Forensic analysis and security assessment of Android m-banking apps

The increasing popularity and constant evolution of mobile technologies have resulted in an increased focus in mobile device and app security and forensics research. Banking apps appear to be an understudied topic, despite their popularity with consumers. In this paper, seven Android m-banking apps in Thailand are analysed. Based on the findings of our study, we describe the forensic artefacts that could be forensically recovered from the apps, and the findings of security assessment of the apps. For example, we found that several of the apps do not implement root device detection, do not encrypt user data, or it is possible to modify the apps and install repackaged apps.     

Work productivity in rhinitis using cell phones: The MASK pilot study

Allergic rhinitis often impairs social life and performance. The aim of this cross‐sectional study was to use cell phone data to assess the impact on work productivity of uncontrolled rhinitis assessed by visual analogue scale (VAS ). A mobile phone app (Allergy Diary, Google Play Store and Apple App Store) collects data from daily visual analogue scales (VAS ) for overall allergic symptoms (VAS ‐global measured), nasal (VAS ‐nasal), ocular (VAS ‐ocular) and asthma symptoms (VAS ‐asthma) as well as work (VAS ‐work). A combined nasal‐ocular score is calculated. The Allergy Diary is available in 21 countries. The app includes the Work Productivity and Activity Impairment Allergic Specific Questionnaire (WPAI :AS ) in six EU countries. All consecutive users who completed the VAS ‐work from 1 June to 31 October 2016 were included in the study. A total of 1136 users filled in 5818 days of VAS ‐work. Symptoms of allergic rhinitis were controlled (VAS ‐global <20) in approximately 60% of the days. In users with uncontrolled rhinitis, approximately 90% had some work impairment and over 50% had severe work impairment (VAS ‐work >50). There was a significant correlation between VAS ‐global calculated and VAS ‐work (Rho=0.83, P <0.00001, Spearman's rank test). In 144 users, there was a significant correlation between VAS ‐work and WPAI :AS (Rho=0.53, P <0.0001). This pilot study provides not only proof‐of‐concept data on the work impairment collected with the app but also data on the app itself, especially the distribution of responses for the VAS . This supports the interpretation that persons with rhinitis report both the presence and the absence of symptoms.     

Determining Pain Catastrophizing From Daily Pain App Assessment Data: Role of Computer-Based Classification

This study compared persons with chronic pain who consistently reported that their pain was worsening with those who reported that their pain was improving or remaining the same per daily assessment data from a smartphone pain app. All participants completed baseline measures and were asked to record their progress every day by answering whether their overall condition had improved, remained the same, or gotten worse (perceived change) on a visual analogue scale. One hundred forty-four individuals with chronic pain who successfully entered daily assessments were included. Those persons who were classified as worse showed significantly higher pain intensity scores, greater activity interference, higher disability and mood disturbance scores, and higher scores on the Pain Catastrophizing Scale both at baseline and after 3 months (P < .001). Repeated measures analyses and multilevel modeling of perceived change data over different time intervals of 20 assessments over 40 days, 10 assessments over 20 days, and 5 assessments over 10 days were examined. These analyses demonstrated that group classification of better, same, and worse could be reliably determined, even with as few as 5 assessments. These results support the use of innovative mobile health technology to identify individuals who are prone to catastrophize about their pain.Perspective: This study demonstrated that daily assessment of overall perceived change with a smartphone pain app was positively correlated with the Pain Catastrophizing Scale and capturing short-term daily assessment trends data using computer-based classification methods might be a future way to help to identify individuals who tend to catastrophize about their pain.     

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps

Background

One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines.

Objective

The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population.

Methods

We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps.

Results

Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified.

Conclusions

A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research.     

Building a Mobile HIV Prevention App for Men Who Have Sex With Men: An Iterative and Community-Driven Process

Background

Gay, bisexual, and other men who have sex with men (MSM) account for a disproportionate burden of new HIV infections in the United States. Mobile technology presents an opportunity for innovative interventions for HIV prevention. Some HIV prevention apps currently exist; however, it is challenging to encourage users to download these apps and use them regularly. An iterative research process that centers on the community’s needs and preferences may increase the uptake, adherence, and ultimate effectiveness of mobile apps for HIV prevention.

Objective

The aim of this paper is to provide a case study to illustrate how an iterative community approach to a mobile HIV prevention app can lead to changes in app content to appropriately address the needs and the desires of the target community.

Methods

In this three-phase study, we conducted focus group discussions (FGDs) with MSM and HIV testing counselors in Atlanta, Seattle, and US rural regions to learn preferences for building a mobile HIV prevention app. We used data from these groups to build a beta version of the app and theater tested it in additional FGDs. A thematic data analysis examined how this approach addressed preferences and concerns expressed by the participants.

