Mobile Apps for the Management of Gastrointestinal Diseases: Systematic Search and Evaluation Within App Stores

Background

Gastrointestinal diseases are associated with substantial cost in health care. In times of the COVID-19 pandemic and further digitalization of gastrointestinal tract health care, mobile health apps could complement routine health care. Many gastrointestinal health care apps are already available in the app stores, but the quality, data protection, and reliability often remain unclear.

Objective

This systematic review aimed to evaluate the quality characteristics as well as the privacy and security measures of mobile health apps for the management of gastrointestinal diseases.

Methods

A web crawler systematically searched for mobile health apps with a focus on gastrointestinal diseases. The identified mobile health apps were evaluated using the Mobile Application Rating Scale (MARS). Furthermore, app characteristics, data protection, and security measures were collected. Classic user star rating was correlated with overall mobile health app quality.

Results

The overall quality of the mobile health apps (N=109) was moderate (mean 2.90, SD 0.52; on a scale ranging from 1 to 5). The quality of the subscales ranged from low (mean 1.89, SD 0.66) to good (mean 4.08, SD 0.57). The security of data transfer was ensured only by 11 (10.1%) mobile health apps. None of the mobile health apps had an evidence base. The user star rating did not correlate with the MARS overall score or with the individual subdimensions of the MARS (all P>.05).

Conclusions

Mobile health apps might have a positive impact on diagnosis, therapy, and patient guidance in gastroenterology in the future. We conclude that, to date, data security and proof of efficacy are not yet given in currently available mobile health apps.

Systematic evaluation of content and quality of English and German pain apps in European app stores

BACKGROUND AND OBJECTIVE

Pain spans a broad spectrum of diseases and types that are highly prevalent and cause substantial disease burden for individuals and society. Up to 40% of people affected by pain receive no or inadequate treatment. Providing a scalable, time-, and location-independent way for pain diagnostic, management, prevention and treatment mobile health applications (MHA) might be a promising approach to improve health care for pain. However, the commercial app market is rapidly growing and unregulated, resulting in an opaque market. Studies investigating the content, privacy and security features, quality and scientific evidence of the available apps are highly needed, to guide patients and clinicians to high quality MHA.Contributing to this challenge, the present study investigates the content, quality, and privacy features of pain apps available in the European app stores.

METHODS

An automated search engine was used to identify pain apps in the European Google Play and Apple App store. Pain apps were screened and checked for systematic criteria (pain-relatedness, functionality, availability, independent usability, English or German). Content, quality and privacy features were assessed by two independent reviewers using the German Mobile Application Rating Scale (MARS-G). The MARS-G assesses quality on four objectives (engagement, functionality, aesthetics, information quality) and two subjective scales (perceived impact, subjective quality).

RESULTS

Out of 1034 identified pain apps 218 were included. Pain apps covered eight different pain types. Content included basic information, advice, assessment and tracking, and stand-alone interventions. The overall quality of the pain apps was average M = 3.13 (SD = 0.56, min = 1, max = 4.69). The effectiveness of less than 1% of the included pain apps was evaluated in a randomized controlled trial. Major problems with data privacy were present: 59% provided no imprint, 70% had no visible privacy policy.

CONCLUSION

A multitude of pain apps is available. Most MHA lack scientific evaluation and have serious privacy issues, posing a potential threat to users. Further research on evidence and improvements privacy and security are needed. Overall, the potential of pain apps is not exploited.

Validation of the Mobile Application Rating Scale (MARS)

BACKGROUND

Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Instruments for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity.

OBJECTIVE

This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.

METHODS

Data was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation.

RESULTS

In total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (RMSEA = 0.074, TLI = 0.922, CFI = 0.940, SRMR = 0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC = 0.82). MARS correlated with ENLIGHT (ps<.05).

CONCLUSION

The metric evaluation of the MARS demonstrated its suitability for the quality assessment. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS.