Review and content analysis of mobile apps for inflammatory bowel disease management using the mobile application rating scale (MARS): Systematic search in app stores.

BACKGROUND: People with inflammatory bowel disease (IBD) need tools for self-management of their disease with the ultimate goal of improving medication adherence and health outcomes. Mobile apps represent a novel opportunity to provide self-management for patients with IBD. Many mobile apps have been developed for IBD self-management, but more evidence is needed about the quality of these mobile apps. OBJECTIVE: This study evaluated mobile apps developed for the IBD community and rated the quality of these apps to provide a roadmap for future development. MATERIALS AND METHODS: The Apple App Store and Google Play Store were systematically searched to identify IBD mobile apps for patients and physicians based on the IBD-related keywords. We included mobile apps that focus on IBD, are in the English language, and are free. The related app quality was evaluated independently by two reviewers using the Mobile Application Rating Scale (MARS). RESULTS: We identified 401 mobile apps. After removing duplicates and unrelated apps, 44 apps were included in the review. Overall, the mean MARS scores were 3.5 (SD = 0.5) on a scale from 1.00 to 5.00, which was the acceptable range.; 12 apps got scores ≥ 4.00. The highest mean domain score belonged to the functionality dimension (mean = 3.9, SD = 0.6) and the lowest belonged to the engagement dimension (mean = 3.2, SD = 0.8). CONCLUSION: The MARS ratings showed that the IBD mobile apps quality meet acceptable criteria. However, more attention must be paid to design features that improve user interest and engagement, especially among children and adolescents. Healthcare professional involvement is crucial for designing mobile health apps.

Rumor surveillance methods in outbreaks: A systematic literature review.

Background: The spreading of health-related rumors can profoundly put society at risk, and the investigation of strategies and methods can efficiently prevent the dissemination of hazardous rumor is necessary, especially during a public health emergency including disease outbreaks. In this article we review the studies that implicated the surveillance system in identifying rumors and discuss the different aspects of current methods in this field. Methods: We searched PubMed, EMBASE, Scopus, and Web of Science databases for relevant publications in English from 2000 to 2020. The PICOS approach was used to select articles, and two reviewers extracted the data. Findings were categorized as a source of rumors, type of systems, data collection, and data transmission methods. The quality of the articles was assessed using the Mixed Method Appraisal Tool (MMAT) checklist. Results: Five studies that presented the methods used for rumor detection in different outbreaks were included in the critical appraisal process. Findings were grouped into four categories: source of rumors, type of systems, data collection, and data transmission methods. The source of rumors in most studies was media, including new social and traditional media. The most used data collection methods were human-computer interaction technique, and automatic and manual methods each were discussed in one study. Also, the data transmission method was asynchronous in the majority of studies. Conclusion: Based on our findings, the most common rumor detection systems used in the outbreaks were manual and/or human-computer methods which are considered to be time-consuming processes. Due to the ever-increasing amount of modern social media platforms and the fast-spreading of misinformation in the times of outbreaks, developing the automatically and real-time tools for rumor detection is a vital need.

A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS).

The expansion of mobile health apps for the management of COVID-19 grew exponentially in recent months. However, no study has evaluated these apps. The objective of this study was to develop a reliable measure and rate the quality of COVID-19 mobile health apps, to eventually provide a roadmap for future mHealth app development. In this study, we used COVID-related keywords to identify apps for iOS and Android devices. 13 apps (13.5% of the total number of apps identified) were selected for evaluation. App quality was assessed independently using MARS by two reviewers. Search queries yielded a total of 97 potentially relevant apps, of which 13 met our final inclusion criteria. Kendall's coefficient of concordance value for the inter-rater agreement was 0.93 (p = .03). COVID-19 GOV PK app had the highest average MARS score (4.7/5), and all of the apps had acceptable MARS scores (> 3.0). This study suggests that most COVID-related apps meet acceptable criteria for quality, content, or functionality, and they must highlight esthetic and interesting features for overall quality improvement to be welcomed by users.