@Article{info:doi/10.2196/57191, author="Baretta, Dario and R{\"u}ttimann, Lynn Carole and Amrein, Alexandra Melanie and Inauen, Jennifer", title="Promoting Hand Hygiene During the COVID-19 Pandemic: Randomized Controlled Trial of the Optimized Soapp+ App", journal="JMIR Mhealth Uhealth", year="2025", month="Apr", day="24", volume="13", pages="e57191", keywords="COVID-19", keywords="hand hygiene", keywords="behavior change technique", keywords="Multiphase Optimization Strategy", keywords="randomized controlled trial", keywords="smartphone apps", keywords="mobile phones", abstract="Background: The adoption of protective behaviors represents a crucial measure to counter the spread of infectious diseases. The development of effective behavior change techniques therefore emerged as a public health priority during the COVID-19 pandemic, but randomized controlled trials (RCTs) testing such interventions during the pandemic were scarce. We conducted a Multiphase Optimization Strategy to develop, optimize, and evaluate a smartphone app, Soapp+, to promote hand hygiene during the COVID-19 pandemic. Objective: This RCT aims to evaluate the efficacy of the Soapp+ app (intervention group) targeting motivation and habit compared to a simplified version of the app mainly delivering hand hygiene information (active control group). We hypothesize that, compared to the control group, the intervention group will show greater improvements in hand hygiene behavior and behavioral determinants post intervention and at a 6-month follow-up. Methods: We conducted an RCT from March 2022 to April 2023, recruiting 193 adults living in Switzerland online. Following baseline assessment, the intervention lasted 32 days, followed by a postintervention assessment and a 6-month follow-up. The primary outcome was the change in hand hygiene behavior from pre- to postintervention and preintervention to follow-up. Hand hygiene was assessed with electronic diaries. The intervention group received content incorporating various behavior change techniques designed to address key motivational and volitional determinants of hand hygiene behavior (eg, skills, knowledge, intention, attitudes toward hand hygiene, risk perception, outcome expectancies, self-efficacy, action planning, coping planning, action control, habit). In contrast, the active control group was exposed to behavior change techniques targeting only a subset of these determinants (ie, skills, knowledge, and intention). The delivery of the intervention content was fully automated. Group differences were tested using an intention-to-treat approach with the nonparametric Wilcoxon rank sum test. Results: Of the 193 randomized participants, 146 completed the first hand hygiene diary preintervention and were included in the main analysis. The mean age was 41 (SD 17) years, and 69.2\% (n=101) were women. The main analysis revealed significant superiority of the intervention compared to controls in the change in hand hygiene pre-post intervention (W=2034; P<.04; effect size r=0.17) and between preintervention and follow-up (W=2005; P<.03; effect size r=0.18). Regarding behavioral determinants, the change in coping planning pre-post intervention (W=3840; P=.03, effect size r=0.16) was significantly greater in the intervention group using Soapp+ compared to controls. Conclusions: Soapp+ was developed through a rigorous experimental method during the ongoing COVID-19 pandemic. The RCT provided evidence for the efficacy of Soapp+ to promote hand hygiene in the context of a pandemic. Trial Registration: ClinicalTrials.gov NCT04830761; https://clinicaltrials.gov/study/NCT04830761 ", doi="10.2196/57191", url="https://mhealth.jmir.org/2025/1/e57191" } @Article{info:doi/10.2196/53339, author="Buchan, Claire M. and Katapally, Reddy Tarun and Bhawra, Jasmin", title="Application of an Innovative Methodology to Build Infrastructure for Digital Transformation of Health Systems: Developmental Program Evaluation", journal="JMIR Form Res", year="2025", month="Apr", day="17", volume="9", pages="e53339", keywords="digital health platform", keywords="citizen science", keywords="evaluation", keywords="health systems", keywords="digital health", keywords="app", keywords="innovative", keywords="digital transformation", keywords="public health", keywords="crises", keywords="communicable disease", keywords="coronavirus", keywords="chronic diseases", keywords="decision-making", keywords="assessment", keywords="thematic analysis", keywords="self-report survey", keywords="risk", keywords="artificial intelligence", keywords="AI", abstract="Background: The current public health crises we face, including communicable disease pandemics such as COVID-19, require cohesive societal efforts to address decision-making gaps in our health systems. Digital health platforms that leverage big data ethically from citizens can transform health systems by enabling real-time data collection, communication, and rapid responses. However, the lack of standardized and evidence-based methods to develop and implement digital health platforms currently limits their application. Objective: This study aims to apply mixed evaluation methods to assess the development of a rapid response COVID-19 digital health platform before public launch by engaging with the development and research team, which consists of interdisciplinary researchers (ie, key stakeholders). Methods: Using a developmental evaluation approach, this study conducted (1) a qualitative survey assessing digital health platform objectives, modifications, and challenges administered to 5 key members of the software development team and (2) a role-play pilot with 7 key stakeholders who simulated 8 real-world users, followed by a self-report survey, to evaluate the utility of the digital health platform for each of its objectives. Survey data were analyzed using an inductive thematic analysis approach. Postpilot test survey data were aggregated and synthesized by participant role. Results: The digital health platform met original objectives and was expanded to accommodate the evolving needs of potential users and COVID-19 pandemic regulations. Key challenges noted by the development team included navigating changing government policies and supporting the data sovereignty of platform users. Strong team cohesion and problem-solving were essential in the overall success of program development. During the pilot test, participants reported positive experiences interacting with the platform and found its features relatively easy to use. Users in the community member role felt that the platform accurately reflected their risk of contracting COVID-19, but reported some challenges interacting with the interface. Those in the decision maker role found the data visualizations helpful for understanding complex information. Both participant groups highlighted the utility of a tutorial for future users. Conclusions: Evaluation of the digital health platform development process informed our decisions to integrate the research team more cohesively with the development team, a practice that is currently uncommon given the use of external technology vendors in health research. In the short term, the developmental evaluation resulted in shorter sprints, and the role-play exercise enabled improvements to the log-in process and user interface ahead of public deployment. In the long term, this exercise informed the decision to include a data scientist as part of both teams going forward to liaise with researchers throughout the development process. More interdisciplinarity was also integrated into the research process by providing health system training to computer programmers, a key factor in human-centered artificial intelligence development. ", doi="10.2196/53339", url="https://formative.jmir.org/2025/1/e53339" } @Article{info:doi/10.2196/60461, author="Golsong, Konstanze and Kaufmann, Luisa and Baldofski, Sabrina and Kohls, Elisabeth and Rummel-Kluge, Christine", title="Acceptability, User Satisfaction, and Feasibility of an App-Based Support Service During the COVID-19 Pandemic in a Psychiatric Outpatient Setting: Prospective Longitudinal Observational Study", journal="JMIR Form Res", year="2024", month="Dec", day="4", volume="8", pages="e60461", keywords="mental health", keywords="eHealth", keywords="app", keywords="health care", keywords="app-based support", keywords="psychiatric symptoms", keywords="mobile phone", keywords="COVID-19", abstract="Background: Patients with mental disorders often have difficulties maintaining a daily routine, which can lead to exacerbated symptoms. It is known that apps can help manage mental health in a low-threshold way and can be used in therapeutic settings to complement existing therapies. Objective: The aim of this study was to evaluate the acceptability, usability, and feasibility of an app-based support service specifically developed for outpatients with severe mental disorders in addition to regular face-to-face therapy during the COVID-19 pandemic. Methods: Patients in a psychiatric outpatient department at a German university hospital were invited to use an app-based support service designed transdiagnostically for mental disorders for 4 weeks. The app included 7 relaxation modules, consisting of video, audio, and psychoeducational text; ecological momentary assessment--like questionnaires on daily mood answered via a visual smiley-face scale; and an activity button to record and encourage daily activities. Standardized questionnaires at baseline (T0; preintervention time point) and after 4 weeks (T2; postintervention time point) were analyzed. Feedback via the smiley-face scale was provided after using the app components (T1; during the intervention). Measures included depressive symptoms, quality of life, treatment credibility and expectancy, and satisfaction. Furthermore, participation rates, use of app modules and the activity button, and daily mood and the provided feedback were analyzed (T2). Results: In total, 57 patients participated in the study, and the data of 38 (67\%) were analyzed; 17 (30\%) dropped out. Satisfaction with the app was high, with 53\% (30/57) of the participants stating being rather satisfied or satisfied. Furthermore, 79\% (30/38) of completers stated they would be more likely or were definitely likely to use an app-based support service again and recommend it. Feasibility and acceptability were high, with nearly half (18/38, 47\%) of the completers trying relaxation modules and 71\% (27/38) regularly responding to the ecological momentary assessment--like questionnaire between 15 and 28 times (mean 19.91, SD 7.57 times). The activity button was used on average 12 (SD 15.72) times per completer, and 58\% (22/38) felt ``definitely'' or ``rather'' encouraged to perform the corresponding activities. Depressive symptomatology improved significantly at the postintervention time point (P=.02). Quality of life showed a nonsignificant increase in the physical, psychological, and social domains (P=.59, P=.06, and P=.42, respectively) and a significant improvement in the environment domain (P=.004). Treatment credibility and expectancy scores were moderate and significantly decreased at T2 (P=.02 and P<.001, respectively). Posttreatment expectancy scores were negatively associated with posttreatment depressive symptomatology (r=--0.36; P=.03). Conclusions: App-based programs seem to be an accessible tool for stabilizing patients with severe mental disorders, supporting them in maintaining a daily routine, complementing existing face-to-face treatments, and overall helping respond to challenging situations such as the COVID-19 pandemic. ", doi="10.2196/60461", url="https://formative.jmir.org/2024/1/e60461", url="http://www.ncbi.nlm.nih.gov/pubmed/39630503" } @Article{info:doi/10.2196/50184, author="Vecino-Ortiz, I. Andres and Guzman-Tordecilla, Nicolas Deivis and Maniar, Vidhi and Agudelo-Londo{\~n}o, Sandra and Franco-Suarez, Oscar and Aya Pastrana, Nathaly and Rodr{\'i}guez-Patarroyo, Mariana and Mej{\'i}a-Rocha, Marino and Cardona, Jaime and Chavez Chamorro, Mariangela and Gibson, Dustin", title="Mobile Phone Syndromic Surveillance for Respiratory Conditions in an Emergency (COVID-19) Context in Colombia: Representative Survey Design", journal="J Med Internet Res", year="2024", month="Oct", day="17", volume="26", pages="e50184", keywords="mobile phone surveys", keywords="syndromic surveillance", keywords="COVID-19", keywords="public health surveillance", keywords="IVR", keywords="interactive voice response", keywords="survey", keywords="surveys", keywords="voice response", keywords="syndromic", keywords="surveillance", keywords="respiratory", keywords="pandemic", keywords="SARS-CoV-2", keywords="feasibility", keywords="data collection", keywords="public health", keywords="emergency", keywords="outbreak", keywords="mobile phone", abstract="Background: Syndromic surveillance for respiratory infections such as COVID-19 is a crucial part of the public health surveillance toolkit as it allows decision makers to detect and prepare for new waves of the disease in advance. However, it is labor-intensive, costly, and increases exposure to survey personnel. This study assesses the feasibility of conducting a mobile phone--based respiratory syndromic surveillance program in a middle-income country during a public health emergency, providing data to support the inclusion of this method in the standard infection control protocols at the population level. Objective: This study aims to assess the feasibility of a national active syndromic surveillance system for COVID-19 disease in Colombia. Methods: In total, 2 pilots of syndromic mobile phone surveys (MPSs) were deployed using interactive voice response technology in Colombia (367 complete surveys in March 2022 and 451 complete surveys in April and May 2022). Respondents aged 18 years and older were sampled using random digit dialing, and after obtaining consent, they were sent a 10-minute survey with modules on sociodemographic status, respiratory symptoms, past exposure to COVID-19 infection and vaccination status, preferences about COVID-19 vaccination, and information source for COVID-19. Pilot 1 used a nationally representative sample while pilot 2 used quota sampling to yield representative results at the regional level. In this work, we assessed the performance characteristics of the survey pilots and compared the demographic information collected with a nationally representative household survey. Results: For both pilots, contact rates were between 1\% and 2\%, while participation rates were above 80\%. The results revealed that younger, female, and higher educated participants were more likely to participate in the syndromic survey. Survey rates as well as demographics, COVID-19 vaccination status, and prevalence of respiratory symptoms are reported for both pilots. We found that respondents of the MPSs are more likely to be younger and female. Conclusions: In a COVID-19 pandemic setting, using an interactive voice response MPS to conduct syndromic surveillance may be a transformational, low-risk, and feasible method to detect outbreaks. This evaluation expects to provide a path forward to the inclusion of MPSs as a traditional surveillance method. ", doi="10.2196/50184", url="https://www.jmir.org/2024/1/e50184", url="http://www.ncbi.nlm.nih.gov/pubmed/39418077" } @Article{info:doi/10.2196/50745, author="Omorou, Y. Abdou and Ndishimye, Pacifique and Hoen, Bruno and Mutesa, L{\'e}on and Karame, Prosper and Nshimiyimana, Ladislas and Galmiche, Simon and Mugabo, Hassan and Murayire, Janvier and Mugisha, Muco and Umulisa, Michele Marie and Uwera, Nsaba Yvonne Delphine and Musanagabanwa, Clarisse and Bigirimana, Noella and Nsanzimana, Sabin and Guillemin, Francis and Rwabihama, Paul Jean", title="Feasibility, Acceptability, Satisfaction, and Challenges of an mHealth App (e-ASCov) for Community-Based COVID-19 Screening by Community Health Workers in Rwanda: Mixed Methods Study", journal="JMIR Mhealth Uhealth", year="2024", month="Oct", day="14", volume="12", pages="e50745", keywords="community health workers", keywords="COVID-19 screening tool", keywords="COVID-19", keywords="SARS-CoV-2", keywords="screening", keywords="acceptability", keywords="feasibility", keywords="satisfaction", keywords="community based", keywords="LMIC", keywords="Africa", keywords="challenges", keywords="barriers", keywords="smartphone", keywords="proof-of-concept", keywords="mHealth", keywords="mobile health", keywords="apps", keywords="COVID-19 screening", abstract="Background: Although at the base of the pyramid-shaped organization of the Rwandan health system, community health workers (CHWs) are central to the community-based management of disease outbreaks. Objective: This mixed methods study aimed to explore the feasibility, acceptability, satisfaction, and challenges of a mobile health (mHealth) tool for community-based COVID-19 screening in Rwanda. Methods: Two urban (Gasabo and Nyarugenge) and 2 rural (Rusizi and Kirehe) districts in Rwanda participated in the project (smartphone app for COVID-19 screening). A mixed methods approach was used to inform the feasibility (awareness and expectation), acceptability (use and perceived benefits), satisfaction, and challenges of the mHealth intervention. At the end of the project, CHWs were asked to complete a quantitative questionnaire on the use of and satisfaction with the app. Then, in-depth interviews and focus group discussions were organized with CHWs. A content analysis was performed on the transcripts. Results: Overall, 383 CHWs were recruited and trained; 378 CHWs participated in the study. The mean age of CHWs was 36.7 (SD 6.6) to 45.3 (SD 9.9) years and most were women (237/378, 62.7\%). More than 7000 people were registered with the use of the app and 20\% were referred to a local COVID-19 testing facility. According to CHW reporting, the median number of people screened by each CHW ranged from 152 (IQR 70-276) for Nyarugenge to 24 (IQR 16-90) for Rusizi. COVID-19 positivity rates were higher in urban than rural districts: more than half of the CHWs in Gasabo reported a confirmed positive case versus only 2.4\% for Kirehe and 15.4\% for Rusizi. Despite the app being a novel tool, CHWs were well aware of the use of such a tool and had appropriate expectations. Acceptability and satisfaction were very high, with differences between urban and rural districts. Satisfaction was higher in Nyarugenge (72.8/100) and Gasabo (80.7/100) than in Kirehe (61.6/100) and Rusizi (64.5/100). More than 80\% of the CHWs were willing to continue using the e-ASCov app, with the exception of CHWs in Kirehe (56.7\%). The app was perceived as a tool to generate information on COVID-19, inform on the status of the pandemic, and help curb the spread of the pandemic in Rwanda. CHWs were satisfied with the app at all stages of its implementation in their districts. Conclusions: In this proof-of-concept study, a smartphone app for screening COVID-19 was useful as an mHealth tool to be used by CHWs, with the potential to increase health system efficiency in an epidemic context. The context should be analyzed for generalization on a country-wide scale, both in case of an epidemic and to take into account certain conditions at the community level. Information is needed on the conditions of generalization and transferability of this type of app to other health conditions so that CHWs can be given their full place in a pyramidal health system. ", doi="10.2196/50745", url="https://mhealth.jmir.org/2024/1/e50745" } @Article{info:doi/10.2196/57309, author="Feng, Yuanyuan and Stenger, Brad and Zhang, Shikun", title="Contextual Acceptance of COVID-19 Mitigation Mobile Apps in the United States: Mixed Methods Survey Study on Postpandemic Data Privacy", journal="J Med Internet Res", year="2024", month="Aug", day="29", volume="26", pages="e57309", keywords="data privacy", keywords="health privacy", keywords="COVID-19", keywords="mobile apps", keywords="contextual integrity", keywords="respiratory", keywords="infectious", keywords="pulmonary", keywords="pandemic", keywords="mobile app", keywords="app", keywords="apps", keywords="digital health", keywords="digital technology", keywords="digital intervention", keywords="digital interventions", keywords="smartphone", keywords="smartphones", keywords="mobile phone", abstract="Background: The COVID-19 pandemic gave rise to countless user-facing mobile apps to help fight the pandemic (``COVID-19 mitigation apps''). These apps have been at the center of data privacy discussions because they collect, use, and even retain sensitive personal data from their users (eg, medical records and location data). The US government ended its COVID-19 emergency declaration in May 2023, marking a unique time to comprehensively investigate how data privacy impacted people's acceptance of various COVID-19 mitigation apps deployed throughout the pandemic. Objective: This research aims to provide insights into health data privacy regarding COVID-19 mitigation apps and policy recommendations for future deployment of public health mobile apps through the lens of data privacy. This research explores people's contextual acceptance of different types of COVID-19 mitigation apps by applying the privacy framework of contextual integrity. Specifically, this research seeks to identify the factors that impact people's acceptance of data sharing and data retention practices in various social contexts. Methods: A mixed methods web-based survey study was conducted by recruiting a simple US representative sample (N=674) on Prolific in February 2023. The survey includes a total of 60 vignette scenarios representing realistic social contexts that COVID-19 mitigation apps could be used. Each survey respondent answered questions about their acceptance of 10 randomly selected scenarios. Three contextual integrity parameters (attribute, recipient, and transmission principle) and respondents' basic demographics are controlled as independent variables. Regression analysis was performed to determine the factors impacting people's acceptance of initial data sharing and data retention practices via these apps. Qualitative data from the survey were analyzed to support the statistical results. Results: Many contextual integrity parameter values, pairwise combinations of contextual integrity parameter values, and some demographic features of respondents have a significant impact on their acceptance of using COVID-19 mitigation apps in various social contexts. Respondents' acceptance of data retention practices diverged from their acceptance of initial data sharing practices in some scenarios. Conclusions: This study showed that people's acceptance of using various COVID-19 mitigation apps depends on specific social contexts, including the type of data (attribute), the recipients of the data (recipient), and the purpose of data use (transmission principle). Such acceptance may differ between the initial data sharing and data retention practices, even in the same context. Study findings generated rich implications for future pandemic mitigation apps and the broader public health mobile apps regarding data privacy and deployment considerations. ", doi="10.2196/57309", url="https://www.jmir.org/2024/1/e57309" } @Article{info:doi/10.2196/47070, author="Lang, Anna-Lena and Hohmuth, Nils and Vi{\vs}kovi{\'c}, Vuka{\vs}in and Konigorski, Stefan and Scholz, Stefan and Balzer, Felix and Remschmidt, Cornelius and Leistner, Rasmus", title="COVID-19 Vaccine Effectiveness and Digital Pandemic Surveillance in Germany (eCOV Study): Web Application--Based Prospective Observational Cohort Study", journal="J Med Internet Res", year="2024", month="Jun", day="4", volume="26", pages="e47070", keywords="COVID-19", keywords="SARS-CoV-2", keywords="COVID-19 vaccines", keywords="BNT162b2", keywords="vaccine effectiveness", keywords="participatory disease surveillance", keywords="web application", keywords="digital public health", keywords="vaccination", keywords="Germany", keywords="effectiveness", keywords="data collection", keywords="disease surveillance", keywords="tool", abstract="Background: The COVID-19 pandemic posed significant challenges to global health systems. Efficient public health responses required a rapid and secure collection of health data to improve the understanding of SARS-CoV-2 and examine the vaccine effectiveness (VE) and drug safety of the novel COVID-19 vaccines. Objective: This study (COVID-19 study on vaccinated and unvaccinated subjects over 16 years; eCOV study) aims to (1) evaluate the real-world effectiveness of COVID-19 vaccines through a