scholarly journals Can Psychological Traits Explain Mobility Behavior During the COVID-19 Pandemic?

2020 ◽  
pp. 194855062095257
Author(s):  
Ho Fai Chan ◽  
Jordan W. Moon ◽  
David A. Savage ◽  
Ahmed Skali ◽  
Benno Torgler ◽  
...  
Keyword(s):  
Regulatory Compliance ◽  
Exogenous Shock ◽  
Psychological Traits ◽  
Individual Level ◽  
Mobility Data ◽  
Level Data ◽  
Before And After ◽  
Mobility Behavior ◽  
And Gender ◽  
And Behavior

The current COVID-19 pandemic is a global, exogenous shock, impacting individuals’ decision making and behavior allowing researchers to test theories of personality by exploring how traits, in conjunction with individual and societal differences, affect compliance and cooperation. Study 1 used Google mobility data and nation-level personality data from 31 countries, both before and after region-specific legislative interventions, finding that agreeable nations are most consistently compliant with mobility restrictions. Study 2 ( N = 105,857) replicated these findings using individual-level data, showing that several personality traits predict sheltering in place behavior, but extraverts are especially likely to remain mobile. Overall, our analyses reveal robust relationships between traits and regulatory compliance (mobility behavior), both before and after region-specific legislative interventions, and the global declaration of the pandemic. Further, we find significant effects on reasons for leaving home, as well as age and gender differences, particularly relating to female agreeableness for previous and future social mobility behaviors. These sex differences, however, are only visible for those living in households with two or more people, suggesting that such findings may be driven by division of labor.

scholarly journals Can psychological traits explain mobility behavior during the COVID-19 pandemic?

2020 ◽  
Author(s):  
Ho Fai Chan ◽  
Jordan W Moon ◽  
David Alan Savage ◽  
Ahmed Skali ◽  
Benno Torgler ◽  
...  
Keyword(s):  
Regulatory Compliance ◽  
Division Of Labour ◽  
Exogenous Shock ◽  
Psychological Traits ◽  
Individual Level ◽  
Mobility Data ◽  
Level Data ◽  
Before And After ◽  
Mobility Behaviour ◽  
And Gender

The current COVID19 pandemic is a global exogenous shock, impacting individuals’ decision making and behaviour allowing researchers to test theories of personality by exploring how traits, in conjunction with individual and societal differences affect compliance and cooperation. Study 1 used Google Mobility data and nation-level personality data from 31 countries, both before and after region-specific legislative interventions, finding that agreeable nations are most consistently compliant with mobility restrictions. Study 2 (N=105,857) replicated these findings using individual-level data, showing that several personality traits predict sheltering in place behavior, but extraverts are especially likely to remain mobile. Overall, our analyses reveal robust relationships between traits and regulatory compliance (mobility behaviour) both before and after region specific legislative interventions, and the global declaration of the pandemic. Further, we find significant effects on reasons for leaving home, as well as age and gender differences, particularly relating to female agreeableness for previous and future social mobility behaviours. These sex differences, however, are only visible for those living in households with two or more people, suggesting that such findings may be driven by division of labour.

Missing Data in Research on Youth and Family Programs

2021 ◽  
pp. 003329412110268
Author(s):  
Jaime Ballard ◽  
Adeya Richmond ◽  
Suzanne van den Hoogenhof ◽  
Lynne Borden ◽  
Daniel Francis Perkins
Keyword(s):  
Missing Data ◽  
Statistical Methods ◽  
Self Report ◽  
Program Participation ◽  
Multilevel Data ◽  
Individual Level ◽  
Level Data ◽  
Before And After ◽  
Post Test ◽  
The Individual

