Malaria Geo-Localization with Mobile-Health Applications

2015 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi
Keyword(s):  
Mobile Health ◽  
Mobile Health Applications ◽  
Health Applications

EFFECTIVNESS OF SPECIFIC MOBILE HEALTH APPLICATIONS (mHEALTH-APPS)in GESTATIONAL DIABTETES MELLITUS: A SYSTEMATIC REVIEW (Preprint)

2020 ◽  
Author(s):  
Claudia Eberle ◽  
Maxine Löhnert
Keyword(s):  
Mobile Health ◽  
Cochrane Library ◽  
Clinical Parameters ◽  
Control Groups ◽  
Manual Search ◽  
Mobile Health Applications ◽  
Short And Long Term ◽  
Mhealth Apps ◽  
Health Applications

BACKGROUND Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), Metabolic Syndrome (MetS) as well as cardiovascular disease (CD). Against this background mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM clearly. OBJECTIVE Since there is – to our knowledge – no systematic literature review published, which focusses on the effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes of mother and child, we conducted these much-needed analyses. METHODS Data sources: A systematic literature search in Medline (Pubmed), Cochrane Library, Embase, CINAHL and Web of Science was performed including full text publications since 2008 up to date. An additional manual search in references and Google Scholar was conducted subsequently. Study Eligibility Criteria: Women diagnosed with GDM using specific mHealth-Apps during pregnancy compared to control groups, which met main clinical parameters and outcomes in GDM management as well as maternity and offspring care. Study appraisal and synthesis methods: Study quality was assessed and rated “strong”, “moderate” or “weak” by using the Effective Public Health Practice Project (EPHPP) tool. Study results were strongly categorized by outcomes; an additional qualitative summary was assessed. Study selection: Overall, n= 114 studies were analyzed, n= 46 duplicates were removed, n=5 studies met the eligible criteria and n=1 study was assessed by manual search subsequently. In total, n=6 publications, analyzing n=408 GDM patients in the interventional and n=405 women diagnosed with GDM in the control groups, were included. These studies were divided into n=5 two-arm randomized controlled trials (RCT) and n=1 controlled clinical trial (CCT). RESULTS Distinct improvements in clinical parameters and outcomes, such as fasting blood glucoses (FBG), 2-hour postprandial blood glucoses (PBG), off target blood glucose measurements (OTBG), delivery modes and patient compliance were analyzed in GDM patients using specific mHealth-Apps compared to matched control groups. CONCLUSIONS mHealth-Apps clearly improve clinical outcomes in management of GDM effectively. More studies need to be done more in detail.

Mobile Health Applications to Support COVID-19 Self-management: Review and Evaluation

2021 ◽  
Author(s):  
Sahar Khenarinezhad ◽  
Ehsan Ghazanfari Savadkoohi ◽  
Leila Shahmoradi
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Healthcare Providers ◽  
Vital Signs ◽  
Complete Information ◽  
Self Management ◽  
Management Measures ◽  
Management Procedures ◽  
Mobile Health Applications ◽  
Health Applications

Aim: During the epidemic and with an increase in coronavirus (COVID-19) disease prevalence, emergency care is essential to help people stay informed and undertake self-management measures to protect their health. One of these self-management procedures is the use of mobile apps in health. Mobile health (mHealth) applications include mobile devices in collecting clinical health data, sharing healthcare information for practitioners and patients, real-time monitoring of patient vital signs, and the direct provision of care (via mobile telemedicine). Mobile apps are increasing to improve health, but before healthcare providers can recommend these applications to patients, they need to be sure the apps will help change patients' lifestyles. Method: A search was conducted systematically using the keywords "Covid-19," "Coronavirus," "Covid-19, and Self-management" at the "Apple App Store". Then we evaluated the apps according to MARS criteria in May 2020. Results: A total of 145 apps for COVID-19 self-management were identified, but only 32 apps met our inclusion criteria after being assessed. The overall mean MARS score was 2.9 out of 5, and more than half of the apps had a minimum acceptability score (range 2.5-3.9). The "who academy" app received the highest functionality score. Who Academy, Corona-Care and First Responder COVID-19 Guide had the highest scores for behavior change. Conclusion: Our findings showed that few apps meet the quality, content, and functionality criteria for Covid-19 self-management. Therefore, developers should use evidence-based medical guidelines in creating mobile health applications so that, they can provide comprehensive and complete information to both patients and healthcare provider.

