The continuous development of mobile apps has led to many health care professionals using them in clinical settings; however, little research is available to guide occupational therapists (OTs) in ...choosing quality apps for use in their respective clinical settings.
The purpose of this study was to use the user version of the Mobile Application Rating Scale (uMARS) to evaluate the quality of the most frequently noted mobile health (mHealth) apps used by OTs and to demonstrate the utility of the uMARS to assess the quality of mHealth apps.
A previous study surveying OTs' use of apps in therapy compiled a list of apps frequently noted. A total of 25 of these apps were evaluated individually by 2 trained researchers using the uMARS, a simple, multidimensional analysis tool that can be reliably used to evaluate the quality of mHealth apps.
The top 10 apps had a total quality score of 4.3, or higher, out of 5 based on the mean scores of engagement, functionality, and aesthetics. Apps scored highest in functionality and lowest in engagement. Apps noted most frequently were not always high-quality apps; apps noted least frequently were not always low-quality apps.
Determining the effectiveness of using apps in clinical settings must be built upon a foundation of the implementation of high-quality apps. Mobile apps should not be incorporated into clinical settings solely based on frequency of use. The uMARS should be considered as a useful tool for OTs, and other professionals, to determine app quality.
Health literacy is critical for cancer patients as they must understand complex procedures or treatment options. Caregivers’ health literacy also plays a crucial role in caring for cancer patients. ...Low health literacy is associated with low adherence to medications, poor health status, and increased health care costs. There is a growing interest in the use of mobile health applications (apps) to improve health literacy. Mobile health apps can empower underserved cancer patients and their caregivers by providing features or functionalities to enhance interactive patient-provider communication and to understand medical information more readily. Despite the potentiality of improving health literacy through mobile health apps, there exist several related concerns: no equal access to mobile technology, no familiarity or knowledge of using mobile health apps, and privacy and security concerns. These elements should be taken into account for health policy making and mobile apps design and development. Importantly, mobile apps should be developed with the goal of achieving a high range of user access by considering all health literacy level and various cultural and linguistic needs.
Mobile apps for health exist in large numbers today, but oftentimes, consumers do not continue to use them after a brief period of initial usage, are averse toward using them at all, or are unaware ...that such apps even exist. The purpose of our study was to examine and qualitatively determine the design and content elements of health apps that facilitate or impede usage from the users' perceptive.
In 2014, six focus groups and five individual interviews were conducted in the Midwest region of the U.S. with a mixture of 44 smartphone owners of various social economic status. The participants were asked about their general and health specific mobile app usage. They were then shown specific features of exemplar health apps and prompted to discuss their perceptions. The focus groups and interviews were audio recorded, transcribed verbatim, and coded using the software NVivo.
Inductive thematic analysis was adopted to analyze the data and nine themes were identified: 1) barriers to adoption of health apps, 2) barriers to continued use of health apps, 3) motivators, 4) information and personalized guidance, 5) tracking for awareness and progress, 6) credibility, 7) goal setting, 8) reminders, and 9) sharing personal information. The themes were mapped to theories for interpretation of the results.
This qualitative research with a diverse pool of participants extended previous research on challenges and opportunities of health apps. The findings provide researchers, app designers, and health care providers insights on how to develop and evaluate health apps from the users' perspective.
With continued increases in smartphone ownership, researchers and clinicians are investigating the use of this technology to enhance the management of chronic illnesses such as bipolar disorder (BD). ...Smartphones can be used to deliver interventions and psychoeducation, supplement treatment, and enhance therapeutic reach in BD, as apps are cost-effective, accessible, anonymous, and convenient. While the evidence-based development of BD apps is in its infancy, there has been an explosion of publicly available apps. However, the opportunity for mHealth to assist in the self-management of BD is only feasible if apps are of appropriate quality.
Our aim was to identify the types of apps currently available for BD in the Google Play and iOS stores and to assess their features and the quality of their content.
A systematic review framework was applied to the search, screening, and assessment of apps. We searched the Australian Google Play and iOS stores for English-language apps developed for people with BD. The comprehensiveness and quality of information was assessed against core psychoeducation principles and current BD treatment guidelines. Management tools were evaluated with reference to the best-practice resources for the specific area. General app features, and privacy and security were also assessed.
Of the 571 apps identified, 82 were included in the review. Of these, 32 apps provided information and the remaining 50 were management tools including screening and assessment (n=10), symptom monitoring (n=35), community support (n=4), and treatment (n=1). Not even a quarter of apps (18/82, 22%) addressed privacy and security by providing a privacy policy. Overall, apps providing information covered a third (4/11, 36%) of the core psychoeducation principles and even fewer (2/13, 15%) best-practice guidelines. Only a third (10/32, 31%) cited their information source. Neither comprehensiveness of psychoeducation information (r=-.11, P=.80) nor adherence to best-practice guidelines (r=-.02, P=.96) were significantly correlated with average user ratings. Symptom monitoring apps generally failed to monitor critical information such as medication (20/35, 57%) and sleep (18/35, 51%), and the majority of self-assessment apps did not use validated screening measures (6/10, 60%).