Results

There was an increased willingness to use the app during theater testing than during the first phase of FGDs. Many concerns that were identified in phase one (eg, disagreements about reminders for HIV testing, concerns about app privacy) were considered in building the beta version. Participants perceived these features as strengths during theater testing. However, some disagreements were still present, especially regarding the tone and language of the app.

Conclusions

These findings highlight the benefits of using an interactive and community-driven process to collect data on app preferences when building a mobile HIV prevention app. Through this process, we learned how to be inclusive of the larger MSM population without marginalizing some app users. Though some issues in phase one were able to be addressed, disagreements still occurred in theater testing. If the app is going to address a large and diverse risk group, we cannot include niche functionality that may offend some of the target population.     

Supporting parents in the NICU: A new app from the US, ‘MyPreemie’: A tool to provide parents of premature babies with support,empowerment, education and participation in their infant's care

This article describes the new MyPreemie app for iPhone and iPad, designed to inform, assist, empower, and support parents of premature babies in the NICU and afterwards. Created by the same team who wrote the book Preemies: The Essential Guide for Parents of Premature Babies, the app contains information on medical and developmental issues; suggested questions for parents to ask doctors and nurses to understand their baby's care; a combined baby journal and adult diary with focused prompts to record events and emotions; tools to track growth; and organizing lists for questions to ask, tasks to do, and mementos to collect. The app's pages can be shared by email or Facebook to facilitate communication with family and friends, and printed in PDF and saved. Overall, the app aims to ease parents' distress by providing meaningful parenting activities during a baby's NICU stay and an increased sense of normality, control, and connection. Nurses are encouraged to advise their patients' families about the MyPreemie app as a way to help meet their practical and emotional needs and support them through the stressful experience of prematurity.     

A Bayesian tool for epilepsy diagnosis in the resource-poor world: Development and early validation

PurposeThe epilepsy treatment gap in resource-poor countries is so large that existing numbers of doctors are unlikely to be able to close it. Other health workers are likely to be needed but they will need help. The diagnosis of an attack as epileptic or not is an essential step in the management of epilepsy. It should be possible to devise a tool to give the probability of episodes being epileptic based on a Bayesian analysis of the results of history taking.MethodWe asked about the nature of episodes in patients referred to epilepsy camps in Nepal. Answers were then compared to the final clinical diagnosis of epilepsy and the likelihood ratio (LR) of the episode being epileptic obtained for each answer. The most informative LRs, tested sequentially, formed the basis for a tool which was validated in a different Nepalese population.ResultsData was obtained from 67 patients. The pre-test probability of having epilepsy was 0.76. Answers to 11 questions with the most informative LRs were then combined into a tool. This was tested on 14 different patients. Post-test probability scores in those with epilepsy ranged from 0.88 to 1 and for those with non-epilepsy from 0.07 to 0.42.ConclusionIt is possible to devise a tool based on simple clinical information using Bayesian principles. Initial validation suggests that this has the potential to enable health workers to diagnose episodes as epileptic or not. This now needs to be tested in different populations. The tool is easily converted to a mobile phone app.     

The role of artificial intelligence technology in the care of diabetic foot ulcers: the past,the present,and the future

Foot ulcers are common complications of diabetes mellitus and substantially increase the morbidity and mortality due to this disease. Wound care by regular monitoring of the progress of healing with clinical review of the ulcers, dressing changes, appropriate antibiotic therapy for infection and proper offloading of the ulcer are the cornerstones of the management of foot ulcers. Assessing the progress of foot ulcers can be a challenge for the clinician and patient due to logistic issues such as regular attendance in the clinic. Foot clinics are often busy and because of manpower issues, ulcer reviews can be delayed with detrimental effects on the healing as a result of a lack of appropriate and timely changes in management. Wound photographs have been historically useful to assess the progress of diabetic foot ulcers over the past few decades. Mobile phones with digital cameras have recently revolutionized the capture of foot ulcer images. Patients can send ulcer photographs to diabetes care professionals electronically for remote monitoring, largely avoiding the logistics of patient transport to clinics with a reduction on clinic pressures. Artificial intelligence-based technologies have been developed in recent years to improve this remote monitoring of diabetic foot ulcers with the use of mobile apps. This is expected to make a huge impact on diabetic foot ulcer care with further research and development of more accurate and scientific technologies in future. This clinical update review aims to compile evidence on this hot topic to empower clinicians with the latest developments in the field.