Evaluation of Clinical Symptoms Improvement by Cognitive Behavioral Therapy Using a Smartphone Application in Patients with Temporomandibular Disorder.

Since the start of the 2019 coronavirus pandemic, interest in digital therapeutics (DTx) has increased. Temporomandibular disorder (TMD) fundamentally requires cognitive behavioral therapy (CBT), including physical self-regulation. An application that records TMD pain and parafunctional activities for CBT has recently been developed. However, evidence of the reduction of clinical symptoms in patients via repetitive software-driven CBT is lacking. The purpose of the present study was to evaluate the impact of applications that support CBT regarding the performance of CBT and the improvement of clinical symptoms in temporomandibular joint patients. From 20 October 2020 to 7 January 2021, we randomly assigned 41 participants diagnosed with TMD to control (conventional treatment) and experimental (conventional treatment + application use) groups. We randomly assigned 41 participants diagnosed with TMD to control (conventional treatment) and experimental (conventional treatment + application use) groups. Improvements regarding the number of tender points, mouth opening, visual analog scale score, pain level upon palpation, joint sound, and stress were compared between the two groups. Compared with the control group, the experimental group showed significant improvements in the number of tender points and degree of mouth opening. They also showed improvements in pain level, joint sound, and locking, although not statistically significantly, as compared with the control group. Thus, further studies with a greater sample size need to be conducted to confirm the findings. Nevertheless, our results showed that repetitive cognitive behavioral therapy using a smartphone application can be used as digital therapeutics for temporomandibular disorder patients.

Efficacy of distance training program for cardiopulmonary resuscitation utilizing smartphone application and home delivery system.

AIM OF THE STUDY: Community cardiopulmonary resuscitation (CPR) education is important for laypersons. However, during the COVID-19 pandemic, with social distancing, conventional face-to-face CPR training was unavailable. We developed a distance learning CPR training course (HEROS-Remote) using a smartphone application that monitors real-time chest compression quality and a home delivery collection system for mannikins. This study aimed to evaluate the efficacy of the HEROS-Remote course by comparing chest compression quality with that of conventional CPR training. METHODS: We applied layperson CPR education with HEROS-Remote and conventional education in Seoul during the COVID-19 pandemic. Both groups underwent a 2-min post-training chest compression test, and we tested non-inferiority. Chest compression depth, rate, complete recoil, and composite chest compression score was measured. Trainees completed a satisfaction survey on CPR education and delivery. The primary outcome was the mean chest compression depth. RESULTS: A total of 180 trainees were enrolled, with 90 assigned to each training group. Chest compression depth of HEROS-Remote training showed non-inferiority to that of conventional training (67.4 vs. 67.8, p = 0.78), as well as composite chest compression score (92.7 vs. 95.5, p = 0.16). The proportions of adequate chest compression depth, chest compression rate, and chest compressions with complete chest recoil were similar in both training sessions. In the HEROS-Remote training, 90% of the trainees were satisfied with CPR training, and 96% were satisfied with the delivery and found it convenient. CONCLUSION: HEROS-Remote training was non-inferior to conventional CPR training in terms of chest compression quality. Distance learning CPR training using a smartphone application and mannikin delivery had high user satisfaction and was logistically feasible.

Stress Data Collection and Analysis Using 'Mind Scale' with the Post-Covid World

In this paper, stress data collection and analysis using 'Mind Scale™' is proposed. A fingertip pulse wave sensor module is utilized along a smartphone application. Biological signals such as pulse, voice and facial expression are analyzed with questionnaire and managed in the cloud. With the post-covid world, this system helps us to detect our mental health condition for new lifestyle. © 2023 IEEE.

Can wrist-worn devices and a smartphone application influence arm activity in children with unilateral cerebral palsy? A proof-of-concept study.

