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1.
JMIR Mhealth Uhealth ; 10(11): e41689, 2022 Nov 07.
Article in English | MEDLINE | ID: covidwho-2109576

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, the general public was concerned about the mental health impacts of unemployment due to COVID-19 and the stress essential workers experienced during this time. Several reports indicated that people in distress were turning to digital technology, but there was little evidence about the impact of these tools on mitigating distress. OBJECTIVE: This study seeks to determine the acceptability, feasibility, usability, and effectiveness of mobile mental health apps for decreasing mental health symptoms in essential workers and unemployed individuals with suicide risk. METHODS: We recruited participants who indicated that they were unemployed because of COVID-19 or were COVID-19-designated essential workers. Participants were randomized to 1 of 4 free commercial mobile apps for managing distress that were (1) highly rated by PsyberGuide and (2) met the criteria for intervention features these participants indicated were desirable in a previous survey. Participants used the apps for 4 weeks and completed baseline and 4-week self-assessments of depression, anxiety emotional regulation, and suicide risk. RESULTS: We found no differences between the apps in any outcome but did find significant changes in depression and anxiety over time (Patient Health Questionnaire [PHQ]-9: estimate=-1.5, SE 0.2, 95% CI -1.1 to -1.8, P<.001; Generalized Anxiety Disorder Scale [GAD]-7: estimate=-1.3, SE 0.2, 95% CI -1.0 to -1.6, P<.001). We found no significant changes in suicidal behavior (Suicide Behaviors Questionnaire-Revised [SBQ-R]) or emotional regulation (Difficulties in Emotion Regulation Scale - Short Form [DERS-SF]) for the 4 weeks. We did find a significant dose-response pattern for changes in depression and anxiety. Using the app at least once a week resulted in greater improvements in treatment conditions over time on depression (estimate=-0.6, SE 0.2, 95% CI 1.0-0.2, P=.003) and anxiety (estimate=0.1, SE 0.2, 95% CI 0.4-0.6, P=.78). There was no association between app frequency and changes in suicidal behavior (SBQ-R) or emotional regulation (DERS-SF). We further found a significant difference between the conditions with regard to app usability, with the control app being the most usable (meanBeautiful Mood 72.9, SD 16.7; meanCOVID Coach 71.2, SD 15.4; meanCalm 66.8, SD 17.3; mean7 Cups 65.2, SD 17.7). We found no significant differences for app acceptability or appropriateness. CONCLUSIONS: Few studies have evaluated prospectively the utility and usability of commercial apps for mood. This study found that free, self-guided commercial mobile mental health apps are seen as usable, but no one app is superior to the other. Although we found that regular use is indicated for effects on depression and anxiety to occur in those who are more symptomatic, regression to the mean cannot be ruled out. TRIAL REGISTRATION: ClinicalTrials.gov NCT04536935; https://tinyurl.com/mr36zx3s.


Subject(s)
COVID-19 , Mobile Applications , Humans , Mental Health , Unemployment , Pandemics
2.
Tourism Planning & Development ; : 1-24, 2022.
Article in English | Web of Science | ID: covidwho-2107178

ABSTRACT

The COVID-19 pandemic has severely affected the tourism industry, with national lockdowns aimed at curbing the spread of the virus mandating travel restrictions and prohibiting events and gatherings. The shift to online video conferencing tools, which offer limited interactivity, has spurred the need to integrate augmented reality (AR) in various contexts, such as meetings, exhibitions, museums, and travel. This quantitative study examines visitors' perspectives on AR-based apps in tourism. It investigates the influence of three kinds of quality determinants, such as information quality, system quality, and service quality, on visitors' perspectives on AR apps. Their impact on visitor satisfaction ultimately triggers visitors to reuse AR-based mobile apps. The research makes a theoretical contribution to the literature on AR and the quality dimensions of mobile apps. We expect demand for AR-based apps to rapidly increase, as people continue to follow preventive measures even after COVID-19.