digital participatory surveillance tool and (2) assess the potential of self-reported data for monitoring key parameters of the COVID-19 pandemic in Germany. Methods: Using a digital study web application, we collected self-reported data between May 1, 2021, and August 1, 2022, to assess VE, test positivity rates, COVID-19 incidence rates, and adverse events after COVID-19 vaccination. Our primary outcome measure was the VE of SARS-CoV-2 vaccines against laboratory-confirmed SARS-CoV-2 infection. The secondary outcome measures included VE against hospitalization and across different SARS-CoV-2 variants, adverse events after vaccination, and symptoms during infection. Logistic regression models adjusted for confounders were used to estimate VE 4 to 48 weeks after the primary vaccination series and after third-dose vaccination. Unvaccinated participants were compared with age- and gender-matched participants who had received 2 doses of BNT162b2 (Pfizer-BioNTech) and those who had received 3 doses of BNT162b2 and were not infected before the last vaccination. To assess the potential of self-reported digital data, the data were compared with official data from public health authorities. Results: We enrolled 10,077 participants (aged ?16 y) who contributed 44,786 tests and 5530 symptoms. In this young, primarily female, and digital-literate cohort, VE against infections of any severity waned from 91.2\% (95\% CI 70.4\%-97.4\%) at week 4 to 37.2\% (95\% CI 23.5\%-48.5\%) at week 48 after the second dose of BNT162b2. A third dose of BNT162b2 increased VE to 67.6\% (95\% CI 50.3\%-78.8\%) after 4 weeks. The low number of reported hospitalizations limited our ability to calculate VE against hospitalization. Adverse events after vaccination were consistent with previously published research. Seven-day incidences and test positivity rates reflected the course of the pandemic in Germany when compared with official numbers from the national infectious disease surveillance system. Conclusions: Our data indicate that COVID-19 vaccinations are safe and effective, and third-dose vaccinations partially restore protection against SARS-CoV-2 infection. The study showcased the successful use of a digital study web application for COVID-19 surveillance and continuous monitoring of VE in Germany, highlighting its potential to accelerate public health decision-making. Addressing biases in digital data collection is vital to ensure the accuracy and reliability of digital solutions as public health tools. ", doi="10.2196/47070", url="https://www.jmir.org/2024/1/e47070", url="http://www.ncbi.nlm.nih.gov/pubmed/38833299" } @Article{info:doi/10.2196/50716, author="Drover, M. Caitlin and Elder, S. Adam and Guthrie, L. Brandon and Revere, Debra and Briggs, L. Nicole and West, M. Laura and Higgins, Amanda and Lober, B. William and Karras, T. Bryant and Baseman, G. Janet", title="Use of Digital COVID-19 Exposure Notifications at a Large Gathering: Survey Analysis of Public Health Conference Attendees", journal="JMIR Form Res", year="2024", month="Mar", day="18", volume="8", pages="e50716", keywords="COVID-19", keywords="exposure notification", keywords="digital public health tool", keywords="survey analysis", keywords="conference", keywords="online survey", keywords="digital tool", keywords="public health", keywords="contact tracing", abstract="Background: WA Notify was Washington State's smartphone-based COVID-19 digital exposure notification (EN) tool, which was used to help limit the spread of COVID-19 between November 30, 2020, and May 11, 2023. Following the 2022 Washington State Public Health Association Annual Conference, attendees who had WA Notify activated began receiving ENs alerting them to a possible COVID-19 exposure during the conference. A survey was emailed to all conference attendees to measure WA Notify adoption, mechanisms through which attendees received ENs, and self-reported engagement in protective behaviors postexposure. Objective: This study aimed to learn more about the experiences of WA Notify adopters and nonadopters who may have been exposed to COVID-19 at a large group gathering. Methods: A web-based survey administered through REDCap (Research Electronic Data Capture; Vanderbilt University) was sent to all attendees of the Washington State Public Health Association conference. Self-reported demographic information and characteristics of respondents were summarized. Regression models were used to estimate relative risks to compare WA Notify adoption and testing behaviors between groups. Results: Of the 464 total registered attendees who were sent the survey, 205 (44\%) responses were received; 201 eligible attendees were included in this analysis. Of those, 149 (74\%) respondents reported having WA Notify activated on their phones at the time of the conference. Among respondents with WA Notify activated, 54\% (n=77) reported learning of their potential exposure from a WA Notify EN. Respondents who reported that they did not have WA Notify activated and learned of their potential exposure via the event-wide email from conference organizers were 39\% less likely to test for COVID-19 compared to respondents with WA Notify activated who learned of their potential exposure from the email (relative risk 0.61, 95\% CI 0.40-0.93; P=.02), and this gap was even larger when compared to respondents who learned of their exposure from a WA Notify EN. The most commonly cited reason for not having WA Notify activated was privacy concerns (n=17, 35\%), followed by not wanting to receive ENs (n=6, 12\%) and being unaware of WA Notify (n=5, 10\%). Conclusions: Digital EN systems are an important tool to directly and anonymously notify close contacts of potential exposures and provide guidance on the next steps in a timely manner. Given the privacy concerns, there is still a need for increasing transparency surrounding EN technology to increase uptake by the public if this technology were to be used in the future to slow the spread of communicable diseases. ", doi="10.2196/50716", url="https://formative.jmir.org/2024/1/e50716", url="http://www.ncbi.nlm.nih.gov/pubmed/38498047" } @Article{info:doi/10.2196/48986, author="Kang, Hyunjin and Lee, Kyu Jeong and Lee, WJ Edmund and Toh, Cindy", title="The Roles of Trust in Government and Sense of Community in the COVID-19 Contact Tracing Privacy Calculus: Mixed Method Study Using a 2-Wave Survey and In-Depth Interviews", journal="JMIR Mhealth Uhealth", year="2024", month="Mar", day="7", volume="12", pages="e48986", keywords="COVID-19", keywords="contact tracing technology", keywords="privacy calculus", keywords="trust in government", keywords="sense of community", keywords="mixed method", keywords="mobile phone", abstract="Background: Contact tracing technology has been adopted in many countries to aid in identifying, evaluating, and handling individuals who have had contact with those infected with COVID-19. Singapore was among the countries that actively implemented the government-led contact tracing program known as TraceTogether. Despite the benefits the contact tracing program could provide to individuals and the community, privacy issues were a significant barrier to individuals' acceptance of the program. Objective: Building on the privacy calculus model, this study investigates how the perceptions of the 2 key groups (ie, government and community members) involved in the digital contact tracing factor into individuals' privacy calculus of digital contact tracing. Methods: Using a mixed method approach, we conducted (1) a 2-wave survey (n=674) and (2) in-depth interviews (n=12) with TraceTogether users in Singapore. Using structural equation modeling, this study investigated how trust in the government and the sense of community exhibited by individuals during the early stage of implementation (time 1) predicted privacy concerns, perceived benefits, and future use intentions, measured after the program was fully implemented (time 2). Expanding on the survey results, this study conducted one-on-one interviews to gain in-depth insights into the privacy considerations involved in digital contact tracing. Results: The results from the survey showed that trust in the government increased perceived benefits while decreasing privacy concerns regarding the use of TraceTogether. Furthermore, individuals who felt a connection to community members by participating in the program (ie, the sense of community) were more inclined to believe in its benefits. The sense of community also played a moderating role in the influence of government trust on perceived benefits. Follow-up in-depth interviews highlighted that having a sense of control over information and transparency in the government's data management were crucial factors in privacy considerations. The interviews also highlighted surveillance as the most prevalent aspect of privacy concerns regarding TraceTogether use. In addition, our findings revealed that trust in the government, particularly the perceived transparency of government actions, was most strongly associated with concerns regarding the secondary use of data. Conclusions: Using a mixed method approach involving a 2-wave survey and in-depth interview data, we expanded our understanding of privacy decisions and the privacy calculus in the context of digital contact tracing. The opposite influences of privacy concerns and perceived benefit on use intention suggest that the privacy calculus in TraceTogether might be viewed as a rational process of weighing between privacy risks and use benefits to make an uptake decision. However, our study demonstrated that existing perceptions toward the provider and the government in the contact tracing context, as well as the perception of the community triggered by TraceTogether use, may bias user appraisals of privacy risks and the benefits of contact tracing. ", doi="10.2196/48986", url="https://mhealth.jmir.org/2024/1/e48986", url="http://www.ncbi.nlm.nih.gov/pubmed/38451602" } @Article{info:doi/10.2196/44406, author="Gheisari, Mehdi and Ghaderzadeh, Mustafa and Li, Huxiong and Taami, Tania and Fern{\'a}ndez-Campusano, Christian and Sadeghsalehi, Hamidreza and Afzaal Abbasi, Aaqif", title="Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review", journal="JMIR Mhealth Uhealth", year="2024", month="Feb", day="22", volume="12", pages="e44406", keywords="COVID-19", keywords="detection", keywords="diagnosis", keywords="internet of things", keywords="cloud computing", keywords="mobile applications", keywords="mobile app", keywords="mobile apps", keywords="artificial intelligence: AI", keywords="mobile phone", keywords="smartphone", abstract="Background: In the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of mobile apps and technology for the detection and diagnosis of COVID-19 has been the subject of numerous investigations, although no thorough analysis of COVID-19 pandemic prevention has been conducted using mobile apps, creating a gap. Objective: With the intention of helping software companies and clinical researchers, this study provides comprehensive information regarding the different fields in which mobile apps were used to diagnose COVID-19 during the pandemic. Methods: In this systematic review, 535 studies were found after searching 5 major research databases (ScienceDirect, Scopus, PubMed, Web of Science, and IEEE). Of these, only 42 (7.9\%) studies concerned with diagnosing and detecting COVID-19 were chosen after applying inclusion and exclusion criteria using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. Results: Mobile apps were categorized into 6 areas based on the content of these 42 studies: contact tracing, data gathering, data visualization, artificial intelligence (AI)--based diagnosis, rule- and guideline-based diagnosis, and data transformation. Patients with COVID-19 were identified via mobile apps using a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. Most studies concentrated on using AI methods to identify people who might have COVID-19. Additionally, symptoms, cough sounds, and radiological images were used more frequently compared to other data types. Deep learning techniques, such as convolutional neural networks, performed comparatively better in the processing of health care data than other types of AI techniques, which improved the diagnosis of COVID-19. Conclusions: Mobile apps could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and the early identification of suspected cases. These technologies can work with the internet of things, cloud storage, 5th-generation technology, and cloud computing. Processing pipelines can be moved to mobile device processing cores using new deep learning methods, such as lightweight neural networks. In the event of future pandemics, mobile apps will play a critical role in rapid diagnosis using various image data and clinical symptoms. Consequently, the rapid diagnosis of these diseases can improve the management of their effects and obtain excellent results in treating patients. ", doi="10.2196/44406", url="https://mhealth.jmir.org/2024/1/e44406", url="http://www.ncbi.nlm.nih.gov/pubmed/38231538" } @Article{info:doi/10.2196/48700, author="Fox, Grace and van der Werff, Lisa and Rosati, Pierangelo and Lynn, Theo", title="Investigating Citizens' Acceptance of Contact Tracing Apps: Quantitative Study of the Role of Trust and Privacy", journal="JMIR Mhealth Uhealth", year="2024", month="Jan", day="18", volume="12", pages="e48700", keywords="privacy", keywords="trust", keywords="public health surveillance", keywords="contact tracing", keywords="mobile apps", keywords="adoption", keywords="information disclosure", abstract="Background: The COVID-19 pandemic accelerated the need to understand citizen acceptance of health surveillance technologies such as contact tracing (CT) apps. Indeed, the success of these apps required widespread public acceptance and the alleviation of concerns about privacy, surveillance, and trust. Objective: This study aims to examine the factors that foster a sense of trust and a perception of privacy in CT apps. Our study also investigates how trust and perceived privacy influence citizens' willingness to adopt, disclose personal data, and continue to use these apps. Methods: Drawing on privacy calculus and procedural fairness theories, we developed a model of the antecedents and behavioral intentions related to trust and privacy perceptions. We used structural equation modeling to test our hypotheses on a data set collected at 2 time points (before and after the launch of a national CT app). The sample consisted of 405 Irish residents. Results: Trust in CT apps was positively influenced by propensity to trust technology ($\beta$=.074; P=.006), perceived need for surveillance ($\beta$=.119; P<.001), and perceptions of government motives ($\beta$=.671; P<.001) and negatively influenced by perceived invasion ($\beta$=?.224; P<.001). Perceived privacy was positively influenced by trust ($\beta$=.466; P<.001) and perceived control ($\beta$=.451; P<.001) and negatively influenced by perceived invasion ($\beta$=?.165; P<.001). Prelaunch intentions toward adoption were influenced by trust ($\beta$=.590; P<.001) and perceived privacy ($\beta$=.247; P<.001). Prelaunch intentions to disclose personal data to the app were also influenced by trust ($\beta$=.215; P<.001) and perceived privacy ($\beta$=.208; P<.001) as well as adoption intentions before the launch ($\beta$=.550; P<.001). However, postlaunch intentions to use the app were directly influenced by prelaunch intentions ($\beta$=.530; P<.001), but trust and perceived privacy only had an indirect influence. Finally, with regard to intentions to disclose after the launch, use intentions after the launch ($\beta$=.665; P<.001) and trust ($\beta$=.215; P<.001) had a direct influence, but perceived privacy only had an indirect influence. The proposed model explained 74.4\% of variance in trust, 91\% of variance in perceived privacy, 66.6\% of variance in prelaunch adoption intentions, 45.9\% of variance in postlaunch use intentions, and 83.9\% and 79.4\% of variance in willingness to disclose before the launch and after the launch, respectively. Conclusions: Positive perceptions of trust and privacy can be fostered through clear communication regarding the need and motives for CT apps, the level of control citizens maintain, and measures to limit invasive data practice. By engendering these positive beliefs before launch and reinforcing them after launch, citizens may be more likely to accept and use CT apps. These insights are important for the launch of future apps and technologies that require mass acceptance and information disclosure. ", doi="10.2196/48700", url="https://mhealth.jmir.org/2024/1/e48700", url="http://www.ncbi.nlm.nih.gov/pubmed/38085914" } @Article{info:doi/10.2196/43105, author="Singh, Akanksha and Schooley, Benjamin and Patel, Nitin", title="Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot: Cross-Sectional Study", journal="JMIR Mhealth Uhealth", year="2023", month="Dec", day="14", volume="11", pages="e43105", keywords="patient engagement", keywords="chatbot", keywords="population health", keywords="health recommender systems", keywords="conversational recommender systems", keywords="design factors", keywords="COVID-19", abstract="Background: The COVID-19 pandemic influenced many to consider methods to reduce human contact and ease the burden placed on health care workers. Conversational agents or chatbots are a set of technologies that may aid with these challenges. They may provide useful interactions for users, potentially reducing the health care worker burden while increasing user satisfaction. Research aims to understand these potential impacts of chatbots and conversational recommender systems and their associated design features. Objective: The objective of this study was to evaluate user perceptions of the helpfulness of an artificial intelligence chatbot that was offered free to the public in response to COVID-19. The chatbot engaged patients and provided educational information and the opportunity to report symptoms, understand personal risks, and receive referrals for care. Methods: A cross-sectional study design was used to analyze 82,222 chats collected from patients in South Carolina seeking services from the Prisma Health system. Chi-square tests and multinomial logistic regression analyses were conducted to assess the relationship between reported risk factors and perceived chat helpfulness using chats started between April 24, 2020, and April 21, 2022. Results: A total of 82,222 chat series were started with at least one question or response on record; 53,805 symptom checker questions with at least one COVID-19--related activity series were completed, with 5191 individuals clicking further to receive a virtual video visit and 2215 clicking further to make an appointment with a local physician. Patients who were aged >65 years (P<.001), reported comorbidities (P<.001), had been in contact with a person with COVID-19 in the last 14 days (P<.001), and responded to symptom checker questions that placed them at a higher risk of COVID-19 (P<.001) were 1.8 times more likely to report the chat as helpful than those who reported lower risk factors. Users who engaged with the chatbot to conduct a series of activities were more likely to find the chat helpful (P<.001), including seeking COVID-19 information (3.97-4.07 times), in-person appointments (2.46-1.99 times), telehealth appointments with a nearby provider (2.48-1.9 times), or vaccination (2.9-3.85 times) compared with those who did not perform any of these activities. Conclusions: Chatbots that are designed to target high-risk user groups and provide relevant actionable items may be perceived as a helpful approach to early contact with the health system for assessing communicable disease symptoms and follow-up care options at home before virtual or in-person contact with health care providers. The results identified and validated significant design factors for conversational recommender systems, including triangulating a high-risk target user population and providing relevant actionable items for users to choose from as part of user engagement. ", doi="10.2196/43105", url="https://mhealth.jmir.org/2023/1/e43105", url="http://www.ncbi.nlm.nih.gov/pubmed/38096007" } @Article{info:doi/10.2196/45875, author="Davoodi, Mansoor and Batista, Ana and Mertel, Adam and Senapati, Abhishek and Abdussalam, Wildan and Vyskocil, Jiri and Barbieri, Giuseppe and Fan, Kai and Schlechte-Welnicz, Weronika and M Calabrese, Justin", title="A Web-Based COVID-19 Tool for Testing Residents in Retirement Homes: Development Study", journal="JMIR Form Res", year="2023", month="Nov", day="21", volume="7", pages="e45875", keywords="application", keywords="COVID-19", keywords="optimized testing", keywords="pandemic", keywords="retirement home", keywords="web application", abstract="Background: Long-term care facilities have been widely affected by the COVID-19 pandemic. Empirical evidence demonstrated that older people are the most impacted and are at higher risk of mortality after being infected. Regularly testing care facility residents is a practical approach to detecting infections proactively. In many cases, the care staff must perform the tests on the residents while also providing essential care, which in turn causes imbalances in their working time. Once an outbreak occurs, suppressing the spread of the virus in retirement homes (RHs) is challenging because the residents are in contact with each other, and isolation measures cannot be widely enforced. Regular testing strategies, on the other hand, have been shown to effectively prevent outbreaks in RHs. However, high-frequency testing may consume substantial staff working time, which results in a trade-off between the time invested in testing and the time spent providing essential care to residents. Objective: We developed a web application (Retirement Home Testing Optimizer) to assist RH managers in identifying effective testing schedules for residents. The outcome of the app, called the ``testing strategy,'' is based on dividing facility residents into groups and then testing no more than 1 group per day. Methods: We created the web application by incorporating influential factors such as the number of residents and staff, the average rate of contacts, the amount of time spent to test, and constraints on the test interval and size of groups. We developed mixed integer nonlinear programming models for balancing staff workload in long-term care facilities while minimizing the expected detection time of a probable infection inside the facility. Additionally, by leveraging symmetries in the problem, we proposed a fast and efficient local search method to find the optimal solution. Results: Considering the number of residents and staff and other practical constraints of the facilities, the proposed application computes the optimal trade-off testing strategy and suggests the corresponding grouping and testing schedule for residents. The current version of the application is deployed on the server of the Where2Test project and is accessible on their website. The application is open source, and all contents are offered in English and German. We provide comprehensive instructions and guidelines for easy use and understanding of the application's functionalities. The application was launched in July 2022, and it is currently being tested in RHs in Saxony, Germany. Conclusions: Recommended testing strategies by our application are tailored to each RH and the goals set by the managers. We advise the users of the application that the proposed model and approach focus on the expected scenarios, that is, the expected risk of infection, and they do not guarantee the avoidance of worst-case scenarios. ", doi="10.2196/45875", url="https://formative.jmir.org/2023/1/e45875", url="http://www.ncbi.nlm.nih.gov/pubmed/37988136" } @Article{info:doi/10.2196/45481, author="Dolezel, Michal and Smutny, Zdenek", title="Adoption of a COVID-19 Contact Tracing App by Czech Youth: Cross-Cultural Replication Study", journal="JMIR Hum Factors", year="2023", month="Nov", day="16", volume="10", pages="e45481", keywords="contact tracing", keywords="proximity tracing", keywords="digital contact tracing", keywords="Health Belief Model", keywords="technology adoption", keywords="COVID-19", keywords="qualitative verification", keywords="Health Belief Model approach", keywords="pandemic crisis", keywords="eRouska", keywords="eMask", abstract="Background: During the worldwide COVID-19 pandemic crisis, the role of digital contact tracing (DCT) intensified. However, the uptake of this technology expectedly differed among age cohorts and national cultures. Various conceptual tools were introduced to strengthen DCT research from a theoretical perspective. However, little has been done to compare theory-supported findings across different cultural contexts and age cohorts. Objective: Building on the original study conducted in Belgium in April 2020 and theoretically underpinned by the Health Belief Model (HBM), this study attempted to confirm the predictors of DCT adoption in a cultural environment different from the original setting, that is, the Czech Republic. In addition, by using brief qualitative evidence, it aimed to shed light on the possible limitations of the HBM in the examined context and to propose certain extensions of the HBM. Methods: A Czech version of the original instrument was administered to a convenience sample of young (aged 18-29 y) Czech adults in November 2020. After filtering, 519 valid responses were obtained and included in the quantitative data analysis, which used structural equation modeling and followed the proposed structure of the relationships among the HBM constructs. Furthermore, a qualitative thematic analysis of the free-text answers was conducted to provide additional insights about the model's validity in the given context. Results: The proposed measurement model exhibited less optimal fit (root mean square error of approximation=0.065, 90\% CI 0.060-0.070) than in the original study (root mean square error of approximation=0.036, 90\% CI 0.033-0.039). Nevertheless, perceived benefits and perceived barriers were confirmed as the main, statistically significant predictors of DCT uptake, consistent with the original study ($\beta$=.60, P<.001 and $\beta$=?.39; P<.001, respectively). Differently from the original study, self-efficacy was not a significant predictor in the strict statistical sense ($\beta$=.12; P=.003). In addition, qualitative analysis demonstrated that in the given cohort, perceived barriers was the most frequent theme (166/354, 46.9\% of total codes). Under this category, psychological fears and concerns was a subtheme, notably diverging from the original operationalization of the perceived barriers construct. In a similar sense, a role for social influence in DCT uptake processes was suggested by some respondents (12/354, 1.7\% of total codes). In summary, the quantitative and qualitative results indicated that the proposed quantitative model seemed to be of limited value in the examined context. Conclusions: Future studies should focus on reconceptualizing the 2 underperforming constructs (ie, perceived severity and cues to action) by considering the qualitative findings. This study also provided actionable insights for policy makers and app developers to mitigate DCT adoption issues in the event of a future pandemic caused by unknown viral agents. ", doi="10.2196/45481", url="https://humanfactors.jmir.org/2023/1/e45481", url="http://www.ncbi.nlm.nih.gov/pubmed/37971804" } @Article{info:doi/10.2196/47219, author="Wang, Hsiao-Chi and Lin, Ting-Yu and Yao, Yu-Chin and Hsu, Chen-Yang and Yang, Chang-Jung and Chen, Hsiu-Hsi Tony and Yeh, Yen-Po", title="Community-Based Digital Contact Tracing of Emerging Infectious Diseases: Design and Implementation Study With Empirical COVID-19 Cases", journal="J Med Internet Res", year="2023", month="Nov", day="8", volume="25", pages="e47219", keywords="COVID-19", keywords="digital contact tracing", keywords="public health", keywords="surveillance", abstract="Background: Contact tracing for containing emerging infectious diseases such as COVID-19 is resource intensive and requires digital transformation to enable timely decision-making. Objective: This study demonstrates the design and implementation of digital contact tracing using multimodal health informatics to efficiently collect personal information and contain community outbreaks. The implementation of digital contact tracing was further illustrated by 3 empirical SARS-CoV-2 infection clusters. Methods: The implementation in Changhua, Taiwan, served as a demonstration of the multisectoral informatics and connectivity between electronic health systems needed for digital contact tracing. The framework incorporates traditional travel, occupation, contact, and cluster approaches and a dynamic contact process enabled by digital technology. A centralized registry system, accessible only to authorized health personnel, ensures privacy and data security. The efficiency of the digital contact tracing system was evaluated through a field study in Changhua. Results: The digital contact tracing system integrates the immigration registry, communicable disease report system, and national health records to provide real-time information about travel, occupation, contact, and clusters for potential contacts and to facilitate a timely assessment of the risk of COVID-19 transmission. The digitalized system allows for informed decision-making regarding quarantine, isolation, and treatment, with a focus on personal privacy. In the first cluster infection, the system monitored 665 contacts and isolated 4 (0.6\%) cases; none of the contacts (0/665, 0\%) were infected during quarantine. The estimated reproduction number of 0.92 suggests an effective containment strategy for preventing community-acquired outbreak. The system was also used in a cluster investigation involving foreign workers, where none of the 462 contacts (0/462, 0\%) tested positive for SARS-CoV-2. Conclusions: By integrating the multisectoral database, the contact tracing process can be digitalized to provide the information required for risk assessment and decision-making in a timely manner to contain a community-acquired outbreak when facing the outbreak of emerging infectious disease. ", doi="10.2196/47219", url="https://www.jmir.org/2023/1/e47219", url="http://www.ncbi.nlm.nih.gov/pubmed/37938887" } @Article{info:doi/10.2196/45549, author="Kr{\"a}mer, Dennis and Brachem, Elisabeth and Schneider-Reuter, Lydia and D'Angelo, Isabella and Vollmann, Jochen and Haltaufderheide, Joschka", title="Smartphone Apps for Containing the COVID-19 Pandemic in Germany: Qualitative Interview Study With Experts Based on Grounded Theory", journal="J Med Internet Res", year="2023", month="Oct", day="20", volume="25", pages="e45549", keywords="Corona-Warn-App", keywords="COVID-19 pandemic", keywords="eHealth", keywords="Germany", keywords="health technology", keywords="mobile phone", keywords="qualitative research", keywords="sovereignty", keywords="transparency", abstract="Background: Smartphone apps, including those for digital contact tracing (DCT), played a crucial role in containing infections during the COVID-19 pandemic. Their primary function is to generate and disseminate information to disrupt transmissions based on various events, such as encounters, vaccinations, locations, or infections. Although the functionality of these apps has been extensively studied, there is still a lack of qualitative research addressing critical issues. Objective: We will demonstrate that the use of DCT presents a challenge due to the tension between continuous health monitoring and uncertainties related to transparency and user sovereignty. On one hand, DCT enables the monitoring of various risk factors, including data-based calculations of infection probabilities. On the other hand, continuous risk management is intertwined with several uncertainties, including the unclear storage of personal data, who has access to it, and how it will be used in the future. Methods: We focus on the German ``Corona-Warn-App'' and support our argument with empirical data from 19 expert interviews conducted between 2020 and 2021. The interviews were conducted using a semistructured questionnaire and analyzed according to the principles of grounded theory. Results: Our data underscores 3 dimensions: transparency, data sovereignty, and the east-west divide. While transparency is considered an essential foundation for establishing trust in the use of DCT by providing a sense of security, data sovereignty is seen as a high value during the pandemic, protecting users from an undesired loss of control. The aspect of the east-west divide highlights the idea of incorporating sociocultural values and standards into technology, emphasizing that algorithms and data-driven elements, such as distance indicators, encounters, and isolations, are also influenced by sociocultural factors. Conclusions: The effective use of DCT for pandemic containment relies on achieving a balance between individual control and technological prevention. Maximizing the technological benefits of these tools is crucial. However, users must also be mindful of the information they share and maintain control over their shared data. ", doi="10.2196/45549", url="https://www.jmir.org/2023/1/e45549", url="http://www.ncbi.nlm.nih.gov/pubmed/37862068" } @Article{info:doi/10.2196/38072, author="Nguyen, Vincent and Liu, Yunzhe and Mumford, Richard and Flanagan, Benjamin and Patel, Parth and Braithwaite, Isobel and Shrotri, Madhumita and Byrne, Thomas and Beale, Sarah and Aryee, Anna and Fong, Erica Wing Lam and Fragaszy, Ellen and Geismar, Cyril and Navaratnam, D. Annalan M. and Hardelid, Pia and Kovar, Jana and Pope, Addy and Cheng, Tao and Hayward, Andrew and Aldridge, Robert and ", title="Tracking Changes in Mobility Before and After the First SARS-CoV-2 Vaccination Using Global Positioning System Data in England and Wales (Virus Watch): Prospective Observational Community Cohort Study", journal="JMIR Public Health Surveill", year="2023", month="Mar", day="8", volume="9", pages="e38072", keywords="COVID-19", keywords="SARS-CoV-2", keywords="vaccination", keywords="global positioning system", keywords="GPS", keywords="movement tracking", keywords="geographical tracking", keywords="mobile app", keywords="health application", keywords="surveillance", keywords="public health", keywords="mHealth", keywords="mobile surveillance", keywords="tracking device", keywords="geolocation", abstract="Background: Evidence suggests that individuals may change adherence to public health policies aimed at reducing the contact, transmission, and spread of the SARS-CoV-2 virus after they receive their first SARS-CoV-2 vaccination when they are not fully vaccinated. Objective: We aimed to estimate changes in median daily travel distance of our cohort from their registered addresses before and after receiving a SARS-CoV-2 vaccine. Methods: Participants were recruited into Virus Watch starting in June 2020. Weekly surveys were sent out to participants, and vaccination status was collected from January 2021 onward. Between September 2020 and February 2021, we invited 13,120 adult Virus Watch participants to contribute toward our tracker subcohort, which uses the GPS via a smartphone app to collect data on movement. We used segmented linear regression to estimate the median daily travel distance before and after the first self-reported SARS-CoV-2 vaccine dose. Results: We analyzed the daily travel distance of 249 vaccinated adults. From 157 days prior to vaccination until the day before vaccination, the median daily travel distance was 9.05 (IQR 8.06-10.09) km. From the day of vaccination to 105 days after vaccination, the median daily travel distance was 10.08 (IQR 8.60-12.42) km. From 157 days prior to vaccination until the vaccination date, there was a daily median decrease in mobility of 40.09 m (95\% CI --50.08 to --31.10; P<.001). After vaccination, there was a median daily increase in movement of 60.60 m (95\% CI 20.90-100; P<.001). Restricting the analysis to the third national lockdown (January 4, 2021, to April 5, 2021), we found a median daily movement increase of 18.30 m (95\% CI --19.20 to 55.80; P=.57) in the 30 days prior to vaccination and a median daily movement increase of 9.36 m (95\% CI 38.6-149.00; P=.69) in the 30 days after vaccination. Conclusions: Our study demonstrates the feasibility of collecting high-volume geolocation data as part of research projects and the utility of these data for understanding public health issues. Our various analyses produced results that ranged from no change in movement after vaccination (during the third national lock down) to an increase in movement after vaccination (considering all periods, up to 105 days after vaccination), suggesting that, among Virus Watch participants, any changes in movement distances after vaccination are small. Our findings may be attributable to public health measures in place at the time such as movement restrictions and home working that applied to the Virus Watch cohort participants during the study period. ", doi="10.2196/38072", url="https://publichealth.jmir.org/2023/1/e38072", url="http://www.ncbi.nlm.nih.gov/pubmed/36884272" } @Article{info:doi/10.2196/38555, author="Tan, Ying Jamaica Pei and Tan, J. Michelle W. and Towle, Marie Rachel and Lee, Win Joanne Sze and Lei, Xiaofeng and Liu, Yong and Goh, Mong Rick Siow and Chee Ping, Tan Franklin and Tan, Choon Teck and Ting, Wei Daniel Shu and Lee, Ee Chen and Low, Leng Lian", title="mHealth App to Facilitate Remote Care for Patients With COVID-19: Rapid Development of the DrCovid+ App", journal="JMIR Form Res", year="2023", month="Feb", day="7", volume="7", pages="e38555", keywords="mobile health", keywords="mHealth", keywords="rapid development", keywords="remote care", keywords="COVID-19", keywords="hospital-at-home", keywords="mobile app", keywords="app development", keywords="virtual care", keywords="Telegram service", keywords="clinical care", keywords="continuity of care", keywords="digital health", abstract="Background: The 2019 novel COVID-19 has severely burdened the health care system through its rapid transmission. Mobile health (mHealth) is a viable solution to facilitate remote monitoring and continuity of care for patients with COVID-19 in a home environment. However, the conceptualization and development of mHealth apps are often time and labor-intensive and are laden with concerns relating to data security and privacy. Implementing mHealth apps is also a challenging feat as language-related barriers limit adoption, whereas its perceived lack of benefits affects sustained use. The rapid development of an mHealth app that is cost-effective, secure, and user-friendly will be a timely enabler. Objective: This project aimed to develop an mHealth app, DrCovid+, to facilitate remote monitoring and continuity of care for patients with COVID-19 by using the rapid development approach. It also aimed to address the challenges of mHealth app adoption and sustained use. Methods: The Rapid Application Development approach was adopted. Stakeholders including decision makers, physicians, nurses, health care administrators, and research engineers were engaged. The process began with requirements gathering to define and finalize the project scope, followed by an iterative process of developing a working prototype, conducting User Acceptance Tests, and improving the prototype before implementation. Co-designing principles were applied to ensure equal collaborative efforts and collective agreement among stakeholders. Results: DrCovid+ was developed on Telegram Messenger and hosted on a cloud server. It features a secure patient enrollment and data interface, a multilingual communication channel, and both automatic and personalized push messaging. A back-end dashboard was also developed to collect patients' vital signs for remote monitoring and continuity of care. To date, 400 patients have been enrolled into the system, amounting to 2822 hospital bed--days saved. Conclusions: The rapid development and implementation of DrCovid+ allowed for timely clinical care management for patients with COVID-19. It facilitated early patient hospital discharge and continuity of care while addressing issues relating to data security and labor-, time-, and cost-effectiveness. The use case for DrCovid+ may be extended to other medical conditions to advance patient care and empowerment within the community, thereby meeting existing and rising population health challenges. ", doi="10.2196/38555", url="https://formative.jmir.org/2023/1/e38555", url="http://www.ncbi.nlm.nih.gov/pubmed/36649223" } @Article{info:doi/10.2196/43241, author="Baretta, Dario and Amrein, Alexandra Melanie and B{\"a}der, Carole and Ruschetti, Giacomo Gian and R{\"u}ttimann, Carole and Del Rio Carral, Maria and Fabian, Carlo and Inauen, Jennifer", title="Promoting Hand Hygiene During the COVID-19 Pandemic: Parallel Randomized Trial for the Optimization of the Soapp App", journal="JMIR Mhealth Uhealth", year="2023", month="Feb", day="3", volume="11", pages="e43241", keywords="COVID-19", keywords="hand hygiene", keywords="behavior change intervention", keywords="Multiphase Optimization Strategy", keywords="MOST", keywords="smartphone apps", keywords="motivation", keywords="habit", keywords="social norm", keywords="mobile phone", abstract="Background: Hand hygiene is an effective behavior for preventing the spread of the respiratory disease COVID-19 and was included in public health guidelines worldwide. Behavior change interventions addressing hand hygiene have the potential to support the adherence to public health recommendations and, thereby, prevent the spread of COVID-19. However, randomized trials are largely absent during a pandemic; therefore, there is little knowledge about the most effective strategies to promote hand hygiene during an ongoing pandemic. This study addresses this gap by presenting the results of the optimization phase of a Multiphase Optimization Strategy of Soapp, a smartphone app for promoting hand hygiene in the context of the COVID-19 pandemic. Objective: This study aimed to identify the most effective combination and sequence of 3 theory- and evidence-based intervention modules (habit, motivation, and social norms) for promoting hand hygiene. To this end, 9 versions of Soapp were developed (conditions), and 2 optimization criteria were defined: the condition with the largest increase in hand hygiene at follow-up and condition with the highest engagement, usability, and satisfaction based on quantitative and qualitative analyses. Methods: This study was a parallel randomized trial with 9 intervention conditions defined by the combination of 2 intervention modules and their sequence. The trial was conducted from March to August 2021 with interested participants from the Swiss general population (N=232; randomized). Randomization was performed using Qualtrics (Qualtrics International Inc), and blinding was ensured. The duration of the intervention was 34 days. The primary outcome was self-reported hand hygiene at follow-up, which was assessed using an electronic diary. The secondary outcomes were user engagement, usability, and satisfaction assessed at follow-up. Nine participants were further invited to participate in semistructured exit interviews. A set of ANOVAs was performed to test the main hypotheses, whereas a thematic analysis was performed to analyze the qualitative data. Results: The results showed a significant increase in hand hygiene over time across all conditions. There was no interaction effect between time and intervention condition. Similarly, no between-group differences in engagement, usability, and satisfaction emerged. Seven themes (eg, ``variety and timeliness of the task load'' and ``social interaction'') were found in the thematic analysis. Conclusions: The effectiveness of Soapp in promoting hand hygiene laid the foundation for the next evaluation phase of the app. More generally, the study supported the value of digital interventions in pandemic contexts. The findings showed no differential effect of intervention conditions involving different combinations and sequences of the habit, motivation, and social norms modules on hand hygiene, engagement, usability, and satisfaction. In the absence of quantitative differences, we relied on the results from the thematic analysis to select the best version of Soapp for the evaluation phase. Trial Registration: ClinicalTrials.gov NCT04830761; https://clinicaltrials.gov/ct2/show/NCT04830761 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2021-055971 ", doi="10.2196/43241", url="https://mhealth.jmir.org/2023/1/e43241", url="http://www.ncbi.nlm.nih.gov/pubmed/36599056" } @Article{info:doi/10.2196/43639, author="Kittipimpanon, Kamonrat and Noyudom, Angun and Panjatharakul, Pawanrat and Visudtibhan, Janepanish Poolsuk", title="Use of and Satisfaction With Mobile Health Education During the COVID-19 Pandemic in Thailand: Cross-sectional Study", journal="JMIR Form Res", year="2023", month="Jan", day="24", volume="7", pages="e43639", keywords="mHealth", keywords="COVID-19", keywords="chatbot", keywords="use", keywords="satisfaction", abstract="Background: RamaCovid is a mobile health (mHealth) education system that provides the Thai population with information about COVID-19 and self-risk assessment. RamaCovid has a chatbot system that provides automatic conversations (available 24 hours per day) and a live chat function that allows users to directly communicate with health professionals (available 4 hours per day in the evening). The system consists of (1) COVID-19 vaccine information, (2) self-care after vaccination, (3) frequently asked questions, (4) self-risk assessment, (5) hospital finding, (6) contact number finding, and (7) live chat with a health professional. Objective: This study investigates the use of and satisfaction with the RamaCovid system. Methods: Overall, 400 people were recruited via RamaCovid by broadcasting an infographic about the study. Questionnaires collected demographic data, users' experiences of RamaCovid, and the use of and satisfaction with the system. The questions were answered using a 5-point Likert scale. Descriptive statistics were used to describe the participant characteristics and their use of and satisfaction with the RamaCovid system. The Mann-Whitney U test was performed to examine the difference in use and satisfaction between the adult and older adult groups. Results: The participants showed high use of and satisfaction with the RamaCovid system. They used the information to take care of themselves and their family, and they gained information about their COVID-19 risk. The users were satisfied with the system because the information was easy to understand, trustworthy, and up to date. However, the older adult group had lower use of and satisfaction with the system compared to the adult group. Conclusions: RamaCovid is an example of the successful implementation of mHealth education. It was an alternative way to work with the call center during the COVID-19 pandemic and increased access to health information and health care services. Providing ongoing updated information, improving the attractiveness of the media information, and the age group difference are important issues for further system development. ", doi="10.2196/43639", url="https://formative.jmir.org/2023/1/e43639", url="http://www.ncbi.nlm.nih.gov/pubmed/36596210" } @Article{info:doi/10.2196/39570, author="Villius Zetterholm, My and Nilsson, Lina and Jokela, P{\"a}ivi", title="Using a Proximity-Detection Technology to Nudge for Physical Distancing in a Swedish Workplace During the COVID-19 Pandemic: Retrospective Case Study", journal="JMIR Form Res", year="2022", month="Dec", day="12", volume="6", number="12", pages="e39570", keywords="case study", keywords="COVID-19", keywords="feasibility", keywords="mixed methods", keywords="nudging", keywords="physical distance", keywords="preventive behavior", keywords="preventive technologies", keywords="proximity detecting technology", keywords="wearables", abstract="Background: The recent COVID-19 pandemic has contributed to the emergence of several technologies for infectious disease management. Although much focus has been placed on contact-tracing apps, another promising new tactic is proximity tracing, which focuses on health-related behavior and can be used for primary prevention. Underpinned by theories on behavioral design, a proximity-detection system can be devised that provides a user with immediate nudges to maintain physical distance from others. However, the practical feasibility of proximity detection during an infectious disease outbreak has not been sufficiently investigated. Objective: We aimed to evaluate the feasibility of using a wearable device to nudge for distance and to gather important insights about how functionality and interaction are experienced by users. The results of this study can guide future research and design efforts in this emerging technology. Methods: