Evidence map›Paper›PMID 21979293›Full record

ReviewJournal of medical Internet research2011

Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines.

Taridzo Chomutare, Luis Fernandez-Luque, Eirik Arsand, Gunnar Hartvigsen

4 registry-linked trialsAbstract readComparative StudyReview
In one paragraph

Review in Journal of medical Internet research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 4 registered trials, which are not on this map. Cited by 196 papers, 19 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
196citing papers in PubMed, 19 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03455816 naunknown statusnot on this mapstarted 2017, after this paper: background citation

Randomized Clinical Study to Evaluate the Bio-Psychosocial Impact of a Mobile App for Diabetes ("SOCIAL DIABETES") and a SMARTMETER® (A. MENARINI DIAGNOSTICS) in the Care of People With Diabetes Mellitus Type 1 and Its Associated Costs

TypeinterventionalSponsorSoledad Ruiz de AdanaRan2017 to 2018Enrolled148ConditionsDiabetes Mellitus, Type 1ArmsSocial Diabetes App, Usual clinical monitoring group (Control group)
NCT03720327 nacompletednot on this mapstarted 2019, after this paper: background citation

Fitness Intensive Therapy (Get FIT) to Promote Healthy Living in Older Adults

TypeinterventionalSponsorUniversity of California, IrvineRan2019 to 2022Enrolled54ConditionsCardiovascular Diseases, Cardiovascular Risk FactorArmsGet FIT, Get FIT+
NCT03744650 nacompletednot on this mapstarted 2014, after this paper: background citation

Improving Awareness, Knowledge and Heart-related Lifestyle of Coronary Heart Disease Among Working Population Through a mHealth Programme

TypeinterventionalSponsorNational University of SingaporeRan2014 to 2017Enrolled160ConditionsCHD - Coronary Heart Disease, Health Knowledge, Attitudes, Practice, Health BehaviorArms"Care4Heart" programme
NCT05228561 naunknown statusnot on this mapstarted 2022, after this paper: background citation

The Effect of Mobile Application Supported Diabetes Education On Type 2 Diabetes Self-Management And Blood Sugar In Newly Diagnosed Type 2 Diabetes Patients

TypeinterventionalSponsorEge UniversityRan2022 to 2022Enrolled140ConditionsDiabetes Mellitus, Type 2, Education, Mobile Applications, Self-ManagementArmsMobile Application Supported Nutrition and Diabetes Education
3 · Its place in the literature

Who cites it

196 citing papers in PubMed, 19 syntheses or guidelines pooled it.

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  16. Mapping mHealth research: a decade of evolution.Journal of medical Internet research · 2013
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  17. Mobile applications for diabetes self-management: status and potential.Journal of diabetes science and technology · 2013
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  20. Trial

136 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Taridzo ChomutareNorwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway. taridzo.chomutare@telemed.no
Luis Fernandez-Luque
Eirik Arsand
Gunnar Hartvigsen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInterest 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.

objectiveOur 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.

methodsWe 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.

resultsThe 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.

conclusionsWhile 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.

Indexed as

Evidence-Based MedicinePractice Guidelines as TopicDiabetes Mellitus, Type 2Health Knowledge, Attitudes, PracticeHealth Services ResearchHumansHypoglycemic AgentsInsulinPatient PreferenceSelf CareTelemedicineUnited KingdomUnited StatesUser-Computer InterfaceHypoglycemic AgentsInsulin

Identifiers

PMID21979293
PMCPMC3222161

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.