Aim: To determine whether a wrist-worn triaxial accelerometer-based device and software (including smartphone application), incorporating feedback, is feasible, acceptable, and can lead to increased affected upper limb use during everyday activities in children with unilateral cerebral palsy (UCP). Methods: Study design: Mixed methods proof of concept study. Participants: Children aged 8-18 years with UCP; age-matched typically developing controls ("Buddies"), therapists. Intervention: Baseline (2 weeks): devices recorded arm activity. Active feedback (6 weeks): devices also gave vibratory prompts if affected arm activity fell below pre-set personalised thresholds (UCP group only; control group continued as per Baseline). Final 2 weeks: as baseline. Both groups accessed a smartphone application providing feedback on relative arm motion throughout the study. Assessment and analysis: ABILHAND-Kids questionnaires and MACS classifications captured baseline participant characteristics (UCP group). Accelerometer data was used to calculate relative arm activity (signal vector magnitude) corrected for time worn/day, and trends in relative arm activity examined using single case experimental design (both groups). In-depth interviews with families, "Buddies" and therapists assessed feasibility and acceptability of implementation. A framework approach was used for qualitative data analysis. Results: We recruited 19 participants with UCP; 19 buddies; and 7 therapists. Five participants (two with UCP) did not complete the study. Baseline mean (stdev) ABILHAND-Kids score of children with UCP who completed the study was 65.7 (16.2); modal MACS score was II.Qualitative analysis demonstrated acceptability and feasibility of the approach. Active therapist input for this group was minimal. Therapists appreciated the potential for summary patient data to inform management. Arm activity in children with UCP increased in the hour following a prompt (mean effect size z = 0.261) for the non-dominant hand, and the dominant hand (z = 0.247). However, a significant increase in affected arm activity between baseline and intervention periods was not demonstrated. Discussion: Children with UCP were prepared to wear the wristband devices for prolonged periods. Whilst arm activity increased bilaterally in the hour following a prompt, increases were not sustained. Delivery of the study during the COVID-19 pandemic may have negatively influenced findings. Technological challenges occurred but could be overcome. Future testing should incorporate structured therapy input.

Evaluation of a Smartphone Application for Self-Rehabilitation after Anterior Cruciate Ligament Reconstruction during a COVID-19 Lockdown.

BACKGROUND: Rehabilitation after surgery is a crucial process that governs the final functional outcome. The self-rehabilitation smartphone application Doct'up (Healing SAS, Lyon, France) is designed for patients who have had anterior cruciate ligament (ACL) reconstruction surgery. In France in the spring of 2020, the lockdown mandated due to the COVID-19 pandemic prevented patients from seeing their physiotherapists for 2 months. The objective of this study was to compare the clinical outcomes in two groups of patients who underwent ACL reconstruction surgery: in one group, surgery performed before the lockdown was followed by standard in-person physiotherapy while, in the other, surgery was done just before the lockdown and rehabilitation was performed by the patients themselves using the phone application. HYPOTHESIS: Using a self-rehabilitation smartphone app limits the negative effects of not receiving physiotherapist rehabilitation after ACL reconstruction. MATERIAL AND METHODS: We performed a case-control study involving the retrospective analysis of prospectively collected data from two groups of patients who had undergone ACL reconstruction surgery. Patients in the App group had surgery just before the 2-month COVID-19-related lockdown that started in France on March 17, 2020,and used only the smartphone app for rehabilitation. The standard-care group was composed of matched controls who had surgery 1 year before the cases and received rehabilitation therapy during in-person physiotherapist visits. The ACL reconstruction technique was the same in the two groups. The primary outcome measure was extension lag 6 weeks after surgery. The secondary outcome measures were extension lag 3 weeks and 6 months after surgery, quadriceps muscle activation, knee extension locking 3 and 6 weeks after surgery, and the 6-month rate of surgical revision for cyclops syndrome. RESULTS: We included 32 cases managed using only self-rehabilitation guided by the phone app, and we identified 101 matched controls managed using standard care. We found no significant between-group difference in extension lag after 6 weeks: 9.4% (28/32) vs. 4.6% (87/101), p=0.39. After 3 weeks, the App group had a higher proportions of patients with quadriceps activation (94% [30/32] vs. 73% [74/101], p=0.015) and extension control using canes (78.1% [25/32] vs. 40.6% [41/101], p=0.0002). None of the other measured outcomes differed significantly between the two groups (extension lag after 3 weeks: 12.5% [4/32] vs. 13.8% 14/101]; extension lag after 6 months: 3.2% [1/32] vs. 1% [1/101]; quadriceps activation after 6 weeks: 97% [31/32] vs. 99% [100/101]; extension locking with canes after 6 weeks: 96.9% [31/32] vs. 93.1% [94/101]; extension locking without canes after 3 weeks: 53.2% [17/32] vs. 47.5% [48/101]; extension locking without canes after 6 weeks: 93.7% [30/32] vs. 82.2% [83/101]; and surgery for cyclops syndrome (3.1% [1/32] vs. 1% [1/101]). DISCUSSION: The use of a self-rehabilitation phone app after ACL reconstruction during a COVID-19 lockdown limited the adverse effects of not receiving in-person physiotherapy. The 6-month outcomes were similar to those seen with standard rehabilitation. The study results demonstrate the usefulness of self-rehabilitation after ACL reconstruction surgery. Self-rehabilitation guided by a phone app could be used as a complement to the protocols generally applied by physiotherapists. LEVEL OF EVIDENCE: IV, single-centre retrospective case-control study.

