The impact of the early stages of COVID-19 on mental health in the United States, Germany, and the United Kingdom.

The impact of COVID-19 on people's physical health is well documented. But how did COVID-19-with all the uncertainty and disruption of daily life it entailed-impact people's mental health? We used ecologically momentary assessments from 22,562 individuals (largely young adults) across the United States, Germany, and the United Kingdom to study the impact of the early stages of COVID-19 on mental health. Exploring within-person trajectories of mood (4,471,810 observations) and depression (274,911 observations) between January 1 and September 30 of 2020, and comparing them to those observed for the same time period in 2019, we provide evidence that people-on average-show high levels of resilience. While the United States saw momentary decreases in mood and increases in depression that quickly returned to baseline, Germany and the United Kingdom did not experience observable negative effects on mental health. In a small subsample of U.S. users, we show that the mental health trajectories appear to be relatively consistent across different sociodemographics groups. Investigating the impact of social distancing on people's mental health within-person, we demonstrate that social distancing-on average-was associated with a decline in mental health. However, our findings also highlight that not all COVID-19 experiences were created equal. While individuals who experienced social distancing as burdensome reported lower levels of mental health, those who did not, indicated normal or even elevated levels of mental health. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Regional personality differences predict variation in early COVID-19 infections and mobility patterns indicative of social distancing.

The early stages of the COVID-19 pandemic revealed stark regional variation in the spread of the virus. While previous research has highlighted the impact of regional differences in sociodemographic and economic factors, we argue that regional differences in social and compliance behaviors-the very behaviors through which the virus is transmitted-are critical drivers of the spread of COVID-19, particularly in the early stages of the pandemic. Combining self-reported personality data that capture individual differences in these behaviors (3.5 million people) with COVID-19 prevalence and mortality rates as well as behavioral mobility observations (29 million people) in the United States and Germany, we show that regional personality differences can help explain the early transmission of COVID-19; this is true even after controlling for a wide array of important sociodemographic, economic, and pandemic-related factors. We use specification curve analyses to test the effects of regional personality in a robust and unbiased way. The results indicate that in the early stages of COVID-19, Openness to experience acted as a risk factor, while Neuroticism acted as a protective factor. The findings also highlight the complexity of the pandemic by showing that the effects of regional personality can differ (a) across countries (Extraversion), (b) over time (Openness), and (c) from those previously observed at the individual level (Agreeableness and Conscientiousness). Taken together, our findings support the importance of regional personality differences in the early spread of COVID-19, but they also caution against oversimplified answers to phenomena as complex as a global pandemic. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Depression predictions from GPS-based mobility do not generalize well to large demographically heterogeneous samples.

Depression is one of the most common mental health issues in the United States, affecting the lives of millions of people suffering from it as well as those close to them. Recent advances in research on mobile sensing technologies and machine learning have suggested that a person's depression can be passively measured by observing patterns in people's mobility behaviors. However, the majority of work in this area has relied on highly homogeneous samples, most frequently college students. In this study, we analyse over 57 million GPS data points to show that the same procedure that leads to high prediction accuracy in a homogeneous student sample (N = 57; AUC = 0.82), leads to accuracies only slightly higher than chance in a U.S.-wide sample that is heterogeneous in its socio-demographic composition as well as mobility patterns (N = 5,262; AUC = 0.57). This pattern holds across three different modelling approaches which consider both linear and non-linear relationships. Further analyses suggest that the prediction accuracy is low across different socio-demographic groups, and that training the models on more homogeneous subsamples does not substantially improve prediction accuracy. Overall, the findings highlight the challenge of applying mobility-based predictions of depression at scale.

Spending reflects not only who we are but also who we are around: The joint effects of individual and geographic personality on consumption.