3.
Internet Interv ; 30: 100585, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2105148

ABSTRACT

Background: As a result of the COVID-19 pandemic and its far-reaching impact, the prevalence of posttraumatic stress disorder (PTSD) symptoms is increasing significantly in China. Yet access to reliable and effective psychological treatment is still limited during the pandemic. The widespread adoption of mobile technologies may provide a new way to address this gap. In this research we will develop an Acceptance and Commitment Therapy (ACT) based intervention delivered by mobile application and will test its usability, efficacy, and mechanism of its effects in relieving PTSD symptoms. Methods: A total of 147 Chinese participants with a diagnosis of PTSD according to the Clinician Administered PTSD Scale (CAPS-5) will be randomly assigned to an intervention group (app-delivered ACT), an active comparison group (app-delivered mindfulness), or a waitlist group. Participants in the intervention group or comparison group will use their respective apps for one month. Online self-report questionnaires will be used to assess the primary outcome of PTSD symptoms and the secondary outcomes symptoms of depression, symptoms of anxiety, and posttraumatic growth. The potential mediating variable to be tested is psychological flexibility and its components. These assessments will be conducted at baseline, at five times during treatment, at the end of treatment, and at 1- and 3-month follow-ups. Discussion: As far as we know, this study is the first randomized controlled trial to investigate the usability, efficacy, and mechanism of an app-delivered ACT intervention for PTSD. Furthermore, the research will assess the effect of treatment in reducing dropout rates, explore effective therapeutic components, and investigate mechanisms of symptom change, which will be valuable in improving the efficacy and usability of PTSD interventions.Trial registration: ChiCTR2200058408.

4.
JMIR Form Res ; 6(11): e38460, 2022 Nov 02.
Article in English | MEDLINE | ID: covidwho-2098992

ABSTRACT

BACKGROUND: Psychiatric inpatients often have limited access to psychotherapeutic education or skills for managing anxiety, a common transdiagnostic concern in severe and acute mental illness. COVID-19-related restrictions further limited access to therapy groups on inpatient psychiatric units. App-based interventions may improve access, but evidence supporting the feasibility of their use, acceptability, and effectiveness in psychiatric inpatient settings is limited. MindShift CBT is a free app based on cognitive behavioral therapy principles with evidence for alleviating anxiety symptoms in the outpatient setting. OBJECTIVE: We aimed to recruit 24 participants from an acute general psychiatric inpatient ward to a 1-month randomized control study assessing the feasibility and acceptability of providing patients with severe and acute mental illness access to the MindShift CBT app for help with managing anxiety symptoms. METHODS: Recruitment, data collection, analysis, and interpretation were completed collaboratively by clinician and peer researchers. Inpatients were randomized to two conditions: treatment as usual (TAU) versus TAU plus use of the MindShift CBT app over 6 days. We collected demographic and quantitative data on acceptability and usability of the intervention. Symptoms of depression, anxiety, and psychological distress were measured in pre- and poststudy surveys for preliminary signals of efficacy. We conducted individual semistructured interviews with participants in the MindShift CBT app group at the end of their trial period, which were interpreted using a standardized protocol for thematic analysis. RESULTS: Over 4 weeks, 33 inpatients were referred to the study, 24 consented to participate, 20 were randomized, and 11 completed the study. Of the 9 randomized participants who did not complete the study, 7 were withdrawn because they were discharged or transferred prior to study completion, with a similar distribution among both conditions. Among the enrolled patients, 65% (13/20) were admitted for a psychotic disorder and no patient was admitted primarily for an anxiety disorder. The average length of stay was 20 days (SD 4.4; range 3-21) and 35% (7/20) of patients were involuntarily admitted to hospital. Small sample sizes limited accurate interpretation of the efficacy data. Themes emerging from qualitative interviews included acceptability and usability of the app, and patient agency associated with voluntary participation in research while admitted to hospital. CONCLUSIONS: Our study benefitted from collaboration between peer and clinician researchers. Due to rapid patient turnover in the acute inpatient setting, additional flexibility in recruitment and enrollment is needed to determine the efficacy of using app-based psychotherapy on an acute psychiatric ward. Despite the limited sample size, our study suggests that similar interventions may be feasible and acceptable for acutely unwell inpatients. Further study is needed to compare the efficacy of psychotherapeutic apps with existing standards of care in this setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT04841603; https://clinicaltrials.gov/ct2/show/NCT04841603.

5.
Mindfulness (N Y) ; 13(11): 2691-2704, 2022.
Article in English | MEDLINE | ID: covidwho-2094805

ABSTRACT

Objectives: Amidst the COVID-19 pandemic, healthcare workers (HCWs) may be at greater risk of suffering from psychological distress compared to the general population. This study aimed to investigate the effects of mindfulness practice as delivered using Headspace on psychological and cognitive outcomes among HCWs in Singapore. Methods: A total of 80 HCWs were recruited and randomly assigned to engage in either 3 weeks (10 min/day) of mindfulness practice using Headspace or an active control condition (Lumosity; involving playing cognitive games). Participants were administered several self-report measures and two working memory (digit span) tasks at pre- and post-intervention, and one-month follow-up. Results: There were no significant between-condition changes on any outcome variables from pre- to post-intervention. From pre-intervention to 1-month follow-up, there were significantly greater improvements among Headspace participants on fear of COVID-19 (p = .005), compassion satisfaction (p = .007), trait mindfulness (p = .002), self-compassion (p = .005), sleep quality (p = .002), and the forward digit span task (p < .001). Several outcomes were mediated by increases in trait mindfulness or self-compassion. Conclusions: Use of Headspace may lead to downstream benefits in reducing distress and improving psychological health outcomes among HCWs. The findings have implications for improving psychological support resources for HCWs amidst a pandemic. Trial Registration: ClinicalTrials.gov (Identifier: NCT04936893).

6.
Int J Environ Res Public Health ; 19(21)2022 Oct 22.
Article in English | MEDLINE | ID: covidwho-2081986

ABSTRACT

The COVID-19 pandemic has changed our daily lives and restricted access to traditional psychological interventions. Hence there is an immediate and growing demand for accessible and scalable mental health solutions. Emotion-focused training for self-compassion and self-protection was developed and distributed using mobile phone technologies, and its effectiveness was tested. The available research sample consisted of 97 participants with a mean age of 26.06 years and a standard deviation of 10.53. Participants using the mobile app underwent a 14-day program aimed at reducing self-criticism while increasing self-compassion and self-protection. Pre- and post-measurements were collected. The results showed a statistically significant medium effect on self-compassion, self-criticism, and self-protection performance and a significant small effect on self-protection distress. The finding that a 14-day mobile app was able to foster well-being in the form of self-compassion, self-protection, and self-criticism is promising. It indicates the potential for individuals to obtain help through the use of remote tools such as MHapps for a fraction of the usual cost, at their own pace, and without other restrictions.


Subject(s)
COVID-19 , Mobile Applications , Humans , Adult , Self-Assessment , Empathy , Self-Compassion , Pandemics/prevention & control , Emotions
7.
International Journal of Advanced Computer Science and Applications ; 13(8):782-790, 2022.
Article in English | Web of Science | ID: covidwho-2067903

ABSTRACT

Over the years, a wide variety of respiratory diseases have caused a high mortality rate throughout the world. This was again observed with the appearance of the pandemic, COVID-19. In addition, the most affected are people living in extreme poverty. The objective is design a mobile health application for the registration and diagnosis of respiratory diseases. For this, the RUP methodology was applied, because it easily adapts to various types of projects. Its use, together with the UML process development software, allows the analysis, implementation and documentation of object oriented systems. For validation, a user survey was carried out and the questionnaire was based on the dimensions of functionality, efficiency, effectiveness and satisfaction. Obtaining as a result a positive qualification to the design of the application and its acceptance due to the reduction in the time to obtain the diagnosis. In conclusion, a mobile health application design was successfully carried out so that patients can register and have the diagnosis of respiratory diseases from the comfort of their home.

