Using Fitbit data to examine factors that affect daily activity levels of college students

Wang, Cheng; Ližardo, Omar; Hachen, David

doi:10.1371/journal.pone.0244747

Cited by 15 publications

(8 citation statements)

References 50 publications

(84 reference statements)

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“…The average daily step count observed in this study population was 6474 (SD 3371), which was a relatively low level of physical activity [ 42 ]. The NetHealth study conducted with 692 college students reported an average prepandemic daily step count of 11258 (SD 5874) [ 43 ]. This large difference in physical activity was likely due to pandemic procedures and norms (eg, isolation, quarantine, and public health guidelines).…”

Section: Discussionmentioning

confidence: 99%

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

Gilley¹,

Baroudi²,

Yu³

et al. 2022

JMIR Ment Health

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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

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Section: Discussionmentioning

confidence: 99%

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

Gilley¹,

Baroudi²,

Yu³

et al. 2022

JMIR Ment Health

View full text Add to dashboard Cite

show abstract

“…The average daily step count observed in this study population was 6474 (SD 3371), which was a relatively low level of physical activity [42]. The NetHealth study conducted with 692 college students reported an average prepandemic daily step count of 11258 (SD 5874) [43]. This large difference in physical activity was likely due to pandemic procedures and norms (eg, isolation, quarantine, and public health guidelines).…”

Section: Comparison With Prior Workmentioning

confidence: 75%

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 (Preprint)

Gilley¹,

Baroudi²,

Yu³

et al. 2021

Preprint

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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

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“…These are all aspects of exercise. It has been established that daily sociability, psychological factors such as high extroversion levels, and behavioral factors such as large network size are important modulators of the physical activity implication in young populations [20]. Providing highly active participants with personalized feedback helps facilitate positive emotional responses.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Physical Activity Recommendation Delivered through a Mobile Fitness App: A Deep Learning Approach

Subramaniyaswamy

Vijayakumar

Srinivasan

et al. 2022

Axioms

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Regular physical activity has a positive impact on our physical and mental health. Adhering to a fixed physical activity regimen is essential for good health and mental wellbeing. Today, fitness trackers and smartphone applications are used to promote physical activity. These applications use step counts recorded by accelerometers to estimate physical activity. In this research, we performed a two-level clustering on a dataset based on individuals’ physical and physiological features, as well as past daily activity patterns. The proposed model exploits the user data with partial or complete features. To include the user with partial features, we trained the proposed model with the data of users who possess exclusive features. Additionally, we classified the users into several clusters to produce more accurate results for the users. This enables the proposed system to provide data-driven and personalized activity planning recommendations every day. A personalized physical activity plan is generated on the basis of hourly patterns for users according to their adherence and past recommended activity plans. Customization of activity plans can be achieved according to the user’s historical activity habits and current activity objective, as well as the likelihood of sticking to the plan. The proposed physical activity recommendation system was evaluated in real time, and the results demonstrated the improved performance over existing baselines.

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Using Fitbit data to examine factors that affect daily activity levels of college students

Cited by 15 publications

References 50 publications

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

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

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 (Preprint)

Dynamic Physical Activity Recommendation Delivered through a Mobile Fitness App: A Deep Learning Approach

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