scholarly journals Measuring Natural Hazard-Related Disasters through Self-Reports

2021 ◽  
Author(s):  
Ben Edwards ◽  
Matthew Gray ◽  
Judith B. Borja
Keyword(s):  
Natural Hazard ◽  
Local Area ◽  
Cumulative Exposure ◽  
Individual Level ◽  
Disaster Impact ◽  
Disaster Impacts ◽  
Self Reports ◽  
Using Data ◽  
Individual Self ◽  
Development And Validation

AbstractExposure to multiple natural hazard-related disasters will become more common due to climate change. This article reports on the development and validation of a cumulative measure of exposure to natural hazard-related disasters (2013–2017) at the area level, and an individual-level measure of disaster impact using data from the Longitudinal Cohort Study on the Filipino Child and linked data from the International Disaster Database (EM-DAT). Caregiver reports of cumulative exposure to disasters had statistically significant associations with disasters reported by neighborhood officials and with disasters in EM-DAT. Using ecometric techniques we generated a reliable community average measure of exposure to natural hazard-related disasters. Based on neighbor but not individual self-reports this exogenous measure of disaster exposure in the local area was more strongly related to EM-DAT and official neighborhood reports than individual reports. To capture household variation we developed an individual-level measure of disaster impacts. Disaster impact was associated with measures of exposure (individual and community average), community ratings by officials, and EM-DAT but only moderately associated with the community average exposure. Both the community average and disaster impacts measures were associated with household income and the adequacy of income in households.

Development and Validation of a German Language Unit-Level Organizational Citizenship Behavior (OCB) Scale

2020 ◽  
Vol 36 (5) ◽  
pp. 852-863 ◽  
Author(s):  
George Gunnesch-Luca ◽  
Klaus Moser
Keyword(s):  
Factor Analysis ◽  
Organizational Citizenship ◽  
Organizational Citizenship Behavior ◽  
Helping Behavior ◽  
Citizenship Behavior ◽  
German Language ◽  
Individual Level ◽  
Unit Level ◽  
Confirmatory Factor ◽  
Development And Validation

Abstract. The current paper presents the development and validation of a unit-level Organizational Citizenship Behavior (OCB) scale based on the Referent-Shift Consensus Model (RSCM). In Study 1, with 124 individuals measured twice, both an Exploratory Factor Analysis (EFA) and a Confirmatory Factor Analysis (CFA) established and confirmed a five-factor solution (helping behavior, sportsmanship, loyalty, civic virtue, and conscientiousness). Test–retest reliabilities at a 2-month interval were high (between .59 and .79 for the subscales, .83 for the total scale). In Study 2, unit-level OCB was analyzed in a sample of 129 work teams. Both Interrater Reliability (IRR) measures and Interrater Agreement (IRA) values provided support for RSCM requirements. Finally, unit-level OCB was associated with group task interdependence and was more predictable (by job satisfaction and integrity of the supervisor) than individual-level OCB in previous research.

It Is Your Decision to Date Interracially: The Influence of Family Approval on the Likelihood of Interracial/Interethnic Dating

2021 ◽  
pp. 0192513X2199413
Author(s):  
Byron Miller ◽  
Savanah Catalina ◽  
Sara Rocks ◽  
Kathryn Tillman
Keyword(s):  
College Students ◽  
Young Adults ◽  
Romantic Relationships ◽  
Family Members ◽  
Individual Level ◽  
Interracial Romance ◽  
Using Data ◽  
Do So

Although attitudes toward interracial romantic relationships (IRRs) have generally improved over the years, many Americans still disapprove of their family members being in IRRs. Prior studies have examined correlates of individual-level attitudes about interracial romance, but less is known about whether family members’ attitudes are directly associated with young people’s decisions to date interracially. Using data collected from 790 romantically involved college students at two large public four-year universities, we find that young adults who believe their siblings, parents, and grandparents approve of IRRs have greater odds of dating interracially. Compared to Whites, Blacks and Hispanics are more likely to be interracially involved but their decision to do so is much less dependent on the approval of their parents and grandparents. We also find young adults are more likely to date interracially if they have five or more relatives with IRR experience themselves. The findings and their implications are discussed.

scholarly journals Blood Pressure Trajectories Across the Life Course

2021 ◽  
Vol 34 (3) ◽  
pp. 234-241
Author(s):  
Norrina B Allen ◽  
Sadiya S Khan
Keyword(s):  
Blood Pressure ◽  
Measurement Errors ◽  
Clinical Care ◽  
Population Level ◽  
Cumulative Exposure ◽  
Older Adulthood ◽  
Individual Level ◽  
The Life Course ◽  
Level Group ◽  
Improve Health

