ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children

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...

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Detalhes bibliográficos
Autores: Tang, Teresa, Álvaro Llorente, Leticia, Alvarez, James, Maule, John, Skelton, Alice, Franklin, Anna, Bosten, Jenny
Tipo de documento: artigo
Data de publicação:2021
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositório:Docta Complutense
Idioma:inglês
OAI Identifier:oai:docta.ucm.es:20.500.14352/95049
Acesso em linha:https://hdl.handle.net/20.500.14352/95049
Access Level:Acceso aberto
Palavra-chave:Color vision deficiency
Visual development
Mobile health applications
Pediatric
Gamification
Percepción
6106.09 Procesos de Percepción
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spelling ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young childrenTang, TeresaÁlvaro Llorente, LeticiaAlvarez, JamesMaule, JohnSkelton, AliceFranklin, AnnaBosten, JennyColor vision deficiencyVisual developmentMobile health applicationsPediatricGamificationPercepción6106.09 Procesos de PercepciónThere 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.SpringerUniversidad Complutense de Madrid20212021-01-0120212021-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/95049reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/950492026-06-02T12:44:21Z
dc.title.none.fl_str_mv ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
title ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
spellingShingle ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
Tang, Teresa
Color vision deficiency
Visual development
Mobile health applications
Pediatric
Gamification
Percepción
6106.09 Procesos de Percepción
title_short ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
title_full ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
title_fullStr ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
title_full_unstemmed ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
title_sort ColourSpot, a novel gamified tablet-based test for accurate diagnosis of color vision deficiency in young children
dc.creator.none.fl_str_mv Tang, Teresa
Álvaro Llorente, Leticia
Alvarez, James
Maule, John
Skelton, Alice
Franklin, Anna
Bosten, Jenny
author Tang, Teresa
author_facet Tang, Teresa
Álvaro Llorente, Leticia
Alvarez, James
Maule, John
Skelton, Alice
Franklin, Anna
Bosten, Jenny
author_role author
author2 Álvaro Llorente, Leticia
Alvarez, James
Maule, John
Skelton, Alice
Franklin, Anna
Bosten, Jenny
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv Color vision deficiency
Visual development
Mobile health applications
Pediatric
Gamification
Percepción
6106.09 Procesos de Percepción
topic Color vision deficiency
Visual development
Mobile health applications
Pediatric
Gamification
Percepción
6106.09 Procesos de Percepción
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01
2021
2021-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/95049
url https://hdl.handle.net/20.500.14352/95049
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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