In general, the content of currently available apps for BD is not in line with practice guidelines or established self-management principles. Apps also fail to provide important information to help users assess their quality, with most lacking source citation and a privacy policy. Therefore, both consumers and clinicians should exercise caution with app selection. While mHealth offers great opportunities for the development of quality evidence-based mobile interventions, new frameworks for mobile mental health research are needed to ensure the timely availability of evidence-based apps to the public.
We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in ...Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20-40% in the infection rate in Europe and 30-70% in the US.
The global impact of COVID-19 pandemic has led to a rapid development and utilization of mobile health applications. These are addressing the unmet needs of healthcare and public health system ...including contact tracing, health information dissemination, symptom checking and providing tools for training healthcare providers. Here we provide an overview of mobile applications being currently utilized for COVID-19 and their assessment using the Mobile Application Rating Scale. We performed a systematic review of the literature and mobile platforms to assess mobile applications currently utilized for COVID-19, and a quality assessment of these applications using the Mobile Application Rating Scale (MARS) for overall quality, Engagement, Functionality, Aesthetics, and Information. Finally, we provide an overview of the key salient features that should be included in mobile applications being developed for future use. Our search identified 63 apps that are currently being used for COVID-19. Of these, 25 were selected from the Google play store and Apple App store in India, and 19 each from the UK and US. 18 apps were developed for sharing up to date information on COVID-19, and 8 were used for contact tracing while 9 apps showed features of both. On MARS Scale, overall scores ranged from 2.4 to 4.8 with apps scoring high in areas of functionality and lower in Engagement. Future steps should involve developing and testing of mobile applications using assessment tools like the MARS scale and the study of their impact on health behaviours and outcomes.
Smartphone diet-tracking apps may help individuals lose weight, manage chronic conditions, and understand dietary patterns; however, the usabilities and functionalities of these apps have not been ...well studied.
The aim of this study was to review the usability of current iPhone operating system (iOS) and Android diet-tracking apps, the degree to which app features align with behavior change constructs, and to assess variations between apps in nutrient coding.
The top 7 diet-tracking apps were identified from the iOS iTunes and Android Play online stores, downloaded and used over a 2-week period. Each app was independently scored by researchers using the System Usability Scale (SUS), and features were compared with the domains in an integrated behavior change theory framework: the Theoretical Domains Framework. An estimated 3-day food diary was completed using each app, and food items were entered into the United States Department of Agriculture (USDA) Food Composition Databases to evaluate their differences in nutrient data against the USDA reference.
Of the apps that were reviewed, LifeSum had the highest average SUS score of 89.2, whereas MyDietCoach had the lowest SUS score of 46.7. Some variations in features were noted between Android and iOS versions of the same apps, mainly for MyDietCoach, which affected the SUS score. App features varied considerably, yet all of the apps had features consistent with Beliefs about Capabilities and thus have the potential to promote self-efficacy by helping individuals track their diet and progress toward goals. None of the apps allowed for tracking of emotional factors that may be associated with diet patterns. The presence of behavior change domain features tended to be weakly correlated with greater usability, with R
ranging from 0 to .396. The exception to this was features related to the Reinforcement domain, which were correlated with less usability. Comparing the apps with the USDA reference for a 3-day diet, the average differences were 1.4% for calories, 1.0% for carbohydrates, 10.4% for protein, and -6.5% for fat.
Almost all reviewed diet-tracking apps scored well with respect to usability, used a variety of behavior change constructs, and accurately coded calories and carbohydrates, allowing them to play a potential role in dietary intervention studies.
To evaluate two user-operated audiometry methods, the AMTAS.sup.TM PC-based audiometry and a low-cost smartphone audiometry research application (R-App). A repeated-measures within-subject study ...design was used to compare both user-operated methods to traditional manual audiometry and to evaluate test-retest reliability of each method. Standard deviation of absolute differences ranged between 3.9-6.9 dB on AMTAS.sup.TM and 4.5-6.8 dB on the R-App. The highest variability was found at the 8000 Hz frequency (R-App and AMTAS.sup.TM test) and 3000 Hz frequency (AMTAS.sup.TM retest). Evaluation of test-retest reliability of AMTAS.sup.TM and R-App showed SD of absolute differences ranging between 3.5-5.8 dB and 3.1-5.0 dB, respectively. The mean threshold difference between test and retest was within ±1.5 dB on AMTAS.sup.TM and ±1 dB on the R-App. Accuracy of AMTAS.sup.TM and the R-App was within acceptable limits for audiometry and comparable to traditional manual audiometry on all tested frequencies (250-8000 Hz). Evaluation of test-retest reliability showed acceptable variation on both AMTAS.sup.TM and R-App. Both user-operated methods could be reliably performed in a quiet non-soundproofed environment.
Since its earliest days, the field of behavioral medicine has leveraged technology to increase the reach and effectiveness of its interventions. Here, we highlight key areas of opportunity and ...recommend next steps to further advance intervention development, evaluation, and commercialization with a focus on three technologies: mobile applications (apps), social media, and wearable devices. Ultimately, we argue that future of digital health behavioral science research lies in finding ways to advance more robust academic-industry partnerships. These include academics consciously working towards preparing and training the work force of the twenty first century for digital health, actively working towards advancing methods that can balance the needs for efficiency in industry with the desire for rigor and reproducibility in academia, and the need to advance common practices and procedures that support more ethical practices for promoting healthy behavior.
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