Specialty Contact Lens Clinic at OCCURA Eyecare Hospital and developing training programs for optometrists and sales staff at R. Kumar Opticians in Ahmedabad, Gujarat, India. Her expertise in clinical care and education is complemented by her research contributions, presentations at industry conferences, and numerous certifications, underscoring her commitment to advancing optometry.

References

1. Ezekiel D. Gas permeable haptic lenses. J Br Contact Lens Assoc 1983;6(4):3. https://doi.org/10.1016/S0141-7037(83)80064-0.

2. Davis R, Eiden SB. Specialty lens designs for “normal” eyes: What to do when stock lenses don’t fit your patients’ comfort or visual performance needs. Contact Lens Spectrum 2015;30:22–27. https://clspectrum.com/issues/2015/february/specialty-lens-designs-for-8220normal8221-eyes/

3. Harthan J, Shorter E, Nau C, et al.: Scleral lens fitting and assessment strategies. Contact Lens Ant Eye 2019;42(1): 9–14. 10.1016/j.clae.2018.10.020

4. Kumar P, Carrasquillo KG, Chaudhary S and Basu S. A multi-parameter grading system for optimal fitting of scleral contact lenses [version 2; peer review: 2 approved] F1000Research 2022, 11:6 https://doi.org/10.12688/f1000research.74638.2 First published: 05 Jan 2022, 11:6 https://doi.org/10.12688/f1000research.74638.1

5. Rute J. Macedo-de-Araújo et al (2019). Practitioner Learning Curve in Fitting Scleral Lenses in Irregular and Regular Corneas Using a Fitting Trial.BioMed Research International Volume 2019, Article ID 5737124, 11 pages https://doi.org/10.1155/2019/5737124

6. Ericsson KA, Nandagopal K, Roring RW. Toward a science of exceptional achievement: attaining superior performance through deliberate practice. Ann N Y Acad Sci. 2009 Aug;1172:199-217. [PubMed]

7. McGaghie W,Wayne D, et al. Deliberate practice and mastery learning contributions to medical education and improved healthcare. J Expertise 2021;4(2):2021. ISSN 2573-2773 https://www.journalofexpertise.org/articles/volume4_issue2/JoE_4_2_McGaghie_etal.html

8. Verhaeghe C, El Hachem H, Inchboard L. et al. Assessment of operator performance during oocyte retrievals: residents’ learning curve and continuous monitoring of senior physicians. BMC Med Educ202l 21:193. https://doi.org/10.1186/s12909-021-02615-w

9. Schunk DH. Self-efficacy and cognitive skill learning. In C. Ames & R. Ames (Eds.), Research on Motivation In Education: Vol. 3. Goals and Cognitions (pp. 13-44).San Diego:Academic; 1989. https://libres.uncg.edu/ir/uncg/f/D_Schunk_Self_1991.pdf

10. Wamg HE, Reitz SR, HostlerD, and Yealy DM. Defining the learning curve for paramedic student endotracheal intubation. Prehospital Emerg Care 2005;9(2):156–162. https://doi.org/10.1080/10903120590924645

11. Artino Jr. AR. Academic self-efficacy: from educational theory to instructional practice. Perspect Med Edu. 2012;1(2):76-85. DOI: https://doi.org/10.1007/S40037-012-0012-5

12. Ericsson, K Anders. Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Academ Med 2004;79(10):S70-S81. Academic Medicine (lww.com)

13. Terry K. Koo, Mae Y. Li. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. National University of Health Sciences. 1556-3707/© 2016 http://dx.doi.org/10.1016/j.jcm.2016.02.012

14. Dessolle L, Freour T, Barriere P, Jean M, Ravel C et al. How soon can I be proficient in embryo transfer? Lessons from the cumulative summation test for learning curve (LC-CUSUM). Human Reproduction 2010; 25(2):380–386, https://doi.org/10.1093/humrep/dep391

15. Papanna R, Biau DJ, Mann LK, Johnson A, Moise KJJ. Use of the Learning Curve-Cumulative Summation test for quantitative and individualised assessment of competency of a surgical procedure in obstetrics and gynecology: fetoscopic laser ablation as a model. Am J Obstet Gynecol 2011;204:218.e1–218.e9. 10.1016/j.ajog.2010.10.910

16. Biau DJ, Williams SM, Schlup MM, Nizard RS, Porcher R. Quantitative and individualised assessment of the learning curve using LC-CUSUM. Br J Surg 2008;95(7):925–929, https://doi.org/10.1002/bjs.6056

17. Arzola C, Carvalho JCA, Cubillos J, et al. Anesthesiologists’ learning curves for bedside qualitative ultrasound assessment of gastric content: a cohort study. Can J Anesth/J Can Anesth 2013;60:771–779. https://doi.org/10.1007/s12630-013-9974-y

18. Brydges R, Butler D. A reflective analysis of medical education research on self-regulation in learning and practice. Med Educ 2012;46:71–79. https://doi.org/10.1111/j.1365-2923.2011.04100.x

19. Son LK, Sethi R. Adaptive learning and the allocation of time. Adaptive Behavior. 2010;18(2):132-140. doi:10.1177/1059712309344776

20. Quirk M. Metacognitive capabilities. In: Quirk ME, ed. Intuition and Metacognition in Medical Education. 1st ed. New York, NY: Springer; 2006:23–35. https://msmu.primo.exlibrisgroup.com/permalink/01MSMC_INST/1016ua1/alma991007803388408321

21. Kornell N, and Metcalfe J. Study efficacy and the region of proximal learning framework. J Experi Psychol: Learn, Mem, Cognit 2006;32(3):609–622. https://doi.org/10.1037/0278-7393.32.3.609

22. Dweck CS, Chiu C, Hong Y. Implicit theories and their role in judgments and reactions: A word from two perspectives. Psychol Inq 1995;6:267–285. https://core.ac.uk/download/pdf/37883398.pdf

23. Rush BR, Biller DS, Davis EG, Higginbotham ML, Klocke E et al. Web-based documentation of clinical skills to assess the competency of veterinary students. J Vet Med Educ 2011;38(3):242–250. https://doi.org/10.3138/jvme.38.3.242

24. Campbell RD, Hecker KG, Biau DJ, Pang DSJ. Student Attainment of Proficiency in a Clinical Skill: The Assessment of Individual Learning Curves. PLoS ONE 2014;9(2): e88526. https://doi.org/10.1371/journal.pone.0088526

25. LIM TO, SORAYA A, DING LM, MORAD Z. Assessing doctors’ competence: application of CUSUM technique in monitoring doctors’ performance, International J Quality Health Care 2002;14(3):251–258. https://doi.org/10.1093/oxfordjournals.intqhc.a002616