A mobile application or app is a computer program or software application designed to run on a mobile device such as a phone, tablet, or watch. Mobile applications often stand in contrast to desktop applications which are designed to run on desktop computers, and web applications which run in mobile web browsers rather than directly on the mobile device.
Apps are broadly classified into three types: native apps, hybrid and web apps. Native applications are designed specifically for a mobile operating system, typically iOS or Android. Web apps are written in HTML5 or CSS and typically run through a browser. Hybrid apps are built using web technologies such as JavaScript, CSS, and HTML5 and function like web apps disguised in a native container.[2]
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With a growing number of mobile applications available at app stores and the improved capabilities of smartphones, people are downloading more applications to their devices.[5] Usage of mobile apps has become increasingly prevalent across mobile phone users.[6] A May 2012 comScore study reported that during the previous quarter, more mobile subscribers used apps than browsed the web on their devices: 51.1% vs. 49.8% respectively.[7] Researchers found that usage of mobile apps strongly correlates with user context and depends on user's location and time of the day.[8] Mobile apps are playing an ever-increasing role within healthcare and when designed and integrated correctly can yield many benefits.[9][10]
Mobile application development requires the use of specialized integrated development environments. Mobile apps are first tested within the development environment using emulators and later subjected to field testing. Emulators provide an inexpensive way to test applications on mobile phones to which developers may not have physical access.[13][14]
Mobile application management (MAM) describes software and services responsible for provisioning and controlling access to internally developed and commercially available mobile apps used in business settings. The strategy is meant to off-set the security risk of a Bring Your Own Device (BYOD) work strategy. When an employee brings a personal device into an enterprise setting, mobile application management enables the corporate IT staff to transfer required applications, control access to business data, and remove locally cached business data from the device if it is lost, or when its owner no longer works with the company. Containerization is an alternate approach to security. Rather than controlling an employee/s entire device, containerization apps create isolated pockets separate from personal data. Company control of the device only extends to that separate container.[36]
Introduction Increasing smartphones access has allowed for increasing development and use of smart phone applications (apps). Mobile health interventions have previously relied on voice or text-based short message services (SMS), however, the increasing availability and ease of use of apps has allowed for significant growth of smartphone apps that can be used for health behaviour change. This review considers the current body of knowledge relating to the evaluation of apps for health behaviour change. The aim of this review is to investigate approaches to the evaluation of health apps to identify any current best practice approaches. Method A systematic review was conducted. Data were collected and analysed in September 2016. Thirty-eight articles were identified and have been included in this review. Results Articles were published between 2011- 2016, and 36 were reviews or evaluations of apps related to one or more health conditions, the remaining two reported on an investigation of the usability of health apps. Studies investigated apps relating to the following areas: alcohol, asthma, breastfeeding, cancer, depression, diabetes, general health and fitness, headaches, heart disease, HIV, hypertension, iron deficiency/anaemia, low vision, mindfulness, obesity, pain, physical activity, smoking, weight management and women's health. Conclusion In order to harness the potential of mobile health apps for behaviour change and health, we need better ways to assess the quality and effectiveness of apps. This review is unable to suggest a single best practice approach to evaluate mobile health apps. Few measures identified in this review included sufficient information or evaluation, leading to potentially incomplete and inaccurate information for consumers seeking the best app for their situation. This is further complicated by a lack of regulation in health promotion generally.
A mobile app (or mobile application) is a software application developed specifically for use on small, wireless computing devices, such as smartphones and tablets, rather than desktop or laptop computers.
Mobile apps are sometimes categorized according to whether they are web-based or native apps, which are created specifically for a given platform. A third category, hybrid apps, combines elements of both native and web apps.
We conducted a systematic review with meta-analysis of randomized controlled trials that evaluated the effect of diabetes mobile phone applications. A total of 1550 participants from 21 studies were included. For type 1 diabetes, a significant 0.49% reduction in HbA1c was seen (95% CI, 0.04-0.94; I2 = 84%), with unexplained heterogeneity and a low GRADE of evidence. For type 2 diabetes, using diabetes apps was associated with a mean reduction of 0.57% (95% CI, 0.32-0.82; I2 = 77%). The results had severe heterogeneity that was explained by the frequency of HCP feedback. In studies with no HCP feedback, low frequency and high frequency HCP feedback, the mean reduction is 0.24% (95% CI, 0.02-0.49; I2 = 0%), 0.33% (95% CI, 0.07-0.59; I2 = 47%) and 1.12% (95% CI, 0.91-1.32; I2 = 0%), respectively, with a high GRADE of evidence. There is evidence that diabetes apps improve glycaemic control in type 1 diabetes patients. A reduction of 0.57% in HbA1c was found in type 2 diabetes patients. However, HCP functionality is important to achieve clinical effectiveness. Future studies are needed to explore the cost-effectiveness of diabetes apps and the optimal intensity of HCP feedback.
Background: Mobile phone applications (apps) have been shown to successfully facilitate the self-management of chronic disease. This study aims to evaluate firstly the experiences, barriers and facilitators to app usage among people with Type 2 Diabetes Mellitus (T2DM) and secondly determine recommendations to improve usage of diabetes apps.
Participants were recruited through responding to a flyer. These were distributed amongst general practices, allied health clinics, Facebook groups and pages which were specific to either diabetes or rural communities, and diabetes support groups. Participants were also recruited through snowballing techniques, whereby participants already in the study recruited future participants by informing people in their social network about the study [26]. These participants contacted researchers to express interest in taking part in the study. The inclusion criteria were: participants aged over 18 years from rural locations in Australia (RA2 or above), with a self-reported T2DM diagnosis for greater than 6 months, and smartphone ownership. Defined by the Australian Government Department of Health, RA2 or above is any area outside of major cities, including inner (RA2) and outer regional (RA3), remote (RA4) and very remote locations (RA5) in Australia. In this classification, remoteness is determined according to population and distance to services [27]. Participants were separated into app and non-app users. All health apps which could be used to facilitate diabetes self-management behaviours were accepted, including diabetes specific participants ranged in age, sex, rurality, app use experience, distance to GP and endocrinologist (time to reach measured in minutes) and diabetes management (management strategies identified by participant) (Table 1).
Secondly, many participants were not aware of apps or their features and often struggled to answer questions specifically relating to app features without prompting. Thirdly, many participants stated they had simply never thought of using an app to manage their diabetes, despite using other apps on their phones. Some non-app users considered management the domain of their GPs and did not see the need for app use unless specifically asked by their GP to do so.
The majority of app users found their apps very user-friendly. They described simple and straightforward navigation, clear layouts and designs and intuitive technology. Many participants also identified convenience as something they liked in their app. What this meant varied from app to app and included: being able to measure BGL easily and discreetly while away from home, being able to carry your phone and thus the app with you, or having the app count steps automatically.
As a first line educational resource, most participants used Google. This was the most easily accessible source. Issues noted with this source were the difficulty of assessing the reliability of information and the lack of personalised information. Most participants liked accessing information from healthcare professionals, usually their GP. Participants perceived this information to be reliable and personalised. Other participants read articles, magazines or pamphlets as their most utilised form of education. Another form of education participants liked was face-to-face communication and/or peer education, including support groups, informal chatting with friends diagnosed with diabetes and phone-based services. This was generally perceived as reliable and personalised information.
Some participants also mentioned factors that were specific to living rurally and indicative of health inequity. These included GP accessibility, a reduction of services in the area and poor phone and internet service. 0852c4b9a8
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