Geolocation Patterns, Wi-Fi Connectivity Rates, and Psychiatric Symptoms Among Urban Homeless Youth: Mixed Methods Study Using Self-report and Smartphone Data

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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.

Related collections

Most cited references 41

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The PHQ-9: validity of a brief depression severity measure.

K Kroenke, R L Spitzer, J. Williams (2001)

While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.

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Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support

Inbal Nahum-Shani, Shawna Smith, Bonnie J Spring … (2017)

Background The just-in-time adaptive intervention (JITAI) is an intervention design aiming to provide the right type/amount of support, at the right time, by adapting to an individual’s changing internal and contextual state. The availability of increasingly powerful mobile and sensing technologies underpins the use of JITAIs to support health behavior, as in such a setting an individual’s state can change rapidly, unexpectedly, and in his/her natural environment. Purpose Despite the increasing use and appeal of JITAIs, a major gap exists between the growing technological capabilities for delivering JITAIs and research on the development and evaluation of these interventions. Many JITAIs have been developed with minimal use of empirical evidence, theory, or accepted treatment guidelines. Here, we take an essential first step towards bridging this gap. Methods Building on health behavior theories and the extant literature on JITAIs, we clarify the scientific motivation for JITAIs, define their fundamental components, and highlight design principles related to these components. Examples of JITAIs from various domains of health behavior research are used for illustration. Conclusions As we enter a new era of technological capacity for delivering JITAIs, it is critical that researchers develop sophisticated and nuanced health behavior theories capable of guiding the construction of such interventions. Particular attention has to be given to better understanding the implications of providing timely and ecologically sound support for intervention adherence and retention We clarify the scientific motivation for the Just-In-Time Adaptive Interventions, define its fundamental components, and discuss key design principles for each component.

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Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study

Sohrab Saeb, Mi Zhang, Christopher Karr … (2015)

Background Depression is a common, burdensome, often recurring mental health disorder that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an increasingly large complement of sensors that can potentially be useful in monitoring behavioral patterns that might be indicative of depressive symptoms. Objective The objective of this study was to explore the detection of daily-life behavioral markers using mobile phone global positioning systems (GPS) and usage sensors, and their use in identifying depressive symptom severity. Methods A total of 40 adult participants were recruited from the general community to carry a mobile phone with a sensor data acquisition app (Purple Robot) for 2 weeks. Of these participants, 28 had sufficient sensor data received to conduct analysis. At the beginning of the 2-week period, participants completed a self-reported depression survey (PHQ-9). Behavioral features were developed and extracted from GPS location and phone usage data. Results A number of features from GPS data were related to depressive symptom severity, including circadian movement (regularity in 24-hour rhythm; r=-.63, P=.005), normalized entropy (mobility between favorite locations; r=-.58, P=.012), and location variance (GPS mobility independent of location; r=-.58, P=.012). Phone usage features, usage duration, and usage frequency were also correlated (r=.54, P=.011, and r=.52, P=.015, respectively). Using the normalized entropy feature and a classifier that distinguished participants with depressive symptoms (PHQ-9 score ≥5) from those without (PHQ-9 score <5), we achieved an accuracy of 86.5%. Furthermore, a regression model that used the same feature to estimate the participants’ PHQ-9 scores obtained an average error of 23.5%. Conclusions Features extracted from mobile phone sensor data, including GPS and phone usage, provided behavioral markers that were strongly related to depressive symptom severity. While these findings must be replicated in a larger study among participants with confirmed clinical symptoms, they suggest that phone sensors offer numerous clinical opportunities, including continuous monitoring of at-risk populations with little patient burden and interventions that can provide just-in-time outreach.

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Author and article information

Contributors

Colleen Stiles-Shields:

ORCID: https://orcid.org/0000-0002-6759-8380

Institute for Juvenile ResearchDepartment of Psychiatry, College of MedicineUniversity of Illinois Chicago1747 West Roosevelt RoadChicago, IL, 60608United States1 3122730185ecss@uic.edu

Journal

Journal ID (nlm-ta): JMIR Form Res

Journal ID (iso-abbrev): JMIR Form Res

Journal ID (publisher-id): JFR

Title: JMIR Formative Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Electronic): 2561-326X

Publication date Collection: 2023

Publication date (Electronic): 18 April 2023

Volume: 7

Electronic Location Identifier: e45309

Affiliations

[1 ] Department of Psychiatry and Behavioral Sciences Rush University Medical Center Chicago, IL United States

[2 ] Rush Medical College Rush University Chicago, IL United States

[3 ] School of Medicine City University of New York New York, NY United States

[4 ] Institute for Juvenile Research Department of Psychiatry, College of Medicine University of Illinois Chicago Chicago, IL United States

[5 ] Center for Health Equity using Machine Learning and Artificial Intelligence (CHEMA) College of Medicine University of Illinois Chicago Chicago, IL United States

[6 ] Department of Psychological Science School of Social Ecology University of California Irvine Irvine, CA United States

Author notes

Corresponding Author: Colleen Stiles-Shields ecss@ 123456uic.edu

Author information

Yousaf Ilyas https://orcid.org/0000-0002-5611-8054

Shahrzad Hassanbeigi Daryani https://orcid.org/0000-0001-5802-7984

Dona Kiriella https://orcid.org/0000-0001-7280-4743

Paul Pachwicewicz https://orcid.org/0000-0002-9285-4921

Randy A Boley https://orcid.org/0000-0002-9365-8412

Karen M Reyes https://orcid.org/0000-0003-0078-3060

Dale L Smith https://orcid.org/0000-0003-0854-9973

Alyson K Zalta https://orcid.org/0000-0002-5159-8431

Stephen M Schueller https://orcid.org/0000-0002-1003-0399

Niranjan S Karnik https://orcid.org/0000-0001-7650-3008

Colleen Stiles-Shields https://orcid.org/0000-0002-6759-8380

Article

Publisher ID: v7i1e45309

DOI: 10.2196/45309

PMC ID: 10155082

PubMed ID: 37071457

SO-VID: dd447126-9b42-4b08-898b-58ed25316485

Copyright © ©Yousaf Ilyas, Shahrzad Hassanbeigi Daryani, Dona Kiriella, Paul Pachwicewicz, Randy A Boley, Karen M Reyes, Dale L Smith, Alyson K Zalta, Stephen M Schueller, Niranjan S Karnik, Colleen Stiles-Shields. Originally published in JMIR Formative Research (https://formative.jmir.org), 18.04.2023.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

History

Date received : 23 December 2022

Date revision requested : 29 January 2023

Date revision received : 17 February 2023

Date accepted : 6 March 2023

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