8.
Acta Inform Med ; 30(3): 236-250, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2067046

ABSTRACT

Background: Digitalization of healthcare led to the optimization of monitoring, diagnostics, and treatment of the range of disorders. Taking into account recent situation with COVID-19 pandemics, digital technologies allowed to improve management of viral infections via remote monitoring and diagnostics of infected patients. Up to date, various mobile health applications (apps) have been proposed, including apps for the patients diagnosed with cardiovascular pathologies. Objective: The presented review aimed at the analyses of a range of mHealth solutions used to improve primary cardiac care. In addition, we studied the factors driving and hindering the wide introduction of mHealth services in the clinics. Methods: The work was based on the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. The publication search was carried out using PubMed, Web of Science, Cochrane Library, Scopus, and Google Scholar databases. Studies published during the period from 2014 until January 2022 were selected for the analysis. The evaluation of risk of bias for the included studies was conducted using the Cochrane Collaboration Risk of Bias tool. Results and Discussion: An overall 5513 studies were assessed for eligibility after which 39 studies were included.. The main trend in the mobile health for cardiological applications is the use of different types of wearable devices and Artificial Intelligence-platforms. In fact, mobile technology allows remotely to monitor, interpret, and analyze biomedical data collected from the patient. Conclusion: The results of this literature search demonstrated that patients diagnosed with cardiovascular disorders can potentially benefit from the application of mHealth in cardiology. However, despite the proven advantages of mHealth for cardiology, there are many challenges and concerns regarding effectiveness, safety, reliability and the lack of official regulation and guidelines from official organizations. Such issues require solutions and further work towards a wide implementation of mHealth technologies in cardiac practice.

9.
J Clin Med ; 11(19)2022 Sep 23.
Article in English | MEDLINE | ID: covidwho-2066172

ABSTRACT

Suicide risk is a multifaceted phenomenon, and many risk factors are involved in its complexity. In the last few decades, mental health apps have spread, providing economic and affordable strategies to prevent suicide. Therefore, the aim of this review is to identify original studies on mobile apps that target suicidal crises. The review follows PRISMA guidelines, searching through four major electronic databases (PubMed/MEDLINE, Scopus, PsycInfo and Web of Science) for relevant titles/abstracts published from January 2010 to May 2022. It includes original studies that explicitly analyze mobile apps for suicide prevention. A total of 32 studies met the inclusion criteria. Sixteen studies assessed the feasibility and acceptability of mobile apps, ten studies assessed the efficacy of mobile apps in preventing suicide, and six studies described randomized control trial protocols not yet implemented. Generally, the apps were judged by participants to be acceptable and helpful, and several improvements to enhance the functionality of apps were suggested. The efficacy of mobile apps, although limited and assessed with very heterogenous methods, was confirmed by most of the studies. Mobile apps could represent a helpful supplement to traditional prevention tactics, providing real-time monitoring of at-risk persons, personalized tools to cope with suicidal crises, and immediate access to specific support.

