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The paper is focused on the third wave of the pandemic and its comparison with the first wave in terms of the quality of life of university students in Czechia. In the first wave, the society came together, with solidarity being a prominent manifestation. The third wave differed from the first one in medical (vaccination was already available) as well as social terms. The paper has two objectives, the first is to measure the quality of life and related variables in the third wave of the pandemic and to compare the values found in the third wave with those in the first wave of the pandemic. The second objective is to identify which of the factors related to quality of life are predictors of that quality. The hypothesis assumes different measured values of quality of life for men and women. The measurement yielded knowledge of the high value of quality of place and environmental quality, which can enrich the quality of life epistemology on the one hand and geographical psychology on the other. Trust, health, happiness, quality of place, and safety were identified as factors. The measurement revealed the finding of different quality of life values in the third and first wave of the pandemic. While quality of life values increased in the first wave compared to the pre-pandemic period, both quality of life values and factors decreased in the third wave compared to the first wave. The only exception was one factor that we consider to be a winner of the third wave of the pandemic. The factor that declined in all measurements is considered to be the loser of the third wave of the pandemic. The paper concludes with implications derived from these findings.

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OBJECTIVE: Personality traits cluster across countries, regions, cities, and neighborhoods. What drives the formation of these clusters? Ecological theory suggests that physical locations shape humans' patterns of behaviors and psychological characteristics. Based on this theory, we examined whether and how differential land-cover relates to individual personality. METHOD: We followed a preregistered three-pronged analysis approach to investigate the associations between personality (N = 2,690,878) and land-cover across the United States. We used eleven land-cover categories to classify landscapes and tested their association with personality against broad physical and socioeconomic factors. RESULTS: Urban areas were positively associated with openness to experience and negatively associated with conscientiousness. Coastal areas were positively associated with openness to experience and neuroticism but negatively associated with agreeableness and conscientiousness. Cultivated areas were negatively associated with openness. Landscapes at the periphery of human activity, such as shrubs, bare lands, or permanent snows, were not reliably associated with personality traits. CONCLUSIONS: Bivariate correlations, multilevel, and random forest models uncovered robust associations between landscapes and personality traits. These findings align with ecological theory suggesting that an individual's environment contributes to their behaviors, thoughts, and feelings.

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Full national coverage below the state level is difficult to attain through survey-based data collection. Even the largest survey-based data collections, such as the CDC's Behavioral Risk Factor Surveillance System or the Gallup-Healthways Well-being Index (both with more than 300,000 responses p.a.) only allow for the estimation of annual averages for about 260 out of roughly U.S. 3,000 counties when a threshold of 300 responses per county is used. Using a relatively high threshold of 300 responses gives substantially higher convergent validity-higher correlations with health variables-than lower thresholds but covers a reduced and biased sample of the population. We present principled methods to interpolate spatial estimates and show that including large-scale geotagged social media data can increase interpolation accuracy. In this work, we focus on Gallup-reported life satisfaction, a widely-used measure of subjective well-being. We use Gaussian Processes (GP), a formal Bayesian model, to interpolate life satisfaction, which we optimally combine with estimates from low-count data. We interpolate over several spaces (geographic and socioeconomic) and extend these evaluations to the space created by variables encoding language frequencies of approximately 6 million geotagged Twitter users. We find that Twitter language use can serve as a rough aggregate measure of socioeconomic and cultural similarity, and improves upon estimates derived from a wide variety of socioeconomic, demographic, and geographic similarity measures. We show that applying Gaussian Processes to the limited Gallup data allows us to generate estimates for a much larger number of counties while maintaining the same level of convergent validity with external criteria (i.e., N = 1,133 vs. 2,954 counties). This work suggests that spatial coverage of psychological variables can be reliably extended through Bayesian techniques while maintaining out-of-sample prediction accuracy and that Twitter language adds important information about cultural similarity over and above traditional socio-demographic and geographic similarity measures. Finally, to facilitate the adoption of these methods, we have also open-sourced an online tool that researchers can freely use to interpolate their data across geographies.

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There is growing evidence that psychological characteristics are spatially clustered across geographic regions and that regionally aggregated psychological characteristics are related to important outcomes. However, much of the evidence comes from research that relied on methods that are theoretically ill-suited for working with spatial data. The validity and generalizability of this work are thus unclear. Here we address two main challenges of working with spatial data (i.e., modifiable areal unit problem and spatial dependencies) and evaluate data-analysis techniques designed to tackle those challenges. To illustrate these issues, we investigate the robustness of regional Big Five personality differences and their correlates within the United States (Study 1; N = 3,387,303) and Germany (Study 2; N = 110,029). First, we display regional personality differences using a spatial smoothing approach. Second, we account for the modifiable areal unit problem by examining the correlates of regional personality scores across multiple spatial levels. Third, we account for spatial dependencies using spatial regression models. Our results suggest that regional psychological differences are robust and can reliably be studied across countries and spatial levels. The results also show that ignoring the methodological challenges of spatial data can have serious consequences for research concerned with regional psychological differences.

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Geographical psychology aims to study the spatial distribution of psychological phenomenon at different levels of geographical analysis and their relations to macro-level important societal outcomes. The geographical perspective provides a new way of understanding interactions between humankind psychological processes and distal macro-environments. Studies have identified the spatial organizations of a wide range of psychological constructs, including (but not limited among) personality, individualism/collectivism, cultural tightness-looseness, and well-being; these variations have been plotted over a range of geographical units (e.g., neighborhoods, cities, states, and countries) and have been linked to a broad array of political, economic, social, public health, and other social consequences. Future research should employ multi-level analysis, taking advantage of more deliberated causality test methods and big data techniques, to further examine the emerging and evolving mechanisms of geographical differences in psychological phenomena.