Poster: Preliminary Outcomes of a Culturally Tailored Mindfulness Mobile App for Mental Health within Underserved African American Communities During COVID-19

This poster presents preliminary findings from a study in progress, which indicate that a specially-designed mobile app can serve as a viable delivery system for a mindfulness-based stress reduction (MBSR) intervention for historically underserved and minority communities experiencing mental health effects of worry and stress during the COVID-19 pandemic. Our early data suggest that the app is well-received and usable for the target population and serves as an effective delivery platform for MBSR interventions for underserved and minority communities. © 2022 ACM.

Understanding user concerns and choice of app architectures in designing Audio-based mHealth Apps

Due to recent advancements in smartphone sensing and computing capabilities, artificially intelligent mobile health (mHealth) applications are getting popular to monitor a range of diseases, including coronavirus-caused COVID-19 disease, chronic obstructive pulmonary disease (COPD), asthma, bronchitis, emphysema, and sleep apnea, among many others utilizing the audio recordings obtained from the smartphone microphones. Compared to other mHealth apps, audio-based apps suffer from various user concerns, including the privacy of data and battery drain rate, among many other concerns, which can adversely affect the user compliance, and app utility and life cycle. To address user concerns, mHealth apps should provide users options to configure the app, i.e., choose an architecture from a set of options based on user concerns and preferences. However, there is a dearth of knowledge about audio-based health monitoring app design. In this work, we present a focused user-centric app design study to better understand various concerns and choices that users want to see in an audio-based mHealth app. From a detailed analysis of 60 subjects with varying backgrounds, we find that around 85% subjects are concerned about the privacy of data and 93% subjects prefer to pick an app architecture that will not send raw audio recordings to a server. Findings from this work can guide the design of future mHealth apps that utilizes privacy-sensitive audio data.

Decision-Making in the Pediatric Emergency Department-A Survey of Guidance Strategies among Residents.

(1) Introduction: Working in an emergency department requires fast and straightforward decisions. Therefore, decision guidance represents an essential tool for successful patient-centered care. Beyond the residents' own knowledge and experience, printed books have been the primary source of information in the past. The aim of this study was to discover which strategies current residents use the most and to identify alternative quick reference strategies in the digital age. (2) Materials and Methods: This study analyzed the responses of a short questionnaire directed at 41 residents in a single pediatric emergency department (32 pediatric and 9 pediatric surgery residents) over a period of one month. (3) Results: Thirty-three (80.5%) residents answered the entire questionnaire. Strikingly, responses indicated that printed books are still pivotal in guiding decision-making. In addition, the acquisition of information via computers or smartphones plays an increasing role. However, the opinion and council of the attending physician is still of great value to the residents and is not to be underestimated. Overall, most of the residents would prefer to have access to a specially designed smartphone application. (4) Conclusions: Certainty and validity are essential in decision-making in a pediatric emergency department. Although printed books and attending physicians are still considered as reliable sources of information, internet-based information plays an increasing role. In order to provide the best up-to-date and most recent information, a validated and consistently updated smartphone application could be a useful option.

Evaluating the Efficacy of the Drinks:Ration Mobile App to Reduce Alcohol Consumption in a Help-Seeking Military Veteran Population: Randomized Controlled Trial.

