Mobile Health Applications for the Most Prevalent Conditions by the World Health Organization: Review and Analysis

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Abstract

Background

New possibilities for mHealth have arisen by means of the latest advances in mobile communications and technologies. With more than 1 billion smartphones and 100 million tablets around the world, these devices can be a valuable tool in health care management. Every aid for health care is welcome and necessary as shown by the more than 50 million estimated deaths caused by illnesses or health conditions in 2008. Some of these conditions have additional importance depending on their prevalence.

Objective

To study the existing applications for mobile devices exclusively dedicated to the eight most prevalent health conditions by the latest update (2004) of the Global Burden of Disease (GBD) of the World Health Organization (WHO): iron-deficiency anemia, hearing loss, migraine, low vision, asthma, diabetes mellitus, osteoarthritis (OA), and unipolar depressive disorders.

Methods

Two reviews have been carried out. The first one is a review of mobile applications in published articles retrieved from the following systems: IEEE Xplore, Scopus, ScienceDirect, Web of Knowledge, and PubMed. The second review is carried out by searching the most important commercial app stores: Google play, iTunes, BlackBerry World, Windows Phone Apps+Games, and Nokia's Ovi store. Finally, two applications for each condition, one for each review, were selected for an in-depth analysis.

Results

Search queries up to April 2013 located 247 papers and more than 3673 apps related to the most prevalent conditions. The conditions in descending order by the number of applications found in literature are diabetes, asthma, depression, hearing loss, low vision, OA, anemia, and migraine. However when ordered by the number of commercial apps found, the list is diabetes, depression, migraine, asthma, low vision, hearing loss, OA, and anemia. Excluding OA from the former list, the four most prevalent conditions have fewer apps and research than the final four. Several results are extracted from the in-depth analysis: most of the apps are designed for monitoring, assisting, or informing about the condition. Typically an Internet connection is not required, and most of the apps are aimed for the general public and for nonclinical use. The preferred type of data visualization is text followed by charts and pictures. Assistive and monitoring apps are shown to be frequently used, whereas informative and educational apps are only occasionally used.

Conclusions

Distribution of work on mobile applications is not equal for the eight most prevalent conditions. Whereas some conditions such as diabetes and depression have an overwhelming number of apps and research, there is a lack of apps related to other conditions, such as anemia, hearing loss, or low vision, which must be filled.

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Most cited references 97

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The effect of osteoarthritis definition on prevalence and incidence estimates: a systematic review.

D. Pereira, B Peleteiro, J. Araujo … (2011)

To understand the differences in prevalence and incidence estimates of osteoarthritis (OA), according to case definition, in knee, hip and hand joints. A systematic review was carried out in PUBMED and SCOPUS databases comprising the date of publication period from January 1995 to February 2011. We attempted to summarise data on the incidence and prevalence of OA according to different methods of assessment: self-reported, radiographic and symptomatic OA (clinical plus radiographic). Prevalence estimates were combined through meta-analysis and between-study heterogeneity was quantified. Seventy-two papers were reviewed (nine on incidence and 63 on prevalence). Higher OA prevalences are seen when radiographic OA definition was used for all age groups. Prevalence meta-analysis showed high heterogeneity between studies even in each specific joint and using the same OA definition. Although the knee is the most studied joint, the highest OA prevalence estimates were found in hand joints. OA of the knee tends to be more prevalent in women than in men independently of the OA definition used, but no gender differences were found in hip and hand OA. Insufficient data for incidence studies didn't allow us to make any comparison according to joint site or OA definition. Radiographic case definition of OA presented the highest prevalences. Within each joint site, self-reported and symptomatic OA definitions appear to present similar estimates. The high heterogeneity found in the studies limited further conclusions. Copyright © 2011 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

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Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines

Taridzo Chomutare, Luis Fernández Luque, Eirik Årsand … (2011)

