Understanding Differences in Types of Opioid Prescriptions Across Time and Space: A Community-Level Analysis

2018 ◽  
Vol 49 (2) ◽  
pp. 405-418 ◽  
Author(s):  
Tammy L. Anderson ◽  
Xiaoke Zhang ◽  
Steven S. Martin ◽  
Yiqian Fang ◽  
Jiamin Li
Keyword(s):  
The United States ◽  
Community Level ◽  
Prescribing Patterns ◽  
Future Research ◽  
Data Set ◽  
Community Factors ◽  
Census Tract Level ◽  
Emerging Trends ◽  
Level Data ◽  
Level Analysis

For the better part of the 21st century, opioid abuse and related consequences have beleaguered the United States. Effectively fighting the crisis may require a better understanding of potential differences among the types of opioids available as treating them as one homogeneous group may mask emerging trends and conflate more benign ones with those more troubling. The purpose of our study is to investigate changes in prescribing patterns of four groups of opioids (hydrocodone, oxycodone, fentanyl, and other) and how community-level factors explain their variation over time. We use a census tract–level data set with population, concentrated disadvantage, and prescription drug monitoring payment variables to address our goals. Findings show disparate prescribing patterns among the four types of opioids and considerable differences in the community factors that predict their change. Implications for future research and interventions follow.

scholarly journals The COVID Connection: Pandemic Anxiety, COVID-19 Comprehension, and Digital Confidence

2021 ◽  
pp. 000276422110031
Author(s):  
Laura Robinson ◽  
Jeremy Schulz ◽  
Øyvind N. Wiborg ◽  
Elisha Johnston
Keyword(s):  
Logistic Models ◽  
The United States ◽  
Sociodemographic Factors ◽  
Future Research ◽  
Lower Probability ◽  
Data Set ◽  
Digital Inequality ◽  
Partner Status ◽  
General Anxiety ◽  
Nationally Representative

This article presents logistic models examining how pandemic anxiety and COVID-19 comprehension vary with digital confidence among adults in the United States during the first wave of the pandemic. As we demonstrate statistically with a nationally representative data set, the digitally confident have lower probability of experiencing physical manifestations of pandemic anxiety and higher probability of adequately comprehending critical information on COVID-19. The effects of digital confidence on both pandemic anxiety and COVID-19 comprehension persist, even after a broad range of potentially confounding factors are taken into account, including sociodemographic factors such as age, gender, race/ethnicity, metropolitan status, and partner status. They also remain discernable after the introduction of general anxiety, as well as income and education. These results offer evidence that the digitally disadvantaged experience greater vulnerability to the secondary effects of the pandemic in the form of increased somatized stress and decreased COVID-19 comprehension. Going forward, future research and policy must make an effort to address digital confidence and digital inequality writ large as crucial factors mediating individuals’ responses to the pandemic and future crises.

Club convergence of crime rates in the United States of America

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kolawole Ogundari
Keyword(s):  
Violent Crime ◽  
Property Crime ◽  
The United States ◽  
Crime Rates ◽  
Community Level ◽  
Club Convergence ◽  
Content Type ◽  
Level Data ◽  
Convergence Club ◽  
Over Time

Purpose The cyclical behavior of US crime rates reflects the dynamics of crime in the country. This paper aims to investigate the US's club convergence of crime rates to provide insights into whether the crime rates increased or decreased over time. The paper also analyzes the factors influencing the probability of states converging to a particular convergence club of crime. Design/methodology/approach The analysis is based on balanced panel data from all 50 states and the district of Columbia on violent and property crime rates covering 1976–2019. This yields a cross-state panel of 2,244 observations with 55 time periods and 51 groups. In addition, the author used a club clustering procedure to investigate the convergence hypothesis in the study. Findings The empirical results support population convergence of violent crime rates. However, the evidence that supports population convergence of property crime rates in the study is not found. Further analysis using the club clustering procedure shows that property crime rates converge into three clubs. The existence of club convergence in property crime rates means that the variation in the property crime rates tends to narrow among the states within each of the clubs identified in the study. Analysis based on an ordered probit model identifies economic, geographic and human capital factors that significantly drive the state's convergence club membership. Practical implications The central policy insight from these results is that crime rates grow slowly over time, as evident by the convergence of violent crime and club convergence of property crime in the study. Moreover, the existence of club convergence of property crime is an indication that policies to mitigate property crime might need to target states within each club. This includes the efforts to use state rather than national crime-fighting policies. Social implications As crimes are committed at the local level, this study's primary limitation is the lack of community-level data on crime and other factors considered. Analysis based on community-level data might provide a better representation of crime dynamics. However, the author hopes to consider this as less aggregated data are available to use in future research. Originality/value The paper provides new insights into the convergence of crime rates using the club convergence procedure in the USA. This is considered an improvement to the methods used in the previous studies.