How mobile health applications can help treat depression

2017 ◽  
Vol 33 (9) ◽  
pp. 1-6
Author(s):  
Adam Rosenfeld ◽  
Sachin Pendse ◽  
Nicole R. Nugent
Keyword(s):  
Mobile Health ◽  
Mobile Health Applications ◽  
Health Applications

Integrating a mobile health applications for self-management to enhance Telecare system

2018 ◽  
Vol 35 (4) ◽  
pp. 815-825 ◽  
Author(s):  
Hao-Yun Kao ◽  
Chun-Wang Wei ◽  
Min-Chun Yu ◽  
Tyng-Yeu Liang ◽  
Wen-Hsiung Wu ◽  
...  
Keyword(s):  
Mobile Health ◽  
Self Management ◽  
Mobile Health Applications ◽  
Health Applications

scholarly journals Security and Privacy Analysis of Mobile Health Applications: The Alarming State of Practice

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 9390-9403 ◽  
Author(s):  
Achilleas Papageorgiou ◽  
Michael Strigkos ◽  
Eugenia Politou ◽  
Efthimios Alepis ◽  
Agusti Solanas ◽  
...  
Keyword(s):  
Mobile Health ◽  
Security And Privacy ◽  
Mobile Health Applications ◽  
Privacy Analysis ◽  
State Of Practice ◽  
Health Applications

Barriers and drivers regarding the use of mobile health applications among type 2 diabetes patients in the Netherlands: an explanatory sequential design (Preprint)

2021 ◽  
Author(s):  
Marloes Bults ◽  
Catharina Margaretha Van Leersum ◽  
Theo Olthuis ◽  
Robin Bekhuis ◽  
Marjolein Elisabeth Maria Den Ouden
Keyword(s):  
Mobile Health ◽  
Healthcare Professionals ◽  
Insurance Companies ◽  
Actual Use ◽  
Mobile Health Applications ◽  
Explanatory Sequential Design ◽  
The Individual ◽  
Depth Interviews ◽  
Health Applications

BACKGROUND In the Netherlands, type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases and the number of patients is expected to increase in the coming years. Self-monitoring of blood glucose levels, food intake and physical activity supports the self-management of patients with T2DM. In the past few years, there has been a rise in the development and availability of mobile health applications (apps) for T2DM. OBJECTIVE The aim of this study was to explore the actual use of diabetes mobile health applications among T2DM-patients and main barriers and drivers among app-users and non-users. METHODS An explanatory sequential design was applied, starting with a web-based questionnaire followed by semi-structured in-depth interviews. Data were collected between July and December 2020. Questionnaire data from 103 respondents were analyzed using IBM SPSS Statistics 25.0. Descriptive statistics were performed for actual use of apps among T2DM-patients and the individual items of the Unified Theory of Acceptance and Use of Technology (UTAUT). Differences between users and non-users were tested through chi-square tests for the individual items. Independent t-tests were performed to test for differences in mean scores per UTAUT-construct. A total of 16 respondents contributed to the in-depth interviews, of which ten were users and six non-users of apps for T2DM. Content analysis with a deductive approach was performed on all transcripts guided by the UTAUT. RESULTS Regarding actual use, 55% (n=57) were non-users and 45% (n=46) were users of apps for T2DM. Mean scores were significantly higher among users of apps for T2DM for the constructs performance expectancy, effort expectancy, facilitating conditions and knowledge compared to the non-users (P<.001). One of the main drivers for use was the belief that using diabetes-apps would result in better personal health and well-being. Time and energy needed to keep track of data and understand the app were mentioned as barriers. Users scored significantly higher regarding social influence compared to the non-users (P.007). Healthcare professionals play an important role in the support of T2DM-patients in using apps. Respondents wanted to use the apps and acquired data together with their healthcare professionals. However, respondents noticed that their professionals often were not supportive regarding the use of diabetes-apps, didn’t had interest or did not talk about apps or acquired data. Reimbursement by insurance companies was mentioned as missing facilitator. CONCLUSIONS Empowering healthcare professionals’ engagement is of utmost important to support T2DM-patients in using apps. Insurance companies can have a role in facilitating the use of diabetes-apps, for example to assure reimbursement. Further research should focus on evaluation of patients experiences with different diabetes-apps and how to integrate mobile health applications with diabetes self-management care.

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