Background Interest in mobile health (mHealth) applications for self-management of diabetes is growing. In July 2009, we found 60 diabetes applications on iTunes for iPhone; by February 2011 the number had increased by more than 400% to 260. Other mobile platforms reflect a similar trend. Despite the growth, research on both the design and the use of diabetes mHealth applications is scarce. Furthermore, the potential influence of social media on diabetes mHealth applications is largely unexplored. Objective Our objective was to study the salient features of mobile applications for diabetes care, in contrast to clinical guideline recommendations for diabetes self-management. These clinical guidelines are published by health authorities or associations such as the National Institute for Health and Clinical Excellence in the United Kingdom and the American Diabetes Association. Methods We searched online vendor markets (online stores for Apple iPhone, Google Android, BlackBerry, and Nokia Symbian), journal databases, and gray literature related to diabetes mobile applications. We included applications that featured a component for self-monitoring of blood glucose and excluded applications without English-language user interfaces, as well as those intended exclusively for health care professionals. We surveyed the following features: (1) self-monitoring: (1.1) blood glucose, (1.2) weight, (1.3) physical activity, (1.4) diet, (1.5) insulin and medication, and (1.6) blood pressure, (2) education, (3) disease-related alerts and reminders, (4) integration of social media functions, (5) disease-related data export and communication, and (6) synchronization with personal health record (PHR) systems or patient portals. We then contrasted the prevalence of these features with guideline recommendations. Results The search resulted in 973 matches, of which 137 met the selection criteria. The four most prevalent features of the applications available on the online markets (n = 101) were (1) insulin and medication recording, 63 (62%), (2) data export and communication, 61 (60%), (3) diet recording, 47 (47%), and (4) weight management, 43 (43%). From the literature search (n = 26), the most prevalent features were (1) PHR or Web server synchronization, 18 (69%), (2) insulin and medication recording, 17 (65%), (3) diet recording, 17 (65%), and (4) data export and communication, 16 (62%). Interestingly, although clinical guidelines widely refer to the importance of education, this is missing from the top functionalities in both cases. Conclusions While a wide selection of mobile applications seems to be available for people with diabetes, this study shows there are obvious gaps between the evidence-based recommendations and the functionality used in study interventions or found in online markets. Current results confirm personalized education as an underrepresented feature in diabetes mobile applications. We found no studies evaluating social media concepts in diabetes self-management on mobile devices, and its potential remains largely unexplored.

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CBT for depression: a pilot RCT comparing mobile phone vs. computer

Sarah Watts, Anna Mackenzie, Cherian Thomas … (2013)

Background This paper reports the results of a pilot randomized controlled trial comparing the delivery modality (mobile phone/tablet or fixed computer) of a cognitive behavioural therapy intervention for the treatment of depression. The aim was to establish whether a previously validated computerized program (The Sadness Program) remained efficacious when delivered via a mobile application. Method 35 participants were recruited with Major Depression (80% female) and randomly allocated to access the program using a mobile app (on either a mobile phone or iPad) or a computer. Participants completed 6 lessons, weekly homework assignments, and received weekly email contact from a clinical psychologist or psychiatrist until completion of lesson 2. After lesson 2 email contact was only provided in response to participant request, or in response to a deterioration in psychological distress scores. The primary outcome measure was the Patient Health Questionnaire 9 (PHQ-9). Of the 35 participants recruited, 68.6% completed 6 lessons and 65.7% completed the 3-months follow up. Attrition was handled using mixed-model repeated-measures ANOVA. Results Both the Mobile and Computer Groups were associated with statistically significantly benefits in the PHQ-9 at post-test. At 3 months follow up, the reduction seen for both groups remained significant. Conclusions These results provide evidence to indicate that delivering a CBT program using a mobile application, can result in clinically significant improvements in outcomes for patients with depression. Trial registration Australian New Zealand Clinical Trials Registry ACTRN 12611001257954

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Author and article information

Contributors

Borja Martínez-Pérez:

University of ValladolidDepartment of Signal Theory and Communications, and Telematics EngineeringUniversity of ValladolidPaseo de Belén, 15Valladolid, 47011Spain34 983423000 ext 370334 983423667borja.martinez@uva.es

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications Inc. (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: June 2013

Publication date (Electronic): 14 June 2013

Volume: 15

Issue: 6

Electronic Location Identifier: e120

Affiliations

[1] ¹University of Valladolid Department of Signal Theory and Communications, and Telematics Engineering. University of Valladolid ValladolidSpain

Author notes

Corresponding Author: Borja Martínez-Pérez borja.martinez@ 123456uva.es

Article

Publisher ID: v15i6e120

DOI: 10.2196/jmir.2600

PMC ID: 3713954

PubMed ID: 23770578

SO-VID: 1c007b9e-87a5-474a-b7c0-a3c9f529b448

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 13 March 2013

Date revision requested : 23 April 2013

Date revision received : 30 April 2013

Date accepted : 08 May 2013

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