Local Labor Market Inequality in the Age of Mass Incarceration

2020 ◽  
pp. 003464462096602
Author(s):  
Luke Petach ◽  
Anita Alves Pena
Keyword(s):  
Civil Rights ◽  
Civil Rights Movement ◽  
Local Level ◽  
Mass Incarceration ◽  
The United States ◽  
Data Set ◽  
Incarceration Rate ◽  
Race And Class ◽  
Level Data ◽  
White Poverty

We contend that the rise of mass incarceration in the United States can be framed through the lens of stratification economics, which views race- and class-based discrimination as a rational attempt on behalf of privileged groups to preserve their relative status and the material benefits which that status confers. Using the first (to our knowledge) local-level data set on incarceration rates by race, we explore the relationship between income inequality, poverty, and incarceration at the commuting zone level from 1950 to the present. Consistent with Michelle Alexander’s hypothesis that expansion of the penal system and the rise of “tough on crime” policy were efforts by privileged groups to drive a wedge into working-class political coalitions formed out of the Civil Rights Movement, we find that labor markets with greater inequality experienced larger increases in the overall incarceration rate. Furthermore, we find that relative rates of poverty play a key role in explaining differential effects of mass incarceration across race. Areas where White poverty rates were large relative to non-White poverty rates experienced no significant change in White incarceration, but an expansion of non-White incarceration. These findings have implications for policies related to economic and judicial systems.

International manufacturing network: past, present, and future

2015 ◽  
Vol 35 (3) ◽  
pp. 392-429 ◽  
Author(s):  
Yang Cheng ◽  
Sami Farooq ◽  
John Johansen
Keyword(s):  
Original Data ◽  
Academic Community ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
Research Themes ◽  
Future Research Directions ◽  
Plant Level ◽  
Manufacturing Network ◽  
Level Analysis

Purpose – The purpose of this paper is to examine, and present a comprehensive review of, the existing literature on the international manufacturing network (IMN). Design/methodology/approach – The original data set used for reviewing the IMN literature consisted of 107 articles selected from 21 journals: more specifically, 40 articles are concerned with plant-level analysis, and 67 articles are related to IMN-level analysis. The literature is simultaneously reviewed by two researchers. The relevance and contribution of each reviewed paper is discussed and mutually agreed upon. Findings – The paper highlights the different concepts related to IMN and traces the evolution of IMN-related research. Based on two levels of analysis (i.e. plant and network), this paper further reviews and discusses the IMN-specific literature in detail to determine the number of IMN articles published across the journals, the dominant methodologies employed, and the research focus reflected in IMN studies. A research trajectory is finally developed to provide an integrated and intuitional view on the development of IMN research. Originality/value – This is the first effort that has been made towards thoroughly investigating the existing literature on IMN, aiming to trace different concepts related to IMN from a historical perspective, to review and discuss the IMN-specific literature in detail, to provide an overview of the evolution trajectory of different existing IMN research themes, and to propose future research directions. Keeping in mind the growing importance of IMN for practitioners as well as the academic community, this study provides a timely overview of existing and emerging IMN research themes.

scholarly journals Emerging Trends and Research Foci in Cataract Genes: A Bibliometric and Visualized Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Hongli Zhu ◽  
Zhichang Zhang
Keyword(s):  
Molecular Mechanisms ◽  
The United States ◽  
Future Research ◽  
Analysis Tool ◽  
Bibliometric Method ◽  
Emerging Trends ◽  
Literature Metrology ◽  
Quantitative Analyses ◽  
Occurrence Matrix ◽  
Analysis Platform