10.
JMIR Public Health Surveill ; 8(11): e41004, 2022 Nov 11.
Article in English | MEDLINE | ID: covidwho-2065330

ABSTRACT

BACKGROUND: Digital proximity-tracing apps have been deployed in multiple countries to assist with SARS-CoV-2 pandemic mitigation efforts. However, it is unclear how their performance and effectiveness were affected by changing pandemic contexts and new viral variants of concern. OBJECTIVE: The aim of this study is to bridge these knowledge gaps through a countrywide digital proximity-tracing app effectiveness assessment, as guided by the World Health Organization/European Center for Prevention and Disease Control (WHO/ECDC) indicator framework to evaluate the public health effectiveness of digital proximity-tracing solutions. METHODS: We performed a descriptive analysis of the digital proximity-tracing app SwissCovid in Switzerland for 3 different periods where different SARS-CoV-2 variants of concern (ie, Alpha, Delta, and Omicron, respectively) were most prevalent. In our study, we refer to the indicator framework for the evaluation of public health effectiveness of digital proximity-tracing apps of the WHO/ECDC. We applied this framework to compare the performance and effectiveness indicators of the SwissCovid app. RESULTS: Average daily registered SARS-CoV-2 case rates during our assessment period from January 25, 2021, to March 19, 2022, were 20 (Alpha), 54 (Delta), and 350 (Omicron) per 100,000 inhabitants. The percentages of overall entered authentication codes from positive tests into the SwissCovid app were 9.9% (20,273/204,741), 3.9% (14,372/365,846), and 4.6% (72,324/1,581,506) during the Alpha, Delta, and Omicron variant phases, respectively. Following receipt of an exposure notification from the SwissCovid app, 58% (37/64, Alpha), 44% (7/16, Delta), and 73% (27/37, Omicron) of app users sought testing or performed self-tests. Test positivity among these exposure-notified individuals was 19% (7/37) in the Alpha variant phase, 29% (2/7) in the Delta variant phase, and 41% (11/27) in the Omicron variant phase compared to 6.1% (228,103/3,755,205), 12% (413,685/3,443,364), and 41.7% (1,784,951/4,285,549) in the general population, respectively. In addition, 31% (20/64, Alpha), 19% (3/16, Delta), and 30% (11/37, Omicron) of exposure-notified app users reported receiving mandatory quarantine orders by manual contact tracing or through a recommendation by a health care professional. CONCLUSIONS: In constantly evolving pandemic contexts, the effectiveness of digital proximity-tracing apps in contributing to mitigating pandemic spread should be reviewed regularly and adapted based on changing requirements. The WHO/ECDC framework allowed us to assess relevant domains of digital proximity tracing in a holistic and systematic approach. Although the Swisscovid app mostly worked, as reasonably expected, our analysis revealed room for optimizations and further performance improvements. Future implementation of digital proximity-tracing apps should place more emphasis on social, psychological, and organizational aspects to reduce bottlenecks and facilitate their use in pandemic contexts.


Subject(s)
COVID-19 , Mobile Applications , Humans , Pandemics/prevention & control , SARS-CoV-2 , Contact Tracing , Cross-Sectional Studies , Switzerland/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control
11.
JMIR Public Health Surveill ; 8(11): e40089, 2022 Nov 22.
Article in English | MEDLINE | ID: covidwho-2065326

ABSTRACT

BACKGROUND: COVID-19 cases are soaring in Asia. Indonesia, Southeast Asia's most populous country, is now ranked second in the number of cases and deaths in Asia, after India. The compliance toward mask wearing, social distancing, and hand washing needs to be monitored to assess public behavioral changes that can reduce transmission. OBJECTIVE: This study aimed to evaluate this compliance in Indonesia between October 2020 and May 2021 and demonstrate the use of the Bersatu Lawan COVID-19 (BLC) mobile app in monitoring this compliance. METHODS: Data were collected in real time by the BLC app from reports submitted by personnel of military services, police officers, and behavioral change ambassadors. Subsequently, the data were analyzed automatically by the system managed by the Indonesia National Task Force for the Acceleration of COVID-19 Mitigation. RESULTS: Between October 1, 2020, and May 2, 2021, the BLC app generated more than 165 million reports, with 469 million people monitored and 124,315,568 locations under observation in 514 districts/cities in 34 provinces in Indonesia. This paper grouped them into 4 colored zones, based on the degree of compliance, and analyzed variations among regions and locations. CONCLUSIONS: Compliance rates vary among the 34 provinces and among the districts and cities of those provinces. However, compliance to mask wearing seems slightly higher than social distancing. This finding suggests that policy makers need to promote higher compliance in other measures, including social distancing and hand washing, whose efficacies have been proven to break the chain of transmission when combined with masks wearing.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics/prevention & control , SARS-CoV-2 , Masks , Indonesia/epidemiology
12.
J Med Internet Res ; 24(10): e37497, 2022 10 05.
Article in English | MEDLINE | ID: covidwho-2054760

ABSTRACT

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.


