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Ilyas Y, Hassanbeigi Daryani S, Kiriella D, Pachwicewicz P, Boley RA, Reyes KM, Smith DL, Zalta AK, Schueller SM, Karnik NS, Stiles-Shields C. Geolocation Patterns, Wi-Fi Connectivity Rates, and Psychiatric Symptoms amongst Urban Homeless Youth Using Self-Report and Smartphone Data: Pilot Study (Preprint). JMIR Form Res 2022; 7:e45309. [PMID: 37071457 PMCID: PMC10155082 DOI: 10.2196/45309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/17/2023] [Accepted: 03/06/2023] [Indexed: 03/08/2023] Open
Abstract
BACKGROUND Despite significant research done on youth experiencing homelessness, few studies have examined movement patterns and digital habits in this population. Examining these digital behaviors may provide useful data to design new digital health intervention models for youth experiencing homelessness. Specifically, passive data collection (data collected without extra steps for a user) may provide insights into lived experience and user needs without putting an additional burden on youth experiencing homelessness to inform digital health intervention design. OBJECTIVE The objective of this study was to explore patterns of mobile phone Wi-Fi usage and GPS location movement among youth experiencing homelessness. Additionally, we further examined the relationship between usage and location as correlated with depression and posttraumatic stress disorder (PTSD) symptoms. METHODS A total of 35 adolescent and young adult participants were recruited from the general community of youth experiencing homelessness for a mobile intervention study that included installing a sensor data acquisition app (Purple Robot) for up to 6 months. Of these participants, 19 had sufficient passive data to conduct analyses. At baseline, participants completed self-reported measures for depression (Patient Health Questionnaire-9 [PHQ-9]) and PTSD (PTSD Checklist for DSM-5 [PCL-5]). Behavioral features were developed and extracted from phone location and usage data. RESULTS Almost all participants (18/19, 95%) used private networks for most of their noncellular connectivity. Greater Wi-Fi usage was associated with a higher PCL-5 score (P=.006). Greater location entropy, representing the amount of variability in time spent across identified clusters, was also associated with higher severity in both PCL-5 (P=.007) and PHQ-9 (P=.045) scores. CONCLUSIONS Location and Wi-Fi usage both demonstrated associations with PTSD symptoms, while only location was associated with depression symptom severity. While further research needs to be conducted to establish the consistency of these findings, they suggest that the digital patterns of youth experiencing homelessness offer insights that could be used to tailor digital interventions.
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Affiliation(s)
- Yousaf Ilyas
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
| | | | - Dona Kiriella
- School of Medicine, City University of New York, New York, NY, United States
| | - Paul Pachwicewicz
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Randy A Boley
- Institute for Juvenile Research, Department of Psychiatry, College of Medicine, University of Illinois Chicago, Chicago, IL, United States
- Center for Health Equity using Machine Learning and Artificial Intelligence (CHEMA), College of Medicine, University of Illinois Chicago, Chicago, IL, United States
| | - Karen M Reyes
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Dale L Smith
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
- Institute for Juvenile Research, Department of Psychiatry, College of Medicine, University of Illinois Chicago, Chicago, IL, United States
- Center for Health Equity using Machine Learning and Artificial Intelligence (CHEMA), College of Medicine, University of Illinois Chicago, Chicago, IL, United States
| | - Alyson K Zalta
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
- Department of Psychological Science, School of Social Ecology, University of California Irvine, Irvine, CA, United States
| | - Stephen M Schueller
- Department of Psychological Science, School of Social Ecology, University of California Irvine, Irvine, CA, United States
| | - Niranjan S Karnik
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
- Institute for Juvenile Research, Department of Psychiatry, College of Medicine, University of Illinois Chicago, Chicago, IL, United States
- Center for Health Equity using Machine Learning and Artificial Intelligence (CHEMA), College of Medicine, University of Illinois Chicago, Chicago, IL, United States
| | - Colleen Stiles-Shields
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
- Institute for Juvenile Research, Department of Psychiatry, College of Medicine, University of Illinois Chicago, Chicago, IL, United States
- Center for Health Equity using Machine Learning and Artificial Intelligence (CHEMA), College of Medicine, University of Illinois Chicago, Chicago, IL, United States
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