ArticleJMIR research protocols2021
Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study.
Article in JMIR research protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04766788 (Monitoring Beliefs and Physiological Measures in Students at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology), which is not on this map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Monitoring Beliefs and Physiological Measures in Students at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review.The Lancet. Digital health · 2022Pooled it
- The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Using Wear Time for the Analysis of Consumer-Grade Wearables' Data: Case Study Using Fitbit Data.JMIR mHealth and uHealth · 2025Article
- Trends in Mental Health Outcomes of College Students Amid the Pandemic (Roadmap mHealth App): Longitudinal Observational Study.Journal of medical Internet research · 2025Observational
- Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression.Cell reports. Medicine · 2022Article
- Risk Factors for COVID-19 in College Students Identified by Physical, Mental, and Social Health Reported During the Fall 2020 Semester: Observational Study Using the Roadmap App and Fitbit Wearable Sensors.JMIR mental health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe 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.
objectiveThrough the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19.
methodsWe 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.
resultsThis study enrolled 2,158 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.
conclusionsThis study examined student health and well-being during the COVID-19 pandemic. It also assessed 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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.