Public Attitudes to Immigration in the Aftermath of COVID-19: Little Change in Policy Preferences, Big Drops in Issue Salience: IMR

How has the COVID-19 pandemic affected public attitudes toward immigration? Long-term evidence in Europe and the United States suggests attitudes to immigration are relatively stable and, in some cases, becoming more favorable with high volatility instead of the perceived importance of the issue. However, theoretically a global pandemic could exacerbate people's fears of outsiders or that migration may contribute to the disease. By contrast, attitudes could remain stable if their distal drivers prove to be robust enough to withstand the shock of COVID-19. We draw from Eurobarometer data from 2014 to 2021 across 28 European countries, weekly national survey data during the outbreak from the United States and individual panel data from the United Kingdom and Germany to find little systematic change in immigration preferences and no country-level correlation between the observed changes and the outbreak's severity. Instead, the perceived importance of immigration has consistently and significantly decreased. These findings suggest that, if COVID-19 is to have an impact on attitudes to migration, it is likely to emerge via longer-term means, such as early-life socialization and value change, rather than reactions to the immediate pandemic shock.

Adaptations to a cohort study in response to the COVID-19 pandemic: insights from Growing Up in Ireland.

Growing Up in Ireland (GUI) is the national longitudinal study of children and young people in the Republic of Ireland and has followed two cohorts for over ten years to date: Cohort '98 who were recruited into the study at age nine years and Cohort '08, recruited at age nine months. The study aims to describe the lives of Irish children and young people in terms of their development, with a view to positively affecting policies and services available for them. Traditionally, data collection involved in-home visits from an interviewer who conducted face-to-face interviews, recorded physical measurements of study participants and administered cognitive assessments. However, with the onset of the COVID-19 pandemic and the associated restrictions, significant adaptations were required to these methods to ensure data collection for the pilot and main fieldwork for Cohort '08 at age 13 could continue to the expected timeline. Face-to-face interviews with participants were replaced with telephone and web-based modes, interviewer training was conducted online, online resources were made available for interviewers and participants and COVID-19 related items were added to questionnaires. In addition to the scheduled data collection, a special COVID-19 survey was also conducted on both GUI cohorts in December 2020 to explore the impact of the pandemic on participants' lives. This paper outlines the adaptations made to traditional data collection methods in GUI, highlighting the challenges that were met, but also the benefits of some changes that may be worth incorporating into future waves of GUI.

Trajectories of internalizing symptoms among autistic and nonautistic youth during the COVID-19 pandemic.

The COVID-19 pandemic elicited increases in anxiety and depression in youth, and youth on the autism spectrum demonstrate elevations in such symptoms pre-pandemic. However, it is unclear whether autistic youth experienced similar increases in internalizing symptoms after the COVID-19 pandemic onset or whether decreases in these symptoms were present, as speculated in qualitative work. In the current study, longitudinal changes in anxiety and depression during the COVID-19 pandemic in autistic youth were assessed in comparison to nonautistic youth. A well-characterized sample of 51 autistic and 25 nonautistic youth (ageM = 12.8, range = 8.5-17.4 years, IQ > 70) and their parents completed the Revised Children's Anxiety and Depression Scale (RCADS), a measure of internalizing symptoms, repeatedly, representing up to 7 measurement occasions from June to December 2020 (N ~ 419 occasions). Multilevel models were used to evaluate changes in internalizing symptoms over time. Internalizing symptoms did not differ between autistic and nonautistic youth in the summer of 2020. As reported by youth themselves, internalizing symptoms decreased in autistic youth, both overall and compared to nonautstic peers. This effect was driven by decreases in generalized anxiety, social anxiety, and depression symptoms in autistic youth. Reductions in generalized anxiety, social anxiety, and depression in autistic youth may be due to COVID-19 pandemic-specific differences in response to social, environmental, and contextual changes that unfolded in 2020. This highlights the importance of understanding unique protective and resilience factors that may be evident in autistic individuals in response to broad societal shifts such as those seen in response to COVID-19.