Subject(s)
COVID-19 , Gastrointestinal Diseases , Mobile Applications , Telemedicine , Gastrointestinal Diseases/therapy , Humans , Pandemics , Reproducibility of Results
13.
2nd ACM Conference on Information Technology for Social Good, GoodIT 2022 ; : 424-430, 2022.
Article in English | Scopus | ID: covidwho-2053350

ABSTRACT

During the periods of social isolation to contain the advance of COVID-19 in 2020 and 2021, educational institutions have had the challenge to adopt technological strategies not only to ensure continuity in students' classes, but also to support their mental health in a period of uncertainty and health risks. Loneliness is an emotional distress caused by the lack of meaningful social connections;it has increasingly affected young adults worldwide during the pandemic's social isolation and still bears psychological effects in the current post-pandemic period. In the light of this challenge, the Nonenliness App was developed as a way to bring together university communities to address issues related to loneliness and mental health disorders through a gamified and social online environment. In this paper, we present the app and its main functionalities (Beta version) and discuss the preliminary results of a pilot clinical study conducted with university students in Germany (N = 12) to verify the app's efficacy and usability, alongside the challenges faced and the next steps to be taken regarding the platform's improvement. © 2022 ACM.

14.
2021 Universitas Riau International Conference on Education Technology, URICET 2021 ; : 28-31, 2021.
Article in English | Scopus | ID: covidwho-2052114

ABSTRACT

The appearance of COVID 19 caused the closure of many higher education institution facilities across the world and Mexico was no exception. This situation interrupted normal teaching and learning activities, fostering the search and development of tools which can guarantee the continuation of learning and teaching activities. Accordingly, this article describes the need for a tool to support learning activities within the context of a challenge-based learning approach. Consequently, after a search for an existing tool it was decided to design a tool suitable for competence development through challenge-based learning. Thus, a mobile app named Klever 21 was designed and released as a test version for this purpose. Additionally, this mobile app is associated with a web platform to aid project management and student competence evaluations. This article describes the main features of Klever 21 which is currently being tested at Tecnologico de Monterrey. This technology represents an evolution of mobile app technologies to face disruptive situations in higher education institutions. © 2021 IEEE.

15.
19th Annual International Conference on Privacy, Security and Trust, PST 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2052070

ABSTRACT

Mental health is an extremely important subject, especially in these unprecedented times of the COVID-19 pandemic. Ubiquitous mobile phones can equip users to supplement psychiatric treatment and manage their mental health. Mobile Mental Health (MMH) apps emerge as an effective alternative to assist with a broad range of psychological disorders filling the much-needed patient-provider accessibility gap. However, it also raises significant concerns with sensitive information leakage. The absence of a transparent privacy policy and lack of user awareness may pose a significant threat to undermining the applicability of such tools. We conducted a multifold study of - 1) Privacy policies (Manually and with Polisis, an automated framework to evaluate privacy policies);2) App permissions;3) Static Analysis for inherent security issues;4) Dynamic Analysis for threat surface and vulnerabilities detection, and 5) Traffic Analysis. Our results indicate that apps' exploitable flaws, dangerous permissions, and insecure data handling pose a potential threat to the users' privacy and security. The Dynamic analysis identified 145 vulnerabilities in 20 top-rated MMH apps where attackers and malicious apps can access sensitive information. 45% of MMH apps use a unique identifier, Hardware Id, which can link a unique id to a particular user and probe users' mental health. Traffic analysis shows that sensitive mental health data can be leaked through insecure data transmission. MMH apps need better scrutiny and regulation for more widespread usage to meet the increasing need for mental health care without being intrusive to the already vulnerable population. © 2022 IEEE.

16.
35th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2022 ; 2022-July:119-124, 2022.
Article in English | Scopus | ID: covidwho-2051942

ABSTRACT

Illness due to infectious diseases has been always a global threat. Millions of people die per year due to COVID-19, pneumonia, and Tuberculosis (TB) as all of them infect the lungs. For all cases, early screening/diagnosis can help provide opportunities for better care. To handle this, we develop an application, which we call MobApp4InfectiousDisease that can identify abnormalities due to COVID-19, pneumonia, and TB using Chest X-ray image. In our MobApp4InfectiousDisease, we implemented a customized deep network with a single transfer learning technique. For validation, we offered in-depth experimental study and we achieved, for COVID-19-pneumonia-TB cases, accuracy of 97.72%196.62%199.75%, precision of 92.72%1100.0%199.29%, recall of 98.89%188.54%199.65%, and F1-score of 95.00%194.00%199.00%. Our results are compared with state-of-the-art techniques. To the best of our knowl-edge, this is the first time we deployed our proof-of-the-concept MobApp4InfectiousDisease for a multi-class infec-tious disease classification. © 2022 IEEE.

