| Literature DB >> 28096708 |
Gregory Gilmour1, James McKivigan2.
Abstract
INTRODUCTION: Historically, testing medical students' skills using a handheld ophthalmoscope has been difficult to do objectively. Many programs train students using plastic models of the eye which are a very limited fidelity simulator of a real human eye. This makes it difficult to be sure that actual proficiency is attained given the differences between the various models and actual patients. The purpose of this article is to introduce a method of testing where a medical student must match a patient with his/her fundus photo, ensuring objective evaluation as well as developing skills on real patients which are more likely to transfer into clinical practice directly. PRESENTATION OF CASE: Fundus photos from standardized patients (SPs) were obtained using a retinal camera and placed into a grid using proprietary software. Medical students were then asked to examine a SP and attempt to match the patient to his/her fundus photo in the grid.Entities:
Keywords: computer-based testing; education; physical exam; software based; standardized patient
Year: 2016 PMID: 28096708 PMCID: PMC5207205 DOI: 10.2147/AMEP.S119440
Source DB: PubMed Journal: Adv Med Educ Pract ISSN: 1179-7258
Figure 1A selection of nine randomized photos from 16 standardized patients were laid out on a grid and numbered with a random letter-combination.
Participants’ responses to survey questions
| Age (years) | Year of training | Ophthalmology elective | Gender | Confidence | Time (seconds) | Answered correctly |
|---|---|---|---|---|---|---|
| 28 | 3 | No | Female | 25% | 120 | No |
| 24 | 3 | No | Male | 50% | 219 | No |
| 25 | 3 | No | Male | 75% | 80 | No |
| 24 | 3 | No | Male | 50% | 65 | No |
| 25 | 3 | No | Male | 25% | 224 | No |
| 27 | 3 | No | Male | 50% | 60 | No |
| 27 | 3 | No | Female | 25% | 110 | No |
| 37 | 3 | No | Male | 50% | 173 | No |
| 25 | 3 | No | Female | 25% | 115 | No |
| 26 | 3 | No | Male | 25% | 67 | No |
| 26 | 3 | No | Female | 50% | 110 | No |
| 26 | 3 | No | Male | 25% | 183 | No |
| 27 | 4 | Yes | Female | 25% | 62 | No |
| 31 | 4 | No | Male | 0% | 120 | No |
| 24 | 3 | No | Male | 25% | 108 | No |
| 28 | 4 | No | Male | 50% | 196 | No |
| 24 | 3 | No | Female | 50% | 87 | No |
| 28 | 4 | Yes | Female | 25% | 115 | No |
| 29 | 3 | No | Male | 50% | 95 | No |
| 25 | 3 | No | Male | 25% | 163 | No |
| 29 | 3 | No | Female | 50% | 200 | No |
| 26 | 3 | No | Male | 25% | 48 | No |
Note: Students who selected the correct photo are emphasized with bolded text.
Figure 2Clicking on a photo could deselect it to remove it from consideration.
Multiple regression of variables against correct photo selection
| Variables | Coefficients | Standard error | |
|---|---|---|---|
| Intercept | −0.0499 | 0.791 | 0.950 |
| Age | 0.037 | 0.015 | 0.023 |
| Year of training | −0.239 | 0.283 | 0.406 |
| Ophthalmology elective | 0.032 | 0.457 | 0.944 |
| Gender | −0.09 | 0.186 | 0.630 |
| Confidence | −0.004 | 0.003 | 0.216 |
| Time | 0.001 | 0.001 | 0.160 |
Note:
Significant p-value (p<0.05).
Correlation matrix of age, year of medical school, gender, confidence, time, and correct selection
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
|---|---|---|---|---|---|---|---|
| 1. Age | 1 | ||||||
| 2. Year | 0.332 | 1 | |||||
| 3. Elective | −0.041 | 0.537 | 1 | ||||
| 4. Gender | −0.144 | 0.021 | 0.382 | 1 | |||
| 5. Confidence | 0.099 | −0.005 | −0.104 | −0.192 | 1 | ||
| 6. Time | 0.174 | 0.250 | −0.191 | −0.195 | −0.129 | 1 | |
| 7. Correct | 0.409 | 0.021 | −0.174 | −0.163 | −0.192 | 0.343 | 1 |