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Leung T, Vuillerme N. The Use of Passive Smartphone Data to Monitor Anxiety and Depression Among College Students in Real-World Settings: Protocol for a Systematic Review. JMIR Res Protoc 2022; 11:e38785. [PMID: 36515983 PMCID: PMC9798267 DOI: 10.2196/38785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 08/01/2022] [Accepted: 08/23/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND College students are particularly at risk of depression and anxiety. These disorders have a serious impact on public health and affect patients' daily lives. The potential for using smartphones to monitor these mental conditions, providing passively collected physiological and behavioral data, has been reported among the general population. However, research on the use of passive smartphone data to monitor anxiety and depression among specific populations of college students has never been reviewed. OBJECTIVE This review's objectives are (1) to provide an overview of the use of passive smartphone data to monitor depression and anxiety among college students, given their specific type of smartphone use and living setting, and (2) to evaluate the different methods used to assess those smartphone data, including their strengths and limitations. METHODS This review will follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Two independent investigators will review English-language, full-text, peer-reviewed papers extracted from PubMed and Web of Science that measure passive smartphone data and levels of depression or anxiety among college students. A preliminary search was conducted in February 2022 as a proof of concept. RESULTS Our preliminary search identified 115 original articles, 8 of which met our eligibility criteria. Our planned full study will include an article selection flowchart, tables, and figures representing the main information extracted on the use of passive smartphone data to monitor anxiety and depression among college students. CONCLUSIONS The planned review will summarize the published research on using passive smartphone data to monitor anxiety and depression among college students. The review aims to better understand whether and how passive smartphone data are associated with indicators of depression and anxiety among college students. This could be valuable in order to provide a digital solution for monitoring mental health issues in this specific population by enabling easier identification and follow-up of the patients. TRIAL REGISTRATION PROSPERO CRD42022316263; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=316263. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/38785.
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Affiliation(s)
| | - Nicolas Vuillerme
- AGEIS, Université Grenoble Alpes, Grenoble, France.,LabCom Telecom4Health, Orange Labs & Université Grenoble Alpes, CNRS, Inria, Grenoble INP-UGA, Grenoble, France.,Institut Universitaire de France, Paris, France
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Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. SENSORS 2022; 22:s22103893. [PMID: 35632301 PMCID: PMC9147201 DOI: 10.3390/s22103893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 05/16/2022] [Accepted: 05/19/2022] [Indexed: 12/10/2022]
Abstract
Recent years have seen significant advances in the sensing capabilities of smartphones, enabling them to collect rich contextual information such as location, device usage, and human activity at a given point in time. Combined with widespread user adoption and the ability to gather user data remotely, smartphone-based sensing has become an appealing choice for health research. Numerous studies over the years have demonstrated the promise of using smartphone-based sensing to monitor a range of health conditions, particularly mental health conditions. However, as research is progressing to develop the predictive capabilities of smartphones, it becomes even more crucial to fully understand the capabilities and limitations of using this technology, given its potential impact on human health. To this end, this paper presents a narrative review of smartphone-sensing literature from the past 5 years, to highlight the opportunities and challenges of this approach in healthcare. It provides an overview of the type of health conditions studied, the types of data collected, tools used, and the challenges encountered in using smartphones for healthcare studies, which aims to serve as a guide for researchers wishing to embark on similar research in the future. Our findings highlight the predominance of mental health studies, discuss the opportunities of using standardized sensing approaches and machine-learning advancements, and present the trends of smartphone sensing in healthcare over the years.