17.
JMIR Form Res ; 6(9): e39718, 2022 Sep 13.
Article in English | MEDLINE | ID: covidwho-2043356

ABSTRACT

BACKGROUND: Mobile apps have been shown to play an important role in the management, care, and prevention of infectious diseases. Thus, skills for self-care-one of the most effective ways to prevent illness-can be improved through mobile health apps. OBJECTIVE: This study aimed to design, develop, and evaluate an educational mobile-based self-care app in order to help the self-prevention of COVID-19 in underdeveloped countries. We intended the app to be easy to use, quick, and inexpensive. METHODS: In 2020 and 2021, we conducted a methodological study. Using the ADDIE (analysis, design, development, implementation, and evaluation) educational model, we developed a self-care management mobile app. According to the ADDIE model, an effective training and performance support tool is built through the 5 phases that comprise its name. There were 27 participants who conducted 2 evaluations of the mobile app's usability and impact using the mobile health app usability and self-care inventory scales. The study design included pre- and posttesting. RESULTS: An Android app called MyShield was developed. The results of pre- and posttests showed that on a scale from 0 to 5, MyShield scored a performance average of 4.17 in the physical health dimension and an average of 3.88 in the mental well-being dimension, thereby showing positive effects on self-care skills. MyShield scored highly on the "interface and satisfaction," "ease of use," and "usefulness" components. CONCLUSIONS: MyShield facilitates learning self-care skills at home, even during quarantine, increasing acquisition of information. Given its low development cost and the ADDIE educational design on which it is based, the app can be helpful in underdeveloped countries. Thus, low-income countries-often lacking other tools-can use the app as an effective tool for fighting COVID-19, if it becomes a standard mobile app recommended by the government.

18.
Health Serv Res Manag Epidemiol ; 9: 23333928221125034, 2022.
Article in English | MEDLINE | ID: covidwho-2029676

ABSTRACT

Introduction: The COVID 19 pandemic increased the need for rapid and accurate diagnostic testing for COVID. When testing became available, a systems response was needed to efficiently accommodate the high-volume flow of patients who needed testing. Self-scheduling of COVID testing was developed to help patients safely and efficiently schedule their COVID testing online or with a mobile app. Methods: We captured the counts of COVID test appointments, time patients spent in scheduling COVID test appointments, appointment lead times, and no-shows for COVID test appointments. For 17 months of self-scheduling, we retrospectively compared self-scheduling with the concurrent staff scheduling of COVID tests. Results: From November 2020 through March 2022 there were 619 104 scheduled appointments for COVID testing with 22% (136 252) being self-scheduled. For asymptomatic self-scheduled COVID tests, accounting for 10.3% (63 605/619 104) of total COVID tests scheduled, median time to self-schedule was 3.1 min, interquartile range (IQR) [2.4,4.7]. For symptomatic self-schedulers accounting for 11.7% (72 647/619 104) of total COVID tests scheduled, the median time to self-triage and self-schedule was 5.8 min, IQR[4.3,8.9]. Self-scheduled COVID appointments increased to 44% (42 387/97 086) of the total COVID appointments during the peak month of January 2022. Median appointment lead time for symptomatic self-scheduled COVID test appointments was 6.6 h compared to 2.9 h (P < .0001) for symptomatic staff scheduled appointments. However, adjusting for the 24% (32 194/135 252) that self-scheduled during hours when testing was unavailable, the median appointment lead time for symptomatic self-scheduled patients dropped to 3.6 h. No-shows were 2.5% for self-scheduled appointments compared to 3.0% no-shows that were staff scheduled (odds ratio 0.83, P < .0001). Conclusion: COVID testing was self-scheduled for a large percent of scheduled COVID tests, taking patients only a few minutes to complete. Self-scheduling use increased over time, associated with a decreasing use of staff scheduled appointments and lower no-shows.