Interactionist theories are considered to have resolved the classic person-situation debate by demonstrating that human behavior is most accurately described as a function of both personal characteristics as well as environmental cues. According to these theories, personality traits form part of the personal characteristics that drive behavior. We suggest that psychological theory stands to gain from also considering personality traits as an important environmental characteristic that shapes sociocultural norms and institutions, and, in turn, behavior. Building on research in geographical psychology, we support this proposition by presenting evidence on the relationship of individual and regional personality with spending behavior. Analyzing the spending records of 111,336 participants (31,915,942 unique transactions) across 374 Local Authority Districts (LAD) in the United Kingdom, we first show that geographic regions with higher aggregate scores on a given personality trait collectively spend more money on categories associated with that trait. Shifting the focus to individual level spending as our behavioral outcome (N = 1,716), we further demonstrate that regional personality of a participant's home LAD predicts individual spending above and beyond individual personality. That is, a person's spending reflects both their own personality traits as well as the personality traits of the people around them. We use conditional random forest predictions to highlight the robustness of these findings in the presence of a comprehensive set of individual and regional control variables. Taken together, our findings empirically support the proposition that spending behaviors reflect personality traits as both personal and environmental characteristics. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Sensing sociability: Individual differences in young adults' conversation, calling, texting, and app use behaviors in daily life.

Sociability as a disposition describes a tendency to affiliate with others (vs. be alone). Yet, we know relatively little about how much social behavior people engage in during a typical day. One challenge to documenting social behavior tendencies is the broad number of channels over which socializing can occur, both in-person and through digital media. To examine individual differences in everyday social behavior patterns, here we used smartphone-based mobile sensing methods (MSMs) in four studies (total N = 926) to collect real-world data about young adults' social behaviors across four communication channels: conversations, phone calls, text messages, and use of messaging and social media applications. To examine individual differences, we first focused on establishing between-person variability in daily social behavior, examining stability of and relationships among daily sensed social behavior tendencies. To explore factors that may explain the observed individual differences in sensed social behavior, we then expanded our focus to include other time estimates (e.g., times of the day, days of the week) and personality traits. In doing so, we present the first large-scale descriptive portrait of behavioral sociability patterns, characterizing the degree to which young adults engaged in social behaviors and mapping these behaviors onto self-reported personality dispositions. Our discussion focuses on how the observed sociability patterns compare to previous research on young adults' social behavior. We conclude by pointing to areas for future research aimed at understanding sociability using mobile sensing and other naturalistic observation methods for the assessment of social behavior. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Uncovering the care setting-turnover intention relationship of geriatric nurses.

In times of global demographic changes, strategies are needed for improving nursing staff retention. We examined the association of care setting (nursing homes and home care) with geriatric nurses' intention to leave their job and their profession. Thus far, it is unclear why nurses' turnover intention and behaviour do not differ between care settings, although working conditions tend to be better in home care. We used the Job Demands-Resources model to explain indirect and buffering effects by job demands (time pressure, social conflicts) and resources (task identity, supervisor support, and co-worker support) via nurses' perceived health and job satisfaction on nurses' leaving intentions. The present cross-sectional questionnaire study was conducted with a sample of N = 278 registered nurses and nursing aides in German geriatric care. As expected, there was no direct relationship between care setting and leaving attitudes. Demands and resources predicted the intention to leave with job satisfaction as mediator. We found more demands in nursing homes but no differences in resources. Serial mediation effects of care setting on intentions to leave via demands/resources and health/job satisfaction as mediators were found only for time pressure and social conflicts. Unexpectedly, there were no clear differences between intention to leave the job and the profession. As hypotheses were only partly confirmed, other buffering and detrimental effects on leaving intentions are discussed. The present data suggest that detailed concepts for personnel and career planning in geriatric care are needed.

The role of cognitive resources for subjective work ability and health in nursing.

Cognitive resources can be considered to be key variables in the context of work ability and health, particularly in the aging workforce. However, research on this issue is sparse, lacking a comprehensive examination of specific cognitive functions. Therefore, the aim of the present study was to examine the association of cognitive resources with subjective work ability and health in more detail. In 166 geriatric care workers (mean age 42.1 years, SD = 11.5, range 20-62), subjective work ability and health were assessed. Additionally, a comprehensive battery of cognitive tests measuring crystallized intelligence, cognitive speed, short-term memory, working memory, and inhibition was administered in a standardized procedure. Controlling for individual differences in age, education, depressive symptoms, self-regulation strategies (in terms of selective optimization with compensation), and cognitive resources (particularly better performance in short-term memory, working memory, and inhibition) were related to better subjective work ability and health. The present results demonstrate the relation of a variety of specific cognitive functions with subjective work ability and health over and above individual differences in age, education, depressive symptoms, and self-regulation strategies. Implications to explicitly consider a set of cognitive resources in models of work and organizational psychology, particularly with respect to the aging workforce, are discussed.