In this retrospective case study, a wearable proximity-detection technology was used in a workplace for 6 weeks during the production of a music competition. The purpose of the technology was to nudge users to maintain their physical distance using auditory feedback. We used a mixed methods sequential approach, including interviews (n=8) and a survey (n=30), to compile the experiences of using wearable technology in a real-life setting. Results: We generated themes from qualitative analysis based on data from interviews and open-text survey responses. The quantitative data were subsequently integrated into these themes: feasibility (implementation and acceptance---establishing a shared problem; distance tags in context---strategy, environment, and activities; understanding and learning; and accomplishing the purpose) and design aspects (a purposefully annoying device; timing, tone, and proximity; and additional functions). Conclusions: This empirical study reports on the feasibility of using wearable technology based on proximity detection to nudge individuals to maintain physical distance in the workplace. The technology supports attention to distance, but the usability of this approach is dependent on the context and situation. In certain situations, the audio signal is frustrating, but most users agree that it needs to be annoying to ensure sufficient behavioral adaption. We proposed a dual nudge that involves vibration followed by sound. There are indications that the technology also facilitates learning how to maintain a greater distance from others, and that this behavior can persist beyond the context of technology use. This study demonstrates that the key value of this technology is that it places the user in control and enables immediate action when the distance to others is not maintained. This study provides insights into the emerging field of personal and wearable technologies used for primary prevention during infectious disease outbreaks. Future research is needed to evaluate the preventive effect on transmission and investigate behavioral changes in detail and in relation to different forms of feedback. ", doi="10.2196/39570", url="https://formative.jmir.org/2022/12/e39570", url="http://www.ncbi.nlm.nih.gov/pubmed/36343202" } @Article{info:doi/10.2196/41689, author="Comtois, Anne Katherine and Mata-Greve, Felicia and Johnson, Morgan and Pullmann, D. Michael and Mosser, Brittany and Arean, Patricia", title="Effectiveness of Mental Health Apps for Distress During COVID-19 in US Unemployed and Essential Workers: Remote Pragmatic Randomized Clinical Trial", journal="JMIR Mhealth Uhealth", year="2022", month="Nov", day="7", volume="10", number="11", pages="e41689", keywords="COVID-19", keywords="COVID", keywords="coronavirus", keywords="pandemic", keywords="SARS-CoV-2", keywords="essential worker", keywords="suicide", keywords="suicidal", keywords="commercial app", keywords="mental health apps", keywords="health app", keywords="mental health", keywords="mHealth", keywords="mobile health", keywords="occupational health", keywords="employee", keywords="employment", keywords="unemployed", keywords="worker", keywords="job", keywords="depression", keywords="anxiety", keywords="stress", keywords="distress", keywords="mobile app", keywords="RCT", keywords="pragmatic trial", keywords="randomized", keywords="health care worker", keywords="health care provider", keywords="frontline staff", 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 ", doi="10.2196/41689", url="https://mhealth.jmir.org/2022/11/e41689", url="http://www.ncbi.nlm.nih.gov/pubmed/36191176" } @Article{info:doi/10.2196/36412, author="Chantziara, Sofia and Brigden L C, Amberly and Mccallum, H. Claire and Craddock, J. Ian", title="Using Digital Tools for Contact Tracing to Improve COVID-19 Safety in Schools: Qualitative Study Exploring Views and Experiences Among School Staff", journal="JMIR Form Res", year="2022", month="Nov", day="1", volume="6", number="11", pages="e36412", keywords="schools", keywords="contact tracing", keywords="COVID-19 mitigation", keywords="COVID-19", keywords="pandemic", keywords="disease prevention", keywords="health technology", keywords="COVID-19 management", keywords="technology support", keywords="digital tool", keywords="mobile health", keywords="mobile technology", abstract="Background: Throughout the pandemic, governments worldwide have issued guidelines to manage the spread and impact of COVID-19 in schools, including measures around social distancing and contact tracing. Whether schools required support to implement these guidelines has not yet been explored in depth. Despite the development of a range of technologies to tackle COVID-19, such as contact-tracing apps and electronic vaccine certificates, research on their usefulness in school settings has been limited. Objective: The aim of the study was to explore the needs of school staff in managing COVID-19 and their experiences and perspectives on technological support in relation to contact tracing. School staff are the ones likely to make key implementation decisions regarding new technologies, and they are also the ones responsible for using the new tools daily. Including both management staff and class teachers in the development of school-based technologies can lead to their successful adoption by schools. Methods: Semistructured interviews were conducted with UK school staff, including primary and secondary school teachers and school managers. Thematic analysis, facilitated by NVivo, was used to analyze the data. Two of the authors independently coded 5 (28\%) of the interviews and reached a consensus on a coding framework. Results: Via purposive sampling, we recruited 18 participants from 5 schools. Findings showed that primary schools did not perform contact tracing, while in secondary schools, digital seating plans were used to identify close contacts in the classroom and manual investigations were also conducted identify social contacts. Participants reported that despite their efforts, high-risk interactions between students were not adequately monitored. There was a need to improve accuracy when identifying close contacts in common areas where students congregate. Proximity tracking, use of access cards, and closed-circuit television (CCTV) emerged as potential solutions, but there were concerns surrounding false alerts, burden, and security. Conclusions: School staff have found it difficult to monitor and implement social distancing and contact-tracing provisions. There are opportunities for mobile digital technologies and CCTV to support school staff in keeping their students and colleagues safe; however, these must place minimal demands on staff and prioritize security measures. Study findings can help researchers and practitioners who work in different contexts and settings understand what particular challenges are faced by school staff, and inform further research on the design and application of digital solutions for contact tracing. ", doi="10.2196/36412", url="https://formative.jmir.org/2022/11/e36412", url="http://www.ncbi.nlm.nih.gov/pubmed/36191172" } @Article{info:doi/10.2196/40233, author="Liu, MingXin and Zhou, SiYu and Jin, Qun and Nishimura, Shoji and Ogihara, Atsushi", title="Effectiveness, Policy, and User Acceptance of COVID-19 Contact-Tracing Apps in the Post--COVID-19 Pandemic Era: Experience and Comparative Study", journal="JMIR Public Health Surveill", year="2022", month="Oct", day="27", volume="8", number="10", pages="e40233", keywords="COVID-19", keywords="contact-tracing app", keywords="digital contact tracing", keywords="mobile phone", abstract="Background: In the post--COVID-19 pandemic era, many countries have launched apps to trace contacts of COVID-19 infections. Each contact-tracing app (CTA) faces a variety of issues owing to different national policies or technologies for tracing contacts. Objective: In this study, we aimed to investigate all the CTAs used to trace contacts in various countries worldwide, including the technology used by each CTA, the availability of knowledge about the CTA from official websites, the interoperability of CTAs in various countries, and the infection detection rates and policies of the specific country that launched the CTA, and to summarize the current problems of the apps based on the information collected. Methods: We investigated CTAs launched in all countries through Google, Google Scholar, and PubMed. We experimented with all apps that could be installed and compiled information about apps that could not be installed or used by consulting official websites and previous literature. We compared the information collected by us on CTAs with relevant previous literature to understand and analyze the data. Results: After screening 166 COVID-19 apps developed in 197 countries worldwide, we selected 98 (59\%) apps from 95 (48.2\%) countries, of which 63 (66.3\%) apps were usable. The methods of contact tracing are divided into 3 main categories: Bluetooth, geolocation, and QR codes. At the technical level, CTAs face 3 major problems. First, the distance and time for Bluetooth- and geolocation-based CTAs to record contact are generally set to 2 meters and 15 minutes; however, this distance should be lengthened, and the time should be shortened for more infectious variants. Second, Bluetooth- or geolocation-based CTAs also face the problem of lack of accuracy. For example, individuals in 2 adjacent vehicles during traffic jams may be at a distance of ?2 meters to make the CTA trace contact, but the 2 users may actually be separated by car doors, which could prevent transmission and infection. In addition, we investigated infection detection rates in 33 countries, 16 (48.5\%) of which had significantly low infection detection rates, wherein CTAs could have lacked effectiveness in reducing virus propagation. Regarding policy, CTAs in most countries can only be used in their own countries and lack interoperability among other countries. In addition, 7 countries have already discontinued CTAs, but we believe that it was too early to discontinue them. Regarding user acceptance, 28.6\% (28/98) of CTAs had no official source of information that could reduce user acceptance. Conclusions: We surveyed all CTAs worldwide, identified their technological policy and acceptance issues, and provided solutions for each of the issues we identified. This study aimed to provide useful guidance and suggestions for updating the existing CTAs and the subsequent development of new CTAs. ", doi="10.2196/40233", url="https://publichealth.jmir.org/2022/10/e40233", url="http://www.ncbi.nlm.nih.gov/pubmed/36190741" } @Article{info:doi/10.2196/41395, author="Kim, Hyung Min and Ryu, Hyoung Un and Heo, Seok-Jae and Kim, Chan Yong and Park, Soo Yoon", title="The Potential Role of an Adjunctive Real-Time Locating System in Preventing Secondary Transmission of SARS-CoV-2 in a Hospital Environment: Retrospective Case-Control Study", journal="J Med Internet Res", year="2022", month="Oct", day="18", volume="24", number="10", pages="e41395", keywords="real-time locating system", keywords="COVID-19", keywords="contact tracing", keywords="secondary transmission", keywords="SARS-CoV-2", abstract="Background: There has been an increasing demand for new technologies regarding infection control in hospital settings to reduce the burden of contact tracing. Objective: This study aimed to compare the validity of a real-time locating system (RTLS) with that of the conventional contact tracing method for identifying high-risk contact cases associated with the secondary transmission of SARS-CoV-2. Methods: A retrospective case-control study involving in-hospital contact cases of confirmed COVID-19 patients, who were diagnosed from January 23 to March 25, 2022, was conducted at a university hospital in South Korea. Contact cases were identified using either the conventional method or the RTLS. The primary endpoint of this study was secondary transmission of SARS-CoV-2 among contact cases. Univariate and multivariable logistic regression analysis comparing test positive and versus negative contact cases were performed. Results: Overall, 509 and 653 cases were confirmed by the conventional method and the RTLS, respectively. Only 74 contact cases were identified by both methods, which could be attributed to the limitations of each method. Sensitivity was higher for the RTLS tracing method (653/1088, 60.0\%) than the conventional tracing method (509/1088, 46.8\%) considering all contact cases identified by both methods. The secondary transmission rate in the RTLS model was 8.1\%, while that in the conventional model was 5.3\%. The multivariable logistic regression model revealed that the RTLS was more capable of detecting secondary transmission than the conventional method (adjusted odds ratio 6.15, 95\% CI 1.92-28.69; P=.007). Conclusions: This study showed that the RTLS is beneficial when used as an adjunctive approach to the conventional method for contact tracing associated with secondary transmission. However, the RTLS cannot completely replace traditional contact tracing. ", doi="10.2196/41395", url="https://www.jmir.org/2022/10/e41395", url="http://www.ncbi.nlm.nih.gov/pubmed/36197844" } @Article{info:doi/10.2196/36003, author="Splinter, Bas and Saadah, H. Nicholas and Chavannes, H. Niels and Kiefte-de Jong, C. Jessica and Aardoom, J. Jiska", title="Optimizing the Acceptability, Adherence, and Inclusiveness of the COVID Radar Surveillance App: Qualitative Study Using Focus Groups, Thematic Content Analysis, and Usability Testing", journal="JMIR Form Res", year="2022", month="Sep", day="9", volume="6", number="9", pages="e36003", keywords="COVID-19", keywords="corona", keywords="eHealth", keywords="self-report", keywords="mobile app", keywords="track-and-trace strategies", keywords="population surveillance", keywords="citizen science", keywords="usability", keywords="mobile phone", abstract="Background: The COVID Radar app was developed as a population-based surveillance instrument to identify at-risk populations and regions in response to the COVID-19 pandemic. The app boasts of >8.5 million completed questionnaires, with >280,000 unique users. Although the COVID Radar app is a valid tool for population-level surveillance, high user engagement is critical to the success of the COVID Radar app in maintaining validity. Objective: This study aimed to identify optimization targets of the COVID Radar app to improve its acceptability, adherence, and inclusiveness. Methods: The main component of the COVID Radar app is a self-report questionnaire that assesses COVID-19 symptoms and social distancing behaviors. A total of 3 qualitative substudies were conducted. First, 3 semistructured focus group interviews with end users (N=14) of the app were conducted to gather information on user experiences. The output was transcribed and thematically coded using the framework method. Second, a similar qualitative thematic analysis was conducted on 1080 end-user emails. Third, usability testing was conducted in one-on-one sessions with 4 individuals with low literacy levels. Results: All 3 substudies identified optimization targets in terms of design and content. The results of substudy 1 showed that the participants generally evaluated the app positively. They reported the app to be user-friendly and were satisfied with its design and functionalities. Participants' main motivation to use the app was to contribute to science. Participants suggested adding motivational tools to stimulate user engagement. A larger national publicity campaign for the app was considered potentially helpful for increasing the user population. In-app updates informing users about the project and its outputs motivated users to continue using the app. Feedback on the self-report questionnaire, stemming from substudies 1 and 2, mostly concerned the content and phrasing of the questions. Furthermore, the section of the app allowing users to compare their symptoms and behaviors to those of their peers was found to be suboptimal because of difficulties in interpreting the figures presented in the app. Finally, the output of substudy 3 resulted in recommendations primarily related to simplification of the text to render it more accessible and comprehensible for individuals with low literacy levels. Conclusions: The convenience of app use, enabling personal adjustments of the app experience, and considering motivational factors for continued app use (ie, altruism and collectivism) were found to be crucial to procuring and maintaining a population of active users of the COVID Radar app. Further, there seems to be a need to increase the accessibility of public health tools for individuals with low literacy levels. These results can be used to improve the this and future public health apps and improve the representativeness of their user populations and user engagement, ultimately increasing the validity of the tools. ", doi="10.2196/36003", url="https://formative.jmir.org/2022/9/e36003", url="http://www.ncbi.nlm.nih.gov/pubmed/35781492" } @Article{info:doi/10.2196/34212, author="Oyibo, Kiemute and Morita, Pelegrini Plinio", title="The Effect of Persuasive Design on the Adoption of Exposure Notification Apps: Quantitative Study Based on COVID Alert", journal="JMIR Form Res", year="2022", month="Sep", day="6", volume="6", number="9", pages="e34212", keywords="contact tracing app", keywords="exposure notification app", keywords="COVID Alert", keywords="COVID-19", keywords="persuasive technology", keywords="behavior change", keywords="exposure", keywords="behavior", keywords="effect", keywords="design", keywords="adoption", keywords="use", keywords="case study", keywords="effectiveness", keywords="user interface", keywords="mobile phone", abstract="Background: The adoption of contact tracing apps worldwide has been low. Although considerable research has been conducted on technology acceptance, little has been done to show the benefit of incorporating persuasive principles. Objective: This research aimed to investigate the effect of persuasive features in the COVID Alert app, created by Health Canada, by focusing on the no-exposure status, exposure status, and diagnosis report interfaces. Methods: We conducted a study among 181 Canadian residents, including 65 adopters and 116 nonadopters. This study was based on screenshots of the 3 interfaces, of which each comprised a persuasive design and a control design. The persuasive versions of the first two interfaces supported self-monitoring (of exposure levels), and that of the third interface supported social learning (about how many other users have reported their diagnosis). The 6 screenshots were randomly assigned to 6 groups of participants to provide feedback on perceived persuasiveness and adoption willingness. Results: A multivariate repeated-measure ANOVA showed that there is an interaction among interface, app design, and adoption status regarding the perceived persuasiveness of the interfaces. This resulted in a 2-way ANOVA for each interface. For the no-exposure interface, there was an interaction between adoption status and app design. Among adopters, there was no significant difference P=.31 between the persuasive design (mean 5.36, SD 1.63) and the control design (mean 5.87, SD 1.20). However, among nonadopters, there was an effect of app design (P<.001), with participants being more motivated by the persuasive design (mean 5.37, SD 1.30) than by the control design (mean 4.57, SD 1.19). For the exposure interface, adoption status had a main effect (P<.001), with adopters (mean 5.91, SD 1.01) being more motivated by the designs than nonadopters (mean 4.96, SD 1.43). For the diagnosis report interface, there was an interaction between adoption status and app design. Among nonadopters, there was no significant difference P=.99 between the persuasive design (mean 4.61, SD 1.84) and the control design (mean 4.77, SD 1.21). However, among adopters, there was an effect of app design (P=.006), with participants being more likely to report their diagnosis using the persuasive design (mean 6.00, SD 0.97) than using the control design (mean 5.03, SD 1.22). Finally, with regard to willingness to download the app, pairwise comparisons showed that nonadopters were more likely to adopt the app after viewing the persuasive version of the no-exposure interface (13/21, 62\% said yes) and the diagnosis report interface (12/17, 71\% said yes) than after viewing the control versions (3/17, 18\% and 7/16, 44\%, respectively, said yes). Conclusions: Exposure notification apps are more likely to be effective if equipped with persuasive features. Incorporating self-monitoring into the no-exposure status interface and social learning into the diagnosis report interface can increase adoption by >30\%. ", doi="10.2196/34212", url="https://formative.jmir.org/2022/9/e34212", url="http://www.ncbi.nlm.nih.gov/pubmed/35580138" } @Article{info:doi/10.2196/31099, author="Ritsema, Feiko and Bosdriesz, R. Jizzo and Leenstra, Tjalling and Petrignani, F. Mariska W. and Coyer, Liza and Schreijer, M. Anja J. and van Duijnhoven, P. Yvonne T. H. and van de Wijgert, M. Janneke H. H. and Schim van der Loeff, F. Maarten and Matser, Amy", title="Factors Associated With Using the COVID-19 Mobile Contact-Tracing App Among Individuals Diagnosed With SARS-CoV-2 in Amsterdam, the Netherlands: Observational Study", journal="JMIR Mhealth Uhealth", year="2022", month="Aug", day="24", volume="10", number="8", pages="e31099", keywords="COVID-19", keywords="contact tracing", keywords="mobile contact tracing app", keywords="pandemic", keywords="mHealth", keywords="digital health", keywords="contact tracing app", keywords="mobile applications", keywords="health applications", keywords="public health", keywords="surveillance", abstract="Background: Worldwide, efforts are being made to stop the COVID-19 pandemic caused by SARS-CoV-2. Contact tracing and quarantining are key in limiting SARS-CoV-2 transmission. Mathematical models have shown that the time between infection, isolation of cases, and quarantining of contacts are the most important components that determine whether the pandemic can be controlled. Mobile contact-tracing apps could accelerate the tracing and quarantining of contacts, including anonymous contacts. However, real-world observational data on the uptake and determinants of contact-tracing apps are limited. Objective: The aim of this paper is to assess the use of a national Dutch contact-tracing app among notified cases diagnosed with SARS-CoV-2 infection and investigate which characteristics are associated with the use of the app. Methods: Due to privacy regulations, data from the app could not be used. Instead, we used anonymized SARS-CoV-2 routine contact-tracing data collected between October 28, 2020, and February 26, 2021, in the region of Amsterdam, the Netherlands. Complete case logistic regression analysis was performed to identify which factors (age, gender, country of birth, municipality, number of close contacts, and employment in either health care or education) were associated with using the app. Age and number of close contacts were modelled as B-splines due to their nonlinear relationship. Results: Of 29,766 SARS-CoV-2 positive cases, 4824 (16.2\%) reported app use. Median age of cases was 41 (IQR 29-55) years, and 46.7\% (n=13,898) were male. In multivariable analysis, males (adjusted odds ratio [AOR] 1.11, 95\% CI 1.04-1.18) and residents of municipalities surrounding Amsterdam were more likely to use the app (Aalsmeer AOR 1.34, 95\% CI 1.13-1.58; Ouder-Amstel AOR 1.96, 95\% CI 1.54-2.50), while people born outside the Netherlands, particularly those born in non-Western countries (AOR 0.33, 95\% CI 0.30-0.36), were less likely to use the app. Odds of app use increased with age until the age of 58 years and decreased sharply thereafter (P<.001). Odds of app use increased with number of contacts, peaked at 8 contacts, and then decreased (P<.001). Individuals working in day care, home care, and elderly nursing homes were less likely to use the app. Conclusions: Contact-tracing app use among people with confirmed SARS-CoV-2 infection was low in the region of Amsterdam. This diminishes the potential impact of the app by hampering the ability to warn contacts. Use was particularly low among older people, people born outside the Netherlands, and people with many contacts. Use of the app was also relatively low compared to those from some other European countries, some of which had additional features beyond contact tracing, making them potentially more appealing. For the Dutch