ABSTRACT
Purpose: According to the US Census 2019 Income and Poverty report, 10.5% of the population lives below the poverty line, and approximately 10.5 million individuals below 18 years were in poverty in 2019. Children and adolescents in poverty are at risk for poor developmental and psychosocial outcomes, presenting a significant financial burden for families and the general public. Yet low-income populations continue to face barriers to healthcare, leaving them vulnerable to worse health outcomes. Unfortunately, medical students may adopt unfavorable attitudes toward low-income patients due to lack of empathy, poor understanding, and burnout, which negatively affects patient care. A poverty simulation module was included in the medical student curriculum at our institution to improve understanding and empathy toward low-income patients. Methods: IRB approval was obtained prior to data collection. Participants included medical students in one US medical school from 2018 to 2021. In 2021, students participated virtually due to the COVID-19 pandemic, though the objectives and methods remained the same as in person. Participants were placed in a poverty simulation, roleplaying as one of 26 different families facing poverty across four, 15-minute weeks with limited resources and additional social and medical challenges. Students completed a pre-simulation and post-simulation survey with free response and 23-items questioning perceptions of socioeconomic barriers (Perceptions), confidence in handling low-income populations (Confidence), and likelihood of addressing poverty (Likelihood). Each category was scored on a numeric scale that was summed together. The difference in scores between pre- and post-simulation survey responses was measured for significance using Wilcoxon and paired t-tests. The virtual simulation scores of 2021 were also compared with in-person scores from 2018 to 2020. Student free responses were then categorized into 10 topics and measured for variation with standard t-tests. Results: The post-simulation survey results showed increased scores from 2018 through 2021 with an average difference of +1.21 for Perceptions, +1.29 for Confidence, +3.27 for Likelihood. Only Confidence and Likelihood score increases were found to be significant with p-values ranging from 3.66E-17 to 9.95E-05 across all years (p < 0.05). The Perceptions category showed no significant difference from 2018-2020, except 2021 which showed a p-value of 1.26E-04 (p < 0.05). For in-person versus virtual simulation, there was a significant difference in average sum difference across all categories of 7.31 and Z score of <0.0001 (p <0.0001). Students’ free responses commonly focused on the difficulty of budgeting in poverty with no significant variation between years (p < 0.05). Conclusions: A significant improvement was seen in confidence when treating low-income populations and likelihood of addressing poverty in several iterations of a poverty simulation among medical students. This study is limited by variance in student responses, issues with pre- and post-simulation survey matching, and response restriction to numbered scales as opposed to free response. The results of this project encourage the continuation of this simulation among medical students and its expansion to other health professional programs. Sources of Support: ELS Staff at University of Southern Florida Morsani College of Medicine.
ABSTRACT
Purpose : One of the most important clinical data points in evaluating ophthalmology patients is visual acuity (VA). During the COVID-19 pandemic, eye health providers are utilizing telehealth to decrease patient and provider risk related to in-person clinic visits, while still providing high-quality care. This study sought to compare at-home VA tests with in-office clinical VA measurements to determine the validity of at-home VA testing for telehealth visits. Methods : Patients from 1 comprehensive and 3 subspecialty ophthalmology clinics had VA greater than or equal to 20/200 in the study eye. The patients were prospectively randomized to perform 2 of 3 at-home VA tests (printed chart - University of Arizona/Banner Eye Care Letter Distance Chart;mobile phone app - Verana Vision Test;website test - Farsight.care) within 3 days of their standard of care clinic visit. Patients also completed a survey to assess usability of home tests. At the clinic visit, best corrected Snellen distance acuity was measured to serve as the reference standard. Results : Of the 44 patients (84 eyes) enrolled, 60% were female and the mean age was 66 years (range 22 to 80). The mean difference between printed chart and Snellen, website test and Snellen, and mobile app and Snellen acuity data was 0.10 (95% CI: 0.09-0.11), 0.13 (95% CI: 0.12-0.14), and 0.12 (95% CI: 0.11-0.13) LogMAR, respectively. The highest degree of correlation was between the website and Snellen tests (0.74, 95% CI: 0.59-0.84) (Table 1). Patients found the tests easy to perform at home and were neutral regarding confidence in their results and desire to continue with home testing. In the survey, there was no significant difference for between the 3 tests regarding any of the 4 questions (P = 0.32- 0.62), although there was a trend toward a more positive response with the printed chart (Table 2). Conclusions : These data suggest that some at-home visual acuity tests are comparable in accuracy to in-clinic Snellen visual acuity tests (within 1 line of difference). Patient surveys indicated the tests were easy to understand and complete at home. Further development and validation of at-home vision testing modalities are needed to provide accurate and accessible tele-ophthalmology care.