Actionable health app evaluation: translating expert frameworks into objective metrics

Abstract As use and availability of mobile health apps have increased, so too has the need for a thorough, accessible framework for app evaluation. The American Psychiatric Association’s app evaluation model has emerged as a way to critically assess an app by considering accessibility, privacy and s...

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Autores principales:	Sarah Lagan, Patrick Aquino, Margaret R. Emerson, Karen Fortuna, Robert Walker, John Torous
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/84c81d972bea497c963e26ad8c7d76b3
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spelling	oai:doaj.org-article:84c81d972bea497c963e26ad8c7d76b32021-12-02T16:31:00ZActionable health app evaluation: translating expert frameworks into objective metrics10.1038/s41746-020-00312-42398-6352https://doaj.org/article/84c81d972bea497c963e26ad8c7d76b32020-07-01T00:00:00Zhttps://doi.org/10.1038/s41746-020-00312-4https://doaj.org/toc/2398-6352Abstract As use and availability of mobile health apps have increased, so too has the need for a thorough, accessible framework for app evaluation. The American Psychiatric Association’s app evaluation model has emerged as a way to critically assess an app by considering accessibility, privacy and security, clinical foundation, engagement, and interoperability; however, there is no centralized database where users can view how various health apps perform when assessed via the APA model. In this perspective, we propose and outline our effort to translate the APA’s model for the evaluation of health apps into a set of objective metrics that can be published online, making the framework actionable and accessible to a broad audience. The questions from the APA model were operationalized into 105 objective questions that are either binary or numeric. These questions serve as the foundation of an online database, where app evaluation consists of answering these 105 questions and can be crowdsourced. While the database has yet to be published and crowdsourced, initial internal testing demonstrated excellent interrater reliability. The database proposed here introduces a public and interactive approach to data collection that is guided by the APA model. The published product enables users to sort through the many mobile health apps and filter them according to individual preferences and priorities, making the ever-growing health app market more navigable.Sarah LaganPatrick AquinoMargaret R. EmersonKaren FortunaRobert WalkerJohn TorousNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 3, Iss 1, Pp 1-8 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Sarah Lagan Patrick Aquino Margaret R. Emerson Karen Fortuna Robert Walker John Torous Actionable health app evaluation: translating expert frameworks into objective metrics
description	Abstract As use and availability of mobile health apps have increased, so too has the need for a thorough, accessible framework for app evaluation. The American Psychiatric Association’s app evaluation model has emerged as a way to critically assess an app by considering accessibility, privacy and security, clinical foundation, engagement, and interoperability; however, there is no centralized database where users can view how various health apps perform when assessed via the APA model. In this perspective, we propose and outline our effort to translate the APA’s model for the evaluation of health apps into a set of objective metrics that can be published online, making the framework actionable and accessible to a broad audience. The questions from the APA model were operationalized into 105 objective questions that are either binary or numeric. These questions serve as the foundation of an online database, where app evaluation consists of answering these 105 questions and can be crowdsourced. While the database has yet to be published and crowdsourced, initial internal testing demonstrated excellent interrater reliability. The database proposed here introduces a public and interactive approach to data collection that is guided by the APA model. The published product enables users to sort through the many mobile health apps and filter them according to individual preferences and priorities, making the ever-growing health app market more navigable.
format	article
author	Sarah Lagan Patrick Aquino Margaret R. Emerson Karen Fortuna Robert Walker John Torous
author_facet	Sarah Lagan Patrick Aquino Margaret R. Emerson Karen Fortuna Robert Walker John Torous
author_sort	Sarah Lagan
title	Actionable health app evaluation: translating expert frameworks into objective metrics
title_short	Actionable health app evaluation: translating expert frameworks into objective metrics
title_full	Actionable health app evaluation: translating expert frameworks into objective metrics
title_fullStr	Actionable health app evaluation: translating expert frameworks into objective metrics
title_full_unstemmed	Actionable health app evaluation: translating expert frameworks into objective metrics
title_sort	actionable health app evaluation: translating expert frameworks into objective metrics
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/84c81d972bea497c963e26ad8c7d76b3
work_keys_str_mv	AT sarahlagan actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT patrickaquino actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT margaretremerson actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT karenfortuna actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT robertwalker actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT johntorous actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics
_version_	1718383885713145856

Actionable health app evaluation: translating expert frameworks into objective metrics

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