Criteria for assessing the quality of mHealth apps: a systematic review

Nouri, Rasool; Kalhori, Sharareh R. Niakan; Ghazisaeedi, Marjan; Marchand, Guillaume; Yasini, Mobin

doi:10.1093/jamia/ocy050

Cited by 202 publications

(186 citation statements)

References 45 publications

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“…A recent review on criteria of assessing the quality of mHealth (mobile health) apps concluded: ‘There will never be a complete and perfect mHealth app assessment criteria because these criteria must apply to apps that are changing in development continuously’ 20. A Canadian-based effort that gathered diverse mental health stakeholders, including patients, noted that they were not able to find a single scale or framework that adequately addressed their needs 21.…”

Section: Discussionmentioning

confidence: 99%

Understanding the quality, effectiveness and attributes of top-rated smartphone health apps

Wisniewski

Liu

Henson

et al. 2019

Evid Based Mental Health

109

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ObjectiveThis study aimed to understand the attributes of popular apps for mental health and comorbid medical conditions, and how these qualities relate to consumer ratings, app quality and classification by the WHO health app classification framework.MethodsWe selected the 10 apps from the Apple iTunes store and the US Android Google Play store on 20 July 2018 from six disease states: depression, anxiety, schizophrenia, addiction, diabetes and hypertension. Each app was downloaded by two authors who provided information on the apps’ attributes, functionality, interventions, popularity, scientific backing and WHO app classification rating.ResultsA total of 120 apps were examined. Although none of these apps had Food and Drug Administration marketing approval, nearly 50% made claims that appeared medical. Most apps offered a similar type of services with 87.5% assigned WHO classification 1.4.2 ‘self-monitoring of health or diagnostic data by a client’ or 1.6.1 ‘client look-up of health information’. The ‘last updated’ attribute was highly correlated with a quality rating of the app although no apps features (eg, uses Global Positioning System, reminders and so on) were.ConclusionDue to the heterogeneity of the apps, we were unable to define a core set of features that would accurately assess app quality. The number of apps making unsupported claims combined with the number of apps offering questionable content warrants a cautious approach by both patients and clinicians in selecting safe and effective ones.Clinical Implications‘Days since last updated’ offers a useful and easy clinical screening test for health apps, regardless of the condition being examined.

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Section: Discussionmentioning

confidence: 99%

Understanding the quality, effectiveness and attributes of top-rated smartphone health apps

Wisniewski

Liu

Henson

et al. 2019

Evid Based Mental Health

109

View full text Add to dashboard Cite

show abstract

“…However, they only provide the crawled app store information and not calculated results. Regarding the second category, summaries that can be used as a very good starting point can be found in [22]- [24] or works that address particular aspects [25]- [27] or the development of rating tools [28], [29]. Furthermore, works can be found that deal with the userfriendly development of mHealth apps, thus increasing their quality by design [30]- [32].…”

Section: Related Workmentioning

confidence: 99%

Mobile Health App Database - A Repository for Quality Ratings of mHealth Apps

Stach

Probst

Meßner

et al. 2020

2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)

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The utilization of mobile technology in the field of medicine and healthcare has become a decisive aspect. The entire field is denoted as mobile health (mHealth). For mHealth, the development and use of mobile applications are crucial. The purposes and goals of mHealth apps, in turn, are manifold. As a consequence, a plethora of mHealth apps can be found in the app stores. Interestingly, for patients, users, and health care providers that consider to use mHealth apps one aspect has been less pursued so far: Systematic and standardized ways that help about the quality of an app or its medical evidence are mainly missing. The Mobile App Rating Scale (MARS) is a standardized instrument that aims at the systematic and comparable evaluation of the quality of mobile health apps as well as categorizing their goals and functions. It comprises 23 items, which are utilized to calculate a rating scale. Having MARS in mind, a database was developed that is called Mobile Health App Database (MHAD). The latter offers technical features to systematically utilize the MARS for researchers as well as clinicians and end-users that (i) want to evaluate apps as well as (ii) want an interactive and easy-to-use web interface that shows the results of the rating procedure. MHAD comprises a rating platform that supports the conduction of MARS ratings and their release process. With the information platform, a web application was developed that prepares the data stored in the rating platform for being freely viewed and studied by users, patients, and health care providers. The goal of MHAD constitutes to be an open science repository that encourages researchers to release their MARS ratings to a broader audience. Such repositories become more and more important in many fields, especially in the field of mHealth.

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“…A recent systematic review identified 23 different published criteria for assessment of mHealth apps. 38 Furthermore, many apps popular with patients are not seen as high quality by clinicians. 32,39 It is important that medical professional societies and clinicians who recommend apps often engage patients in the decision-making process.…”

Section: How Can Clinicians Support Patients In Obtaining Value From mentioning

confidence: 99%

What is the clinical value of mHealth for patients?

et al. 2020

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Despite growing interest from both patients and healthcare providers, there is little clinical guidance on how mobile apps should be utilized to add value to patient care. We categorize apps according to their functionality (e.g. preventative behavior change, digital self-management of a specific condition, diagnostic) and discuss evidence for effectiveness from published systematic reviews and meta-analyses and the relevance to patient care. We discuss the limitations of the current literature describing clinical outcomes from mHealth apps, what FDA clearance means now (510(k)/de novo FDA clearance) and in the future. We discuss data security and privacy as a major concern for patients when using mHealth apps. Patients are often not involved in the development of mobile health guidelines, and professionals' views regarding high-quality health apps may not reflect patients' views. We discuss efforts to develop guidelines for the development of safe and effective mHealth apps in the US and elsewhere and the role of independent app reviews sites in identifying mHealth apps for patient care. There are only a small number of clinical scenarios where published evidence suggests that mHealth apps may improve patient outcomes.

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Criteria for assessing the quality of mHealth apps: a systematic review

Abstract: There is a wide heterogeneity in assessment criteria for mHealth apps. It is necessary to define the exact meanings and degree of distinctness of each criterion. This will help to improve the existing tools and may lead to achieve a better comprehensive mHealth app assessment tool.

Cited by 202 publications

References 45 publications

Understanding the quality, effectiveness and attributes of top-rated smartphone health apps

Understanding the quality, effectiveness and attributes of top-rated smartphone health apps

Mobile Health App Database - A Repository for Quality Ratings of mHealth Apps

What is the clinical value of mHealth for patients?

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