Abstract High blood pressure (BP) is a strong modifiable risk factor for cardiovascular disease (CVD). Longitudinal BP patterns themselves may reflect the burden of risk and vascular damage due to prolonged cumulative exposure to high BP levels. Current studies have begun to characterize BP patterns as a trajectory over an individual’s lifetime. These BP trajectories take into account the absolute BP levels as well as the slope of BP changes throughout the lifetime thus incorporating longitudinal BP patterns into a single metric. Methodologic issues that need to be considered when examining BP trajectories include individual-level vs. population-level group-based modeling, use of distinct but complementary BP metrics (systolic, diastolic, mean arterial, mid, and pulse pressure), and potential for measurement errors related to varied settings, devices, and number of readings utilized. There appear to be very specific developmental periods during which divergent BP trajectories may emerge, specifically adolescence, the pregnancy period, and older adulthood. Lifetime BP trajectories are impacted by both individual-level and community-level factors and have been associated with incident hypertension, multimorbidity (CVD, renal disease, cognitive impairment), and overall life expectancy. Key unanswered questions remain around the additive predictive value of BP trajectories, intergenerational contributions to BP patterns (in utero BP exposure), and potential genetic drivers of BP patterns. The next phase in understanding BP trajectories needs to focus on how best to incorporate this knowledge into clinical care to reduce the burden of hypertensive-related outcomes and improve health equity.

scholarly journals Childlessness, Individual Socioeconomic Resources, and Health: Exploring Variation in 20 Countries

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 515-516
Author(s):  
Nekehia Quashie ◽  
Christine Mair ◽  
Radoslaw Antczak ◽  
Bruno Arpino
Keyword(s):  
Older Adults ◽  
Health Outcomes ◽  
Health Indicators ◽  
Data Repository ◽  
Middle Income ◽  
Individual Level ◽  
Socioeconomic Resources ◽  
Middle Income Countries ◽  
Using Data ◽  
The Impact

Abstract Childless older adults may be at risk for poorer health cross-nationally, yet most studies on this topic analyze only a small number of countries and only 1 or 2 health outcomes. To our knowledge, two papers exist that explore associations between childlessness and multiple indicators of health using data from a large number of regionally diverse countries (e.g., 20 countries from North America, Asia, and Europe), but neither study includes an examination of socioeconomic resources. The level of health risk faced by childless older adults is likely to be distinctly shaped by older adults’ socioeconomic resources (e.g., education, income, wealth). Associations between childlessness, socioeconomic resources, and health may also differ by country context. Using harmonized, cross-national data for adults aged 50 and older across 20 high- and middle-income countries (United States (HRS), European Union (SHARE), Mexico (MHAS), and China (CHARLS) from the Gateway to Global Aging data repository), we explore if and how individual-level socioeconomic resources (income, education, wealth) moderate associations between childlessness and five health indicators (self-rated health, ADL limitations, IADL limitations, chronic conditions, and depression). Results suggest that associations between childlessness and health outcomes vary by individual socioeconomic resources in some country contexts, but not in others. We discuss these findings in light of the impact of individual-level socioeconomic resources on older adults’ support options and health outcomes cross-nationally.

scholarly journals The Network Structure of Police Misconduct

2019 ◽  
Vol 5 ◽  
pp. 237802311987979 ◽  
Author(s):  
George Wood ◽  
Daria Roithmayr ◽  
Andrew V. Papachristos
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Police Officers ◽  
Police Misconduct ◽  
Police Departments ◽  
Top Down ◽  
Network Ties ◽  
Individual Level ◽  
Factors Associated ◽  
Using Data

Conventional explanations of police misconduct generally adopt a microlevel focus on deviant officers or a macrolevel focus on the top-down organization of police departments. Between these levels are social networks of misconduct. This study recreates these networks using data on 16,503 complaints and 15,811 police officers over a six-year period in Chicago. We examine individual-level factors associated with receiving a complaint, the basic properties of these misconduct networks, and factors related to officer co-naming in complaints. We find that the incidence of police misconduct is associated with attributes including race, age, and tenure and that almost half of police officers are connected in misconduct ties in broader networks of misconduct. We also find that certain dyadic factors, especially seniority and race, strongly predict network ties and the incidence of group misconduct. Our results provide actionable information regarding possible ways to leverage the co-complaint network structure to reduce misconduct.

scholarly journals Analysis of Behavioral Characteristics of Smartphone Addiction Using Data Mining

2018 ◽  
Vol 8 (7) ◽  
pp. 1191 ◽  
Author(s):  
MyungSuk Lee ◽  
MuMoungCho Han ◽  
JuGeon Pak
Keyword(s):  
Data Mining ◽  
Emotional Regulation ◽  
Smartphone Addiction ◽  
Behavioral Characteristics ◽  
World Population ◽  
Self Reports ◽  
Usage Patterns ◽  
Input Variables ◽  
Using Data ◽  
Reporting Method

