Cargando…
Actionable health app evaluation: translating expert frameworks into objective metrics
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,...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393366/ https://www.ncbi.nlm.nih.gov/pubmed/32821855 http://dx.doi.org/10.1038/s41746-020-00312-4 |
_version_ | 1783565030484082688 |
---|---|
author | Lagan, Sarah Aquino, Patrick Emerson, Margaret R. Fortuna, Karen Walker, Robert Torous, John |
author_facet | Lagan, Sarah Aquino, Patrick Emerson, Margaret R. Fortuna, Karen Walker, Robert Torous, John |
author_sort | Lagan, Sarah |
collection | PubMed |
description | 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 | Online Article Text |
id | pubmed-7393366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73933662020-08-18 Actionable health app evaluation: translating expert frameworks into objective metrics Lagan, Sarah Aquino, Patrick Emerson, Margaret R. Fortuna, Karen Walker, Robert Torous, John NPJ Digit Med Perspective 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. Nature Publishing Group UK 2020-07-30 /pmc/articles/PMC7393366/ /pubmed/32821855 http://dx.doi.org/10.1038/s41746-020-00312-4 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Perspective Lagan, Sarah Aquino, Patrick Emerson, Margaret R. Fortuna, Karen Walker, Robert Torous, John Actionable health app evaluation: translating expert frameworks into objective metrics |
title | 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_short | Actionable health app evaluation: translating expert frameworks into objective metrics |
title_sort | actionable health app evaluation: translating expert frameworks into objective metrics |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393366/ https://www.ncbi.nlm.nih.gov/pubmed/32821855 http://dx.doi.org/10.1038/s41746-020-00312-4 |
work_keys_str_mv | AT lagansarah actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT aquinopatrick actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT emersonmargaretr actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT fortunakaren actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT walkerrobert actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics AT torousjohn actionablehealthappevaluationtranslatingexpertframeworksintoobjectivemetrics |