Pre-pandemic electrodermal activity predicts current COVID-related fears: household size during lockdown as a moderating factor

Adaptive thresholding increases sensitivity to detect changes in the rate of skin conductance responses to psychologically arousing stimuli in both laboratory and ambulatory settings

Psychophysiologists recording electrodermal activity (EDA) often derive measures of slow, tonic activity-skin conductance level (SCL)-and faster, more punctate changes-skin conductance responses (SCRs). A SCR is conventionally considered to have occurred when the local amplitude of the EDA signal exceeds a researcher-determined threshold (e.g., 0.05 μS), typically fixed across study participants and conditions. However, fixed SCR thresholds can preferentially exclude data from individuals with low SCL because their SCRs are smaller on average, thereby reducing statistical power for group-level analyses. Thus, we developed a fixed plus adaptive (FA) thresholding method that adjusts identification of SCRs based on an individual's SC at the onset of the SCR to increase statistical power and include data from more participants. We assess the utility of applying FA thresholding across two independent samples and explore age and race-related associations with EDA outcomes. Study 1 uses wired EDA measurements from 254 healthy adults responding to evocative images and sounds in a laboratory setting. Study 2 uses wireless EDA measurements from 20 children with autism in a clinical environment while they completed behavioral tasks. Compared to a 0.01, 0.03, and 0.05 μS fixed threshold, FA thresholding at 1.9% modestly increases statistical power to detect a difference in SCR rate between tasks with higher vs. lower subjective arousal and reduces exclusion of participants by up to 5% across both samples. This novel method expands the EDA analytical toolbox and may be useful in populations with highly variable basal SCL or when comparing groups with different basal SCL. Future research should test for reproducibility and generalizability in other tasks, samples, and contexts. IMPACT STATEMENTS: This article is important because it introduces a novel method to enhance sensitivity and statistical power in analyses of skin conductance responses from electrodermal data.

Sociodemographic effects on pandemic fatigue are multifaceted and context-specific: A longitudinal analysis of physical distancing adherence

Background

Pandemic fatigue emerged early during the COVID-19 pandemic and remains a concern as new variants emerge and ongoing public health measures are needed to control them. A wide range of factors can affect pandemic fatigue, but empiric research indicating which may be most important to adherence in specific populations is lacking.

Design & Methods

We conducted a longitudinal study of changes in physical distancing in two cohorts: adults living with children <18 years and adults ≥50 years old. Six types of non-work, non-household contacts were ascertained at six times from April to October 2020. We used generalized estimating equations Poisson regression to estimate the one-week change in contact rate and how this differed based on sociodemographic characteristics.

Results

The rate of all contact types increased during the middle of the study period and decreased toward the end. Changes in contact rates over time differed according to several sociodemographic characteristics, including age, gender, race/ethnicity, education, household composition, and access to transportation. Furthermore, the factors influencing the rate of change in contact rates differed by the type or setting of the contact, for example contacts as a result of visiting another person's home versus during a retail outing.

Conclusions

These results provide evidence for potential mechanisms by which pandemic fatigue has resulted in lower physical distancing adherence.

Happiness before and during the COVID-19 pandemic in Italy: A population-based longitudinal study

The aims of the present study were to investigate (1) whether the COVID-19 pandemic and the restrictive measures to control its spread were associated with changes in happiness before and after the pandemic and (2) whether household size, living with a partner/spouse, living with at least one son/daughter, financial support, income loss, and job loss following the pandemic were associated with happiness after controlling for previous levels of happiness. We use data from the Italian Survey on Household Income and Wealth (SHIW). Specifically, we used longitudinal data from 2283 respondents who participated in the SHIW 2016 and SHIW 2020. Results revealed a small but significant increase in happiness from 2016 to 2021. In addition, living with a partner/spouse predicted higher happiness with a medium effect size, and total income loss predicted lower happiness with a small to medium effect size. Household size, living with at least one son/daughter, financial support, partial income loss, and job loss following the pandemic were unrelated to happiness.

EmotIoT: An IoT System to Improve Users’ Wellbeing

IoT provides applications and possibilities to improve people’s daily lives and business environments. However, most of these technologies have not been exploited in the field of emotions. With the amount of data that can be collected through IoT, emotions could be detected and anticipated. Since the study of related works indicates a lack of methodological approaches in designing IoT systems from the perspective of emotions and smart adaption rules, we introduce a methodology that can help design IoT systems quickly in this scenario, where the detection of users is valuable. In order to test the methodology presented, we apply the proposed stages to design an IoT smart recommender system named EmotIoT. The system allows anticipating and predicting future users’ emotions using parameters collected from IoT devices. It recommends new activities for the user in order to obtain a final state. Test results validate our recommender system as it has obtained more than 80% accuracy in predicting future user emotions.