Smartwatch-based ecological momentary assessments for occupant wellness and privacy in buildings

This paper describes the adaptation of an open-source ecological momentary assessment smartwatch platform with three sets of micro-survey wellness-related questions focused on i) infectious disease (COVID-19) risk perception, ii) privacy and distraction in an office context, and iii) triggers of various movement-related behaviors in buildings. This platform was previously used to collect data for thermal comfort, and this work extends its use to other domains. Several research participants took part in a proof-of-concept experiment by wearing a smartwatch to collect their micro-survey question preferences and perception responses for two of the question sets. Participants were also asked to install an indoor localization app on their phone to detect where precisely in the building they completed the survey. The experiment identified occupant information such as the tendencies for the research participants to prefer privacy in certain spaces and the difference between infectious disease risk perception in naturally versus mechanically ventilated spaces. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring.

COVID-19 has challenged health systems to learn how to learn. This paper describes the context, methods and challenges for learning to improve COVID-19 care at one academic health center. Challenges to learning include: (1) choosing a right clinical target; (2) designing methods for accurate predictions by borrowing strength from prior patients' experiences; (3) communicating the methodology to clinicians so they understand and trust it; (4) communicating the predictions to the patient at the moment of clinical decision; and (5) continuously evaluating and revising the methods so they adapt to changing patients and clinical demands. To illustrate these challenges, this paper contrasts two statistical modeling approaches - prospective longitudinal models in common use and retrospective analogues complementary in the COVID-19 context - for predicting future biomarker trajectories and major clinical events. The methods are applied to and validated on a cohort of 1,678 patients who were hospitalized with COVID-19 during the early months of the pandemic. We emphasize graphical tools to promote physician learning and inform clinical decision making.

The association between online learning, parents' marital status, and internet addiction among adolescents during the COVID-19 pandemic period: A cross-lagged panel network approach.

INTRODUCTION: Previous research has identified the association between online learning and Internet addiction (IA) and the role of family factors in it. However, few studies have treated IA as a multidimensional mechanism and explored the underlying linkage of online learning, IA, and parental marital status with a cross-lagged network approach. The study aimed to examine the relationship between online learning during the COVID-19 pandemic, Internet addiction (IA), and parental marital status among Chinese adolescents. METHODS: The sample consisted of 2356 adolescents who completed the Internet Addiction Test twice over a four-month period. Four symptom networks and two cross-lagged panel networks were performed. RESULTS: The results showed that adolescents from divorced families had a higher prevalence of IA (27 %) compared to those from non-divorced families (17 %). The strongest cross-lagged association was found between "spending more time online" and "preferring the excitement online". In the divorced group, "school grades suffering" had the highest influence, while in the non-divorced group, "anticipation" had the highest influence. CONCLUSION: This study highlights the relationship between online learning, IA, and parental divorce and suggests that long-term online learning may contribute to IA, and parental divorce may exacerbate problematic Internet use and increase IA levels.

Life course psychosocial precursors of parent mental health resilience during the COVID-19 pandemic: A three-decade prospective cohort study.

BACKGROUND: There has been widespread interest in the implications of COVID-19 containment measures on the mental health of parents. Most of this research has focused on risk. Much less is known about resilience; yet such studies are key to protecting populations during major crises. Here we map precursors of resilience using life course data spanning three decades. METHODS: The Australian Temperament Project commenced in 1983 and now follows three generations. Parents (N = 574, 59 % mothers) raising young children completed a COVID-19 specific module in the early (May-September 2020) and/or later (October-December, 2021) phases of the pandemic. Decades prior, parents had been assessed across a broad range of individual, relational and contextual risk and promotive factors during childhood (7-8 years to 11-12 years), adolescence (13-14 years to 17-18 years) and young adulthood (19-20 years to 27-28 years). Regressions examined the extent to which these factors predicted mental health resilience, operationalised as lower than expected anxiety and depressive symptoms during the pandemic relative to pre-pandemic symptoms. RESULTS: Parent mental health resilience during the COVID-19 pandemic was consistently predicted by several factors assessed decades before the pandemic. These included lower ratings of internalizing difficulties, less difficult temperament/personality traits and stressful life events, and higher ratings of relational health. LIMITATIONS: The study included 37-39-year-old Australian parents with children age between 1 and 10 years. DISCUSSION: Results identified psychosocial indicators across the early life course that, if replicated, could constitute targets for long-term investment to maximise mental health resilience during future pandemics and crises.

The use of wearables in the sleep clinic and at home

As consumer sleep technology becomes ubiquitous, sleep clinicians are tasked with navigating these new technologies and must decide if and how to incorporate these technologies into a typical sleep clinical visit. We explore the potential applications of wearables, nearables, and apps in sleep medicine and consider how our acceptance of technology has changed since the COVID-19 pandemic. © 2023 Elsevier Inc. All rights reserved

Social Support as Technostress Inhibitor: Even More Important During the COVID-19 Pandemic?