19.
JMIR Form Res ; 6(9): e36525, 2022 Sep 14.
Article in English | MEDLINE | ID: covidwho-2029897

ABSTRACT

BACKGROUND: Recently, the use of telehealth for patient treatment under the COVID-19 pandemic has gained interest around the world. As a result, many infodemiology and infoveillance studies using web-based sources such as Google Trends were reported, focusing on the first wave of the COVID-19 pandemic. Although public interest in telehealth has increased in many countries during this time, the long-term interest has remained unknown among people living in Japan. Moreover, various mobile telehealth apps have become available for remote areas in the COVID-19 era, but the accessibility of these apps in epidemic versus nonepidemic regions is unknown. OBJECTIVE: We aimed to investigate the public interest in telehealth during the first pandemic wave and after the wave in the first part of this study, and the accessibility of medical institutions using telehealth in the epidemic and nonepidemic regions, in the second part. METHODS: We examined and compared the first wave and after the wave with regards to severe cases, number of deaths, relative search volume (RSV) of telehealth and COVID-19, and the correlation between RSV and COVID-19 cases, using open sources such as Google Trends and the Japanese Ministry of Health, Labour and Welfare (JMHLW) data. The weekly mean and the week-over-week change rates of RSV and COVID-19 cases were used to examine the correlation coefficients. In the second part, the prevalence of COVID-19 cases, severe cases, number of deaths, and the telehealth accessibility rate were compared between epidemic regions and nonepidemic regions, using the JMHLW data. We also examined the regional correlation between telehealth accessibility and the prevalence of COVID-19 cases. RESULTS: Among the 83 weeks with 5 pandemic waves, the overall mean for the RSV of telehealth and COVID-19 was 11.3 (95% CI 8.0-14.6) and 30.7 (95% CI 27.2-34.2), respectively. The proportion of severe cases (26.54% vs 18.16%; P<.001), deaths (5.33% vs 0.99%; P<.001), RSV of telehealth (mean 33.1, 95% CI 16.2-50.0 vs mean 7.3, 95% CI 6.7-8.0; P<.001), and RSV of COVID-19 (mean 52.1, 95% CI 38.3-65.9 vs mean 26.3, 95% CI 24.4-29.2; P<.001) was significantly higher in the first wave compared to after the wave. In the correlation analysis, the public interest in telehealth was 0.899 in the first wave and -0.300 overall. In Japan, the accessibility of telehealth using mobile apps was significantly higher in epidemic regions compared to nonepidemic regions in both hospitals (3.8% vs 2.0%; P=.004) and general clinics (5.2% vs 3.1%; P<.001). In the regional correlation analysis, telehealth accessibility using mobile apps was 0.497 in hospitals and 0.629 in general clinics. CONCLUSIONS: Although there was no long-term correlation between the public interest in telehealth and COVID-19, there was a regional correlation between mobile telehealth app accessibility in Japan, especially for general clinics. We also revealed that epidemic regions had higher mobile telehealth app accessibility. Further studies about the actual use of telehealth and its effect after the COVID-19 pandemic are necessary.

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2022 IEEE International Conference on Communications, ICC 2022 ; 2022-May:3346-3351, 2022.
Article in English | Scopus | ID: covidwho-2029231

ABSTRACT

With outbreak of the COVID-19 pandemic, contact tracing has become an important problem. It has been proven that maintaining social distance and isolating affected people are highly beneficial for curbing the spread of COVID-19, which all depend on identifying people's trajectories. However, the current interview-based approach is costly, and the existing mobile app-based schemes rely on complete and accurate data. In this paper, we propose a transformer encoder-based approach with spatial position embedding extracted using a graph Combinatorial Laplacian matrix to interpolate incomplete human trajectories. To model human trajectory, we propose a graphical embedded module to extract spatial features based on predefined location clusters. The incomplete trajectory sequences are first preprocessed into matrices and then used to train a deep transformer encoder network for trajectory completion. Our experiments using a real world Bluetooth Low Energy (BLE) dataset validate the efficacy of our proposed approach, which outperforms several baseline methods. © 2022 IEEE.

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