Mobile Apps for Hematological Conditions: Review and Content Analysis Using the Mobile App Rating Scale

Use of Patient-Centered Technology and Digital Interventions in Pediatric and Adult Patients with Hematologic Malignancies

PURPOSE OF REVIEW

As society continues to advance in technology, it is important to address how this advancement can impact and enhance patient care. The purpose of this review is to identify patient-centered technology currently available for adult and pediatric patients with and those having survived hematologic malignancies. Given that patients with hematologic malignancies often have to adhere to strenuous medication regimens, coordinate care with many different providers, manage symptoms associated with treatment, and manage late effects associated with survivorship, they would benefit greatly from patient-centered technology aimed at decreasing these burdens.

RECENT FINDINGS

This review found various available digital interventions for this patient population and focuses on an overview of commercially available smartphone applications, patient portals, and technology for remote monitoring. In summary, many digital interventions exist for use in the medical care of oncology patients. The incorporation of these interventions can allow for more personalized medical care, better organization of treatment plans by caregivers at home, and easy delivery of accurate medical information.

Quality Assessment of Smartphone Medication Management Apps in France: Systematic Search

BACKGROUND

Adherence to medication is estimated to be around 50% for chronically ill patients in high-income countries. Improving the effectiveness of adherence interventions could have a far greater impact on population health than any improvement in specific medical treatments. Mobile health (mHealth) is one of the most effective solutions for helping patients improve their medication intake, notably through the use of mobile apps with reminder systems. With more than 327,000 apps available in the mHealth field, it is difficult for health care professionals and patients alike to choose which apps to recommend and use.

OBJECTIVE

We aim to carry out a systematic search of medication management smartphone apps available in France that send reminders to patients and assess their quality using a validated scale.

METHODS

Mobile apps were identified in October and November 2022 after a systematic keyword search on the 2 main app download platforms: App Store (Apple Inc) and Google Play Store. Inclusion criteria were free availability, date of last update, and availability in French. Next, 2 health care professionals independently evaluated the included apps using the French version of the Mobile App Rating Scale (MARS-F), an objective scoring system validated for assessing the overall quality of apps in the mHealth field. An intraclass correlation coefficient was calculated to determine interrater reliability.

RESULTS

In total, 960 apps were identified and 49 were selected (25 from the App Store and 24 from the Google Play Store). Interrater reliability was excellent (intraclass correlation coefficient 0.92; 95% CI 0.87-0.95; P<.001). The average MARS-F score was 3.56 (SD 0.49) for apps on the App Store and 3.51 (SD 0.46) for those on the Google Play Store, with 10 apps scoring above 4 out of 5. Further, 2 apps were tested in at least one randomized controlled trial and showed positive results. The 2 apps with the highest ratings were Mediteo rappel de médicaments (Mediteo GmbH) and TOM rappel medicaments, pilule (Innovation6 GmbH), available on both platforms. Each app's MARS-F score was weakly correlated with user ratings on the App Store and moderately correlated on the Google Play Store.

CONCLUSIONS

To our knowledge, this is the first study that used a validated scoring system to evaluate medication management apps that send medication reminders. The quality of the apps was heterogeneous, with only 2 having been studied in a randomized controlled trial with positive results. The evaluation of apps in real-life conditions by patients is necessary to determine their acceptability and effectiveness. Certification of apps is also essential to help health care professionals and patients identify validated apps.

Assessing the Usefulness of Mobile Apps for Noise Management in Occupational Health and Safety: Quantitative Measurement and Expert Elicitation Study

Background

Overexposure to occupational noise can lead to hearing loss. Occupational noise mapping is conventionally performed with a calibrated sound level meter (SLM). With the rise of mobile apps, there is a growing number of SLM apps available on mobile phones. However, few studies have evaluated such apps for accuracy and usefulness to guide those with occupational noise detection needs in selecting a quality app.

Objective

The purpose of this study was to evaluate the accuracy and usefulness of SLM mobile apps to guide workplace health and safety professionals in determining these apps' suitability for assessing occupational noise exposure.