BACKGROUND: Alcohol misuse is higher in the UK armed forces (AF) than in the general population. Research demonstrates that alcohol misuse persists after an individual leaves service, and this is notably the case for those who are seeking help for a mental health difficulty. Despite this, there is no work on testing a mobile alcohol reduction intervention that is personalized to support the UK AF. OBJECTIVE: To address this gap, we investigated the efficacy of a 28-day brief alcohol intervention delivered via a mobile app in reducing weekly self-reported alcohol consumption among UK veterans seeking help for mental health difficulties. METHODS: We performed a 2-arm participant-blinded randomized controlled trial (RCT). We compared a mobile app that included interactive features designed to enhance participants' motivation and personalized messaging (intervention arm) with a version that provided government guidance on alcohol consumption only (control arm). Adults were eligible if they had served in the UK AF, were currently receiving or had received clinical support for mental health symptoms, and consumed 14 units (approximately 112 g of ethanol) or more of alcohol per week. Participants received the intervention or the control mobile app (1:1 ratio). The primary outcome was a change in self-reported weekly alcohol consumption between baseline and day 84 assessed using the validated Timeline Follow Back for Alcohol Consumption (TLFB) (prior 7 days), with a secondary outcome exploring self-reported change in the Alcohol Use Disorder Identification Test (AUDIT) score. RESULTS: Between October 2020 and April 2021, 2708 individuals were invited to take part, of which 2531 (93.5%) did not respond, 54 (2%) were ineligible, and 123 (4.5%) responded and were randomly allocated (62, 50.4%, intervention; 61, 49.6%, control). At day 84, 41 (66.1%) participants in the intervention arm and 37 (60.7%) in the control arm completed the primary outcome assessment. Between baseline and day 84, weekly alcohol consumption reduced by -10.5 (95% CI -19.5 to -1.5) units in the control arm and -28.2 (95% CI -36.9 to -19.5) units in the intervention arm (P=.003, Cohen d=0.35). We also found a significant reduction in the AUDIT score of -3.9 (95% CI -6.2 to -1.6) in the intervention arm (Cohen d=0.48). Our primary and secondary effects did not persist over the longer term (day 168). Two adverse events were detected during the trial. CONCLUSIONS: This study examined the efficacy of a fully automated 28-day brief alcohol intervention delivered via a mobile app in a help-seeking sample of UK veterans with hazardous alcohol consumption. We found that participants receiving Drinks:Ration reduced their alcohol consumption more than participants receiving guidance only (at day 84). In the short term, we found Drinks:Ration is efficacious in reducing alcohol consumption in help-seeking veterans. TRIAL REGISTRATION: ClinicalTrials.gov NCT04494594; https://tinyurl.com/34em6n9f. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19720.

A smartphone application of diabetes coaching intervention to prevent the onset of complications and to improve diabetes self-management: A randomized control trial.

BACKGROUND AND AIM: Diabetes mellitus (DM) has been a worldwide public health problem during the last two decades. To examine the effect of a smartphone application of diabetes coaching intervention on improving self-management behaviors and preventing onset diabetes complications. METHODS: A randomized control trial, two groups, pre-test, and post-test design with a non-equivalent control group was conducted. The intervention group received a 12-week smartphone application of diabetes coaching intervention to improve diabetes self-management behaviors and to prevent onset diabetes complications. While the control group received the usual care from the community health centers. The smartphone application consisted of narrative App-based coaching, a printed user guide, mindfulness-based coaching; skill-based coaching, and a small App-interaction. RESULTS: After implementation, the self-management behaviors among the experimental group were improved than the control group in terms of dietary control, physical exercise, blood glucose monitoring, medication adherence, and screening of complications. The clinical outcomes were also significantly improved among the experimental group and to the control group. CONCLUSIONS: A smartphone application-based diabetes coaching intervention was feasible to apply as a nationwide program to promote diabetes self-management (DSM) during the covid-19 pandemic.

Development of smartphone application for personalized physical fitness education for university students in COVID-19 pandemic era

Online distance learning during the COVID-19 pandemic can impact decreasing physical activity and increasing sedentary behaviour, leading to the reduced physical fitness of students. The research aims to develop an android application (app) to assist students in developing physical fitness independently. Four stages of development have been carried out to create the Mahasiswa Bugar application. The advantages of the Mahasiswa Bugar app are as a guide to measuring physical fitness that can be done by students themselves and based on existing literature. Physical fitness test items guided through this application are health-related fitness, body composition, cardiorespiratory fitness, muscle strength and endurance, and flexibility, including features for feedback, history or recording of test results and training program. The results of the quasi-experiment show that the percentage of student involvement in vigorous physical activity has increased. Although the fit student android application's socialization did not significantly impact increasing the intensity of physical activity and motivation to train, this application could be a solution for students in fostering physical fitness independently during the COVID-19 pandemic. © 2021 University of Kuwait. All rights reserved.

