Background The COVID-19 pandemic has significantly impacted lives and greatly affected the mental health and public safety of an already vulnerable population—college students. Social distancing and isolation measures have presented challenges to students’ mental health. mHealth apps and wearable sensors may help monitor students at risk of COVID-19 and support their mental well-being. Objective This study aimed to monitor students at risk of COVID-19 by using a wearable sensor and a smartphone-based survey. Methods We conducted a prospective study on undergraduate and graduate students at a public university in the Midwest United States. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal smartphone devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints: at baseline, 1 month later, 2 months later, 3 months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. Results This study enrolled 2158 college students between September 2020 and January 2021. Subjects are currently being followed-up for 1 academic year. Data collection and analysis are currently underway. Conclusions This study examined student health and well-being during the COVID-19 pandemic and assessed the feasibility of using a wearable sensor and a survey in a college student population, which may inform the role of our mHealth tools in assessing student health and well-being. Finally, using data derived from a wearable sensor, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data toward the development of a model for the early prediction and detection of COVID-19. Trial Registration ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788 International Registered Report Identifier (IRRID) DERR1-10.2196/29561

Background The COVID-19 pandemic triggered a seismic shift in education to web-based learning. With nearly 20 million students enrolled in colleges across the United States, the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic. Objective This study leveraged mobile health (mHealth) technology and sought to (1) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; (2) assess physical activity through consumer-grade wearable sensors (Fitbit); and (3) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine. Methods After completing a baseline assessment (ie, at Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, wear the Fitbit, and complete subsequent assessments at T1, T2, and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: ~14 days after T3). Continuous measures were described using mean (SD) values, while categorical measures were summarized as n (%) values. Formal comparisons were made on the basis of COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<.05) in univariable associations at once and then removing one variable at a time through backward selection until the optimal model was obtained. Results During the fall 2020 semester, 1997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index, with moderate and severe levels in 465 (24%) and 970 (49%) students, respectively. Approximately one-third of students reported having a mental health disorder (n=656, 33%). The average daily steps recorded in this student population was approximately 6500 (mean 6474, SD 3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=.52). Our analyses revealed significant associations of COVID-19 positivity with the use of marijuana and alcohol (P=.02 and P=.046, respectively) and with lower belief in public health measures (P=.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=.009). Conclusions Mental health problems were common in this student population. Several factors, including substance use, were associated with the risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students. Trial Registration ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788 International Registered Report Identifier (IRRID) RR2-10.2196/29561

Background Health care workers (HCWs) have been working on the front lines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID-19 testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families. Objective By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19. Methods We conducted a prospective, longitudinal study of HCWs at a single institution. The study duration was 1 year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30 days. Participants consented to provide biospecimens (ie, nasal swabs, saliva swabs, and blood) for up to 1 year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life surveys at study entry and 30 days later. Semistructured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use. Results A total of 226 HCWs were enrolled between April 28 and December 7, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing. Conclusions Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in an HCW population. Trial Registration ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869 International Registered Report Identifier (IRRID) DERR1-10.2196/29562

BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic triggered a seismic shift in education, to online learning. With nearly 20 million students enrolled in colleges across the U.S., the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic. OBJECTIVE This study leveraged mobile health (mHealth) technology and sought to: i) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; ii) assess physical activity through consumer-grade wearable sensors (Fitbit®); and iii) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine. METHODS Detailed methods were previously published in JMIR Res Protocols (Cislo et al). After completing a baseline assessment (i.e., Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, to wear the Fitbit®, and complete subsequent assessments at T1, T2 and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: ~14 days after T3). Continuous measures were described using means (M) and standard deviations (SD), while categorical measures were summarized using frequencies and proportions. Formal comparisons were made based on COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<0.05) in univariable associations at once and then removing one variable at a time by backward selection until the optimal model was obtained. RESULTS During the fall 2020 semester, 1,997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index (STAI), with moderate and severe levels in N=465 (24%) and N=970 (49%) students, respectively. Approximately, one-third of students reported having a mental health disorder (N=656, 33%). The average daily steps recorded in this student population was approximately 6500 (M=6474, SD=3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=0.52). Our analyses revealed significant associations of COVID-positivity with use of marijuana and alcohol (p=0.020 and 0.046, respectively) and lower belief in public health measures (P=0.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=0.009). CONCLUSIONS Mental health problems were common in this student population. Several factors, including substance use, were associated with risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students. CLINICALTRIAL ClinicalTrials.gov (NCT04766788) INTERNATIONAL REGISTERED REPORT RR2-10.2196/29561

BACKGROUND The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student’s mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being. OBJECTIVE Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19. METHODS We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. RESULTS This study enrolled 2158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing. CONCLUSIONS This study examined student health and well-being during the COVID-19 pandemic. While data collection and analyses are ongoing, the study will assess the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19. CLINICALTRIAL ClinicalTrials.gov NCT04766788

BACKGROUND Health care workers (HCWs) have been working in the frontlines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families. OBJECTIVE By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aimed to assist HCWs in self-monitoring of COVID-19. METHODS We conducted a prospective, longitudinal study of HCWs at a single institution. Study duration was one year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30-days. Participants consented to providing biospecimens (e.g., nasal swabs, saliva swabs, blood) for up to one year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life (HRQOL) surveys at study entry and 30 days later. Semi-structured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use. RESULTS Two hundred twenty-six HCWs were enrolled between April 28, 2020 and December 07, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing. CONCLUSIONS Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in a HCW population. CLINICALTRIAL ClinicalTrials.gov #NCT04756869