State-level differences in public vocational rehabilitation closures among transition-aged youth with traumatic brain injury

2020 ◽  
Vol 26 (2) ◽  
pp. 136-142
Author(s):  
Charles Edmund Degeneffe ◽  
Mark Tucker ◽  
Zaccheus James Ahonle
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Vocational Rehabilitation ◽  
Population Size ◽  
Unemployment Rate ◽  
Capita Income ◽  
State Level ◽  
Fiscal Year ◽  
Per Capita Income ◽  
Per Capita

AbstractThis study aimed to understand state-level variation in participation in the State/Federal Vocational Rehabilitation (State VR) System in the United States among transition-aged youth (persons under the age of 22 years at application for State VR services) with traumatic brain injury (TBI) in Federal Fiscal Year 2016. A weighted least squares regression analysis was conducted to determine the relationship of state-level population size, unemployment rate, and per-capita income to the number of State VR closures in each state for transition-aged youth with TBI. Population size and per-capita income significantly predicted closures, while there was no relationship between closures and unemployment rate. Research is needed that further explores and explains state-level disparities in participation among transition-aged youth with TBI.

The Influence of State-Level Contextual Factors on State/Federal System Vocational Rehabilitation Employment Outcomes for Persons With Traumatic Brain Injury

2022 ◽  
pp. 003435522110675
Author(s):  
Charles Edmund Degeneffe ◽  
Mark Tucker ◽  
Meredith Ross ◽  
Emre Umucu
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Vocational Rehabilitation ◽  
Contextual Factors ◽  
State Level ◽  
Employment Outcomes ◽  
Fiscal Year ◽  
Hierarchical Logistic Regression ◽  
Rehabilitation System ◽  
Veteran Status

The purpose of this exploratory study was to develop a preliminary understanding of the influence of state-level contextual factors predictive of employment outcomes for State/Federal Vocational Rehabilitation System (State VR) participants with traumatic brain injury (TBI). Participants were 5,213 individuals with TBI with Individualized Plans for Employment closed during Federal Fiscal Year 2016. A four-step hierarchical logistic regression model (5.6% explained variance) containing five demographic, three state-level economic, six state TBI service climate, and nine State VR service variable expenditures correctly classified 57.0% of cases as attaining or not attaining an employment outcome at closure. Significant predictors associated with an employment closure were (a) education, veteran status, and presence of a secondary area of disability impairment; (b) state-level per-capita income; (c) State VR specialized acquired brain injury (ABI)/TBI service and state TBI Implementation Partnership grant funding; and (d) State VR service expenditures on diagnosis and treatment, occupational or vocational training, on-the-job training, job readiness training, transportation, maintenance support, and benefits counseling. The practice, policy, and research implications of these findings are presented.

scholarly journals Income and Unemployment Are Associated with Proportion of Baby-Friendly Hospital Initiative Facilities in US States (OR30-01-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Sara Benjamin-Neelon ◽  
Sarah Gonzalez-Nahm ◽  
Brian Neelon
Keyword(s):  
Low Income ◽  
Capita Income ◽  
Census Data ◽  
Newborn Infants ◽  
State Level ◽  
Baby Friendly Hospital Initiative ◽  
Per Capita Income ◽  
American Hospital ◽  
Us States ◽  
Per Capita

Abstract Objectives The Baby-Friendly Hospital Initiative (BFHI) is a global effort designed to enhance the health of mothers and their newborn infants by protecting, promoting, and supporting breastfeeding. Evidence has shown that BFHI hospitals can help reduce disparities in breastfeeding rates—especially in low-income communities. We aimed to evaluate the geographic distribution of BFHI hospitals, considering the socioeconomic factors of income and unemployment in the US. Methods We considered all hospitals within each state. We categorized hospitals as having the BFHI designation (“established”), being on the formal path to obtaining this designation (“emerging”), and not having the designation. We obtained a list of hospitals from the American Hospital Association's annual survey and information on BFHI designation from Baby-Friendly USA. We further obtained state-level employment and income information from census data and ranked states into quintiles for each variable. We then conducted separate one-way analysis of variance tests to compare the mean % of BFHI hospitals and mean state-level 1) per capita income, and 2) unemployment rates separated into quintiles. We examined all BFHI hospitals that were established and emerging separately. Finally, we created maps using ArcGIS, overlaying the location of all hospitals on the socioeconomic data. Results Our sample included 2,589 hospitals from all US states and the District of Columbia. Of those, 519 were established BFHI hospitals (Figure 1) and 298 were emerging (Figure 2). We found that higher unemployment was associated with a greater percentage of emerging but not established BFHI hospitals were present in states in the highest quintile for unemployment (P = 0.01). Similarly for income, we observed a greater percentage of emerging BFHI hospitals in states with both the lowest and highest quintiles of per-capita income (P = 0.003). Conclusions Emerging BFHI hospitals were present at a higher percentage in states in the highest quintile for unemployment and the lowest quintile for income. These emerging hospitals are on the pathway to achieving the BFHI designation, which may ultimately help reduce socioeconomic disparities in breastfeeding. Interestingly, states in the highest quintile for income also had a high percentage of emerging BFHI hospitals. Funding Sources W.K. Kellogg Foundation. Supporting Tables, Images and/or Graphs