contact-tracing app to have an impact, uptake needs to be higher; therefore, investing more into promotional efforts and additional features could be considered. ", doi="10.2196/31099", url="https://mhealth.jmir.org/2022/8/e31099", url="http://www.ncbi.nlm.nih.gov/pubmed/35867842" } @Article{info:doi/10.2196/35195, author="Bardus, Marco and Al Daccache, Melodie and Maalouf, Noel and Al Sarih, Rayan and Elhajj, H. Imad", title="Data Management and Privacy Policy of COVID-19 Contact-Tracing Apps: Systematic Review and Content Analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Jul", day="12", volume="10", number="7", pages="e35195", keywords="COVID-19", keywords="mobile applications", keywords="contact tracing", abstract="Background: COVID-19 digital contact-tracing apps were created to assist public health authorities in curbing the pandemic. These apps require users' permission to access specific functions on their mobile phones, such as geolocation, Bluetooth or Wi-Fi connections, or personal data, to work correctly. As these functions have privacy repercussions, it is essential to establish how contact-tracing apps respect users' privacy. Objective: This study aimed to systematically map existing contact-tracing apps and evaluate the permissions required and their privacy policies. Specifically, we evaluated the type of permissions, the privacy policies' readability, and the information included in them. Methods: We used custom Google searches and existing lists of contact-tracing apps to identify potentially eligible apps between May 2020 and November 2021. We included contact-tracing or exposure notification apps with a Google Play webpage from which we extracted app characteristics (eg, sponsor, number of installs, and ratings). We used Exodus Privacy to systematically extract the number of permissions and classify them as dangerous or normal. We computed a Permission Accumulated Risk Score representing the threat level to the user's privacy. We assessed the privacy policies' readability and evaluated their content using a 13-item checklist, which generated a Privacy Transparency Index. We explored the relationships between app characteristics, Permission Accumulated Risk Score, and Privacy Transparency Index using correlations, chi-square tests, or ANOVAs. Results: We identified 180 contact-tracing apps across 152 countries, states, or territories. We included 85.6\% (154/180) of apps with a working Google Play page, most of which (132/154, 85.7\%) had a privacy policy document. Most apps were developed by governments (116/154, 75.3\%) and totaled 264.5 million installs. The average rating on Google Play was 3.5 (SD 0.7). Across the 154 apps, we identified 94 unique permissions, 18\% (17/94) of which were dangerous, and 30 trackers. The average Permission Accumulated Risk Score was 22.7 (SD 17.7; range 4-74, median 16) and the average Privacy Transparency Index was 55.8 (SD 21.7; range 5-95, median 55). Overall, the privacy documents were difficult to read (median grade level 12, range 7-23); 67\% (88/132) of these mentioned that the apps collected personal identifiers. The Permission Accumulated Risk Score was negatively associated with the average App Store ratings (r=?0.20; P=.03; 120/154, 77.9\%) and Privacy Transparency Index (r=?0.25; P<.001; 132/154, 85.7\%), suggesting that the higher the risk to one's data, the lower the apps' ratings and transparency index. Conclusions: Many contact-tracing apps were developed covering most of the planet but with a relatively low number of installs. Privacy-preserving apps scored high in transparency and App Store ratings, suggesting that some users appreciate these apps. Nevertheless, privacy policy documents were difficult to read for an average audience. Therefore, we recommend following privacy-preserving and transparency principles to improve contact-tracing uptake while making privacy documents more readable for a wider public. ", doi="10.2196/35195", url="https://mhealth.jmir.org/2022/7/e35195", url="http://www.ncbi.nlm.nih.gov/pubmed/35709334" } @Article{info:doi/10.2196/30976, author="Catuara-Solarz, Silvina and Skorulski, Bartlomiej and Estella-Aguerri, I{\~n}aki and Avella-Garcia, Bibiana Claudia and Shepherd, Sarah and Stott, Emily and Hemmings, R. Nicola and Ruiz de Villa, Aleix and Schulze, Laura and Dix, Sophie", title="The Efficacy of ``Foundations,'' a Digital Mental Health App to Improve Mental Well-being During COVID-19: Proof-of-Principle Randomized Controlled Trial", journal="JMIR Mhealth Uhealth", year="2022", month="Jul", day="1", volume="10", number="7", pages="e30976", keywords="mental well-being", keywords="digital health", keywords="cognitive behavioral therapy", keywords="positive psychology", keywords="insomnia", keywords="COVID-19", keywords="mental health", keywords="mobile app", keywords="anxiety", keywords="health app", abstract="Background: Against a long-term trend of increasing demand, the COVID-19 pandemic has led to a global rise in common mental disorders. Now more than ever, there is an urgent need for scalable, evidence-based interventions to support mental well-being. Objective: The aim of this proof-of-principle study was to evaluate the efficacy of a mobile-based app in adults with self-reported symptoms of anxiety and stress in a randomized control trial that took place during the first wave of the COVID-19 pandemic in the United Kingdom. Methods: Adults with mild to severe anxiety and moderate to high levels of perceived stress were randomized to either the intervention or control arm. Participants in the intervention arm were given access to the Foundations app for the duration of the 4-week study. All participants were required to self-report a range of validated measures of mental well-being (10-item Connor-Davidson Resilience scale [CD-RISC-10], 7-item Generalized Anxiety Disorder scale [GAD-7], Office of National Statistics Four Subjective Well-being Questions [ONS-4], World Health Organization-5 Well-Being Index [WHO-5]) and sleep (Minimal Insomnia Scale [MISS]) at baseline and at weeks 2 and 4. The self-reported measures of perceived stress (10-item Perceived Stress Score [PSS-10]) were obtained weekly. Results: A total of 136 participants completed the study and were included in the final analysis. The intervention group (n=62) showed significant improvements compared to the control group (n=74) on measures of anxiety, with a mean GAD-7 score change from baseline of --1.35 (SD 4.43) and --0.23 (SD 3.24), respectively (t134=1.71, P=.04); resilience, with a mean change in CD-RISC score of 1.79 (SD 4.08) and --0.31 (SD 3.16), respectively (t134=--3.37, P<.001); sleep, with a mean MISS score change of --1.16 (SD 2.67) and --0.26 (SD 2.29), respectively (t134=2.13, P=.01); and mental well-being, with a mean WHO-5 score change of 1.53 (SD 5.30) and --0.23 (SD 4.20), respectively (t134=--2.16, P=.02), within 2 weeks of using Foundations, with further improvements emerging at week 4. Perceived stress was also reduced within the intervention group, although the difference did not reach statistical significance relative to the control group, with a PSS score change from baseline to week 2 of --2.94 (SD 6.84) and --2.05 (SD 5.34), respectively (t134= 0.84, P=.20). Conclusions: This study provides a proof of principle that the digital mental health app Foundations can improve measures of mental well-being, anxiety, resilience, and sleep within 2 weeks of use, with greater effects after 4 weeks. Foundations therefore offers potential as a scalable, cost-effective, and accessible solution to enhance mental well-being, even during times of crisis such as the COVID-19 pandemic. Trial Registration: OSF Registries osf.io/f6djb; https://osf.io/vm3xq ", doi="10.2196/30976", url="https://mhealth.jmir.org/2022/7/e30976", url="http://www.ncbi.nlm.nih.gov/pubmed/34978535" } @Article{info:doi/10.2196/33951, author="Sousa, Sonia and Kalju, Tiina", title="Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study", journal="JMIR Hum Factors", year="2022", month="Jun", day="13", volume="9", number="2", pages="e33951", keywords="human-computer interaction", keywords="COVID-19", keywords="human factors", keywords="trustworthy AI", keywords="contact-tracing", keywords="app", keywords="safety", keywords="trust", keywords="artificial intelligence", keywords="Estonia", keywords="case study", keywords="monitoring", keywords="surveillance", keywords="perspective", keywords="awareness", keywords="design", keywords="covid", keywords="mobile app", keywords="mHealth", keywords="mobile health", abstract="Background: The COVID-19 pandemic has caused changes in technology use worldwide, both socially and economically. This pandemic crisis has brought additional measures such as contact-tracing apps (CTAs) to help fight against spread of the virus. Unfortunately, the low adoption rate of these apps affected their success. There could be many reasons for the low adoption, including concerns of security and privacy, along with reported issues of trust in CTAs. Some concerns are related with how CTAs could be used as surveillance tools or their potential threats to privacy as they involve health data. For example, in Estonia, the CTA named HOIA had approximately 250,000 downloads in the middle of January 2021. However, in 2021, only 4.7\% of the population used HOIA as a COVID-19 CTA. The reasons for the low adoption include lack of competency, and privacy and security concerns. This lower adoption and the lack of trustworthiness persist despite efforts of the European Union in building ethics and trustworthy artificial intelligence (AI)-based apps. Objective: The aim of this study was to understand how to measure trust in health technologies. Specifically, we assessed the usefulness of the Human-Computer Trust Scale (HCTS) to measure Estonians' trust in the HOIA app and the causes for this lack of trust. Methods: The main research question was: Can the HCTS be used to assess citizens' perception of trust in health technologies? We established four hypotheses that were tested with a survey. We used a convenience sample for data collection, including sharing the questionnaire on social network sites and using the snowball method to reach all potential HOIA users in the Estonian population. Results: Among the 78 respondents, 61 had downloaded the HOIA app with data on usage patterns. However, 20 of those who downloaded the app admitted that it was never opened despite most claiming to regularly use mobile apps. The main reasons included not understanding how it works, and privacy and security concerns. Significant correlations were found between participants' trust in CTAs in general and their perceived trust in the HOIA app regarding three attributes: competency (P<.001), risk perception (P<.001), and reciprocity (P=.01). Conclusions: This study shows that trust in the HOIA app among Estonian residents did affect their predisposition to use the app. Participants did not generally believe that HOIA could help to control the spread of the virus. The result of this work is limited to HOIA and health apps that use similar contact-tracing methods. However, the findings can contribute to gaining a broader understanding and awareness of the need for designing trustworthy technologies. Moreover, this work can help to provide design recommendations that ensure trustworthiness in CTAs, and the ability of AI to use highly sensitive data and serve society. ", doi="10.2196/33951", url="https://humanfactors.jmir.org/2022/2/e33951", url="http://www.ncbi.nlm.nih.gov/pubmed/35699973" } @Article{info:doi/10.2196/36065, author="Schmeelk, Suzanna and Davis, Alison and Li, Qiaozheng and Shippey, Caroline and Utah, Michelle and Myers, Annie and Reading Turchioe, Meghan and Masterson Creber, Ruth", title="Monitoring Symptoms of COVID-19: Review of Mobile Apps", journal="JMIR Mhealth Uhealth", year="2022", month="Jun", day="1", volume="10", number="6", pages="e36065", keywords="COVID-19", keywords="mobile apps", keywords="mobile health", keywords="mHealth", keywords="symptom assessment", keywords="symptom tracking", keywords="public health", keywords="mobile health application", keywords="surveillance", keywords="digital surveillance", keywords="monitoring system", keywords="digital health", abstract="Background: Mobile health (mHealth) apps have facilitated symptom monitoring of COVID-19 symptoms globally and have been used to share data with health care professionals and support disease prediction, prevention, management, diagnostics, and improvements in treatments and patient education. Objective: The aim of this review is to evaluate the quality and functionality of COVID-19 mHealth apps that support tracking acute and long-term symptoms of COVID-19. Methods: We systematically reviewed commercially available mHealth apps for COVID-19 symptom monitoring by searching Google Play and Apple iTunes using search terms such as ``COVID-19,'' ``Coronavirus,'' and ``COVID-19 and symptoms.'' All apps underwent three rounds of screening. The final apps were independently assessed using the Mobile Application Rating Scale (MARS), an informatics functionality scoring system, and the Center for Disease Control and World Health Organization symptom guidelines. The MARS is a 19-item standardized tool to evaluate the quality of mHealth apps on engagement, functionality, aesthetics, and information quality. Functionality was quantified across the following criteria: inform, instruct, record (collect, share, evaluate, and intervene), display, guide, remind or alert, and communicate. Interrater reliability between the reviewers was calculated. Results: A total of 1017 mobile apps were reviewed, and 20 (2\%) met the inclusion criteria. The majority of the 20 included apps (n=18, 90\%) were designed to track acute COVID-19 symptoms, and only 2 (10\%) addressed long-term symptoms. Overall, the apps scored high on quality, with an overall MARS rating of 3.89 out of 5, and the highest domain score for functionality (4.2). The most common functionality among all apps was the instruct function (n=19, 95\%). The most common symptoms included in the apps for tracking were fever and dry cough (n=18, 90\%), aches and pains (n=17, 85\%), difficulty breathing (n=17, 85\%), tiredness, sore throat, headache, loss of taste or smell (n=16, 80\%), and diarrhea (n=15, 75\%). Only 2 (10\%) apps specifically tracked long-term symptoms of COVID-19. The top 4 rated apps overall were state-specific apps developed and deployed for public use. Conclusions: Overall, mHealth apps designed to monitor symptoms of COVID-19 were of high quality, but the majority of apps focused almost exclusively on acute symptoms. Future apps should also incorporate monitoring long-term symptoms of COVID-19 and evidence-based educational materials; they should also include a feature that would allow patients to communicate their symptoms to specific caregivers or their own health care team. App developers should also follow updated technical and clinical guidelines from the Center for Disease Control and the World Health Organization. ", doi="10.2196/36065", url="https://mhealth.jmir.org/2022/6/e36065", url="http://www.ncbi.nlm.nih.gov/pubmed/35609313" } @Article{info:doi/10.2196/36238, author="Ahmad, Kashif and Alam, Firoj and Qadir, Junaid and Qolomany, Basheer and Khan, Imran and Khan, Talhat and Suleman, Muhammad and Said, Naina and Hassan, Zohaib Syed and Gul, Asma and Househ, Mowafa and Al-Fuqaha, Ala", title="Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing", journal="JMIR Form Res", year="2022", month="May", day="11", volume="6", number="5", pages="e36238", keywords="COVID-19", keywords="sentiment analysis", keywords="contact tracing applications", keywords="NLP", keywords="text classification", keywords="BERT", keywords="fastText", keywords="transformers", keywords="RoBerta", abstract="Background: Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. To this aim, several mobile apps have been developed. However, there are ever-growing concerns over the working mechanism and performance of these applications. The literature already provides some interesting exploratory studies on the community's response to the applications by analyzing information from different sources, such as news and users' reviews of the applications. However, to the best of our knowledge, there is no existing solution that automatically analyzes users' reviews and extracts the evoked sentiments. We believe such solutions combined with a user-friendly interface can be used as a rapid surveillance tool to monitor how effective an application is and to make immediate changes without going through an intense participatory design method. Objective: In this paper, we aim to analyze the efficacy of AI and NLP techniques for automatically extracting and classifying the polarity of users' sentiments by proposing a sentiment analysis framework to automatically analyze users' reviews on COVID-19 contact tracing mobile apps. We also aim to provide a large-scale annotated benchmark data set to facilitate future research in the domain. As a proof of concept, we also developed a web application based on the proposed solutions, which is expected to help the community quickly analyze the potential of an application in the domain. Methods: We propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding with the development and training of artificial intelligence (AI) models for automatic sentiment analysis of users' reviews. In detail, we collected and annotated a large-scale data set of user reviews on COVID-19 contact tracing applications. We used both classical and deep learning methods for classification experiments. Results: We used 8 different methods on 3 different tasks, achieving up to an average F1 score of 94.8\%, indicating the feasibility of the proposed solution. The crowd-sourcing activity resulted in a large-scale benchmark data set composed of 34,534 manually annotated reviews. Conclusions: The existing literature mostly relies on the manual or exploratory analysis of users' reviews on applications, which is tedious and time-consuming. In existing studies, generally, data from fewer applications are analyzed. In this work, we showed that AI and natural language processing techniques provide good results for analyzing and classifying users' sentiments' polarity and that automatic sentiment analysis can help to analyze users' responses more accurately and quickly. We also provided a large-scale benchmark data set. We believe the presented analysis, data set, and proposed solutions combined with a user-friendly interface can be used as a rapid surveillance tool to analyze and monitor mobile apps deployed in emergency situations leading to rapid changes in the applications without going through an intense participatory design method. ", doi="10.2196/36238", url="https://formative.jmir.org/2022/5/e36238", url="http://www.ncbi.nlm.nih.gov/pubmed/35389357" } @Article{info:doi/10.2196/22544, author="Akpan, Ubong Godwin and Bello, Mohammed Isah and Touray, Kebba and Ngofa, Reuben and Oyaole, Rasheed Daniel and Maleghemi, Sylvester and Babona, Marie and Chikwanda, Chanda and Poy, Alain and Mboussou, Franck and Ogundiran, Opeayo and Impouma, Benido and Mihigo, Richard and Yao, Michel Nda Konan and Ticha, Muluh Johnson and Tuma, Jude and A Mohamed, Farouk Hani and Kanmodi, Kehinde and Ejiofor, Ephraim Nonso and Kipterer, Kapoi John and Manengu, Casimir and Kasolo, Francis and Seaman, Vincent and Mkanda, Pascal", title="Leveraging Polio Geographic Information System Platforms in the African Region for Mitigating COVID-19 Contact Tracing and Surveillance Challenges: Viewpoint", journal="JMIR Mhealth Uhealth", year="2022", month="Mar", day="17", volume="10", number="3", pages="e22544", keywords="contact tracing", keywords="GIS", keywords="COVID-19", keywords="surveillance", abstract="Background: The ongoing COVID-19 pandemic in Africa is an urgent public health crisis. Estimated models projected over 150,000 deaths and 4,600,000 hospitalizations in the first year of the disease in the absence of adequate interventions. Therefore, electronic contact tracing and surveillance have critical roles in decreasing COVID-19 transmission; yet, if not conducted properly, these methods can rapidly become a bottleneck for synchronized data collection, case detection, and case management. While the continent is currently reporting relatively low COVID-19 cases, digitized contact tracing mechanisms and surveillance reporting are necessary for standardizing real-time reporting of new chains of infection in order to quickly reverse growing trends and halt the pandemic. Objective: This paper aims to describe a COVID-19 contact tracing smartphone app that includes health facility surveillance with a real-time visualization platform. The app was developed by the AFRO (African Regional Office) GIS (geographic information system) Center, in collaboration with the World Health Organization (WHO) emergency preparedness and response team. The app was developed through the expertise and experience gained from numerous digital apps that had been developed for polio surveillance and immunization via the WHO's polio program in the African region. Methods: We repurposed the GIS infrastructures of the polio program and the database structure that relies on mobile data collection that is built on the Open Data Kit. We harnessed the technology for visualization of real-time COVID-19 data using dynamic dashboards built on Power BI, ArcGIS Online, and Tableau. The contact tracing app was developed with the pragmatic considerations of COVID-19 peculiarities. The app underwent testing by field surveillance colleagues to meet the requirements of linking contacts to cases and monitoring chains of transmission. The health facility surveillance app was developed from the knowledge and assessment of models of surveillance at the health facility level for other diseases of public health importance. The Integrated Supportive Supervision app was added as an appendage to the pre-existing paper-based surveillance form. These two mobile apps collected information on cases and contact tracing, alongside alert information on COVID-19 reports at the health facility level; the information was linked to visualization platforms in order to enable actionable insights. Results: The contact tracing app and platform were piloted between April and June 2020; they were then put to use in Zimbabwe, Benin, Cameroon, Uganda, Nigeria, and South Sudan, and their use has generated some palpable successes with respect to COVID-19 surveillance. However, the COVID-19 health facility--based surveillance app has been used more extensively, as it has been used in 27 countries in the region. Conclusions: In light of the above information, this paper was written to give an overview of the app and visualization platform development, app and platform deployment, ease of replicability, and preliminary outcome evaluation of their use in the field. From a regional perspective, integration of contact tracing and surveillance data into one platform provides the AFRO with a more accurate method of monitoring countries' efforts in their response to COVID-19, while guiding public health decisions and the assessment of risk of COVID-19. ", doi="10.2196/22544", url="https://mhealth.jmir.org/2022/3/e22544", url="http://www.ncbi.nlm.nih.gov/pubmed/34854813" } @Article{info:doi/10.2196/30691, author="Tsvyatkova, Damyanka and Buckley, Jim and Beecham, Sarah and Chochlov, Muslim and O'Keeffe, R. Ian and Razzaq, Abdul and Rekanar, Kaavya and Richardson, Ita and Welsh, Thomas and Storni, Cristiano and ", title="Digital Contact Tracing Apps for COVID-19: Development of a Citizen-Centered Evaluation Framework", journal="JMIR Mhealth Uhealth", year="2022", month="Mar", day="11", volume="10", number="3", pages="e30691", keywords="COVID-19", keywords="mHealth", keywords="digital contact tracing apps", keywords="framework", keywords="evaluation", keywords="mobile health", keywords="health apps", keywords="digital health", keywords="contact tracing", abstract="Background: The silent transmission of COVID-19 has led to an exponential growth of fatal infections. With over 4 million deaths worldwide, the need to control and stem transmission has never been more critical. New COVID-19 vaccines offer hope. However, administration timelines, long-term protection, and effectiveness against potential variants are still unknown. In this context, contact tracing and digital contact tracing apps (CTAs) continue to offer a mechanism to help contain transmission, keep people safe, and help kickstart