Evaluation of a Free Public Smartphone Application to Detect Leukocoria in High-Risk Children Aged 1 to 6 Years

Clinical Utility of Smartphone Applications in Ophthalmology: A Systematic Review

Topic

Numerous smartphone applications have been devised for diagnosis, treatment, and symptom management in ophthalmology. Despite the importance of systematic evaluation of the purpose, target disease, effectiveness, and utility of smartphone applications to their effective utilization, few studies have formally evaluated their validity, reliability, and clinical utility.

Clinical Relevance

This report identifies smartphone applications with potential for clinical implementation in ophthalmology and summarizes the evidence on their practical utility.

Methods

We searched PubMed and EMBASE on July 28, 2022, for articles reporting original data on the effectiveness of treatment, disease detection, diagnostic accuracy, disease monitoring, and usability of smartphone applications in ophthalmology published between January 1, 1987, and July 25, 2022. Their quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist.

Results

The initial search yielded 510 articles. After removing 115 duplicates and 285 articles based on inclusion and exclusion criteria, the full texts of the remaining 110 articles were reviewed. Furthermore, 71 articles were included in the final qualitative synthesis. All studies were determined to be of high (87.3%) or moderate (12.7%) quality. In terms of respective application of interest, 24 (33.8%) studies assessed diagnostic accuracy, 17 (23.9%) assessed disease detection, and 3 (4.2%) assessed intervention efficacy. A total of 48 smartphone applications were identified, of which 27 (56.3%) were publicly available. Seventeen (35.4%) applications included functions for ophthalmic examinations, 13 (27.1%) included functions aimed at disease detection, 10 (20.8%) included functions to support medical personnel, five (10.4%) included functions related to disease education, and three (6.3%) included functions to promote treatment adherence for patients. The largest number of applications targeted amblyopia (18.8%), followed by retinal disease (10.4%). Two (4.2%) smartphone applications reported significant efficacy in treating diseases.

Conclusion

In this systematic review, a comprehensive appraisal is presented on studies related to diagnostic accuracy, disease detectability, and efficacy of smartphone applications in ophthalmology. Forty-eight applications with potential clinical utility are identified. Appropriate smartphone applications are expected to enable early detection of undiagnosed diseases via telemedicine and prevent visual dysfunction via remote monitoring of chronic diseases.

Financial Disclosures

Proprietary or commercial disclosure may be found after the references.

Home-based screening tools for amblyopia: a systematic review

Amblyopia is an important public health concern. While home-based screening may present an effective solution, this has not been rigorously assessed in a systematic review. A systematic review was performed using Ovid MEDLINE, PubMed, The Cochrane Library, Embase, Web of Science Core Collection, and Clinicaltrials.gov. All studies reporting the diagnostic accuracy of home-based screening tools for amblyopia among children were included. Studies involving orthoptist or ophthalmologist-led screening and adult subjects were excluded. The main outcome measure was the diagnostic accuracy expressed as sensitivity and specificity. Among 3670 studies identified, 28 were eligible for inclusion in our systematic review. The age range of patients were less than 1 month to 16 years old. 7 studies used internet-based tools, 16 used smartphone/tablet applications, 3 used digital cameras, and 3 used home-based questionnaires and visual acuity tools. All studies included a reference standard except one, which was a longitudinal study. 21 studies had full ophthalmological examination whilst 6 studies had validated visual acuity measurement tools as gold standards. Of the 27 studies which compared against a reference test, only 25 studies reported sensitivity and specificity values. Using the QUADAS-2 tool, 50% of studies were deemed to have applicability concern due to patient selection from tertiary centres and unclear methods for recruitment. There is a need to improve the quality of diagnostic accuracy studies, standardise thresholds for detecting amblyopia, and ensure consistent reporting of results. Further research is needed to evaluate the suitability of these tools for amblyopia screening.

Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis

The coronavirus disease (COVID-19) pandemic has emphasized the paucity of non-contact and non-invasive methods for the objective evaluation of dry eye disease (DED). However, robust evidence to support the implementation of mHealth- and app-based biometrics for clinical use is lacking. This study aimed to evaluate the reliability and validity of app-based maximum blink interval (MBI) measurements using DryEyeRhythm and equivalent traditional techniques in providing an accessible and convenient diagnosis. In this single-center, prospective, cross-sectional, observational study, 83 participants, including 57 with DED, had measurements recorded including slit-lamp-based, app-based, and visually confirmed MBI. Internal consistency and reliability were assessed using Cronbach's alpha and intraclass correlation coefficients. Discriminant and concurrent validity were assessed by comparing the MBIs from the DED and non-DED groups and Pearson's tests for each platform pair. Bland-Altman analysis was performed to assess the agreement between platforms. App-based MBI showed good Cronbach's alpha coefficient, intraclass correlation coefficient, and Pearson correlation coefficient values, compared with visually confirmed MBI. The DED group had significantly shorter app-based MBIs, compared with the non-DED group. Bland-Altman analysis revealed minimal biases between the app-based and visually confirmed MBIs. Our findings indicate that DryEyeRhythm is a reliable and valid tool that can be used for non-invasive and non-contact collection of MBI measurements, which can assist in accessible DED detection and management.

Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis

Background

Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health.

Objective

This paper aims to explore research trends, coauthorship networks, and the research hot spots of mobile health app research.

Methods

Publications related to mobile health apps were retrieved and extracted from the Web of Science database with no language restrictions. Bibliographic Item Co-Occurrence Matrix Builder was employed to extract bibliographic information (publication year and journal source) and perform a descriptive analysis. We then used the VOSviewer (Leiden University) tool to construct and visualize the co-occurrence networks of researchers, research institutions, countries/regions, citations, and keywords.

Results

We retrieved 2802 research papers on mobile health apps published from 2000 to 2019. The number of annual publications increased over the past 19 years. JMIR mHealth and uHealth (323/2802, 11.53%), Journal of Medical Internet Research (106/2802, 3.78%), and JMIR Research Protocols (82/2802, 2.93%) were the most common journals for these publications. The United States (1186/2802, 42.33%), England (235/2802, 8.39%), Australia (215/2802, 7.67%), and Canada (112/2802, 4.00%) were the most productive countries of origin. The University of California San Francisco, the University of Washington, and the University of Toronto were the most productive institutions. As for the authors’ contributions, Schnall R, Kuhn E, Lopez-Coronado M, and Kim J were the most active researchers. The co-occurrence cluster analysis of the top 100 keywords forms 5 clusters: (1) the technology and system development of mobile health apps; (2) mobile health apps for mental health; (3) mobile health apps in telemedicine, chronic disease, and medication adherence management; (4) mobile health apps in health behavior and health promotion; and (5) mobile health apps in disease prevention via the internet.

Conclusions

We summarize the recent advances in mobile health app research and shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance on future research directions and perspectives in this rapidly developing field.