Due to ongoing digitalization and the social distancing measures that came along with the COVID-19 pandemic, the working conditions and environments have changed for many individuals. Because of increased telework, the use of digital technologies for communicating and collaborating at work has been intensified, which can cause technostress. With longitudinal data from two surveys – one before and one during the COVID-19 pandemic – the paper analyzes the relationship between four social support dimensions (supervisor support, co-worker support, sense of community at work, and family support) and technostress creators. The study shows that social support can be an effective inhibitor of technostress creators. However, social support dimensions have to be differentiated in that regard. Further, the results show that the inhibiting effect of family support has become even more important during the COVID-19 pandemic. The results contribute to technostress research and research with regard to the new normal of working after the pandemic. © 2023, The Author(s).

A mixed effects changepoint quantile regression model for longitudinal data with application on COVID-19 data

Introduction: Longitudinal individual response profiles could exhibit a mixture of two or more phases of increase or decrease in trend throughout the follow-up period, with one or more unknown transition points (changepoints). The detection and estimation of these changepoints is crucial. Most of the proposed statistical methods for detecting and estimating changepoints in literature rely on distributional assumptions that may not hold. In this case, a good alternative is to use a robust approach;the quantile regression model. There are methods in the literature to deal with quantile regression models with a changepoint. These methods ignore the within-subject dependence of longitudinal data. Methods: We propose a mixed effects quantile regression model with changepoints to account for dependence structure in the longitudinal data. Fixed effects parameters, in addition to the location of the changepoint, are estimated using the profile estimation method. The stochastic approximation EM algorithm is proposed to estimate the fixed effects parameters exploiting the link between an asymmetric Laplace distribution and the quantile regression. In addition, the location of the changepoint is estimated using the usual optimization methods. Results and discussion: A simulation study shows that the proposed estimation and inferential procedures perform reasonably well in finite samples. The practical use of the proposed model is illustrated using COVID-19 data. The data focus on the effect of global economic and health factors on the monthly death rate due to COVID-19 from 1 April 2020 to 30th April 2021. the results show a positive effect on the monthly number of patients with COVID-19 in intensive care units (ICUs) for both 0.5th and 0.8th quantiles of new monthly deaths per million. The stringency index, hospital beds, and diabetes prevalence have no significant effect on both 0.5th and 0.8th quantiles of new monthly deaths per million. Copyright © 2023 Ibrahim, Gad and Abd-Rabou.

PTSD and Partial PTSD among First Responders One and Five Years after the Paris Terror Attacks in November 2015.

Following the Paris terror attacks in November 2015, a large number of first responders (FR) were mobilized and consequently were at risk of developing posttraumatic stress disorder (PTSD). Based on the ESPA 13 November survey, the objectives of this study were to 1) describe the prevalence of PTSD and partial PTSD in FR five years after the attacks, 2) describe the changes in PTSD and partial PTSD from one to five years after the attacks, and 3) examine factors associated with PTSD and partial PTSD five years after the attacks. Data were collected using an online questionnaire. PTSD and partial PTSD were measured using the Post-Traumatic Stress Disorder Checklist based on the DSM-5 (PCL-5). Gender, age, responder category, education level, exposure, mental health history, history of traumatic events, training, social support, concern about the COVID-19 epidemic, and somatic problems present after the attacks were all analyzed as potential factors associated with PTSD and partial PTSD using multinomial logistic regression. A total of 428 FR were included 5 years after the attacks, of which 258 had participated also 1 year after the attacks. Five years after the attacks, the prevalence of PTSD and partial PTSD were 8.6% and 22%, respectively. Presence of somatic problems after the attacks were associated with PTSD. Involvement in dangerous crime scenes was associated with a higher risk of partial PTSD. No awareness of psychological risks in the context of professional activity through specific training was associated with partial PTSD, in particular among participants aged 45 years or more. To mitigate PTSD for FR, monitoring mental health symptoms, providing mental health education, and providing treatment may be needed for several years after the attacks.

The longitudinal association between working from home and musculoskeletal pain during the COVID-19 pandemic.