Background Multilevel data can be missing at the individual level or at a nested level, such as family, classroom, or program site. Increased knowledge of higher-level missing data is necessary to develop evaluation design and statistical methods to address it. Methods Participants included 9,514 individuals participating in 47 youth and family programs nationwide who completed multiple self-report measures before and after program participation. Data were marked as missing or not missing at the item, scale, and wave levels for both individuals and program sites. Results Site-level missing data represented a substantial portion of missing data, ranging from 0–46% of missing data at pre-test and 35–71% of missing data at post-test. Youth were the most likely to be missing data, although site-level data did not differ by the age of participants served. In this dataset youth had the most surveys to complete, so their missing data could be due to survey fatigue. Conclusions Much of the missing data for individuals can be explained by the site not administering those questions or scales. These results suggest a need for statistical methods that account for site-level missing data, and for research design methods to reduce the prevalence of site-level missing data or reduce its impact. Researchers can generate buy-in with sites during the community collaboration stage, assessing problematic items for revision or removal and need for ongoing site support, particularly at post-test. We recommend that researchers conducting multilevel data report the amount and mechanism of missing data at each level.

Antecedents of growth-oriented entrepreneurship before and during the Greek economic crisis

2017 ◽  
Vol 24 (3) ◽  
pp. 528-544 ◽  
Author(s):  
Ioannis Giotopoulos ◽  
Alexandra Kontolaimou ◽  
Aggelos Tsakanikas
Keyword(s):  
Work Experience ◽  
Early Stage ◽  
New Ventures ◽  
High Growth ◽  
Content Type ◽  
Crisis Period ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
Before And After

Purpose The purpose of this paper is to explore potential drivers of high-growth intentions of early-stage entrepreneurs in Greece before and after the onset of the financial crisis of 2008. Design/methodology/approach To this end, the authors use individual-level data retrieved from Global Entrepreneurship Monitor annual surveys (2003-2015). Findings The results show that high-growth intentions of Greek entrepreneurs are driven by different factors in the crisis compared to the non-crisis period. Male entrepreneurs and entrepreneurs with significant work experience seem to be more likely to be engaged in growth-oriented new ventures during the crisis period. The same appears to hold for entrepreneurs who are motivated by an opportunity and also perceive future business opportunities in adverse economic conditions. On the other hand, the educational level and the social contacts of founders with other entrepreneurs are found to drive ambitious Greek entrepreneurship in the years before the crisis, while they were insignificant after the crisis outbreak. Originality/value Based on the concept of ambitious entrepreneurship, this study contributes to the literature by investigating the determinants of entrepreneurial high-growth expectations in the Greek context emphasizing the crisis period in comparison to the pre-crisis years.

scholarly journals Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ronald de Vlaming ◽  
Eric A. W. Slob ◽  
Philip R. Jansen ◽  
Alain Dagher ◽  
Philipp D. Koellinger ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Gray Matter Volume ◽  
Genetic Correlations ◽  
Brain Morphology ◽  
Computationally Efficient ◽  
Individual Level ◽  
Level Data ◽  
The Uk ◽  
And Behavior ◽  
The Brain

AbstractHuman variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce a computationally efficient approach for multivariate genomic-relatedness-based restricted maximum likelihood (MGREML) to estimate the genetic correlation between a large number of phenotypes simultaneously. Using individual-level data (N = 20,190) from the UK Biobank, we provide estimates of the heritability of gray-matter volume in 74 regions of interest (ROIs) in the brain and we map genetic correlations between these ROIs and health-relevant behavioral outcomes, including intelligence. We find four genetically distinct clusters in the brain that are aligned with standard anatomical subdivision in neuroscience. Behavioral traits have distinct genetic correlations with brain morphology which suggests trait-specific relevance of ROIs. These empirical results illustrate how MGREML can be used to estimate internally consistent and high-dimensional genetic correlation matrices in large datasets.

scholarly journals Time Series Analysis of Head Injury during Pandemic

2021 ◽  
Author(s):  
Lekhansh Shukla
Keyword(s):  
Time Series ◽  
Traffic Accidents ◽  
Principal Component ◽  
Ratio Test ◽  
Severe Injuries ◽  
Mobility Data ◽  
Community Mobility ◽  
Before And After ◽  
And Gender ◽  
Alcohol Sales