Digitalizing Gratitude and Building Trust through Technology in a Post-COVID-19 World—Report of a Case from Japan

Employee engagement has become a critical issue in Japanese companies. One way to develop it is to improve the relationship among employees through gratitude expressions. In the post-COVID-19 remote work environment, digital devices are essential. This paper confirms that expressions of gratitude delivered via digital devices enhance the relationship between employees. We experimented in a small-town government office where participants (n = 88) were asked to (1) use the Thanks App, an app we developed to express gratitude, for two months and (2) respond to an engagement survey we developed before and after the experimental period. Through cross-analysis of the data from the app and questionnaire, we found that the “trust in colleagues” factor had a strong correlation (r = 0.80, p < 0.001) with our new index computed by the app’s data. The results suggest that the use of the Thanks App may help visualize the trust relationship among teams. This study has a practical value in providing a new team management tool for visualizing team trust. In addition, it provides a new research method for emotional and social psychology using digital devices. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Impact of COVID-19 pandemic on migraine management in the United States: insights from migraine tracking app users.

BACKGROUND: The nature of COVID-19 pandemic measures has altered the clinical management of migraine, and has also created barriers to evaluate the impact of such measures of migraine patients. Using the Migraine Buddy smartphone application, we assessed the impact of the COVID-19 pandemic on migraine in users residing in the United States. METHODS: Migraine Buddy is a smartphone application by individuals to record their migraine headache episodes, characteristics, and coping mechanisms. For this study, anonymized self-reported data from 163,176 adult Migraine Buddy users in the United States between January 2020 and May 2020, were analyzed for migraines associated with stress. A stress-related migraine is defined as one in which stress or anxiety was reported as a trigger or symptom. A questionnaire on the impact of COVID-19 on migraine and its management was also completed by 923 users from the United States in the app between April 2020 and May 2020. RESULTS: 88% of the Migraine Buddy database extract and 84% of the respondents are female, with a mean age of 36.2 years. The proportion of stress-related migraine attacks peaked at 53% on March 21 to 23, although the number of migraine attacks decreased. This followed the declaration of the COVID-19 national emergency on March 13 and a spike in the number of COVID-19 cases in the United States. Questionnaire respondents felt that the following added more stress: social isolation (22.6%), information overdose (21.2%), access to essentials (food, medication, etc.) (18.7%), and financial concerns (17.8%). To help manage migraine during COVID-19, respondents suggested stress and diet coaching programs and resources (medical articles, etc.) (34.0%), having the option for home delivery of medication (30.6%) and tele-consulting (25.5%). CONCLUSION: Here, we report the change in the proportion of self-reported stress-related migraine in relation to evolution of the COVID-19 pandemic, as well as its impact of migraine management. Our data will help increase the understanding of patients' needs and help with planning and execution of mitigating strategies.

The association between problematic internet use, psychological distress, and sleep problems during COVID-19.

The implementation of mandatory stay-at-home and isolation policies during the COVID-19 pandemic has resulted in people relying more on smartphone use to obtain the latest developments regarding the pandemic, interact with people, and for entertainment. Unfortunately, as people spend more time participating in Internet activities, they are more likely to encounter problematic internet use (PIU) issues. The main purpose of this study was to examine the association between two kinds of PIU [problematic smartphone use (PSU) and problematic social media use (PSMU)], psychological distress, and sleep problems. In addition, the moderating effect of sleep problems was examined. A total of 11014 school teachers completed the online survey. The participants were divided into two (high and low sleep problem) groups, according to the severity of their sleep problems, for comparison. The research conducted a comparison between the degree of PIU and psychological distress, and then provided correction for the two groups separately. The results indicated that the high sleep problem group exhibited significantly greater psychological distress [mean (SD) = 12.94 (11.29)] than the low sleep problem group [(mean (SD) = 3.42 (6.57)]. Both PSU and PSMU were positively correlated with psychological distress in the two groups. The moderating effect of sleep problems was supported and PSMU was more harmful to psychological distress in the high sleep problem group, while the effect of PSU on psychological distress was not significantly different between the two groups.

