ArticleBehavior research methods2022
ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children.
Article in Behavior research methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 23 citations in OpenAlex.
- A comparative analysis of an AI-assisted virtual reality platform with technician-based examination for visual field, visual acuity, and color vision in neuro-ophthalmology.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Rapid test for detecting red-green color vision deficiencies using a neural network-assisted color-naming task.Scientific reports · 2026Article
- Novel color vision assessment tool: AIM color detection and discrimination.Journal of translational medicine · 2025Article
- A Global Perspective of Color Vision Deficiency: Awareness, Diagnosis, and Lived Experiences.Healthcare (Basel, Switzerland) · 2025Review
- Gamification in Mobile Apps for Children With Disabilities: Scoping Review.JMIR serious games · 2024Article
- Effects of visual diet on colour discrimination and preference.Proceedings. Biological sciences · 2024Article
- Assessment of visual function using mobile Apps.Eye (London, England) · 2024Review
- Rapid measurement and machine learning classification of colour vision deficiency.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2023Article
- Chromatic and spatial image statistics predict infants' visual preferences and adults' aesthetic preferences for art.Journal of vision · 2023Article
- Rapid measurement and machine learning classification of color vision deficiency.medRxiv : the preprint server for health sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a need for a straightforward, accessible and accurate pediatric test for color vision deficiency (CVD). We present and evaluate ColourSpot, a self-administered, gamified and color calibrated tablet-based app, which diagnoses CVD from age 4. Children tap colored targets with saturations that are altered adaptively along the three dichromatic confusion lines. Two cohorts (Total, N = 772; Discovery, N = 236; Validation, N = 536) of 4-7-year-old boys were screened using the Ishihara test for Unlettered Persons and the Neitz Test of Color Vision. ColourSpot was evaluated by testing any child who made an error on the Ishihara Unlettered test alongside a randomly selected control group who made no errors. Psychometric functions were fit to the data and "threshold ratios" were calculated as the ratio of tritan to protan or deutan thresholds. Based on the threshold ratios derived using an optimal fitting procedure that best categorized children in the discovery cohort, ColourSpot showed a sensitivity of 1.00 and a specificity of 0.97 for classifying CVD against the Ishihara Unlettered in the independent validation cohort. ColourSpot was also able to categorize individuals with ambiguous results on the Ishihara Unlettered. Compared to the Ishihara Unlettered, the Neitz Test generated an unacceptably high level of false positives. ColourSpot is an accurate test for CVD, which could be used by anyone to diagnose CVD in children from the start of their education. ColourSpot could also have a wider impact: its interface could be adapted for measuring other aspects of children's visual performance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.