In 2016, the number of mobile phone subscriptions worldwide had surpassed the total world population; moreover, the number of smartphone addicts is increasing each year. Thus, the objective of this study is to analyze smartphone addiction by considering the differences between smartphone usage patterns as well as cognition. Our proposed method involves automatically collecting and analyzing data through an app instead of using the existing self-reporting method, thereby improving the accuracy of data and ensuring data reliability from respondents. Based on the results of our study, we observed that there is a significant cognitive bias between the self-reports and automatically collected data. As a result of applying data mining, among the six criteria out of the total 24 items of the questionnaire, the higher the “recurrence” item, the higher the addiction; further, “forbidden” item 1 had the largest effect on addiction. In addition, the input variables that have the greatest influence on the high-risk users were the number of times the screen was turned on and real-use time/cognitive-use time. However, the amount of data and time of smartphone usage were not related to addiction. In the future, we will modify the app to obtain more accurate data, based on which, we can analyze the effects of smartphone addiction, such as depression, anxiety, stress, self-esteem, and emotional regulation, among others.

scholarly journals Reliable Deep Learning–Based Detection of Misplaced Chest Electrodes During Electrocardiogram Recording: Algorithm Development and Validation

10.2196/25347 ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. e25347
Author(s):  
Khaled Rjoob ◽  
Raymond Bond ◽  
Dewar Finlay ◽  
Victoria McGilligan ◽  
Stephen J Leslie ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ventricular Hypertrophy ◽  
Left Ventricular ◽  
Intercostal Space ◽  
The Past ◽  
Body Surface Potential Maps ◽  
Body Surface Potential ◽  
Using Data ◽  
Development And Validation ◽  
Electrocardiogram Ecg

Background A 12-lead electrocardiogram (ECG) is the most commonly used method to diagnose patients with cardiovascular diseases. However, there are a number of possible misinterpretations of the ECG that can be caused by several different factors, such as the misplacement of chest electrodes. Objective The aim of this study is to build advanced algorithms to detect precordial (chest) electrode misplacement. Methods In this study, we used traditional machine learning (ML) and deep learning (DL) to autodetect the misplacement of electrodes V1 and V2 using features from the resultant ECG. The algorithms were trained using data extracted from high-resolution body surface potential maps of patients who were diagnosed with myocardial infarction, diagnosed with left ventricular hypertrophy, or a normal ECG. Results DL achieved the highest accuracy in this study for detecting V1 and V2 electrode misplacement, with an accuracy of 93.0% (95% CI 91.46-94.53) for misplacement in the second intercostal space. The performance of DL in the second intercostal space was benchmarked with physicians (n=11 and age 47.3 years, SD 15.5) who were experienced in reading ECGs (mean number of ECGs read in the past year 436.54, SD 397.9). Physicians were poor at recognizing chest electrode misplacement on the ECG and achieved a mean accuracy of 60% (95% CI 56.09-63.90), which was significantly poorer than that of DL (P<.001). Conclusions DL provides the best performance for detecting chest electrode misplacement when compared with the ability of experienced physicians. DL and ML could be used to help flag ECGs that have been incorrectly recorded and flag that the data may be flawed, which could reduce the number of erroneous diagnoses.

scholarly journals On “Nationology”: The Gravitational Field of National Culture

2021 ◽  
pp. 002202212110447
Author(s):  
Plamen Akaliyski ◽  
Christian Welzel ◽  
Michael Harris Bond ◽  
Michael Minkov
Keyword(s):  
Gravitational Field ◽  
Cultural Values ◽  
National Culture ◽  
Random Noise ◽  
Religious Groups ◽  
Individual Values ◽  
Individual Level ◽  
Collective Phenomenon ◽  
Using Data ◽  
The Individual

Nations have been questioned as meaningful units for analyzing culture due to their allegedly limited variance-capturing power and large internal heterogeneity. Against this skepticism, we argue that culture is by definition a collective phenomenon and focusing on individual differences contradicts the very concept of culture. Through the “miracle of aggregation,” we can eliminate random noise and arbitrary variation at the individual level in order to distill the central cultural tendencies of nations. Accordingly, we depict national culture as a gravitational field that socializes individuals into the orbit of a nation’s central cultural tendency. Even though individuals are also exposed to other gravitational forces, subcultures in turn gravitate within the limited orbit of their national culture. Using data from the World Values Survey, we show that individual values cluster in concentric circles around their nation’s cultural gravity center. We reveal the miracle of aggregation by demonstrating that nations capture the bulk of the variation in the individuals’ cultural values once they are aggregated into lower-level territorial units such as towns and sub-national regions. We visualize the gravitational force of national cultures by plotting various intra-national groups from five large countries that form distinct national clusters. Contrary to many scholars’ intuitions, alternative social aggregates, such as ethnic, linguistic, and religious groups, as well as diverse socio-demographic categories, add negligible explained variance to that already captured by nations.

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