Methods

The following three iOS apps were assessed: the NIOSH (National Institute for Occupational Safety and Health) Sound Level Meter, Decibel X, and SoundMeter X apps. The selected apps were evaluated for their accuracy in measuring sound levels in low-, moderate-, and high-noise settings within both simulated environments and real-world environments by comparing them to a conventional SLM. The usefulness of the apps was then assessed by occupational health specialists using the Mobile App Rating Scale (MARS).

Results

The NIOSH Sound Level Meter app accurately measured noise across a range of sound levels in both simulated settings and real-world settings. However, considerable variation was observed between readings. In comparison, the Decibel X and SoundMeter X apps showed more consistent readings but consistently underestimated noise levels, suggesting that they may pose a risk for workers. Nevertheless, none of the differences in sound measurements between the three apps and the conventional SLM were statistically significant (NIOSH Sound Level Meter: P=.78; Decibel X: P=.38; SoundMeter X: P=.40). The MARS scores for the three apps were all above 3.0, indicating the usefulness of these apps.

Conclusions

Under the conditions of this study, the NIOSH Sound Level Meter app had equivalent accuracy to the calibrated SLM and a degree of usefulness according to the MARS. This suggests that the NIOSH Sound Level Meter app may be suitable for mapping noise levels as part of a monitoring strategy in workplaces. However, it is important to understand its limitations. Mobile apps should complement but not replace conventional SLMs when trying to assess occupational noise exposure risk. Our outcomes also suggest that the MARS tool may have limited applicability to measurement-based apps and may be more suited to information-based apps that collect, record, and store information.

Mobile applications for cognitive training: Content analysis and quality review

Background

As the number of individuals suffering from cognitive diseases continues to rise, dealing with the diminished cognitive function that comes with age has become a serious public health concern. While the use of mobile applications (apps) as digital treatments for cognitive training shows promise, the analysis of their content and quality remains unclear.

Objective

The aim of this study was to systematically search and assess cognitive training apps using the multidimensional mobile app rating scale (MARS) to rate objective quality and identify critical points.

Methods

A search was conducted on the Google Play Store and Apple App Store in February 2022 using the terms "cognitive training" and "cognitive rehabilitation." The cognitive domains provided by each app were analyzed, and the frequency and percentage according to the apps were obtained. The MARS, a mHealth app quality rating tool including multidimensional measures, was used to analyze the quality of the apps. The relationship between the MARS score, the number of reviews, and 5-star ratings were examined.

Results

Of the 53 apps, 52 (98 %) included memory function, 48 (91 %) included attention function, 24 (45 %) included executive function, and 19 (36 %) included visuospatial function. The mean (SD) scores of MARS, 5-star ratings, and reviews of 53 apps were 3.09 (0.61), 4.33 (0.30), and 62,415.43 (121,578.77). From the between-section comparison, engagement (mean 2.97, SD 0.68) obtained lower scores than functionality (mean 3.18, SD 0.62), aesthetics (mean 3.13, SD 0.72), and information (mean 3.11, SD 0.54). The mean quality score and reviews showed a statistically significant association (r = 0.447 and P = .001*). As the number of domains increased, the mean quality score showed a statistically significant increasing trend (P = .002*).

Conclusions

Most apps provided training for the memory and attention domains, but few apps included executive function or visuospatial domains. The quality of the apps improved significantly when more domains were provided, and was positively associated with the number of reviews received. These results could be useful for the future development of mobile apps for cognitive training.

Mobile applications in the Philippines during the COVID-19 pandemic: systematic search, use case mapping, and quality assessment using the Mobile App Rating Scale (MARS)

Background

In the Philippines, various mobile health apps were implemented during the COVID-19 pandemic with very little knowledge in terms of their quality. The aims of this paper were 1) to systemically search for mobile apps with COVID-19 pandemic use case that are implemented in the Philippines; 2) to assess the apps using Mobile App Rating Scale (MARS); and 3) to identify the critical points for future improvements of these apps.

Methods

To identify existing mobile applications with COVID-19 pandemic use case employed in the Philippines, Google Play and Apple App Stores were systematically searched. Further search was conducted using the Google Search. Data were extracted from the app web store profile and apps were categorized according to use cases. Mobile apps that met the inclusion criteria were independently assessed and scored by two researchers using the MARS-a 23-item, expert-based rating scale for assessing the quality of mHealth applications.