economies. However, CTAs must address a wide range of often conflicting concerns, which make their development/evolution complex. For example, the app must preserve citizens' privacy while gleaning their close contacts and as much epidemiological information as possible. Objective: In this study, we derived a compare-and-contrast evaluative framework for CTAs that integrates and expands upon existing works in this domain, with a particular focus on citizen adoption; we call this framework the Citizen-Focused Compare-and-Contrast Evaluation Framework (C3EF) for CTAs. Methods: The framework was derived using an iterative approach. First, we reviewed the literature on CTAs and mobile health app evaluations, from which we derived a preliminary set of attributes and organizing pillars. These attributes and the probing questions that we formulated were iteratively validated, augmented, and refined by applying the provisional framework against a selection of CTAs. Each framework pillar was then subjected to internal cross-team scrutiny, where domain experts cross-checked sufficiency, relevancy, specificity, and nonredundancy of the attributes, and their organization in pillars. The consolidated framework was further validated on the selected CTAs to create a finalized version of C3EF for CTAs, which we offer in this paper. Results: The final framework presents seven pillars exploring issues related to CTA design, adoption, and use: (General) Characteristics, Usability, Data Protection, Effectiveness, Transparency, Technical Performance, and Citizen Autonomy. The pillars encompass attributes, subattributes, and a set of illustrative questions (with associated example answers) to support app design, evaluation, and evolution. An online version of the framework has been made available to developers, health authorities, and others interested in assessing CTAs. Conclusions: Our CTA framework provides a holistic compare-and-contrast tool that supports the work of decision-makers in the development and evolution of CTAs for citizens. This framework supports reflection on design decisions to better understand and optimize the design compromises in play when evolving current CTAs for increased public adoption. We intend this framework to serve as a foundation for other researchers to build on and extend as the technology matures and new CTAs become available. ", doi="10.2196/30691", url="https://mhealth.jmir.org/2022/3/e30691", url="http://www.ncbi.nlm.nih.gov/pubmed/35084338" } @Article{info:doi/10.2196/30872, author="Idris, Yassin Muhammed and Korin, Maya and Araya, Faven and Chowdhury, Sayeeda and Medina, Patty and Cruz, Larissa and Hawkins, Trey-Rashad and Brown, Humberto and Claudio, Luz", title="Including the Public in Public eHealth: The Need for Community Participation in the Development of State-Sponsored COVID-19--Related Mobile Apps", journal="JMIR Mhealth Uhealth", year="2022", month="Mar", day="9", volume="10", number="3", pages="e30872", keywords="mobile apps", keywords="COVID-19", keywords="CBPR", keywords="digital health", keywords="eHealth", keywords="community health", keywords="health disparities", doi="10.2196/30872", url="https://mhealth.jmir.org/2022/3/e30872", url="http://www.ncbi.nlm.nih.gov/pubmed/35113793" } @Article{info:doi/10.2196/31857, author="Buhr, Lorina and Schicktanz, Silke and Nordmeyer, Eike", title="Attitudes Toward Mobile Apps for Pandemic Research Among Smartphone Users in Germany: National Survey", journal="JMIR Mhealth Uhealth", year="2022", month="Jan", day="24", volume="10", number="1", pages="e31857", keywords="user", keywords="pandemic", keywords="smartphone apps", keywords="mobile apps", keywords="telephone-based survey", keywords="Germany", keywords="data sharing", keywords="data donation", keywords="ethics", keywords="trust", keywords="COVID-19", keywords="mHealth", keywords="mobile applications", keywords="digital health", keywords="health applications", abstract="Background: During the COVID-19 pandemic, but also in the context of previous epidemic diseases, mobile apps for smartphones were developed with different goals and functions, such as digital contact tracing, test management, symptom monitoring, quarantine compliance, and epidemiological and public health research. Objective: The aim of this study was to explore the potential for the acceptance of research-orientated apps (ROAs) in the German population. To this end, we identified distinctive attitudes toward pandemic apps and data sharing for research purposes among smartphone users in general and with a focus on differences in attitudes between app users and nonusers in particular. Methods: We conducted a cross-sectional, national, telephone-based survey of 1003 adults in Germany, of which 924 were useable for statistical analysis. The 17-item survey assessed current usage of pandemic apps, motivations for using or not using pandemic apps, trust in app distributors and attitudes toward data handling (data storage and transmission), willingness to share coded data with researchers using a pandemic app, social attitudes toward app use, and demographic and personal characteristics. Results: A vast majority stated that they used a smartphone (778/924, 84.2\%), but less than half of the smartphone users stated that they used a pandemic app (326/778, 41.9\%). The study focused on the subsample of smartphone users. Interestingly, when asked about preferred organizations for data storage and app distribution, trust in governmental (federal or state government, regional health office), public-appointed (statutory health insurance), or government-funded organizations (research institutes) was much higher than in private organizations (private research institutions, clinics, health insurances, information technology [IT] companies). Having a university degree significantly (P<.001) increased the likelihood of using a pandemic app, while having a migration background significantly (P<.001) decreased it. The overwhelming majority (653/778, 83.9\%) of smartphone users were willing to provide their app data for state-funded research. Regarding attitudes toward app usage, striking differences between users and nonusers were found. Almost all app users (317/327, 96.9\%) stated they would be willing to share data, whereas only 74.3\% (336/452) of nonusers supported data sharing via an app. Two-thirds (216/326, 66.3\%) of app users fully or rather agreed with the statement that using a pandemic app is a social duty, whereas almost the same proportion of nonusers entirely or rather disagreed with that statement (273/451, 60.5\%). Conclusions: These findings indicate a high potential for the adoption of ROAs among smartphone users in Germany as long as organizational providers engaged in development, operation, and distribution are state-funded or governmental institutions and transparency about data-using research institutions is provided. ", doi="10.2196/31857", url="https://mhealth.jmir.org/2022/1/e31857", url="http://www.ncbi.nlm.nih.gov/pubmed/35072646" } @Article{info:doi/10.2196/22113, author="Walrave, Michel and Waeterloos, Cato and Ponnet, Koen", title="Reasons for Nonuse, Discontinuation of Use, and Acceptance of Additional Functionalities of a COVID-19 Contact Tracing App: Cross-sectional Survey Study", journal="JMIR Public Health Surveill", year="2022", month="Jan", day="14", volume="8", number="1", pages="e22113", keywords="COVID-19", keywords="SARS-CoV-2", keywords="coronavirus", keywords="contact tracing", keywords="proximity tracing", keywords="mHealth", keywords="mobile app", keywords="user acceptability", keywords="surveillance", keywords="privacy", abstract="Background: In several countries, contact tracing apps (CTAs) have been introduced to warn users if they have had high-risk contacts that could expose them to SARS-CoV-2 and could, therefore, develop COVID-19 or further transmit the virus. For CTAs to be effective, a sufficient critical mass of users is needed. Until now, adoption of these apps in several countries has been limited, resulting in questions on which factors prevent app uptake or stimulate discontinuation of app use. Objective: The aim of this study was to investigate individuals' reasons for not using, or stopping use of, a CTA, in particular, the Coronalert app. Users' and nonusers' attitudes toward the app's potential impact was assessed in Belgium. To further stimulate interest and potential use of a CTA, the study also investigated the population's interest in new functionalities. Methods: An online survey was administered in Belgium to a sample of 1850 respondents aged 18 to 64 years. Data were collected between October 30 and November 2, 2020. Sociodemographic differences were assessed between users and nonusers. We analyzed both groups' attitudes toward the potential impact of CTAs and their acceptance of new app functionalities. Results: Our data showed that 64.9\% (1201/1850) of our respondents were nonusers of the CTA under study; this included individuals who did not install the app, those who downloaded but did not activate the app, and those who uninstalled the app. While we did not find any sociodemographic differences between users and nonusers, attitudes toward the app and its functionalities seemed to differ. The main reasons for not downloading and using the app were a perceived lack of advantages (308/991, 31.1\%), worries about privacy (290/991, 29.3\%), and, to a lesser extent, not having a smartphone (183/991, 18.5\%). Users of the CTA agreed more with the potential of such apps to mitigate the consequences of the pandemic. Overall, nonusers found the possibility of extending the CTA with future functionalities to be less acceptable than users. However, among users, acceptability also tended to differ. Among users, functionalities relating to access and control, such as digital certificates or ``green cards'' for events, were less accepted (358/649, 55.2\%) than functionalities focusing on informing citizens about the spread of the virus (453/649, 69.8\%) or making an appointment to get tested (525/649, 80.9\%). Conclusions: Our results show that app users were more convinced of the CTA's utility and more inclined to accept new app features than nonusers. Moreover, nonusers had more CTA-related privacy concerns. Therefore, to further stimulate app adoption and use, its potential advantages and privacy-preserving mechanisms need to be stressed. Building further knowledge on the forms of resistance among nonusers is important for responding to these barriers through the app's further development and communication campaigns. ", doi="10.2196/22113", url="https://publichealth.jmir.org/2022/1/e22113", url="http://www.ncbi.nlm.nih.gov/pubmed/34794117" } @Article{info:doi/10.2196/32587, author="Stewart, Callum and Ranjan, Yatharth and Conde, Pauline and Rashid, Zulqarnain and Sankesara, Heet and Bai, Xi and Dobson, B. Richard J. and Folarin, A. Amos", title="Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)", journal="JMIR Res Protoc", year="2021", month="Dec", day="8", volume="10", number="12", pages="e32587", keywords="mobile health", keywords="COVID-19", keywords="digital health", keywords="smartphone", keywords="wearable devices", keywords="mental health", keywords="wearable", keywords="data", keywords="crowdsourced", keywords="monitoring", keywords="surveillance", keywords="observational", keywords="feasibility", keywords="infectious disease", keywords="recovery", keywords="mobile phone", abstract="Background: The ubiquity of mobile phones and increasing use of wearable fitness trackers offer a wide-ranging window into people's health and well-being. There are clear advantages in using remote monitoring technologies to gain an insight into health, particularly under the shadow of the COVID-19 pandemic. Objective: Covid Collab is a crowdsourced study that was set up to investigate the feasibility of identifying, monitoring, and understanding the stratification of SARS-CoV-2 infection and recovery through remote monitoring technologies. Additionally, we will assess the impacts of the COVID-19 pandemic and associated social measures on people's behavior, physical health, and mental well-being. Methods: Participants will remotely enroll in the study through the Mass Science app to donate historic and prospective mobile phone data, fitness tracking wearable data, and regular COVID-19--related and mental health--related survey data. The data collection period will cover a continuous period (ie, both before and after any reported infections), so that comparisons to a participant's own baseline can be made. We plan to carry out analyses in several areas, which will cover symptomatology; risk factors; the machine learning--based classification of illness; and trajectories of recovery, mental well-being, and activity. Results: As of June 2021, there are over 17,000 participants---largely from the United Kingdom---and enrollment is ongoing. Conclusions: This paper introduces a crowdsourced study that will include remotely enrolled participants to record mobile health data throughout the COVID-19 pandemic. The data collected may help researchers investigate a variety of areas, including COVID-19 progression; mental well-being during the pandemic; and the adherence of remote, digitally enrolled participants. International Registered Report Identifier (IRRID): DERR1-10.2196/32587 ", doi="10.2196/32587", url="https://www.researchprotocols.org/2021/12/e32587", url="http://www.ncbi.nlm.nih.gov/pubmed/34784292" } @Article{info:doi/10.2196/30004, author="Daniore, Paola and Nittas, Vasileios and Moser, Andr{\'e} and H{\"o}glinger, Marc and von Wyl, Viktor", title="Using Venn Diagrams to Evaluate Digital Contact Tracing: Panel Survey Analysis", journal="JMIR Public Health Surveill", year="2021", month="Dec", day="6", volume="7", number="12", pages="e30004", keywords="digital contact tracing", keywords="exposure notification", keywords="COVID-19", keywords="SARS-CoV-2", keywords="contact tracing", keywords="digital health", keywords="tracing apps", keywords="mHealth", keywords="mobile apps", keywords="key performance indicators", keywords="Venn diagram approach", abstract="Background: Mitigation of the spread of infection relies on targeted approaches aimed at preventing nonhousehold interactions. Contact tracing in the form of digital proximity tracing apps has been widely adopted in multiple countries due to its perceived added benefits of tracing speed and breadth in comparison to traditional manual contact tracing. Assessments of user responses to exposure notifications through a guided approach can provide insights into the effect of digital proximity tracing app use on managing the spread of SARS-CoV-2. Objective: The aim of this study was to demonstrate the use of Venn diagrams to investigate the contributions of digital proximity tracing app exposure notifications and subsequent mitigative actions in curbing the spread of SARS-CoV-2 in Switzerland. Methods: We assessed data from 4 survey waves (December 2020 to March 2021) from a nationwide panel study (COVID-19 Social Monitor) of Swiss residents who were (1) nonusers of the SwissCovid app, (2) users of the SwissCovid app, or (3) users of the SwissCovid app who received exposure notifications. A Venn diagram approach was applied to describe the overlap or nonoverlap of these subpopulations and to assess digital proximity tracing app use and its associated key performance indicators, including actions taken to prevent SARS-CoV-2 transmission. Results: We included 12,525 assessments from 2403 participants, of whom 50.9\% (1222/2403) reported not using the SwissCovid digital proximity tracing app, 49.1\% (1181/2403) reported using the SwissCovid digital proximity tracing app and 2.5\% (29/1181) of the digital proximity tracing app users reported having received an exposure notification. Most digital proximity tracing app users (75.9\%, 22/29) revealed taking at least one recommended action after receiving an exposure notification, such as seeking SARS-CoV-2 testing (17/29, 58.6\%) or calling a federal information hotline (7/29, 24.1\%). An assessment of key indicators of mitigative actions through a Venn diagram approach reveals that 30\% of digital proximity tracing app users (95\% CI 11.9\%-54.3\%) also tested positive for SARS-CoV-2 after having received exposure notifications, which is more than 3 times that of digital proximity tracing app users who did not receive exposure notifications (8\%, 95\% CI 5\%-11.9\%). Conclusions: Responses in the form of mitigative actions taken by 3 out of 4 individuals who received exposure notifications reveal a possible contribution of digital proximity tracing apps in mitigating the spread of SARS-CoV-2. The application of a Venn diagram approach demonstrates its value as a foundation for researchers and health authorities to assess population-level digital proximity tracing app effectiveness by providing an intuitive approach for calculating key performance indicators. ", doi="10.2196/30004", url="https://publichealth.jmir.org/2021/12/e30004", url="http://www.ncbi.nlm.nih.gov/pubmed/34874890" } @Article{info:doi/10.2196/31271, author="Janvrin, Lynn Miranda and Korona-Bailey, Jessica and Koehlmoos, P{\'e}rez Tracey", title="Re-examining COVID-19 Self-Reported Symptom Tracking Programs in the United States: Updated Framework Synthesis", journal="JMIR Form Res", year="2021", month="Dec", day="6", volume="5", number="12", pages="e31271", keywords="COVID-19", keywords="coronavirus", keywords="framework analysis", keywords="information resources", keywords="monitoring", keywords="patient-reported outcome measures", keywords="self-reported", keywords="surveillance", keywords="symptom tracking", keywords="synthesis", keywords="digital health", abstract="Background: Early in the pandemic, in 2020, Koehlmoos et al completed a framework synthesis of currently available self-reported symptom tracking programs for COVID-19. This framework described relevant programs, partners and affiliates, funding, responses, platform, and intended audience, among other considerations. Objective: This study seeks to update the existing framework with the aim of identifying developments in the landscape and highlighting how programs have adapted to changes in pandemic response. Methods: Our team developed a framework to collate information on current COVID-19 self-reported symptom tracking programs using the ``best-fit'' framework synthesis approach. All programs from the previous study were included to document changes. New programs were discovered using a Google search for target keywords. The time frame for the search for programs ranged from March 1, 2021, to May 6, 2021. Results: We screened 33 programs, of which 8 were included in our final framework synthesis. We identified multiple common data elements, including demographic information such as race, age, gender, and affiliation (all were associated with universities, medical schools, or schools of public health). Dissimilarities included questions regarding vaccination status, vaccine hesitancy, adherence to social distancing, COVID-19 testing, and mental health. Conclusions: At this time, the future of self-reported symptom tracking for COVID-19 is unclear. Some sources have speculated that COVID-19 may become a yearly occurrence much like the flu, and if so, the data that these programs generate is still valuable. However, it is unclear whether the public will maintain the same level of interest in reporting their symptoms on a regular basis if the prevalence of COVID-19 becomes more common. ", doi="10.2196/31271", url="https://formative.jmir.org/2021/12/e31271", url="http://www.ncbi.nlm.nih.gov/pubmed/34792469" } @Article{info:doi/10.2196/28146, author="Scholl, Annika and Sassenberg, Kai", title="How Identification With the Social Environment and With the Government Guide the Use of the Official COVID-19 Contact Tracing App: Three Quantitative Survey Studies", journal="JMIR Mhealth Uhealth", year="2021", month="Nov", day="24", volume="9", number="11", pages="e28146", keywords="COVID-19", keywords="SARS-CoV-2", keywords="contact tracing app", keywords="social identification", keywords="technology acceptance", keywords="pandemic", keywords="outbreak", keywords="health technology", abstract="Background: Official contact tracing apps have been implemented and recommended for use across nations to track and contain the spread of COVID-19. Such apps can be effective if people are willing to use them. Accordingly, many attempts are being made to motivate citizens to make use of the officially recommended apps. Objective: The aim of this research was to contribute to an understanding of the preconditions under which people are willing to use a COVID-19 contact tracing app (ie, their use intentions and use). To go beyond personal motives in favor of app use, it is important to take people's social relationships into account, under the hypothesis that the more people identify with the beneficiaries of app use (ie, people living close by in their social environment) and with the source recommending the app (ie, members of the government), the more likely they will be to accept the officially recommended contact tracing app. Methods: Before, right after, and 5 months after the official contact tracing app was launched in Germany, a total of 1044 people participated in three separate surveys. Structural equation modeling was used to test the hypotheses, examining the same model in all studies at these critical points in time. Results: Across the three surveys, both identification with the beneficiaries (people living in their social environment) and with the source recommending the app (members of the government) predicted greater intention to use and use (installation) of the official contact tracing app. Trust in the source (members of the government) served as a mediator. Other types of identification (with people in Germany or people around the world) did not explain the observed results. The findings were highly consistent across the three surveys. Conclusions: Attempts to motivate people to use new health technology (or potentially new measures more generally) not only for their personal benefit but also for collective benefits should take the social context into account (ie, the social groups people belong to and identify with). The more important the beneficiaries and the sources of such measures are to people's sense of the self, the more willing they will likely be to adhere to and support such measures. ", doi="10.2196/28146", url="https://mhealth.jmir.org/2021/11/e28146", url="http://www.ncbi.nlm.nih.gov/pubmed/34662289" } @Article{info:doi/10.2196/29181, author="Jones, Kerina and Thompson, Rachel", title="To Use or Not to Use a COVID-19 Contact Tracing App: Mixed Methods Survey in Wales", journal="JMIR Mhealth Uhealth", year="2021", month="Nov", day="22", volume="9", number="11", pages="e29181", keywords="COVID-19", keywords="survey", keywords="Wales", keywords="contact tracing", keywords="app", keywords="mHealth", keywords="mobile apps", keywords="digital health", keywords="public health", abstract="Background: Many countries remain in the grip of the COVID-19 global pandemic, with a considerable journey still ahead toward normalcy and free mobility. Contact tracing smartphone apps are among a raft of measures introduced to reduce spread of the virus, but their uptake depends on public choice. Objective: The objective of this study was to ascertain the views of citizens in Wales on their intended use of a COVID-19 contact tracing smartphone app, including self-proposed reasons for or against use and what could lead to a change of decision. Methods: We distributed an anonymous survey among 4000 HealthWise Wales participants in May 2020. We adopted a mixed methods approach: responses to closed questions were analyzed using descriptive and inferential statistics; open question responses were analyzed and grouped into categories. Results: A total of 976 (24.4\%) people completed the survey. Smartphone usage was 91.5\% overall, but this varied among age groups. In total, 97.1\% were aware of contact tracing apps, but only 67.2\% felt sufficiently informed. Furthermore, 55.7\% intended to use an app, 23.3\% refused, and 21.0\% were unsure. The top reasons for app use were as follows: controlling the spread of the virus, mitigating risks for others and for oneself, and increasing freedoms. The top reasons against app use were as follows: mistrusting the government, concerns about data security and privacy, and doubts about efficacy. The top response for changing one's mind about app use from being willing to