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Test refinement. Within-subject (test-retest) measurement variability, as a function of N trials for the (b) Faces test and (c) Search Test. Coefficients of Repeatability were derived using Bland-Altman analysis, as detailed in Figure 5, below. Panel (a) shows the target locations (blue circles) associated with each Search grid.
Source publication
Purpose:
To describe, refine, evaluate, and provide normative control data for two freely available tablet-based tests of real-world visual function, using a cohort of young, normally-sighted adults.
Methods:
Fifty young (18-40 years), normally-sighted adults completed tablet-based assessments of (1) face discrimination and (2) visual search. Ea...
Contexts in source publication
Context 1
... test was intentionally run for longer than piloting indicated was necessary. To determine how many trials were actually required to obtain stable estimates of performance, we examined how test-retest variability (the 95% Coefficient of Repeatability; CoR) varied as a function of test duration/number of trials (Figure 2). For Faces, this involved simply analysing the first N trials (i.e., since the adaptive algorithm provides an updated, maximum-likelihood estimate of discrimination ability after every trial). ...
Context 2
... Faces, this involved simply analysing the first N trials (i.e., since the adaptive algorithm provides an updated, maximum-likelihood estimate of discrimination ability after every trial). For Search, data were analysed from progressively more sparse subsets of spatially-distributed locations, as shown in Figure 2a. ...
Citations
... Compared to conventual paper-and-pencil or PC-based testing, touchscreen tablet/iPad tests have advantages such as better standardization, more objective measurement, easier and quicker administration, greater availability for clients, cheaper costs, and immediate scoring and use of test results (Bennett et al., 2020;Bignardi et al., 2020;Jenkins et al., 2016;Jones et al., 2020). Additionally, interacting with a tablet may increase children's interest in testing, which can lead to their better performance than on conventional paper tests (Trifunović et al., 2022). ...
As predictive motor control is an important index of neuromotor development and maturation, we developed two touchscreen tablet-based tests of this function. Our aim was to investigate the reliability and validity of both a rapid manual interception test and a pursuit tracking test, using a sample of 124 children (62 boys and 62 girls) from two age groups (7-8-year-oldss and 9–10-year-olds). Participants performed both tablet tests with a stylus (sample rate 100 Hz) with both a visible and a temporarily invisible moving target. Confirmatory factor analyses and omega coefficients showed that both tests were univariate methods that provided a reliable assessment of the latent factor related to predictive visuomotor control. As would be expected, compared to younger children, older children performed better on both manual interception and pursuit tracking. The correlations between the latent factors of the two tests at 95% confidence intervals (−.276, −.608) suggested shared variance. Thus, the touchscreen-tablet based tests of rapid manual interception and manual pursuit tracking appear psychometrically suitable for assessing the neuromotor ability of predictive control in 7-10-year-old children.
... Looking for something (visual search) is a ubiquitous everyday activity. Visual search is important to people and we have previously shown this can be measured on a computer-based task [5,6]. For example, we have previously demonstrated that people with AMD, certainly those with advanced disease, have measurable difficulties beyond those observed in visually healthy peers on a computer-based visual search task [5]. ...
... In turn we believe they would make an enjoyable and useful addition to clinics, especially if the tests themselves could be performed on portable devices like a tablet computer. We have evaluated the use of the visual search task on a tablet-based platform and the preliminary assessment indicated that it provided a simple, quick and easy-to-administer measure of real-world visual function in healthy volunteers [6]. Our study has indicated that these tasks can be used in people with AMD and older adults. ...
... Our study has indicated that these tasks can be used in people with AMD and older adults. The potential applications include their use in clinic waiting rooms, and as an objective complement to PROMs, especially in a clinical trial setting [6]. Furthermore, a low-contrast or scotopic version of our assessments may provide better discrimination between visually healthy controls and people with AMD. ...
Purpose
To test the hypothesis that the performance in novel computer-based tasks of everyday visual function worsens with disease severity in people with non-neovascular age-related macular degeneration.
Methods
Participants with and without non-neovascular age-related macular degeneration (≥60 years, minimum logMAR binocular visual acuity 0.7) performed a series of standard visual function tests and two novel computer-based tasks. In a visual search task, participants had to locate an image of a single real-world object within an array of 49 distractor images. Next, in a series of simulated dynamic driving scenes, participants were asked to identify one or two approaching real-world road signs and then select these road signs from four options. Outcome measures were median response times and total correct responses.