Results

A total of 27 apps were identified and assessed using MARS. The majority of the apps are designed for managing exposure to COVID-19 and for promoting health monitoring. The overall MARS score of all the apps is 3.62 points (SD 0.7), with a maximum score of 4.7 for an app used for telehealth and a minimum of 2.3 for a COVID-19 health declaration app. The majority (n = 19, 70%) of the apps are equal to or exceeded the minimum "acceptable" MARS score of 3.0. Looking at the categories, the apps for raising awareness received the highest MARS score of 4.58 (SD 0.03) while those designed for managing exposure to COVID-19 received the lowest mean score of 3.06 (SD 0.6).

Conclusions

There is a heterogenous quality of mHealth apps implemented during the COVID-19 pandemic in the Philippines. The study also identified areas to better improve the tools. Considering that mHealth is expected to be an integral part of the healthcare system post-pandemic, the results warrant better policies and guidance in the development and implementation to ensure quality across the board and as a result, positively impact health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44247-023-00007-2.

Menstrual Tracking Mobile App Review by Consumers and Health Care Providers: Quality Evaluations Study

BACKGROUND

Women's menstrual cycle is an important component of their overall health. Physiological cycles and associated symptoms can be monitored continuously and used as indicators in various fields. Menstrual apps are accessible and can be used to promote overall female health. However, no study has evaluated these apps' functionality from both consumers' and health care providers' perspectives. As such, the evidence indicating whether the menstrual apps available on the market provide user satisfaction is insufficient.

OBJECTIVE

This study was performed to investigate the key content and quality of menstrual apps from the perspectives of health care providers and consumers. We also analyzed the correlations between health care provider and consumer evaluation scores. On the basis of this analysis, we offer technical and policy recommendations that could increase the usability and convenience of future app.

METHODS

We searched the Google Play Store and iOS App Store using the keywords "period" and "menstrual cycle" in English and Korean and identified relevant apps. An app that met the following inclusion criteria was selected as a research app: nonduplicate; with >10,000 reviews; last updated ≤180 days ago; relevant to this topic; written in Korean or English; available free of charge; and currently operational. App quality was evaluated by 6 consumers and 4 health care providers using Mobile Application Rating Scale (MARS) and user version of the Mobile Application Rating Scale (uMARS). We then analyzed the correlations among MARS scores, uMARS scores, star ratings, and the number of reviews.

RESULTS

Of the 34 apps, 31 (91%) apps could be used to predict the menstrual cycle, and 2 (6%) apps provided information pertinent to health screening. All apps that scored highly in the MARS evaluation offer a symptom logging function and provide the user with personalized notifications. The "Bom Calendar" app had the highest MARS (4.51) and uMARS (4.23) scores. The MARS (2.22) and uMARS (4.15) scores for the "Menstrual calendar-ovulation & pregnancy calendar" app were different. In addition, there was no relationship between MARS and uMARS scores (r=0.32; P=.06).

CONCLUSIONS

We compared consumer and health care provider ratings for menstrual apps. Continuous monitoring of app quality from consumer and health care provider perspectives is necessary to guide their development and update content.

Premature ejaculation in the era of mobile health application: A current analysis and evaluation of adherence to EAU guidelines

Introduction: Several mobile health applications (MHAs) have been developed to assist and improve the quality of life of patients affected by premature ejaculation, but the scientific quality and adherence to guidelines are not yet addressed. Materials and methods: On 25 May 2022, we conducted a search in the Apple App Store and Google Play Store. We reviewed all mobile apps from Apple App Store and Google Play Store for premature ejaculation and evaluated their usage in screening, prevention, management, and adherence to EAU guidelines. Results: In total 9 MHA were reviewed. All MHAs are geared towards the patient and provide information about diagnoses and treatment of PE. The mean score were 2.87, 3.69, 2.77, 2.55, 2.86 for Engagement, Functionality, Aesthetics, Information, and Subjective quality respectively. MHAs reported low and medium adherence to EAU guidelines. Conclusions: MHAs provide different services in many medical fields, including male sexual dysfunction. Their development is constantly increasing, but the problems of scientific validation, content, and quality are not yet solved. Much future research is necessary to improve the quality of the apps and promote new user designed, and high-quality apps.