being unwilling was that nothing would; that is, they felt that nothing would cause them to become unwilling to use a contact tracing app. This was also the top response for changing one's mind from being unwilling to being willing to use contact tracing apps. Among those who were unsure of using contact tracing apps, the top response was the need for more information. Conclusions: Respondents demonstrated a keenness to help themselves, others, society, and the government to avoid contracting the virus and to control its spread. However, digital inclusion varied among age groups, precluding participation for some people. Nonetheless, unwillingness was significant, and considering the nature of the concerns raised and the perceived lack of information, policy and decision-makers need to do more to act openly, increase communication, and demonstrate trustworthiness if members of the public are to be confident in using an app. ", doi="10.2196/29181", url="https://mhealth.jmir.org/2021/11/e29181", url="http://www.ncbi.nlm.nih.gov/pubmed/34698645" } @Article{info:doi/10.2196/28956, author="Oyibo, Kiemute and Morita, Pelegrini Plinio", title="Designing Better Exposure Notification Apps: The Role of Persuasive Design", journal="JMIR Public Health Surveill", year="2021", month="Nov", day="16", volume="7", number="11", pages="e28956", keywords="contact tracing app", keywords="exposure notification app", keywords="COVID Alert", keywords="COVID-19", keywords="persuasive technology", keywords="behavior change", abstract="Background: Digital contact tracing apps have been deployed worldwide to limit the spread of COVID-19 during this pandemic and to facilitate the lifting of public health restrictions. However, due to privacy-, trust-, and design-related issues, the apps are yet to be widely adopted. This calls for an intervention to enable a critical mass of users to adopt them. Objective: The aim of this paper is to provide guidelines to design contact tracing apps as persuasive technologies to make them more appealing and effective. Methods: We identified the limitations of the current contact tracing apps on the market using the Government of Canada's official exposure notification app (COVID Alert) as a case study. Particularly, we identified three interfaces in the COVID Alert app where the design can be improved. The interfaces include the no exposure status interface, exposure interface, and diagnosis report interface. We propose persuasive technology design guidelines to make them more motivational and effective in eliciting the desired behavior change. Results: Apart from trust and privacy concerns, we identified the minimalist and nonmotivational design of exposure notification apps as the key design-related factors that contribute to the current low uptake. We proposed persuasive strategies such as self-monitoring of daily contacts and exposure time to make the no exposure and exposure interfaces visually appealing and motivational. Moreover, we proposed social learning, praise, and reward to increase the diagnosis report interface's effectiveness. Conclusions: We demonstrated that exposure notification apps can be designed as persuasive technologies by incorporating key persuasive features, which have the potential to improve uptake, use, COVID-19 diagnosis reporting, and compliance with social distancing guidelines. ", doi="10.2196/28956", url="https://publichealth.jmir.org/2021/11/e28956", url="http://www.ncbi.nlm.nih.gov/pubmed/34783673" } @Article{info:doi/10.2196/30462, author="Lee, Kyu Jeong and Lin, Lavinia and Kang, Hyunjin", title="The Influence of Normative Perceptions on the Uptake of the COVID-19 TraceTogether Digital Contact Tracing System: Cross-sectional Study", journal="JMIR Public Health Surveill", year="2021", month="Nov", day="12", volume="7", number="11", pages="e30462", keywords="COVID-19", keywords="social norms", keywords="TraceTogether", keywords="Singapore", keywords="contact tracing", keywords="mobile app", keywords="token", abstract="Background: In 2020, the Singapore government rolled out the TraceTogether program, a digital system to facilitate contact tracing efforts in response to the COVID-19 pandemic. This system is available as a smartphone app and Bluetooth-enabled token to help identify close contacts. As of February 1, 2021, more than 80\% of the population has either downloaded the mobile app or received the token in Singapore. Despite the high adoption rate of the TraceTogether mobile app and token (ie, device), it is crucial to understand the role of social and normative perceptions in uptake and usage by the public, given the collective efforts for contact tracing. Objective: This study aimed to examine normative influences (descriptive and injunctive norms) on TraceTogether device use for contact tracing purposes, informed by the theory of normative social behavior, a theoretical framework to explain how perceived social norms are related to behaviors. Methods: From January to February 2021, cross-sectional data were collected by a local research company through emailing their panel members who were (1) Singapore citizens or permanent residents aged 21 years or above; (2) able to read English; and (3) internet users with access to a personal email account. The study sample (n=1137) was restricted to those who had either downloaded the TraceTogether mobile app or received the token. Results: Multivariate (linear and ordinal logistic) regression analyses were carried out to assess the relationships of the behavioral outcome variables (TraceTogether device usage and intention of TraceTogether device usage) with potential correlates, including perceived social norms, perceived community, and interpersonal communication. Multivariate regression analyses indicated that descriptive norms (unstandardized regression coefficient $\beta$=0.31, SE=0.05; P<.001) and injunctive norms (unstandardized regression coefficient $\beta$=0.16, SE=0.04; P<.001) were significantly positively associated with the intention to use the TraceTogether device. It was also found that descriptive norms were a significant correlate of TraceTogether device use frequency (adjusted odds ratio [aOR] 2.08, 95\% CI 1.66-2.61; P<.001). Though not significantly related to TraceTogether device use frequency, injunctive norms moderated the relationship between descriptive norms and the outcome variable (aOR 1.12, 95\% CI 1.03-1.21; P=.005). Conclusions: This study provides useful implications for the design of effective intervention strategies to promote the uptake and usage of digital methods for contact tracing in a multiethnic Asian population. Our findings highlight that influence from social networks plays an important role in developing normative perceptions in relation to TraceTogether device use for contact tracing. To promote the uptake of the TraceTogether device and other preventive behaviors for COVID-19, it would be useful to devise norm-based interventions that address these normative perceptions by presenting high prevalence and approval of important social referents, such as family and close friends. ", doi="10.2196/30462", url="https://publichealth.jmir.org/2021/11/e30462", url="http://www.ncbi.nlm.nih.gov/pubmed/34623956" } @Article{info:doi/10.2196/32093, author="Lee, Bohee and Ibrahim, Aishah Siti and Zhang, Tiying", title="Mobile Apps Leveraged in the COVID-19 Pandemic in East and South-East Asia: Review and Content Analysis", journal="JMIR Mhealth Uhealth", year="2021", month="Nov", day="11", volume="9", number="11", pages="e32093", keywords="mobile apps", keywords="applications", keywords="eHealth", keywords="mHealth", keywords="mobile health", keywords="digital health", keywords="telemedicine", keywords="telehealth", keywords="COVID-19", keywords="coronavirus", keywords="pandemic", keywords="public health", keywords="health policy", abstract="Background: The COVID-19 pandemic increased attention to digital tools to support governmental public health policies in East and South-East Asia. Mobile apps related to the COVID-19 pandemic continue to emerge and evolve with a wide variety of characteristics and functions. However, there is a paucity of studies evaluating such apps in this region, with most of the available studies conducted in the early days of the pandemic. Objective: This study aimed to examine free apps developed or supported by governments in the East and South-East Asian region and highlight their key characteristics and functions. We also sought to interpret how the release dates of these apps were related to the commencement dates of other COVID-19 public health policies. Methods: We systematically searched for apps in Apple App Store and Google Play Store and analyzed the contents of eligible apps. Mobile apps released or updated with COVID-19--related functions between March 1 and May 7, 2021, in Singapore, Taiwan, South Korea, China (mainland), Japan, Thailand, Hong Kong, Vietnam, Malaysia, Indonesia, and the Philippines were included. The CoronaNet Research Project database was also examined to determine the timeline of public health policy commencement dates in relation to the release dates of the included apps. We assessed each app's official website, media reports, and literature through content analysis. Descriptive statistics were used to summarize relevant information gathered from the mobile apps using RStudio. Results: Of the 1943 mobile apps initially identified, 46 were eligible, with almost 70\% of the apps being intended for the general public. Most apps were from Vietnam (n=9, 20\%), followed by Malaysia, Singapore, and Thailand (n=6 each, 13\%). Of note, most apps for quarantine monitoring (n=6, 13\%) were mandatory for the target users or a population subset. The most common function was health monitoring (32/46, 70\%), followed by raising public health awareness (19/46, 41\%) through education and information dissemination. Other functions included monitoring quarantine (12/46, 26\%), providing health resources (12/46, 26\%). COVID-19 vaccination management functions began to appear in parallel with vaccine rollout (7/46, 15\%). Regarding the timing of the introduction of mobile solutions, the majority of mobile apps emerged close to the commencement dates of other public health policies in the early stages of the pandemic between March and April 2020. Conclusions: In East and South-East Asia, most governments used mobile health apps as adjuncts to public health measures for tracking COVID-19 cases and delivering credible information. In addition, these apps have evolved by expanding their functions for COVID-19 vaccination. ", doi="10.2196/32093", url="https://mhealth.jmir.org/2021/11/e32093", url="http://www.ncbi.nlm.nih.gov/pubmed/34748515" } @Article{info:doi/10.2196/27301, author="Albouy-Llaty, Marion and Martin, Caroline and Benamouzig, Daniel and Bothorel, Eric and Munier, Gilles and Simonin, Catherine and Gu{\'e}ant, Jean-Louis and Rusch, Emmanuel", title="Positioning Digital Tracing Applications in the Management of the COVID-19 Pandemic in France", journal="J Med Internet Res", year="2021", month="Oct", day="7", volume="23", number="10", pages="e27301", keywords="COVID-19 pandemic", keywords="digital contact tracing applications", keywords="health inequalities", keywords="Europe", keywords="health promotion", doi="10.2196/27301", url="https://www.jmir.org/2021/10/e27301", url="http://www.ncbi.nlm.nih.gov/pubmed/34313588" } @Article{info:doi/10.2196/30444, author="De Ridder, David and Loizeau, Jutta Andrea and Sandoval, Luis Jos{\'e} and Ehrler, Fr{\'e}d{\'e}ric and Perrier, Myriam and Ritch, Albert and Violot, Guillemette and Santolini, Marc and Greshake Tzovaras, Bastian and Stringhini, Silvia and Kaiser, Laurent and Pradeau, Jean-Fran{\c{c}}ois and Joost, St{\'e}phane and Guessous, Idris", title="Detection of Spatiotemporal Clusters of COVID-19--Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study", journal="JMIR Res Protoc", year="2021", month="Oct", day="6", volume="10", number="10", pages="e30444", keywords="participatory surveillance", keywords="infectious disease", keywords="COVID-19", keywords="SARS-CoV-2", keywords="space-time clustering", keywords="digital health", keywords="mobile app", keywords="mHealth", keywords="epidemiology", keywords="surveillance", keywords="digital surveillance", keywords="public health", abstract="Background: The early detection of clusters of infectious diseases such as the SARS-CoV-2--related COVID-19 disease can promote timely testing recommendation compliance and help to prevent disease outbreaks. Prior research revealed the potential of COVID-19 participatory syndromic surveillance systems to complement traditional surveillance systems. However, most existing systems did not integrate geographic information at a local scale, which could improve the management of the SARS-CoV-2 pandemic. Objective: The aim of this study is to detect active and emerging spatiotemporal clusters of COVID-19--associated symptoms, and to examine (a posteriori) the association between the clusters' characteristics and sociodemographic and environmental determinants. Methods: This report presents the methodology and development of the @choum (English: ``achoo'') study, evaluating an epidemiological digital surveillance tool to detect and prevent clusters of individuals (target sample size, N=5000), aged 18 years or above, with COVID-19--associated symptoms living and/or working in the canton of Geneva, Switzerland. The tool is a 5-minute survey integrated into a free and secure mobile app (CoronApp-HUG). Participants are enrolled through a comprehensive communication campaign conducted throughout the 12-month data collection phase. Participants register to the tool by providing electronic informed consent and nonsensitive information (gender, age, geographically masked addresses). Symptomatic participants can then report COVID-19--associated symptoms at their onset (eg, symptoms type, test date) by tapping on the @choum button. Those who have not yet been tested are offered the possibility to be informed on their cluster status (information returned by daily automated clustering analysis). At each participation step, participants are redirected to the official COVID-19 recommendations websites. Geospatial clustering analyses are performed using the modified space-time density-based spatial clustering of applications with noise (MST-DBSCAN) algorithm. Results: The study began on September 1, 2020, and will be completed on February 28, 2022. Multiple tests performed at various time points throughout the 5-month preparation phase have helped to improve the tool's user experience and the accuracy of the clustering analyses. A 1-month pilot study performed among 38 pharmacists working in 7 Geneva-based pharmacies confirmed the proper functioning of the tool. Since the tool's launch to the entire population of Geneva on February 11, 2021, data are being collected and clusters are being carefully monitored. The primary study outcomes are expected to be published in mid-2022. Conclusions: The @choum study evaluates an innovative participatory epidemiological digital surveillance tool to detect and prevent clusters of COVID-19--associated symptoms. @choum collects precise geographic information while protecting the user's privacy by using geomasking methods. By providing an evidence base to inform citizens and local authorities on areas potentially facing a high COVID-19 burden, the tool supports the targeted allocation of public health resources and promotes testing. International Registered Report Identifier (IRRID): DERR1-10.2196/30444 ", doi="10.2196/30444", url="https://www.researchprotocols.org/2021/10/e30444", url="http://www.ncbi.nlm.nih.gov/pubmed/34449403" } @Article{info:doi/10.2196/30339, author="Gonsalves, P. Pattie and Sharma, Rhea and Hodgson, Eleanor and Bhat, Bhargav and Jambhale, Abhijeet and Weiss, A. Helen and Fairburn, G. Christopher and Cavanagh, Kate and Cuijpers, Pim and Michelson, Daniel and Patel, Vikram", title="A Guided Internet-Based Problem-Solving Intervention Delivered Through Smartphones for Secondary School Pupils During the COVID-19 Pandemic in India: Protocol for a Pilot Randomized Controlled Trial", journal="JMIR Res Protoc", year="2021", month="Oct", day="6", volume="10", number="10", pages="e30339", keywords="randomized controlled trial", keywords="internet-based intervention", keywords="smartphone", keywords="adolescent", keywords="schools", keywords="mental health", keywords="COVID-19", keywords="app", keywords="protocol", keywords="problem-solving", keywords="intervention", keywords="teenager", keywords="young adult", keywords="India", keywords="feasibility", keywords="effective", abstract="Background: ``POD Adventures'' is a gamified mental health intervention delivered via a smartphone app and supported by counsellors for a target population of secondary school students in India. This paper describes the protocol for a pilot randomized controlled trial of a remotely delivered version of the intervention in the context of COVID-19 restrictions. Objective: Our objectives are to assess the feasibility of research procedures and intervention delivery and to generate preliminary estimates of the effectiveness of the intervention to inform the sample size calculation of a full-scale trial. Methods: We will conduct a parallel, 2-arm, individually randomized pilot controlled trial in 11 secondary schools in Goa, India. This pilot trial aims to recruit 70 participants with a felt need for psychological support. Participants will receive either the POD Adventures intervention delivered over 4 weeks or usual care comprising information about local mental health services and national helplines. Outcomes will be assessed at two timepoints: baseline and 6 weeks post randomization. Results: The first participant was enrolled on January 28, 2021, and 6-week assessment completed on April 4, 2021. Owing to a second wave of the COVID-19 pandemic in India, schools in Goa were closed on April 22, 2021. Trial participants are currently receiving the intervention or completing follow-up assessments. Conclusions: This pilot trial will help understand the feasibility of implementing and evaluating a remotely delivered digital mental health intervention in a low-resource setting. Our findings will be used to design future trials that can address difficulties of accessing psychosocial support in-person and support wider efforts to scale up evidence-based mental health interventions for young people. Trial Registration: ClinicalTrials.gov NCT04672486; https://clinicaltrials.gov/ct2/show/NCT04672486 International Registered Report Identifier (IRRID): DERR1-10.2196/30339 ", doi="10.2196/30339", url="https://www.researchprotocols.org/2021/10/e30339", url="http://www.ncbi.nlm.nih.gov/pubmed/34586075" } @Article{info:doi/10.2196/30871, author="Seberger, S. John and Patil, Sameer", title="Post-COVID Public Health Surveillance and Privacy Expectations in the United States: Scenario-Based Interview Study", journal="JMIR Mhealth Uhealth", year="2021", month="Oct", day="5", volume="9", number="10", pages="e30871", keywords="COVID-19", keywords="pandemic-tracking apps", keywords="privacy concerns", keywords="infrastructure", keywords="health surveillance", keywords="scenario", keywords="interview", keywords="thematic analysis", abstract="Background: Smartphone-based apps designed and deployed to mitigate the COVID-19 pandemic may become infrastructure for postpandemic public health surveillance in the United States. Through the lenses of privacy concerns and user expectations of digital pandemic mitigation techniques, we identified possible long-term sociotechnical implications of such an infrastructure. Objective: We explored how people in the United States perceive the possible routinization of pandemic tracking apps for public health surveillance in general. Our interdisciplinary analysis focused on the interplay between privacy concerns, data practices of surveillance capitalism, and trust in health care providers. We conducted this analysis to achieve a richer understanding of the sociotechnical issues raised by the deployment and use of technology for pandemic mitigation. Methods: We conducted scenario-based, semistructured interviews (n=19) with adults in the United States. The interviews focused on how people perceive the short- and long-term privacy concerns associated with a fictional smart thermometer app deployed to mitigate the ``outbreak of a contagious disease.'' In order to elicit future-oriented discussions, the scenario indicated that the app would continue functioning ``after the disease outbreak has dissipated.'' We analyzed interview transcripts using reflexive thematic analysis. Results: In the context of pandemic mitigation technology, including app-based tracking, people perceive a core trade-off between public health and personal privacy. People tend to rationalize this trade-off by invoking the concept of ``the greater good.'' The interplay between the trade-off and rationalization forms the core of sociotechnical issues that pandemic mitigation technologies raise. Participants routinely expected that data collected through apps related to public health would be shared with unknown third parties for the financial gain of the app makers. This expectation suggests a perceived alignment between an app-based infrastructure for public health surveillance and the broader economics of surveillance capitalism. Our results highlight unintended and unexpected sociotechnical impacts of routinizing app-based tracking on postpandemic life, which are rationalized by invoking a nebulous concept of the greater good. Conclusions: While technologies such as app-based tracking could be useful for pandemic mitigation and preparedness, the routinization of such apps as a form of public health surveillance may have broader, unintentional sociotechnical implications for individuals and the societies in which they live. Although technology has the potential to increase the efficacy of pandemic mitigation, it exists within a broader network of sociotechnical concerns. Therefore, it is necessary to consider the long-term implications of pandemic mitigation technologies beyond the immediate needs of addressing the COVID-19 pandemic. Potential negative consequences include the erosion of patient trust in health care systems and providers, grounded in concerns about privacy violations and overly broad surveillance. ", doi="10.2196/30871", url="https://mhealth.jmir.org/2021/10/e30871", url="http://www.ncbi.nlm.nih.gov/pubmed/34519667" } @Article{info:doi/10.2196/29085, author="Dowthwaite, Liz and Fischer, Joel and Perez Vallejos, Elvira and Portillo, Virginia and Nichele, Elena and Goulden, Murray and McAuley, Derek", title="Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study", journal="J Med Internet Res", year="2021", month="Sep", day="17", volume="23", number="9", pages="e29085", keywords="trust", keywords="technology adoption", keywords="COVID-19", keywords="digital contact tracing", keywords="coronavirus", keywords="vulnerable populations", keywords="attitudes", keywords="SARS-CoV-2", keywords="digital proximity tracing", keywords="compliance", abstract="Background: Digital contact tracing is employed to monitor and manage the spread of COVID-19. However, to be effective the system must be adopted by a substantial proportion of the population. Studies of mostly hypothetical contact tracing apps show generally high acceptance, but little is known about the drivers and barriers to adoption of deployed systems. Objective: The aim of this study was to investigate adoption of and attitudes toward the NHS (National Health Service) COVID-19 smartphone app, the digital contact tracing solution in the United Kingdom. Methods: An online survey based on the extended Technology Acceptance Model with the added factor of trust was carried out with a representative sample of the UK population. Statistical analysis showed adoption rates, attitudes toward and trust in the app, and compliance with self-isolation advice and highlighted differences for vulnerable populations (ie, older adults aged 65 years and over and members of Black, Asian, and minority ethnic [BAME] communities). Results: A total of 1001 participants took part in the study. Around half of the participants who had heard of the NHS COVID-19 mobile phone app (490/963, 50.9\%; 95\% CI 47.8\%-54.0\%) had downloaded and kept the app, but more than one-third (345/963, 35.8\%; 95\% CI 32.8\%-38.8\%) either did not intend to download it or had deleted it. Significantly more BAME respondents than White respondents