Breaking Isolation: Self Care for When Coronavirus Quarantine Ends

This brief describes how prolonged periods of solitude affect our mental health and provides some strategies for how we can protect our mental and emotional health as we reengage with society

Why Monitoring your Media Consumption during COVID-19 is Important

Are you spending more time consuming media (news, television, video games) than before COVID-19? Social distancing and stay-at-home orders have led to a surge in media consumption. This brief explains how too much media consumption (including the news) can affect your psychological and physiological wellbeing and provides strategies for monitoring your media consumption

"Reading Between the Heat": Co-Teaching Body Thermal Signatures for Non-intrusive Stress Detection

Stress impacts our physical and mental health as well as our social life. A passive and contactless indoor stress monitoring system can unlock numerous important applications such as workplace productivity assessment, smart homes, and personalized mental health monitoring. While the thermal signatures from a user's body captured by a thermal camera can provide important information about the "fight-flight" response of the sympathetic and parasympathetic nervous system, relying solely on thermal imaging for training a stress prediction model often lead to overfitting and consequently a suboptimal performance. This paper addresses this challenge by introducing ThermaStrain, a novel co-teaching framework that achieves high-stress prediction performance by transferring knowledge from the wearable modality to the contactless thermal modality. During training, ThermaStrain incorporates a wearable electrodermal activity (EDA) sensor to generate stress-indicative representations from thermal videos, emulating stress-indicative representations from a wearable EDA sensor. During testing, only thermal sensing is used, and stress-indicative patterns from thermal data and emulated EDA representations are extracted to improve stress assessment. The study collected a comprehensive dataset with thermal video and EDA data under various stress conditions and distances. ThermaStrain achieves an F1 score of 0.8293 in binary stress classification, outperforming the thermal-only baseline approach by over 9%. Extensive evaluations highlight ThermaStrain's effectiveness in recognizing stress-indicative attributes, its adaptability across distances and stress scenarios, real-time executability on edge platforms, its applicability to multi-individual sensing, ability to function on limited visibility and unfamiliar conditions, and the advantages of its co-teaching approach.Comment: 29 page

The Daily Patterns of Emergency Medical Events

This study examines population level daily patterns of time-stamped emergency medical service (EMS) dispatches to establish their situational predictability. Using visualization, sinusoidal regression, and statistical tests to compare empirical cumulative distributions, we analyzed 311,848,450 emergency medical call records from the U.S. National Emergency Medical Services Information System (NEMSIS) for years 2010 through 2022. The analysis revealed a robust daily pattern in the hourly distribution of distress calls across 33 major categories of medical emergency dispatch types. Sinusoidal regression coefficients for all types were statistically significant, mostly at the p \u3c 0.0001 level. The coefficient of determination ($R^2$) ranged from 0.84 and 0.99 for all models, with most falling in the 0.94 to 0.99 range. The common sinusoidal pattern, peaking in mid-afternoon, demonstrates that all major categories of medical emergency dispatch types appear to be influenced by an underlying daily rhythm that is aligned with daylight hours and common sleep/wake cycles. A comparison of results with previous landmark studies revealed new and contrasting EMS patterns for several long-established peak occurrence hours--specifically for chest pain, heart problems, stroke, convulsions and seizures, and sudden cardiac arrest/death. Upon closer examination, we also found that heart attacks, diagnosed by paramedics in the field via 12-lead cardiac monitoring, followed the identified common daily pattern of a mid-afternoon peak, departing from prior generally accepted morning tendencies. Extended analysis revealed that the normative pattern prevailed across the NEMSIS data when re-organized to consider monthly, seasonal, daylight-savings vs civil time, and pre-/post- COVID-19 periods. The predictable daily EMS patterns provide impetus for more research that links daily variation with causal risk and protective factors. Our methods are straightforward and presented with detail to provide accessible and replicable implementation for researchers and practitioners

Culturally congruent mentorship can reduce disruptive behavior among elementary school students: results from a pilot study

Abstract Background Our study objective was to examine the feasibility of implementing a culturally congruent mentorship pilot program, Youth-First (YF), that targets behavior modification among elementary school-aged children with disruptive behavior and a history of school suspension. We hypothesize that it is feasible to implement the YF program to reduce disruptive behaviors and recidivism of level III/IV infractions in school settings among at-risk African American students. Methods We assessed program feasibility based on the success of program acceptance by parents/guardians, study enrollment, and intervention compliance by students. A pre/posttest study design was used to examine whether the YF program reduced recidivism of disruptive behavior among enrolled at-risk African American elementary school children between September 2016 and January 2017. Generalized linear mixed models examined whether student behavioral scores improved over time and varied by program mentor. A McNemar test examined the reduction in cumulative incidence of level III/IV infractions pre-post YF program intervention. Results Intervention acceptance, enrollment, and compliance were 100% (95% confidence interval [CI] 86 to 100%), 100% (95% CI 86 to 100%), and 67% (95% CI 45 to 84%), respectively (N = 24). Overall, student behavioral scores improved and plateaued over time (Time2 effect: b = − 0.01, 95% CI − 0.02, < 0.01); a two-week period was associated with a seven-point improvement (effect size: Cohen’s d = 0.47, 95% CI 0.03, 0.94) in behavioral scores. Behavioral score improvements were class-specific, based on respectfulness behavior (b = 0.11, 95% CI < 0.01, 0.26). No recidivism of level III/IV infractions was reported during and post YF intervention. Conclusion The integration of culturally congruent mentorship in elementary school-settings is feasible and can reduce risk of disruptive behaviors among at-risk African American students. Future studies should use randomized clinical trials to determine the effectiveness of culturally congruent mentorship interventions (void of potential selection and confounding biases) in reducing disruptive behavior, level III/IV infractions, and school suspensions among at-risk children