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This research challenges the claim that engaging in formal volunteering improves health. Using data for the 50 American states pertaining to 2015-2016, multiple regression equations with differing control and entry order demonstrated the capacity of state resident neuroticism to eliminate relations between state volunteering rates and state health outcomes. In Study 1, with state SES, White population percent, urban population percent, and health environment considered and controlled, volunteering accounted for 11.5% of state health variance. However, with neuroticism entered between the demographic controls and volunteering, neuroticism accounted for 18.0% but additional variance accounted for by volunteering was reduced to 0.7%. Similarly, in Study 2, with data for those 65 and older, the results were replicated. It is speculated that higher neuroticism produces social anxiety that discourages volunteering and fosters poorer health at both the individual and the state level for the general population and for those 65 and over.

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BACKGROUND: Opioid overdoses have reached epidemic levels in the United States and have clustered in Northeastern and "Rust Belt" states. Five Factor Model (FFM) personality traits also vary at the state level, with anger-prone traits clustered in the Northeast region. This study tested the hypothesis that state-level anger proneness would be associated with a greater increase in rates of opioid overdose death. METHODS: This was a secondary analysis of state-level data on FFM traits, opioid overdose deaths, and other classes of preventable death. Robust mixed models tested whether change in rates of opioid overdose death from 2008 to 2016 was moderated by state-level anger proneness. RESULTS: State-level anger proneness was significantly associated with greater increases in rates of opioid overdose deaths (B = 1.01, standard error = 0.19, P < .001, 95% confidence interval: 0.63-1.39). The slope of increase in opioid overdose death rates was 380% greater in anger-prone states and held after adjustment for potential confounders such as state-level prevalence of major depressive disorder, number of mental health facilities, and historical patterns of manufacturing decline. A similar pattern was observed between state-level anger proneness and benzodiazepine overdose deaths but was not significant for the latter after adjustment for potential confounders. CONCLUSION: These findings suggest that states characterized as more anger prone have experienced greater increases in opioid overdose deaths.

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OBJECTIVE: There is growing evidence that certain regional personality differences function as important drivers of regional economic development (e.g., via effects on entrepreneurship and innovation activity). The present investigation examines the impact that regional variation in the trait courage has on entrepreneurship. METHOD: Using data from a new large-scale internet-based study, we provide the first psychological map of courage across the United States (N = 390,341 respondents from 283 U.S. metropolitan regions). We apply regression analyses to relate regional courage scores to archival data on the emergence and survival of start-ups across American regions. RESULTS: Our mapping approach reveals comparatively high levels of regional courage in the Eastern and Southern regions of the United States. Regional courage scores were positively related to entrepreneurial activity, but negatively related to start-up survival-even when controlling for a wide variety of standard economic predictors. Several robustness checks corroborated these results. Finally, regional differences in economic risk-taking accounted for significant proportions of variance in the relationship between regional courage and entrepreneurship. CONCLUSION: Our results suggest that regional courage may contribute to a pattern of enterprising and also risky economic behavior, which can lead to high levels of entrepreneurial activity but also shorter start-up survival.

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The present study extended traditional nation-based research on person-culture-fit to the regional level. First, we examined the geographical distribution of Big Five personality traits in Switzerland. Across the 26 Swiss cantons, unique patterns were observed for all traits. For Extraversion and Neuroticism clear language divides emerged between the French- and Italian-speaking South-West vs. the German-speaking North-East. Second, multilevel modeling demonstrated that person-environment-fit in Big Five, composed of elevation (i.e., mean differences between individual profile and cantonal profile), scatter (differences in mean variances) and shape (Pearson correlations between individual and cantonal profiles across all traits; Furr, 2008, 2010), predicted the development of subjective wellbeing (i.e., life satisfaction, satisfaction with personal relationships, positive affect, negative affect) over a period of 4 years. Unexpectedly, while the effects of shape were in line with the person-environment-fit hypothesis (better fit predicted higher subjective wellbeing), the effects of scatter showed the opposite pattern, while null findings were observed for elevation. Across a series of robustness checks, the patterns for shape and elevation were consistently replicated. While that was mostly the case for scatter as well, the effects of scatter appeared to be somewhat less robust and more sensitive to the specific way fit was modeled when predicting certain outcomes (negative affect, positive affect). Distinguishing between supplementary and complementary fit may help to reconcile these findings and future research should explore whether and if so under which conditions these concepts may be applicable to the respective facets of person-culture-fit.

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Residential location is thought to influence people's well-being, but different individuals may value residential areas differently. We examined how life satisfaction and personality traits are geographically distributed within the UK London metropolitan area, and how the strength of associations between personality traits and life satisfaction vary by residential location (i.e., personality-neighborhood interactions). Residential area was recorded at the level of postal districts (216 districts, n = 56,019 participants). Results indicated that the strength of associations between personality traits and life satisfaction depended on neighborhood characteristics. Higher openness to experience was more positively associated with life satisfaction in postal districts characterized by higher average openness to experience, population density, and ethnic diversity. Higher agreeableness and conscientiousness were more strongly associated with life satisfaction in postal districts with lower overall levels of life satisfaction. The associations of extraversion and emotional stability were not modified by neighborhood characteristics. These findings suggest that people's life satisfaction depends, in part, on the interaction between individual personality and particular features of the places they live.

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