Background: Approximately 50% of cataracts are associated with genetic factors. Genetic etiology and molecular mechanisms based on gene research increase the understanding of cataracts and provide direction for diagnosis and intervention. In the present study, SCIE papers related to the modeling of cataract gene research from 2010–2019 were evaluated and qualitative and quantitative analyses with modeling performed.Methods: The SCIE database was searched on July 6, 2021 for cataract gene publications and relevant papers published since 2010 were considered for review. Subsequently, 1,904 SCIE papers associated with cataract genes from 2010–2019 were analyzed using a bibliometric method. The publication, country, institution, journal, references, knowledgebase, keywords, and research hotspots of the papers were analyzed using an online analysis platform of literature metrology, bibliographic item co-occurrence matrix builder (BICOMB), CiteSpace V, and VOS viewer analysis tool.Results: 78 countries published the related articles, and the United States ranks of America had the most publications. Two thousand seven hundred and eighty three institutions contributed to the related publications. Fudan University had the most publications. The reference clusters of SCI papers were clustered into six categories, namely, causing congenital cataract-microcornea syndrome, functional snp, cataractous lenses, a1 mutation, foxe3 mutation, cell adhesion gene pvrl3, nid1 gene. The key words representing the research frontiers were cerebrotendinous xanthomatosis (2017-2019), oxidative stress (2017–2019).Conclusion: This study provided a systematic, objective and comprehensive analysis of the literature related to gene research of cataract. Moreover, this study demonstrated the current hotspots and the future trends in the field of gene research of cataract. This review will help ophthalmologist to discern the dynamic evolution of cataract gene research, as well as highlight areas for future research.

scholarly journals The Unequal Availability of Rental Housing Information Across Neighborhoods

Demography ◽  
2021 ◽  
Author(s):  
Max Besbris ◽  
Ariela Schachter ◽  
John Kuk
Keyword(s):  
Rental Housing ◽  
The United States ◽  
Urban Residents ◽  
Search Process ◽  
Online Information ◽  
Census Tract Level ◽  
Level Data ◽  
Different Types ◽  
Housing Search ◽  
Types Of Information

Abstract As more urban residents find their housing through online search tools, recent research has theorized the potential for online information to transform and equalize the housing search process. Yet, very little is known about what rental housing information is available online. Using a corpus of millions of geocoded Craigslist advertisements for rental housing across the 50 largest metropolitan statistical areas in the United States merged with census tract–level data from the American Community Survey, we identify and describe the types of information commonly included in listings across different types of neighborhoods. We find that in the online housing market, renters are exposed to fundamentally different types of information depending on the ethnoracial and socioeconomic makeup of the neighborhoods where they are searching.

scholarly journals Measuring Job Creation, Growth, and Survival among the Universe of Start-ups in the United States Using a Combined Start-up Panel Data Set

ILR Review ◽  
2019 ◽  
Vol 72 (5) ◽  
pp. 1262-1277 ◽  
Author(s):  
Robert W. Fairlie ◽  
Javier Miranda ◽  
Nikolas Zolas
Keyword(s):  
United States ◽  
Panel Data ◽  
The United States ◽  
Future Research ◽  
Data Set ◽  
Growth And Survival ◽  
Start Up ◽  
The Us ◽  
Start Ups ◽  
The Universe

The field of entrepreneurship is growing rapidly and expanding into new areas. This article presents a new compilation of administrative panel data on the universe of business start-ups in the United States, which will be useful for future research in entrepreneurship. To create the US start-up panel data set, the authors link the universe of non-employer firms to the universe of employer firms in the Longitudinal Business Database (LBD). Start-up cohorts of more than five million new businesses per year, which create roughly three million jobs, can be tracked over time. To illustrate the potential of the new start-up panel data set for future research, the authors provide descriptive statistics for a few examples of research topics using a representative start-up cohort.

An examination of organizational and community effects on police response time

2020 ◽  
Vol 43 (6) ◽  
pp. 935-946
Author(s):  
Nicholas Andrew Salimbene ◽  
Yan Zhang
Keyword(s):  
Response Time ◽  
Hierarchical Linear Modeling ◽  
Police Department ◽  
Organizational Factors ◽  
Community Level ◽  
Police Response ◽  
Data Set ◽  
Content Type ◽  
Community Factors ◽  
The Impact

PurposeThe primary objective of the current study is to examine the impact that the size of a police department and workload on a department have on response time. Secondarily, the authors look at the effect that incident-level factors such as the severity of a call for service (CFS) and community-level factors such as ethnic diversity have on police response time.Design/methodology/approachThe current study examined CFSs data collected over a three-year period and organizational information from 26 police departments in Northeast Texas, as well as community-level information. In order to measure the effect of organizational variables, community factors and incident-level variables on police response time, the authors employed the use of hierarchical linear models (HLMs).FindingsThe results of hierarchical linear modeling indicated that incident-level factors and police department size are significant predictors of response time.Research limitations/implicationsThere are two primary limitations: first, there were a lack of available organizational structure correlates such as age and differentiation. Second, the primary data set had a significant number of incomplete or repeating cases, thereby limiting the accuracy of the current study’s analysis.Originality/valueThe most unique aspect of this manuscript is that it examines how organizational factors affect police response time. Numerous studies analyzed determinants of police response time such as incident- and community-level factors, but the importance of organizational factors has not been analyzed.

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