had deleted the app (16/115, 13.9\%; 95\% CI 11.8\%-16.0\%, vs 65/876, 7.4\%; 95\% CI 5.8\%-9.0\%), and significantly more older adults 65 years and over than those under 65 years did not intend to download it (44/127, 34.6\%; 95\% CI 31.7\%-37.5\%, vs 220/874, 25.2\%; 95\% CI 22.5\%-27.9\%). Broadly, one of the reasons for uptake was to help the NHS and other people, especially among older adults, although significantly fewer BAME participants agreed that they did so to help the NHS. Reported compliance with received notifications to self-isolate was high but was significantly lower than reported intended compliance without received notifications. Only one-fifth (136/699, 19.5\%; 95\% CI 17.0\%-22.0\%) of participants understood that the decision to send self-isolation notifications was automated by the app. There were a range of significantly more negative views among BAME participants, including lower trust in the NHS, while older adults were often significantly more positive. Respondents without the app reported significantly lower trust and more negative views toward the app and were less likely to report that they understood how the app works. Conclusions: While compliance on the part of the approximately 50\% of participants who had the app was fairly high, there were issues surrounding trust and understanding that hindered adoption and, therefore, the effectiveness of digital contact tracing, particularly among BAME communities. This study highlights that more needs to be done to improve adoption among groups who are more vulnerable to the effects of the virus in order to enhance uptake and acceptance of contact tracing apps. ", doi="10.2196/29085", url="https://www.jmir.org/2021/9/e29085", url="http://www.ncbi.nlm.nih.gov/pubmed/34406960" } @Article{info:doi/10.2196/30819, author="Yamagami, Kan and Nomura, Akihiro and Kometani, Mitsuhiro and Shimojima, Masaya and Sakata, Kenji and Usui, Soichiro and Furukawa, Kenji and Takamura, Masayuki and Okajima, Masaki and Watanabe, Kazuyoshi and Yoneda, Takashi", title="Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation", journal="JMIR Form Res", year="2021", month="Sep", day="16", volume="5", number="9", pages="e30819", keywords="COVID-19", keywords="silent hypoxia", keywords="wearable device", keywords="Fitbit", keywords="estimated oxygen variation", keywords="detection", keywords="infectious disease", keywords="pilot study", keywords="symptom", keywords="outpatient", keywords="oxygen", keywords="sleep", keywords="wearable", abstract="Background: Some patients with COVID-19 experienced sudden death due to rapid symptom deterioration. Thus, it is important to predict COVID-19 symptom exacerbation at an early stage prior to increasing severity in patients. Patients with COVID-19 could experience a unique ``silent hypoxia'' at an early stage of the infection when they are apparently asymptomatic, but with rather low SpO2 (oxygen saturation) levels. In order to continuously monitor SpO2 in daily life, a high-performance wearable device, such as the Apple Watch or Fitbit, has become commercially available to monitor several biometric data including steps, resting heart rate (RHR), physical activity, sleep quality, and estimated oxygen variation (EOV). Objective: This study aimed to test whether EOV measured by the wearable device Fitbit can predict COVID-19 symptom exacerbation. Methods: We recruited patients with COVID-19 from August to November 2020. Patients were asked to wear the Fitbit for 30 days, and biometric data including EOV and RHR were extracted. EOV is a relative physiological measure that reflects users' SpO2 levels during sleep. We defined a high EOV signal as a patient's oxygen level exhibiting a significant dip and recovery within the index period, and a high RHR signal as daily RHR exceeding 5 beats per day compared with the minimum RHR of each patient in the study period. We defined successful prediction as the appearance of those signals within 2 days before the onset of the primary outcome. The primary outcome was the composite of deaths of all causes, use of extracorporeal membrane oxygenation, use of mechanical ventilation, oxygenation, and exacerbation of COVID-19 symptoms, irrespective of readmission. We also assessed each outcome individually as secondary outcomes. We made weekly phone calls to discharged patients to check on their symptoms. Results: We enrolled 23 patients with COVID-19 diagnosed by a positive SARS-CoV-2 polymerase chain reaction test. The patients had a mean age of 50.9 (SD 20) years, and 70\% (n=16) were female. Each patient wore the Fitbit for 30 days. COVID-19 symptom exacerbation occurred in 6 (26\%) patients. We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80\%, specificity=90\%), whereas the sensitivity and specificity of high RHR signals were 50\% and 80\%, respectively, both lower than those of high EOV signals. Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals. Conclusions: This pilot study successfully detected early COVID-19 symptom exacerbation by measuring EOV, which may help to identify the early signs of COVID-19 exacerbation. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry UMIN000041421; https://upload.umin.ac.jp/cgi-open-bin/ctr\_e/ctr\_view.cgi?recptno=R000047290 ", doi="10.2196/30819", url="https://formative.jmir.org/2021/9/e30819", url="http://www.ncbi.nlm.nih.gov/pubmed/34516390" } @Article{info:doi/10.2196/26318, author="Tretiakov, Alexei and Hunter, Inga", title="User Experiences of the NZ COVID Tracer App in New Zealand: Thematic Analysis of Interviews", journal="JMIR Mhealth Uhealth", year="2021", month="Sep", day="8", volume="9", number="9", pages="e26318", keywords="COVID-19", keywords="contact tracing", keywords="app", keywords="New Zealand", keywords="adoption", keywords="use", keywords="civic responsibility", keywords="privacy", abstract="Background: For mobile app--based COVID-19 contact tracing to be fully effective, a large majority of the population needs to be using the app on an ongoing basis. However, there is a paucity of studies of users, as opposed to potential adopters, of mobile contact tracing apps and of their experiences. New Zealand, a high-income country with western political culture, was successful in managing the COVID-19 pandemic, and its experience is valuable for informing policy responses in similar contexts. Objective: This study asks the following research questions: (1) How do users experience the app in their everyday contexts? and (2) What drives the use of the app? Methods: Residents of New Zealand's Auckland region, which encompasses the country's largest city, were approached via Facebook, and 34 NZ COVID Tracer app users were interviewed. Interview transcripts were analyzed using thematic analysis. Results: Interviews ranged in duration from 15 to 50 minutes. Participants ranged in age from those in their late teens to those in their early sixties. Even though about half of the participants identified as White New Zealanders of European origin, different ethnicities were represented, including New Zealanders of South Pacific, Indian, Middle Eastern, South American, and Southeast Asian descent. Out of 34 participants, 2 (6\%) identified as M?ori (Indigenous New Zealanders). A broad range of careers were represented, from top-middle management to health support work and charity work. Likewise, educational backgrounds ranged broadly, from high school completion to master's degrees. Out of 34 participants, 2 (6\%) were unemployed, having recently lost their jobs because of the pandemic. The thematic analysis resulted in five major themes: perceived benefits, patterns of use, privacy, social influence, and need for collective action. Benefits of using the app to society in general were more salient to the participants than immediate health benefits to the individual. Use, however, depended on the alert level and tended to decline for many participants at low alert levels. Privacy considerations played a small role in shaping adoption and use, even though the participants were highly aware of privacy discourse around the app. Participants were aware of the need for high levels of adoption and use of the app to control the pandemic. Attempts to encourage others to use the app were common, although not always successful. Conclusions: Appeals to civic responsibility are likely to drive the use of a mobile contact tracing app under the conditions of high threat. Under the likely scenario of COVID-19 remaining endemic and requiring ongoing vigilance over the long term, other mechanisms promoting the use of mobile contact tracing apps may be needed, such as offering incentives. As privacy is not an important concern for many users, flexible privacy settings in mobile contact tracing apps allowing users to set their optimal levels of privacy may be appropriate. ", doi="10.2196/26318", url="https://mhealth.jmir.org/2021/9/e26318", url="http://www.ncbi.nlm.nih.gov/pubmed/34292868" } @Article{info:doi/10.2196/29923, author="Shoji, Masahiro and Ito, Asei and Cato, Susumu and Iida, Takashi and Ishida, Kenji and Katsumata, Hiroto and McElwain, Mori Kenneth", title="Prosociality and the Uptake of COVID-19 Contact Tracing Apps: Survey Analysis of Intergenerational Differences in Japan", journal="JMIR Mhealth Uhealth", year="2021", month="Aug", day="19", volume="9", number="8", pages="e29923", keywords="COVID-19", keywords="contact tracing app", keywords="place attachment", keywords="place identity", keywords="contact tracing", keywords="pandemic", keywords="mHealth", keywords="health policy", abstract="Background: To control the COVID-19 pandemic, it is essential to trace and contain infection chains; for this reason, policymakers have endorsed the usage of contact tracing apps. To date, over 50 countries have released such apps officially or semiofficially, but those that rely on citizens' voluntary uptake suffer from low adoption rates, reducing their effectiveness. Early studies suggest that the low uptake is driven by citizens' concerns about security and privacy, as well as low perceptions of infection risk and benefits from the usage. However, these do not explore important generational differences in uptake decision or the association between individuals' prosociality and uptake. Objective: The objective of our study was to examine the role of individuals' prosociality and other factors discussed in the literature, such as perceived risk and trust in government, in encouraging the usage of contact tracing apps in Japan. We paid particular attention to generational differences. Methods: A web-based survey was conducted in Japan 6 months after the release of a government-sponsored contact tracing app. Participants were recruited from individuals aged between 20 and 69 years. Exploratory factor analyses were conducted to measure prosociality, risk perception, and trust in government. Logistic regression was used to examine the association between these factors and uptake. Results: There was a total of 7084 respondents, and observations from 5402 respondents were used for analysis, of which 791 respondents (14.6\%) had ever used the app. Two factors of prosociality were retained: agreeableness and attachment to the community. Full-sample analysis demonstrated app uptake was determined by agreeableness, attachment to the community, concern about health risks, concern about social risks, and trust in the national government; however, important differences existed. The uptake decision of respondents aged between 20 and 39 years was attributed to their attachment to the community (odds ratio [OR] 1.28, 95\% CI 1.11-1.48). Agreeable personality (OR 1.18, 95\% CI 1.02-1.35), concern about social risk (OR 1.17, 95\% CI 1.02-1.35), and trust in national government (OR 1.16, 95\% CI 1.05-1.28) were key determinants for those aged between 40 and 59 years. For those aged over 60 years, concerns about health risks determined the uptake decision (OR 1.49, 95\% CI 1.24-1.80). Conclusions: Policymakers should implement different interventions for each generation to increase the adoption rate of contact tracing apps. It may be effective to inform older adults about the health benefits of the apps. For middle-age adults, it is important to mitigate concerns about security and privacy issues, and for younger generations, it is necessary to boost their attachment to their community by utilizing social media and other web-based network tools. ", doi="10.2196/29923", url="https://mhealth.jmir.org/2021/8/e29923", url="http://www.ncbi.nlm.nih.gov/pubmed/34313601" } @Article{info:doi/10.2196/29268, author="gro{\ss}e Deters, Fenne and Meier, Tabea and Milek, Anne and Horn, B. Andrea", title="Self-Focused and Other-Focused Health Concerns as Predictors of the Uptake of Corona Contact Tracing Apps: Empirical Study", journal="J Med Internet Res", year="2021", month="Aug", day="10", volume="23", number="8", pages="e29268", keywords="COVID-19", keywords="corona contact tracing app", keywords="digital proximity tracing", keywords="preventive behavior", keywords="health concern", keywords="prosocial motivation", keywords="public health", keywords="risk perception, eHealth, Corona-Warn-App", keywords="SwissCovid", keywords="contact tracing app", keywords="contact tracing", abstract="Background: Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial. Objective: This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one's own health and concern to unknowingly infect others. Methods: A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables. Results: Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one's own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that ``too much'' concern leads to defensive reactions and reduces app uptake. Conclusions: As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed. ", doi="10.2196/29268", url="https://www.jmir.org/2021/8/e29268", url="http://www.ncbi.nlm.nih.gov/pubmed/34227995" } @Article{info:doi/10.2196/28947, author="Piotto, Stefano and Di Biasi, Luigi and Marrafino, Francesco and Concilio, Simona", title="Evaluating Epidemiological Risk by Using Open Contact Tracing Data: Correlational Study", journal="J Med Internet Res", year="2021", month="Aug", day="2", volume="23", number="8", pages="e28947", keywords="SARS-CoV-2", keywords="COVID-19", keywords="contact tracing", keywords="Bluetooth Low Energy", keywords="transmission dynamics", keywords="infection spread", keywords="mobile apps", keywords="mHealth", keywords="digital apps", keywords="mobile phone", abstract="Background: During the 2020s, there has been extensive debate about the possibility of using contact tracing (CT) to contain the SARS-CoV-2 pandemic, and concerns have been raised about data security and privacy. Little has been said about the effectiveness of CT. In this paper, we present a real data analysis of a CT experiment that was conducted in Italy for 8 months and involved more than 100,000 CT app users. Objective: We aimed to discuss the technical and health aspects of using a centralized approach. We also aimed to show the correlation between the acquired contact data and the number of SARS-CoV-2--positive cases. Finally, we aimed to analyze CT data to define population behaviors and show the potential applications of real CT data. Methods: We collected, analyzed, and evaluated CT data on the duration, persistence, and frequency of contacts over several months of observation. A statistical test was conducted to determine whether there was a correlation between indices of behavior that were calculated from the data and the number of new SARS-CoV-2 infections in the population (new SARS-CoV-2--positive cases). Results: We found evidence of a correlation between a weighted measure of contacts and the number of new SARS-CoV-2--positive cases (Pearson coefficient=0.86), thereby paving the road to better and more accurate data analyses and spread predictions. Conclusions: Our data have been used to determine the most relevant epidemiological parameters and can be used to develop an agent-based system for simulating the effects of restrictions and vaccinations. Further, we demonstrated our system's ability to identify the physical locations where the probability of infection is the highest. All the data we collected are available to the scientific community for further analysis. ", doi="10.2196/28947", url="https://www.jmir.org/2021/8/e28947", url="http://www.ncbi.nlm.nih.gov/pubmed/34227997" } @Article{info:doi/10.2196/30709, author="Beauchamp, R. Mark and Hulteen, M. Ryan and Ruissen, R. Geralyn and Liu, Yan and Rhodes, E. Ryan and Wierts, M. Colin and Waldhauser, J. Katrina and Harden, H. Samantha and Puterman, Eli", title="Online-Delivered Group and Personal Exercise Programs to Support Low Active Older Adults' Mental Health During the COVID-19 Pandemic: Randomized Controlled Trial", journal="J Med Internet Res", year="2021", month="Jul", day="30", volume="23", number="7", pages="e30709", keywords="COVID-19", keywords="randomized trial", keywords="mental health", keywords="physical activity", abstract="Background: In response to the COVID-19 pandemic, experts in mental health science emphasized the importance of developing and evaluating approaches to support and maintain the mental health of older adults. Objective: The aim of this study was to assess whether a group-based exercise program relative to a personal exercise program (both delivered online) and waitlist control (WLC) can improve the psychological health of previously low active older adults during the early stages of the COVID-19 pandemic. Methods: The Seniors COVID-19 Pandemic and Exercise (SCOPE) trial was a 3-arm, parallel randomized controlled trial conducted between May and September 2020 in which low active older adults (aged ?65 years) were recruited via media outlets and social media. After baseline assessments, consented participants were randomized to one of two 12-week exercise programs (delivered online by older adult instructors) or a WLC condition. A total of 241 older adults (n=187 women) provided baseline measures (via online questionnaires), were randomized (ngroup=80, npersonal=82, ncontrol=79), and completed measures every 2 weeks for the duration of the trial. The trial's primary outcome was psychological flourishing. Secondary outcomes included global measures of mental and physical health, life satisfaction, and depression symptoms. Results: The results of latent growth modeling revealed no intervention effects for flourishing, life satisfaction, or depression symptoms (P>.05 for all). Participants in the group condition displayed improved mental health relative to WLC participants over the first 10 weeks (effect size [ES]=0.288-0.601), and although the week 12 effect (ES=0.375) was in the same direction the difference was not statistically significant (P=.089). Participants in the personal condition displayed improved mental health, when compared with WLC participants, in the same medium ES range (ES=0.293-0.565) over the first 8 weeks, and while the effects were of a similar magnitude at weeks 10 (ES=0.455, P=.069) and 12 (ES=0.258, P=.353), they were not statistically significant. In addition, participants in the group condition displayed improvements in physical health when compared with the WLC (ES=0.079-0.496) across all 12 weeks of the study following baseline. No differences were observed between the personal exercise condition and WLC for physical health (slope P=.271). Conclusions: There were no intervention effects for the trial's primary outcome (ie, psychological flourishing). It is possible that the high levels of psychological flourishing at baseline may have limited the extent to which those indicators could continue to improve further through intervention (ie, potential ceiling effects). However, the intervention effects for mental and physical health point to the potential capacity of low-cost and scalable at-home programs to support the mental and physical health of previously inactive adults in the COVID-19 pandemic. Trial Registration: ClinicalTrials.gov NCT04412343; https://clinicaltrials.gov/ct2/show/NCT04412343 ", doi="10.2196/30709", url="https://www.jmir.org/2021/7/e30709", url="http://www.ncbi.nlm.nih.gov/pubmed/34328433" } @Article{info:doi/10.2196/29315, author="Park, Jihwan and Han, Jinhyun and Kim, Yerin and Rho, Jung Mi", title="Development, Acceptance, and Concerns Surrounding App-Based Services to Overcome the COVID-19 Outbreak in South Korea: Web-Based Survey Study", journal="JMIR Med Inform", year="2021", month="Jul", day="30", volume="9", number="7", pages="e29315", keywords="COVID-19", keywords="app-based services", keywords="acceptance", keywords="concerns", keywords="epidemiological investigation, self-route management app, privacy", abstract="Background: Since the COVID-19 outbreak, South Korea has been engaged in various efforts to overcome the pandemic. One of them is to provide app-based COVID-19--related services to the public. As the pandemic continues, a need for various apps has emerged, including COVID-19 apps that can support activities aimed at overcoming the COVID-19 pandemic. Objective: We aimed to determine which apps were considered the most necessary according to users and evaluate the current status of the development of COVID-19--related apps in South Korea. We also aimed to determine users' acceptance and concerns related to using apps to support activities to combat COVID-19. Methods: We collected data from 1148 users from a web-based survey conducted between November 11 and December 6, 2020. Basic statistical analysis, multiple response analysis, and the Wilcoxon rank sum test were performed using R software. We then manually classified the current status of the development of COVID-19--related apps. Results: In total, 68.4\% (785/1148) of the respondents showed high willingness to protect themselves from COVID-19 by using related apps. Users considered the epidemiological investigation app to be the most necessary app (709/1148, 61.8\%) overall, followed by the self-management app for self-isolation (613/1148, 53.4\%), self-route management app (605/1148, 52.7\%), COVID-19 symptom management app (483/1148, 42.1\%), COVID-19--related information provision app (339/1148, 29.5\%), and mental health management app (270/1148, 23.5\%). Despite the high intention to use these apps, users were also concerned about privacy issues and media exposure. Those who had an underlying disease and had experience using COVID-19--related apps showed significantly higher intentions to use those apps (P=.05 and P=.01, respectively). Conclusions: Targeting users is very important in order to design and develop the most necessary apps. Furthermore, to gain the public's trust and make the apps available to as many people as possible, it is vital to develop diverse apps in which privacy protection is maximized. ", doi="10.2196/29315", url="https://medinform.jmir.org/2021/7/e29315", url="http://www.ncbi.nlm.nih.gov/pubmed/34137726" } @Article{info:doi/10.2196/25926, author="Mhende, Josephine and Bell, A. Sharrill and Cottrell-Daniels, Cherell and Luong, Jackie and Streiff, Micah and Dannenfelser, Mark and Hayat, J. Matthew and Spears, Adams Claire", title="Mobile Delivery of Mindfulness-Based Smoking Cessation Treatment Among Low-Income Adults During the COVID-19 Pandemic: Pilot Randomized Controlled Trial", journal="JMIR Form Res", year="2021", month="Jul", day="23", volume="5", number="7", pages="e25926", keywords="acceptability", keywords="addiction", keywords="African American", keywords="cessation", keywords="COVID-19", keywords="feasibility", keywords="income", keywords="low socioeconomic status", keywords="mHealth", keywords="mindfulness", keywords="minority", keywords="smoking", keywords="SMS", keywords="text messaging", keywords="treatment", abstract="Background: Smoking is the leading cause of premature death, and low-income adults experience disproportionate burden from tobacco. Mindfulness interventions show promise for improving smoking cessation. A text messaging program ``iQuit Mindfully'' was developed to deliver just-in-time support for quitting smoking among low-income adults. A pilot study of iQuit Mindfully was conducted in spring 2020, during the COVID-19 pandemic, among low-income and predominantly African American smokers. Objective: This pilot study examined the acceptability and feasibility of delivering Mindfulness-Based Addiction Treatment via mHealth during the COVID-19 pandemic. Methods: Participants were adult cigarette smokers (n=23), of whom 8 (34.8\%) were female, 19 (82.6\%) were African American, and 18 (78.3\%) had an annual income of