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Nguyen B, Torres A, Sim W, Kenny D, Campbell DM, Beavers L, Lou W, Kapralos B, Peter E, Dubrowski A, Krishnan S, Bhat V. Digital Interventions to Reduce Distress Among Health Care Providers at the Frontline: Protocol for a Feasibility Trial. JMIR Res Protoc 2021; 11:e32240. [PMID: 34871178 PMCID: PMC8852627 DOI: 10.2196/32240] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/20/2021] [Accepted: 11/22/2021] [Indexed: 12/16/2022] Open
Abstract
Background Stress, anxiety, distress, and depression are high among health care workers during the COVID-19 pandemic, and they have reported acting in ways that are contrary to their moral values and professional commitments that degrade their integrity. This creates moral distress and injury due to constraints they have encountered, such as limited resources. Objective The purpose of this study is to develop and show the feasibility of digital platforms (a virtual reality and a mobile platform) to understand the causes and ultimately reduce the moral distress of health care providers during the COVID-19 pandemic. Methods This will be a prospective, single cohort, pre- and posttest study examining the effect of a brief informative video describing moral distress on perceptual, psychological, and physiological indicators of stress and decision-making during a scenario known to potentially elicit moral distress. To accomplish this, we have developed a virtual reality simulation that will be used before and after the digital intervention for monitoring short-term impacts. The simulation involves an intensive care unit setting during the COVID-19 pandemic, and participants will be placed in morally challenging situations. The participants will be engaged in an educational intervention at the individual, team, and organizational levels. During each test, data will be collected for (1) physiological measures of stress and after each test, data will be collected regarding (2) thoughts, feelings and behaviors during a morally challenging situation, and (3) perceptual estimates of psychological stress. In addition, participants will continue to be monitored for moral distress and other psychological stresses for 8 weeks through our Digital intervention/intelligence Group mobile platform. Finally, a comparison will be conducted using machine learning and biostatistical techniques to analyze the short- and long-term impacts of the virtual reality intervention. Results The study was funded in November 2020 and received research ethics board approval in March 2021. The study is ongoing. Conclusions This project is a proof-of-concept integration to demonstrate viability over 6 months and guide future studies to develop these state-of-the-art technologies to help frontline health care workers work in complex moral contexts. In addition, the project will develop innovations that can be used for future pandemics and in other contexts prone to producing moral distress and injury. This project aims to demonstrate the feasibility of using digital platforms to understand the continuum of moral distress that can lead to moral injury. Demonstration of feasibility will lead to future studies to examine the efficacy of digital platforms to reduce moral distress. Trial Registration ClinicalTrials.gov NCT05001542; https://clinicaltrials.gov/ct2/show/NCT05001542 International Registered Report Identifier (IRRID) DERR1-10.2196/32240
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Affiliation(s)
- Binh Nguyen
- Department of Electrical, Computer, and Biomedical Engineering, Ryerson University, Toronto, CA
| | - Andrei Torres
- maxSIMhealth Group, Ontario Tech University, 2000 Simcoe St N, Oshawa, CA
| | - Walter Sim
- Interventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, 193 Yonge Street, Suite 6-013, Toronto, CA
| | - Deborah Kenny
- Department of Nursing, University of Colorado, Colorado Springs, US
| | - Douglas M Campbell
- Neonatal Intensive Care Unit, St. Michael's Hospital, Unity Health Toronto, Toronto, CA.,Allan Waters Family Simulation Program, St. Michael's Hospital, Unity Health Toronto, Toronto, CA.,Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, CA.,Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, CA
| | - Lindsay Beavers
- Allan Waters Family Simulation Program, St. Michael's Hospital, Unity Health Toronto, Toronto, CA.,Department of Physical Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, CA
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, CA
| | - Bill Kapralos
- maxSIMhealth Group, Ontario Tech University, 2000 Simcoe St N, Oshawa, CA
| | - Elizabeth Peter
- Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, CA
| | - Adam Dubrowski
- maxSIMhealth Group, Ontario Tech University, 2000 Simcoe St N, Oshawa, CA
| | - Sridhar Krishnan
- Department of Electrical, Computer, and Biomedical Engineering, Ryerson University, Toronto, CA
| | - Venkat Bhat
- Interventional Psychiatry Program, St. Michael's Hospital, Unity Health Toronto, 193 Yonge Street, Suite 6-013, Toronto, CA.,Department of Psychiatry, University of Toronto, Toronto, CA
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