UWEXP News and Publications

The UWEXP Study has been publishing research on a range of topics. Here are some publications to date

A lecturer showing a slide with an image of 3D printed gears on it. Students sit with their backs to us watching the lecture.

A Multi-StakeholderAnalysis of Accessibility in Higher Education

People with disabilities face extra hardship in institutions of higher education because of accessibility barriers built into the educational system. While prior work investigates the needs of individual stakeholders, this work ofers insights into the communication and collaboration between key stakeholders in creating access in institutions of higher education. The authors present refectionsfrom their experiences … Continue reading A Multi-StakeholderAnalysis of Accessibility in Higher Education

Example messages about COVI-19 safety including "after we meet up, can you walk me to the bus stop? I've had some bad experiences, and as an asian-american woman I don't feel safe" and "I know everyone's vaccinated, but can we still be careful? A few things I had in mind..." and "These guidelines would help me feel safe: everyone is vaccinated; no physical contact; masks on; no sharing food/drink"

COVID-19 Risk Negotation

During the COVID-19 pandemic, risk negotiation became an important precursor to in-person contact. For young adults, social planning generally occurs through computer-mediated communication. Given the importance of social connectedness for mental health and academic engagement, we sought to understand how young adults plan in-person meetups over computer-mediated communication in the context of the pandemic. We … Continue reading COVID-19 Risk Negotation

GLOBEM logo, blue text with a world for the O.

Cross-Dataset Generalization for Human Behavior Modeling

Overview; Data; Code There is a growing body of research revealing that longitudinal passive sensing data from smartphones and wearable devices can capture daily behavior signals for human behavior modeling, such as depression detection. Most prior studies build and evaluate machine learning models using data collected from a single population. However, to ensure that a … Continue reading Cross-Dataset Generalization for Human Behavior Modeling

A complex diagram showing the flow of information from sensors through feature extraction, formation of a user behavior profile, and then final prediction.

Personalized behavior modeling: depression detection

Xuhai Xu, Prerna Chikersal, Janine M. Dutcher, Yasaman S. Sefidgar, Seo Woosuk, Michael J. Tumminia, Daniella K. Villalba, Sheldon Cohen,Kasey G. Creswell, Creswell, J. David, Afsaneh Doryab, Paula S. Nurius, Eve Riskin, Anind K. Dey, & Jennifer Mankoff. Leveraging Collaborative-Filtering for Personalized Behavior Modeling: A Case Study of Depression Detection among College Students. Proc. ACM … Continue reading Personalized behavior modeling: depression detection

A diagram showing how we build stress & resilience frameworks for student mental health. The framework has three components -- social characteristics, cumulative stress, and resilience resources. At the center where all three overlap is perceived stress, anxiety and depression.

Distress and resilience among marginalized undergraduates

Nurius, P. S., Sefidgar, Y. S., Kuehn, K. S, Jake, X, Zhang, H., Browning, A., Riskin, E., Dey, A. K., & Mankoff, J.  Distress among undergraduates: Marginality, stressors and resilience supports. Journal of American College Health, 1-9. Stress and related mental health struggles are of growing concern at colleges and universities across the country and … Continue reading Distress and resilience among marginalized undergraduates

A quote from the paper

COVID-19 and Remote Learning for Students with Disabilities

Han Zhang, Margaret E. Morris, Paula S. Nurius, Kelly Mack, Jennifer Brown, Kevin S. Kuehn, Yasaman S. Sefidgar, Xuhai Xu, Eve A. Riskin, Anind K. Dey and Jennifer Mankoff. Impact of Online Learning in the Context of COVID-19 on Undergraduates with Disabilities and Mental Health Concerns. ACM Transactions on Accessible Computing (TACCESS). The COVID-19 pandemic … Continue reading COVID-19 and Remote Learning for Students with Disabilities

Practices and Needs of Mobile Sensing Researchers

Passive mobile sensing for the purpose of human state modeling is a fast-growing area. It has been applied to solve a wide range of behavior-related problems, including physical and mental health monitoring, affective computing, activity recognition, routine modeling, etc. However, in spite of the emerging literature that has investigated a wide range of application scenarios, … Continue reading Practices and Needs of Mobile Sensing Researchers

A lineplot showing anxiousness (Y axis, varying from 0 to 4) over time (X axis). Each student in the study is plotted as a different line over each day of the quarter. The plot overall looks very messy, but two things are clear; Every student has a very different trajectory from every other, with all of them going up and down multiple times. And the average, overall, shown is a fit line, is fairly low and slightly increasing (from about .75 to just under 1).

College during COVID

Mental health of UW students during Spring 2020 varied tremendously: the challenges of online learning during the pandemic were entwined with social isolation, family demands and socioeconomic pressures. In this context, individual differences in coping mechanisms had a big impact. The findings of this paper underline the need for interventions oriented towards problem-focused coping and … Continue reading College during COVID

Detecting Loneliness

Feelings of loneliness are associated with poor physical and mental health. Detection of loneliness through passive sensing on personal devices can lead to the development of interventions aimed at decreasing rates of loneliness. Doryab, Afsaneh, et al. “Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning … Continue reading Detecting Loneliness

Passively-sensing Discrimination

See the UW News article featuring this study! A deeper understanding of how discrimination impacts psychological health and well-being of students would allow us to better protect individuals at risk and support those who encounter discrimination. While the link between discrimination and diminished psychological and physical well-being is well established, existing research largely focuses on … Continue reading Passively-sensing Discrimination

Other publications:

Dutcher, J.M., Lederman, J., Jain, M., Price, S., Kumar, A., Villalba, D.K., Tumminia, M.J., Doryab, A., Cohen, S., Creswell, K.G., Mankoff, J., Dey, A., & Creswell, J.D. (In Press). Lack of Feelings of Belonging Predicts Depressive Symptomatology in College Students. Psychological Science.

Chikersal, P., Doryab, A., Tumminia, M., Villalba, D.K., Dutcher, J.M., Liu, X., Cohen, S., Creswell, K.G., Mankoff, J., Creswell, J.D., Goel, M., & Dey, A.K. (2021) Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing: A Machine Learning Approach With Robust Feature Selection. ACM Transactions on Computer-Human Interaction (TOCHI), 28, 1, Article 3 (January 2021).

Kuehn, K.S., Sefidgar, Y.S., Nurius, P., Browning, A., Riskin, E., Dey, A., & Mankoff, J. (October, 2019). Using Passive Data Monitoring and Machine Learning Algorithms to Examine Negative Affect and Coping Behaviors Among College Students Experiencing Suicidal Ideation. Paper presented at the 2019 IASR/AFSP International Summit on Suicide Research, Miami, FL.

A Tech-Forward Approach

UW EXP uses data from surveys, phones, Fitbits, and more to capture a comprehensive understanding of the UW student experience.


The UWEXP study is an expensive study to run. Our funders have been crucial to our success. Currently, the study is funded by internally by the College of Engineering (including the Department of Electrical and Computer Engineering and the Allen School of Computer Science and Engineering), Population Health Initiative, and Alcohol and Drug Abuse Institute. In addition, we have funding from the National Science Foundation; Samsung Advanced Institute of Technology; and Google.

Overview of Findings

UW EXP is analyzing data from 2018 to understand who reports discrimination and how micro-climates in the College of Engineering may correlate with lower stress and depression.

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