JMIR Research Protocols (May 2024)

Digital Interventions to Understand and Mitigate Stress Response: Protocol for Process and Content Evaluation of a Cohort Study

  • Josh Martin,
  • Alice Rueda,
  • Gyu Hee Lee,
  • Vanessa K Tassone,
  • Haley Park,
  • Martin Ivanov,
  • Benjamin C Darnell,
  • Lindsay Beavers,
  • Douglas M Campbell,
  • Binh Nguyen,
  • Andrei Torres,
  • Hyejung Jung,
  • Wendy Lou,
  • Anthony Nazarov,
  • Andrea Ashbaugh,
  • Bill Kapralos,
  • Brett Litz,
  • Rakesh Jetly,
  • Adam Dubrowski,
  • Gillian Strudwick,
  • Sridhar Krishnan,
  • Venkat Bhat

DOI
https://doi.org/10.2196/54180
Journal volume & issue
Vol. 13
p. e54180

Abstract

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BackgroundStaffing and resource shortages, especially during the COVID-19 pandemic, have increased stress levels among health care workers. Many health care workers have reported feeling unable to maintain the quality of care expected within their profession, which, at times, may lead to moral distress and moral injury. Currently, interventions for moral distress and moral injury are limited. ObjectiveThis study has the following aims: (1) to characterize and reduce stress and moral distress related to decision-making in morally complex situations using a virtual reality (VR) scenario and a didactic intervention; (2) to identify features contributing to mental health outcomes using wearable, physiological, and self-reported questionnaire data; and (3) to create a personal digital phenotype profile that characterizes stress and moral distress at the individual level. MethodsThis will be a single cohort, pre- and posttest study of 100 nursing professionals in Ontario, Canada. Participants will undergo a VR simulation that requires them to make morally complex decisions related to patient care, which will be administered before and after an educational video on techniques to mitigate distress. During the VR session, participants will complete questionnaires measuring their distress and moral distress, and physiological data (electrocardiogram, electrodermal activity, plethysmography, and respiration) will be collected to assess their stress response. In a subsequent 12-week follow-up period, participants will complete regular assessments measuring clinical outcomes, including distress, moral distress, anxiety, depression, and loneliness. A wearable device will also be used to collect continuous data for 2 weeks before, throughout, and for 12 weeks after the VR session. A pre-post comparison will be conducted to analyze the effects of the VR intervention, and machine learning will be used to create a personal digital phenotype profile for each participant using the physiological, wearable, and self-reported data. Finally, thematic analysis of post-VR debriefing sessions and exit interviews will examine reoccurring codes and overarching themes expressed across participants’ experiences. ResultsThe study was funded in 2022 and received research ethics board approval in April 2023. The study is ongoing. ConclusionsIt is expected that the VR scenario will elicit stress and moral distress. Additionally, the didactic intervention is anticipated to improve understanding of and decrease feelings of stress and moral distress. Models of digital phenotypes developed and integrated with wearables could allow for the prediction of risk and the assessment of treatment responses in individuals experiencing moral distress in real-time and naturalistic contexts. This paradigm could also be used in other populations prone to moral distress and injury, such as military and public safety personnel. Trial RegistrationClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398 International Registered Report Identifier (IRRID)DERR1-10.2196/54180