Introduction: Traumatic Brain Injury (TBI) is the most important cause of neurological disability worldwide. This study aims to find a change in TBI pattern during the coronavirus disease (COVID 19) pandemic.Methods: We have collected the number of TBI cases seen every day between 01/12/19 and 03/01/21 (400 days) in the emergency department of a tertiary neuropsychiatric centre in Bangalore and estimated a changepoint. Two predictors of this change — community mobility data from Google mobility reports (pre-processed with principal component analysis) and alcohol sales data from the wholesaler are examined. A time-series model using generalised linear regression for scale and shape is fit, and bootstrap confidence intervals are used for inference. We have compared the clinical details — mode and severity of the injury, compliance with safety regulations, age, residence and gender of patients seen before and after the changepoint.Results: An optimal changepoint is detected on 20/03/20 following which the mean number of TBI cases seen every day has decreased and variance has increased (Mean 1 = 29.4, Variance 1 = 50.1; Mean 2 = 19.5, Variance 2 = 59.7, Loglikelihood Ratio Test: χ2 = 130, df = 1, p < 0.001). Two principal components of community mobility, alcohol sales and weekday, explain the change in the number of TBI cases (Pseudo R-square = 58.1). A significant decrease in traffic accidents, falls, mild/moderate injuries, but an increase in assault and severe injuries is seen during the pandemic period.Conclusions: Decongestion of roads and regulation of alcohol sales can decrease TBI occurrence substantially. An increase in violent trauma during lockdown needs further research in the light of domestic violence. Acute care facilities for TBI should be maintained even during a strict lockdown as the proportion of severe TBI requiring admission increases.

scholarly journals Profiling Residents’ Mobility with Grid-Aggregated Mobile Phone Trace Data Using Chengdu as the Case

2021 ◽  
Vol 13 (24) ◽  
pp. 13713
Author(s):  
Xuesong Gao ◽  
Hui Wang ◽  
Lun Liu
Keyword(s):  
Mobile Phone ◽  
Mobile Phone Data ◽  
Future Research ◽  
Aggregate Level ◽  
Individual Level ◽  
Privacy Leakage ◽  
Mobility Data ◽  
Level Data ◽  
Data Source ◽  
Movement Trace

People’s movement trace harvested from mobile phone signals has become an important new data source for studying human behavior and related socioeconomic topics in social science. With growing concern about privacy leakage of big data, mobile phone data holders now tend to provide aggregate-level mobility data instead of individual-level data. However, most algorithms for measuring mobility are based on individual-level data—how the existing mobility algorithms can be properly transformed to apply on aggregate-level data remains undiscussed. This paper explores the transformation of individual data-based mobility metrics to fit with grid-aggregate data. Fifteen candidate metrics measuring five indicators of mobility are proposed and the most suitable one for each indicator is selected. Future research about aggregate-level mobility data may refer to our analysis to assist in the selection of suitable mobility metrics.

Candidate Sexual Orientation Didn't Matter (in the Way You Might Think) in the 2015 UK General Election

2018 ◽  
Vol 112 (3) ◽  
pp. 713-720 ◽  
Author(s):  
GABRIELE MAGNI ◽  
ANDREW REYNOLDS
Keyword(s):  
Sexual Orientation ◽  
Negative Impact ◽  
Demographic Characteristics ◽  
Individual Level ◽  
Rapid Social Change ◽  
Political Experience ◽  
Original Dataset ◽  
Level Data ◽  
And Gender ◽  
The Impact

Does sexual orientation and gender identity matter at election time? While previous literature has explored the effect of candidate gender and ethnicity on electoral results, this is the first study to quantitatively investigate the impact of sexual orientation. We build an original dataset combining individual-level data on more than 3,000 candidates in the 2015 UK election with sociodemographic indicators at the constituency level. In addition to sexual orientation and other demographic characteristics, we include candidate education, political experience, and campaign spending. We find that LGBT candidates generally do not have a negative impact on party vote share. Even in more conservative environments, LGBT candidates perform at least as well as their straight counterparts. This work is important to understand the consequences of descriptive representation and, relatedly, how rapid social change happens.

