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Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps

BACKGROUND: There are over 165,000 mHealth apps currently available to patients, but few have undergone an external quality review. Furthermore, no standardized review method exists, and little has been done to examine the consistency of the evaluation systems themselves. OBJECTIVE: We sought to det...

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Autores principales: Powell, Adam C, Torous, John, Chan, Steven, Raynor, Geoffrey Stephen, Shwarts, Erik, Shanahan, Meghan, Landman, Adam B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766362/
https://www.ncbi.nlm.nih.gov/pubmed/26863986
http://dx.doi.org/10.2196/mhealth.5176
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author Powell, Adam C
Torous, John
Chan, Steven
Raynor, Geoffrey Stephen
Shwarts, Erik
Shanahan, Meghan
Landman, Adam B
author_facet Powell, Adam C
Torous, John
Chan, Steven
Raynor, Geoffrey Stephen
Shwarts, Erik
Shanahan, Meghan
Landman, Adam B
author_sort Powell, Adam C
collection PubMed
description BACKGROUND: There are over 165,000 mHealth apps currently available to patients, but few have undergone an external quality review. Furthermore, no standardized review method exists, and little has been done to examine the consistency of the evaluation systems themselves. OBJECTIVE: We sought to determine which measures for evaluating the quality of mHealth apps have the greatest interrater reliability. METHODS: We identified 22 measures for evaluating the quality of apps from the literature. A panel of 6 reviewers reviewed the top 10 depression apps and 10 smoking cessation apps from the Apple iTunes App Store on these measures. Krippendorff’s alpha was calculated for each of the measures and reported by app category and in aggregate. RESULTS: The measure for interactiveness and feedback was found to have the greatest overall interrater reliability (alpha=.69). Presence of password protection (alpha=.65), whether the app was uploaded by a health care agency (alpha=.63), the number of consumer ratings (alpha=.59), and several other measures had moderate interrater reliability (alphas>.5). There was the least agreement over whether apps had errors or performance issues (alpha=.15), stated advertising policies (alpha=.16), and were easy to use (alpha=.18). There were substantial differences in the interrater reliabilities of a number of measures when they were applied to depression versus smoking apps. CONCLUSIONS: We found wide variation in the interrater reliability of measures used to evaluate apps, and some measures are more robust across categories of apps than others. The measures with the highest degree of interrater reliability tended to be those that involved the least rater discretion. Clinical quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability. Subsequent research is needed to determine consistent means for evaluating the performance of apps. Patients and clinicians should consider conducting their own assessments of apps, in conjunction with evaluating information from reviews.
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spelling pubmed-47663622016-03-14 Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps Powell, Adam C Torous, John Chan, Steven Raynor, Geoffrey Stephen Shwarts, Erik Shanahan, Meghan Landman, Adam B JMIR Mhealth Uhealth Original Paper BACKGROUND: There are over 165,000 mHealth apps currently available to patients, but few have undergone an external quality review. Furthermore, no standardized review method exists, and little has been done to examine the consistency of the evaluation systems themselves. OBJECTIVE: We sought to determine which measures for evaluating the quality of mHealth apps have the greatest interrater reliability. METHODS: We identified 22 measures for evaluating the quality of apps from the literature. A panel of 6 reviewers reviewed the top 10 depression apps and 10 smoking cessation apps from the Apple iTunes App Store on these measures. Krippendorff’s alpha was calculated for each of the measures and reported by app category and in aggregate. RESULTS: The measure for interactiveness and feedback was found to have the greatest overall interrater reliability (alpha=.69). Presence of password protection (alpha=.65), whether the app was uploaded by a health care agency (alpha=.63), the number of consumer ratings (alpha=.59), and several other measures had moderate interrater reliability (alphas>.5). There was the least agreement over whether apps had errors or performance issues (alpha=.15), stated advertising policies (alpha=.16), and were easy to use (alpha=.18). There were substantial differences in the interrater reliabilities of a number of measures when they were applied to depression versus smoking apps. CONCLUSIONS: We found wide variation in the interrater reliability of measures used to evaluate apps, and some measures are more robust across categories of apps than others. The measures with the highest degree of interrater reliability tended to be those that involved the least rater discretion. Clinical quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability. Subsequent research is needed to determine consistent means for evaluating the performance of apps. Patients and clinicians should consider conducting their own assessments of apps, in conjunction with evaluating information from reviews. JMIR Publications Inc. 2016-02-10 /pmc/articles/PMC4766362/ /pubmed/26863986 http://dx.doi.org/10.2196/mhealth.5176 Text en ©Adam C Powell, John Torous, Steven Chan, Geoffrey Stephen Raynor, Erik Shwarts, Meghan Shanahan, Adam B Landman. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 10.02.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Powell, Adam C
Torous, John
Chan, Steven
Raynor, Geoffrey Stephen
Shwarts, Erik
Shanahan, Meghan
Landman, Adam B
Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps
title Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps
title_full Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps
title_fullStr Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps
title_full_unstemmed Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps
title_short Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps
title_sort interrater reliability of mhealth app rating measures: analysis of top depression and smoking cessation apps
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766362/
https://www.ncbi.nlm.nih.gov/pubmed/26863986
http://dx.doi.org/10.2196/mhealth.5176
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