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

BackgroundThere 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....

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Main Authors: Powell, Adam C, Torous, John, Chan, Steven, Raynor, Geoffrey Stephen, Shwarts, Erik, Shanahan, Meghan, Landman, Adam B
Format: Article
Language:English
Published: JMIR Publications 2016-02-01
Series:JMIR mHealth and uHealth
Online Access:http://mhealth.jmir.org/2016/1/e15/
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spelling doaj-9ddb059489174280bdbaa3e8af495e4c2021-05-03T01:40:28ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222016-02-0141e1510.2196/mhealth.5176Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation AppsPowell, Adam CTorous, JohnChan, StevenRaynor, Geoffrey StephenShwarts, ErikShanahan, MeghanLandman, Adam B BackgroundThere 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. ObjectiveWe sought to determine which measures for evaluating the quality of mHealth apps have the greatest interrater reliability. MethodsWe 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. ResultsThe 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. ConclusionsWe 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.http://mhealth.jmir.org/2016/1/e15/
collection DOAJ
language English
format Article
sources DOAJ
author Powell, Adam C
Torous, John
Chan, Steven
Raynor, Geoffrey Stephen
Shwarts, Erik
Shanahan, Meghan
Landman, Adam B
spellingShingle 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
JMIR mHealth and uHealth
author_facet Powell, Adam C
Torous, John
Chan, Steven
Raynor, Geoffrey Stephen
Shwarts, Erik
Shanahan, Meghan
Landman, Adam B
author_sort Powell, Adam C
title 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_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_sort interrater reliability of mhealth app rating measures: analysis of top depression and smoking cessation apps
publisher JMIR Publications
series JMIR mHealth and uHealth
issn 2291-5222
publishDate 2016-02-01
description BackgroundThere 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. ObjectiveWe sought to determine which measures for evaluating the quality of mHealth apps have the greatest interrater reliability. MethodsWe 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. ResultsThe 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. ConclusionsWe 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.
url http://mhealth.jmir.org/2016/1/e15/
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