scholarly journals The 1968 Influenza Pandemic and COVID-19 Outcomes

2021 ◽  
Author(s):  
Charles A Taylor ◽  
Christopher Boulos ◽  
Matthew J Memoli
Keyword(s):  
Influenza Pandemic ◽  
Population Level ◽  
Related Factors ◽  
Death Rates ◽  
Individual Level ◽  
Age Cohorts ◽  
Differential Outcomes ◽  
Level Data ◽  
The Us ◽  
Before And After

Past pandemic experience at an individual or population level may affect health outcomes in future pandemics. In this study, we focus on how the influenza pandemic of 1968 (H3N2), which killed up to 100,000 people in the US, may have produced differential COVID-19 (SARS-CoV-2) outcomes. Our analysis finds that areas with high influenza-related mortality in 1968 experienced 1-2% lower COVID-19 death rates. We employ an identification strategy that isolates variation in COVID-19 rates across age cohorts born before and after 1968. Locales in the US with high 1968 influenza mortality have lower COVID-19 death rates among older cohorts relative to younger ones. The relationship holds using county-level and patient-level data, as well as data from hospitals and nursing homes. Results do not appear to be driven by systemic or policy-related factors that would affect a population, but instead suggest a potential individual-level response to prior influenza pandemic exposure. The findings merit substantial further investigation into potential biological, immunological, or other mechanisms that can account for these differential outcomes.

Effectiveness of tax reform on entrepreneurship

2019 ◽  
Vol 9 (1) ◽  
pp. 94-111
Author(s):  
Chigozie Andy Ngwaba ◽  
SeyedSoroosh Azizi
Keyword(s):  
South Africa ◽  
South African ◽  
Tax Reform ◽  
Cross Sectional ◽  
Content Type ◽  
Individual Level ◽  
Self Employment ◽  
The World Bank ◽  
Level Data ◽  
Before And After

Purpose The purpose of this paper is to investigate the effects of tax reform on entrepreneurship in South Africa using repeated cross-sectional data from the World Bank. Design/methodology/approach The paper adopts a difference-in-difference estimation technique as well as contrasting periods before and after the tax reform. This contrast is achieved by examining individuals in the formal and informal sector and measuring the effectiveness of the reform on self-employment. Findings The results indicate that the tax reform had a positive and significant effect on the probability of becoming self-employed in South Africa and is robust across different econometric specifications. Originality/value The authors use individual-level data to measure the effectiveness of a tax reform policy on entrepreneurship. Utilizing the South African post-Apartheid tax reform as a natural experiment allows the authors to identify the effects of taxes on the choice of becoming self-employed.

Police Use of Force Interactions: Is Race Relevant or Gender Germane?

2020 ◽  
Vol 50 (8) ◽  
pp. 851-864 ◽  
Author(s):  
James E. Wright ◽  
Andrea M. Headley
Keyword(s):  
Race And Ethnicity ◽  
Use Of Force ◽  
Representative Bureaucracy ◽  
Police Departments ◽  
Police Use Of Force ◽  
Individual Level ◽  
Level Data ◽  
And Gender ◽  
The Individual

Representative bureaucracy research has examined the influence of race and ethnicity on policing outcomes, yet little is known about police use of force specifically at the individual-level. To address this topic more meticulously, we utilize individual-level data (from Indianapolis and Dallas police departments) to explore differences in the amount of force used by officers in ethnic, racial, and gender matches in police–civilian dyads. Findings suggest that there are heightened levels of force used when there is racial and gender incongruenc between the officer and the civilian, particularly White officers interacting with Black civilians. We discuss how this finding may impact police departments moving forward.

Sign in / Sign up

Export Citation Format

Share Document