Results
Forty-nine participants had no macular disease (n = 11), early/intermediate age-related macular degeneration (n = 16) or geographic atrophy (n = 22). Groups were age-similar with median (interquartile range) logMAR visual acuity of 0.00 (-0.08,0.12), 0.13 (-0.08,0.70) and 0.32 (0.12,0.70) respectively. Median (interquartile range) visual search response times were 1.9 (1.0,2.4), 1.8 (1.1,3.7) and 2.4 (1.2,6.0) seconds respectively. Median (interquartile range) road sign response times (single road signs) were 1.2 (0.4,1.7), 1.5 (0.9,2.8) and 1.8 (1.0,5.5) seconds respectively. Median (interquartile range) road sign response times (double road signs) were 1.7 (0.7,2.4), 2.3 (1.2,3.1) and 2.5 (1.7,6) seconds respectively. Participants with geographic atrophy recorded slower response times in all tasks and over 50% performed outside the normative limit for task performance. There were no significant differences between groups in total correct responses across all tasks.
Conclusions
In a novel computer-based assessment, people with increasing severity of age-related macular degeneration take longer to perform visual search of everyday objects and take longer to identify road signs than those with no age-related macular degeneration. These novel assessments could be useful as patient-relevant, secondary outcomes for clinical trials.
Purpose
(1) To assess the feasibility of conducting tablet‐based vision tests in hospital clinic waiting areas; (2) To test the hypothesis that increasing severity of diabetic macular oedema (DME) is associated with the performance of tablet‐based surrogates of everyday tasks and self‐reported visual function.
Methods
Sixty‐one people with mild ( n = 28), moderate ( n = 24) or severe ( n = 9) DME performed two tablet‐based tests of ‘real‐world’ visual function ( visual search and face recognition ) while waiting for appointments in a hospital outpatient clinic. Participants also completed a tablet‐based version of a seven‐item, visual‐functioning (VF‐7) patient‐reported outcome measure. Test performance was compared to previously published 99% normative limits for normally sighted individuals.
Results
Thirty‐four participants (56%; 95% confidence interval [CI] 43%–68%) exceeded normative limits for visual search, while eight (13%; 95% CI 65%–24%) exceeded normative limits for face discrimination. Search duration was significantly longer for people with severe DME than those with mild and moderate DME ( p = 0.01). Face discrimination performance was not significantly associated with DME severity. VF‐7 scores were statistically similar across DME severity groups. Median time to complete all elements (eligibility screening, both tablet‐based tasks and the VF‐7) was 22 (quartiles 19, 25) min. Further, 98% and 87% of participants, respectively, reported the search task and face discrimination task to be enjoyable, while 25% and 97%, respectively, reported finding the two tasks to be difficult.
Conclusions
Portable tablet‐based tests are quick, acceptable to patients and feasible to be performed in a clinic waiting area with minimal supervision. They have the potential to be piloted in patients' homes for self‐monitoring.
Peekaboo Vision is an iPad grating acuity app built with typically developing children in mind. Given the ease of using this app in the pediatric age group, this study determined its clinical utility in children with Down syndrome. Two groups of participants (children with Down syndrome and age-matched controls) were included. Presenting binocular grating acuity was measured using Peekaboo Vision and Teller acuity cards II in random order. Parents' feedback about their child's engagement and time taken to complete each test was documented. Thirty-seven children with Down syndrome (males = 23; mean age = 8.1 ± 4.2 years) and 28 controls (males = 15; mean age = 8.71 ± 3.84 years) participated. Time taken to complete the tests was comparable (p = 0.83) in children with Down syndrome. Controls were significantly faster with Peekaboo Vision (p = 0.01). Mean logMAR acuities obtained with Peekaboo Vision (0.16 ± 0.34) and Teller acuity cards II (0.63 ± 0.34) were significantly different (p < 0.001) in children with Down syndrome (mean difference in acuities: -0.44 ± 0.38 logMAR (95% LoA: -1.18 to 0.3). For controls, the mean logMAR acuity with Peekaboo Vision (-0.13 ± 0.12) and Teller acuity cards II (0.12 ± 0.09) was also found to be significantly different (p < 0.001) (mean difference in acuities: -0.24 ± 0.14 logMAR (95% LoA: -0.51 to 0.03) Peekaboo Vision test can be used on children with Down syndrome. Peekaboo Vision and Teller acuity cards II can be used independently but not interchangeably. The differences in the acuity values between the two tests could be a result of the differences in the thresholding paradigms, different testing mediums and the range of acuities covered.