OBJECTIVE: This study investigates the associations between working from home and the presence of MSP during the COVID-19 pandemic. Working from home often involves a lot of sedentary computer screen work and the home working environment might not be optimally equipped, which can lead to health problems, including musculoskeletal pain (MSP). METHODS: Longitudinal data from 16 questionnaire rounds of the Lifelines COVID-19 cohort during the first year of the COVID-19 pandemic (March 2020-February 2021) were used. In total, 40,702 Dutch workers were included. In every round, participants reported whether they worked on location, from home, or hybrid. Logistic Generalized Estimating Equations were used to study the association of work situation with the presence of MSP and the presence of severe MSP. RESULTS: Working from home was associated with higher risks of having MSP in the lower back (OR: 1.05, 95% CI 1.02-1.08), in the upper back (OR: 1.24, 95% CI 1.18-1.31), and in the neck, shoulder(s) and/or arm(s) (OR: 1.18, 95% CI 1.13-1.22). Hybrid working was associated with higher risks of having pain in the upper back (OR: 1.09, 95% CI 1.02-1.17) and in the neck, shoulder(s) and/or arm(s) (OR: 1.14, 95% CI 1.09-1.20). Both home and hybrid workers had higher risks of severe MSP in the different body areas. CONCLUSION: Home workers, and to a smaller extent hybrid workers, had higher risks of having MSP than location workers during the first year of the COVID-19 pandemic. The results indicate the importance of measures to prevent MSP in future policies involving working from home.

Determinants of participation in a longitudinal survey during the COVID-19 pandemic: the case of a low-infection country.

A large-scale crisis, such as the COVID-19 pandemic, has the potential to affect non-response in cross-sectional and longitudinal surveys. This study utilises a longitudinal survey, conducted prior to and during the COVID-19 pandemic, to examine the factors associated with participation in longitudinal surveys during the COVID-19 period, and how this has changed from prior to the pandemic. We find that a number of demographic groups are more likely to be non-responders to COVID-19 surveys, despite having completed pre-COVID surveys, as well as a number of other economic and personality factors. Reassuringly though, there were many more factors that did not have an association. The findings also highlight that two simple questions (with a low time cost) on subjective survey experience early in the pandemic were highly useful in predicting future survey participation. These findings can help to support survey practitioners and data collection companies to develop more robust response improvement strategies during the COVID-19 period.

Effects of the COVID-19 Pandemic on Mental Health and Brain Maturation in Adolescents: Implications for Analyzing Longitudinal Data.

Background: The COVID-19 pandemic has caused significant stress and disruption for young people, likely leading to alterations in their mental health and neurodevelopment. In this context, it is not clear whether youth who lived through the pandemic and its shutdowns are comparable psychobiologically to their age- and sex-matched peers assessed before the pandemic. This question is particularly important for researchers who are analyzing longitudinal data that span the pandemic. Methods: In this study we compared carefully matched youth assessed before the pandemic (n=81) and after the pandemic-related shutdowns ended (n=82). Results: We found that youth assessed after the pandemic shutdowns had more severe internalizing mental health problems, reduced cortical thickness, larger hippocampal and amygdala volume, and more advanced brain age. Conclusions: Thus, not only does the COVID-19 pandemic appear to have led to poorer mental health and accelerated brain aging in adolescents, but it also poses significant challenges to researchers analyzing data from longitudinal studies of normative development that were interrupted by the pandemic.

Stress/depression across the COVID-19 pandemic in Denmark.

BACKGROUND: Global estimates suggest strained mental health during the first year of the COVID-19 pandemic, but the lack of nationally representative and longitudinal data with clinically validated measures limits knowledge longer into the pandemic. METHODS: Data from 10 rounds of nationally representative surveys from Denmark tracked trends in risk of stress/depression from just before the first lockdown and through to April 2022. We focused on age groups and men and women in different living arrangements and controlled for seasonality in mental health that could otherwise be spuriously related to pandemic intensity. RESULTS: Prior to first lockdown, we observed a "parent gap", which closed with the first lockdown. Instead, a gender gap materialized, with women experiencing higher risks than men-and higher than levels predating first lockdown. Older respondents (+ 70 years) experienced increasing risks of stress/depression early in the pandemic, while all other groups experienced decreases. But longer into the pandemic, risks increased for all age groups and reached (and sometimes exceeded) levels from before first lockdown. CONCLUSION: Denmark had low infection rates throughout most of the pandemic, low mortality rates across the entire pandemic, and offered financial aid packages to curb financial strains. Despite this circumstance, initial improvements to mental health during the first lockdown in Denmark were short-lived. Two years of pandemic societal restrictions correspond with deteriorating mental health, as well as a change from a parenthood gap in mental health before first lockdown to a gender gap two years into the pandemic.