A preliminary analysis of AI based smartphone application for diagnosis of COVID-19 using chest X-ray images.

The COVID-19 outbreak has catastrophically affected both public health system and world economy. Swift diagnosis of the positive cases will help in providing proper medical attention to the infected individuals and will also aid in effective tracing of their contacts to break the chain of transmission. Blending Artificial Intelligence (AI) with chest X-ray images and incorporating these models in a smartphone can be handy for the accelerated diagnosis of COVID-19. In this study, publicly available datasets of chest X-ray images have been utilized for training and testing of five pre-trained Convolutional Neural Network (CNN) models namely VGG16, MobileNetV2, Xception, NASNetMobile and InceptionResNetV2. Prior to the training of the selected models, the number of images in COVID-19 category has been increased employing traditional augmentation and Generative Adversarial Network (GAN). The performance of the five pre-trained CNN models utilizing the images generated with the two strategies has been compared. In the case of models trained using augmented images, Xception (98%) and MobileNetV2 (97.9%) turned out to be the ones with highest validation accuracy. Xception (98.1%) and VGG16 (98.6%) emerged as models with the highest validation accuracy in the models trained with synthetic GAN images. The best performing models have been further deployed in a smartphone and evaluated. The overall results suggest that VGG16 and Xception, trained with the synthetic images created using GAN, performed better compared to models trained with augmented images. Among these two models VGG16 produced an encouraging Diagnostic Odd Ratio (DOR) with higher positive likelihood and lower negative likelihood for the prediction of COVID-19.

Characterizing Breakthrough Cancer Pain Using Ecological Momentary Assessment with a Smartphone App: Feasibility and Clinical Findings.

BACKGROUND: mobile applications (apps) facilitate cancer pain ecological momentary assessment (EMA) and provide more reliable data than retrospective monitoring. The aims of this study are (a) to describe the status of persons with cancer pain when assessed ecologically, (b) to analyze the utility of clinical alarms integrated into the app, and (c) to test the feasibility of implementing an app for daily oncological pain monitoring. METHODS: in this feasibility study, 21 patients (mean age = 56.95 years, SD = 10.53, 81.0% men) responded to an app-based evaluation of physical status (baseline and breakthrough cancer pain (BTcP)) and mental health variables (fatigue, mood, and coping) daily during 30 days. RESULTS: cancer pain characterization with the app was similar to data from the literature using retrospective assessments in terms of BTcP duration and perceived medication effectiveness. However, BTcP was less frequent when evaluated ecologically. Pain, fatigue, and mood were comparable in the morning and evening. Passive coping strategies were the most employed daily. Clinical alarms appear to be useful to detect and address adverse events. App implementation was feasible and acceptable. CONCLUSION: apps reduce recall bias and facilitate a rapid response to adverse events in oncological care. Future efforts should be addressed to integrate EMA and ecological momentary interventions to facilitate pain self-management via apps.

Using artificial intelligence to improve COVID-19 rapid diagnostic test result interpretation.

Serological rapid diagnostic tests (RDTs) are widely used across pathologies, often providing users a simple, binary result (positive or negative) in as little as 5 to 20 min. Since the beginning of the COVID-19 pandemic, new RDTs for identifying SARS-CoV-2 have rapidly proliferated. However, these seemingly easy-to-read tests can be highly subjective, and interpretations of the visible "bands" of color that appear (or not) in a test window may vary between users, test models, and brands. We developed and evaluated the accuracy/performance of a smartphone application (xRCovid) that uses machine learning to classify SARS-CoV-2 serological RDT results and reduce reading ambiguities. Across 11 COVID-19 RDT models, the app yielded 99.3% precision compared to reading by eye. Using the app replaces the uncertainty from visual RDT interpretation with a smaller uncertainty of the image classifier, thereby increasing confidence of clinicians and laboratory staff when using RDTs, and creating opportunities for patient self-testing.

A Systematic Review of Smartphone Applications Available for Corona Virus Disease 2019 (COVID19) and the Assessment of their Quality Using the Mobile Application Rating Scale (MARS).

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.