Development of a data-driven digital phenotype profile of distress experience of healthcare workers during COVID-19 pandemic.

BACKGROUND AND OBJECTIVE: Due to the constraints of the COVID-19 pandemic, healthcare workers have reported acting in ways that are contrary to their moral values, and this may result in moral distress. This paper proposes the novel digital phenotype profile (DPP) tool, developed specifically to evaluate stress experiences within participants. The DPP tool was evaluated using the COVID-19 VR Healthcare Simulation of Stress Experience (HSSE) dataset (NCT05001542), which is composed of passive physiological signals and active mental health questionnaires. The DPP tool focuses on correlating electrocardiogram, respiration, photoplethysmography, and galvanic skin response with moral injury outcome scale (Brief MIOS). METHODS: Data-driven techniques are encompassed to develop a tool for robust evaluation of distress among participants. To accomplish this, we applied pre-processing techniques which involved normalization, data sanitation, segmentation, and windowing. During feature analysis, we extracted domain-specific features, followed by feature selection techniques to rank the importance of the feature set. Prior to classification, we employed k-means clustering to group the Brief MIOS scores to low, moderate, and high moral distress as the Brief MIOS lacks established severity cut-off scores. Support vector machine and decision tree models were used to create machine learning models to predict moral distress severities. RESULTS: Weighted support vector machine with leave-one-subject-out-cross-validation evaluated the separation of the Brief MIOS scores and achieved an average accuracy, precision, sensitivity, and F1 of 98.67%, 98.83%, 99.44%, and 99.13%, respectively. Various machine learning ablation tests were performed to support our results and further enhance the understanding of the predictive model. CONCLUSION: Our findings demonstrate the feasibility to develop a DPP tool to predict distress experiences using a combination of mental health questionnaires and passive signals. The DPP tool is the first of its kind developed from the analysis of the HSSE dataset. Additional validation is needed for the DPP tool through replication in larger sample sizes.

Association of COVID-19 Government-Instituted Mask Mandates With Incidence of Mask Use Among Children in Alberta, Canada.

Importance: To help prevent the spread of SARS-CoV-2, government-instituted nonpharmaceutical interventions (eg, social distancing, mask use, isolating), a provincewide government-instituted mask mandate occurred on December 8, 2020, in Alberta, Canada, although some local jurisdictions implemented an earlier mask mandate. There remains a limited understanding of the association between government-implemented public health measures and individual health behaviors of children. Objective: To examine the association between government mask mandates and mask use among children in Alberta, Canada. Design, Setting, and Participants: A cohort of children from Alberta, Canada, was recruited to examine longitudinal SARS-CoV-2 serologic factors. Parents were prospectively asked about their child's mask use in public places every 3 months (5-point Likert scale: never to always) from August 14, 2020, to June 24, 2022. A multivariable logistic generalized estimating equation was used to examine government mandatory masking mandates and child mask use. Child mask use was operationalized into a single composite dichotomous outcome by grouping parents who reported their child often or always wore a mask vs those who reported their child never, rarely, or occasionally wore a mask. Exposures: The primary exposure variable was the government masking mandate (began on different dates in 2020). The secondary exposure variable was government private indoor and outdoor gathering restrictions. Main Outcomes and Measures: The primary outcome was parent report of child mask use. Results: A total of 939 children participated (467 female [49.7%]; mean [SD] age, 10.61 [1.6] years). The odds of parents' report of child mask use (often or always) was 18.3 times higher (95% CI, 5.7-58.6; P < .001; risk ratio, 1.7; 95% CI, 1.5-1.8; P < .001) with the mask mandate on compared with the mask mandate off. There was no significant change in mask use over the course of the mask mandate due to time. In contrast, each day with the mask mandate off was associated with a 1.6% decrease in mask use (odds ratio, 0.98; 95% CI, 0.98-0.99; P < .001). Conclusions and Relevance: The results of this study suggest that government-mandated mask use and providing the public with up-to-date health information (eg, case counts) is associated with increased parent-reported child mask use, while increasing time without a mask mandate is associated with decreased mask use.

Digital Interventions to Reduce Distress Among Health Care Providers at the Frontline: Protocol for a Feasibility Trial.

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.

The Impact of COVID-19 on a Large, Canadian Community Emergency Department.

INTRODUCTION: As the COVID-19 pandemic unfolded, emergency departments (EDs) across the world braced for surges in volume and demand. However, many EDs experienced decreased demand even for higher acuity illnesses. In this study we sought to examine the change in utilization at a large Canadian community ED, including changes in patient demographics and presentations, as well as structural and administrative changes made in response to the pandemic. METHODS: This retrospective observational study took place in Ontario, Canada, from March 17-June 30, 2020, during province-wide lockdowns in response to COVID-19. We used a control period of March 17-June 30 in 2018-2019. Differences between observed and expected values were calculated for total visits, Canadian Triage and Acuity Scale (CTAS) groups, and age groups using Fisher's exact test. Length of stay (LOS), physician initial assessment time (PIA), and top primary and admission diagnoses were also examined. RESULTS: Patient visits fell to 66.3% of expected volume in the exposure period (20,901 vs 31,525, P<0.0001). CTAS-1 (highest acuity) patient volumes dropped to 86.8% of expected (P = 0.1964) while CTAS-5 (lowest acuity) patient volumes dropped to 32.4% of expected (P <0.0001). Youth (0-17), adult (18-64), and senior (65+) visits all decreased to 37.4%, 71.7%, and 72.9% of expected volumes, respectively (P <0.0001). Median PIA and median ED LOS both decreased (1.1 to 0.6 hours and 3.3 to 3.0 hours, respectively). The most common primary diagnosis in both periods was "other chest pain." Viral syndromes were more prevalent in the exposure period. The top admission diagnoses were congestive heart failure in the control period (4.8%) and COVID-19 in the study period (3.5%). CONCLUSION: ED utilization changed drastically during COVID-19. Our ED responded with wide stakeholder engagement, spatial reorganization, and human resources changes informed by real-time data. Our experiences can help prepare for potential subsequent "waves" of COVID-19 and future pandemics.