Natural cubic splines for the analysis of Alzheimer's clinical trials.

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.

An anonymised longitudinal GPS location dataset to understand changes in activity-travel behaviour between pre- and post-COVID periods.

Collecting GPS data using mobile devices is essential to understanding human mobility. However, getting this type of data is tricky because of some specific features of mobile operating systems, the high-power consumption of mobile devices, and users' privacy concerns. Therefore, data of this kind are rarely publicly available for scientific purposes, while private companies that own the data are often reluctant to share it. Here we present a large anonymous longitudinal dataset of Activity Point Location (APL) generated from mobile devices' GPS tracking. The GPS data were collected by using the Google Location History (GLH), accessible in the Google Maps application. Our dataset, named AnLoCOV hereafter, includes anonymised data from 338 persons with corresponding socio-demographics over approximately ten years (2012-2022), thus covering pre- and post-COVID periods, and calculates over 2 million weekly-classified APL extracted from approximately 16 million GPS tracking points in Ecuador. Furthermore, we made our models publicly available to enable advanced analysis of human mobility and activity spaces based on the collected datasets.

Are Attitudes towards COVID-19 Pandemic Related to Subjective Physical and Mental Health?

In this paper, we investigate the relationship between a person's psychological distress, subjective physical health and their attitudes towards the COVID-19 pandemic. The evaluation was performed on the basis of data from two waves of the Saxon Longitudinal Study, carried out in 2019 (pre-pandemic) and 2021. The number of study participants in both waves was 291. We tested in autoregressive cross-lagged models the stability of the respondents' health status before and during the pandemic and reviewed their influence on attitudes towards COVID-19. Our results show that COVID-19-related concerns are controlled by subjective physical health, while pandemic denial is linked to psychological distress. In an unknown and critical situation, with limited control over the situation, the strategy of avoidance or suppression may be used by individuals for protection by psychologically downplaying the stressor and danger.

The Impact of the COVID-19 Pandemic Quarantine on Adults with Autism Spectrum Disorders and Intellectual Disability: A Longitudinal Study.

The impact of the pandemic is being very significant psychologically, especially for people who were already vulnerable in these aspects, such as adults with Autism Spectrum Disorders (ASD) and Intellectual Disability (ID). A longitudinal analysis of motor aspects such as balance and gait, executive functions in daily life, severity of symptoms characteristic of autism, and degree of subjective well-being was performed in 53 adults with ASD and ID. A repeated measures ANOVA was performed and three measures were taken, the first in December 2019, the second in March 2020, and the last in July 2020. The results demonstrated a significant decrease in balance on the latter measure, along with a deterioration in well-being and ASD symptoms in the period of seclusion and an improvement in executive functions after seclusion.

Relationship between adjustment disorder symptoms and probable diagnosis before and after second lockdown in Israel: longitudinal symptom network analysis.

BACKGROUND: There is cumulative evidence of the importance of exploring the change of dynamics between symptoms over time as reflective of consolidation of psychopathology. AIMS: To explore the interactions between symptoms of ICD-11 adjustment disorder before and after the second lockdown of the COVID-19 pandemic in Israel and identify the most central symptoms and their concurrent and prospective associations with probable adjustment disorder. METHOD: This is a population-based study drawn from a probability-based internet panel. A representative sample of the adult Israeli population was assessed at two time points (T1, pre-second lockdown, n = 1029, response rate 76.17%; T2, post-second lockdown, n = 764, response rate 74.24%). Symptoms of adjustment disorder were assessed by the International Adjustment Disorder Questionnaire (IADQ). RESULTS: Although the overall strength of associations at the two measurement points was similar and two same communities were found, there was a significant change in their structure, with a more consolidated network at T2. The most central item was 'difficult to relax' in both networks. Cross-sectionally, all symptoms of failure to adapt significantly predicted adjustment disorder. 'Worry a lot more' (preoccupation) and 'difficult to adapt to life' (failure to adapt) at T1 significantly predicted this diagnosis at T2. CONCLUSIONS: Adjustment disorder symptoms consolidated during the second lockdown of the pandemic. In line with the ICD-11 conceptualisation of adjustment disorder, both preoccupation and failure-to-adapt symptoms have prognostic validity. This highlights the importance of identifying and targeting adjustment disorder symptoms during a period of stress such as the COVID-19 pandemic.