Relationships among States' Fiscal and Demographic Data and the Implementation of P.L. 94–142

1992 ◽  
Vol 59 (3) ◽  
pp. 247-261 ◽  
Author(s):  
Margaret J. McLaughlin ◽  
Maria F. Owings
Keyword(s):  
Special Education ◽  
Capita Income ◽  
Demographic Data ◽  
State Level ◽  
Special Education Students ◽  
Per Capita Income ◽  
Students With Learning Disabilities ◽  
Study Implementation ◽  
Per Capita ◽  
Restrictive Settings

This study examined the relationships between state-level fiscal and demographic variables and identification rates and cumulative placement rates for certain categories of special education students in 1976, 1980, and 1983. The study explored the feasibility of using extant national data to study implementation of special education programs. Identification rates for students with learning disabilities and emotional disturbance were associated with level of state per-capita income and proportion of rural school-age population. States with higher per-capita income tended to have higher cumulative placement rates in special classes and all more restrictive settings.

scholarly journals Economic Factors behind Social Entrepreneurship in Bangladesh

2019 ◽  
Vol 2 (2) ◽  
pp. p115
Author(s):  
Farhana Yasmin ◽  
Farhana Ferdousi Aziz
Keyword(s):  
Human Capital ◽  
Regression Analysis ◽  
Labor Force ◽  
Unemployment Rate ◽  
Capita Income ◽  
The Self ◽  
Per Capita Income ◽  
Literacy Rate ◽  
Self Employment ◽  
Per Capita

Bangladesh has pool of entrepreneurs whereas there are also new establishments; new employment opportunities and so are the income sources. For the better measurement of entrepreneurship characteristics, the growth and different indicators impact on entrepreneurship needs to be identified. Thus this paper tries to find out the key economic indicators of entrepreneurship in the context of Bangladesh. The research is based on secondary research; has used entrepreneurship as a dependent variable proxied by self-employment and seven independent variables—per capita income, unemployment rate, labor force, industrial structure change, capital, human capital and literacy rate. Two regression models have been used encompassing the stated variable data from year 2008 to 2018. In the first regression analysis it has been tried to identify whether the model can be constructed with the overall economic variables with the self employment. At second regression model it has been tried to find out whether there is the explain ability of the variables result in the regression analysis and what is the degree and pattern of the relationship. The research shows that literacy rate and human capital have aligned with the self employment. But all the other variables are not matched with the self employment and could not provide the support for self employment to thrive. And the linear regression analysis shows that per capita income, labor force and literacy rate play the most important role in case of nourishing self employment. Unemployment rate is found as contradictory with the findings in the context of Bangladesh.

scholarly journals Var Modelling of Dynamics of Poverty, Unemployment, Literacy and Per Capita Income in Nigeria

2019 ◽  
Vol 19 (1) ◽  
pp. 73-88
Author(s):  
Adefemi Alamu Obalade ◽  
Ayooluwade Ebiwonjumi ◽  
Anthony Olugbenga Adaramola
Keyword(s):  
Unemployment Rate ◽  
Capita Income ◽  
Poverty Reduction ◽  
High Rate ◽  
Var Model ◽  
National Bureau ◽  
Per Capita Income ◽  
Literacy Rate ◽  
Per Capita ◽  
The Impact

Abstract Research background: Poverty, unemployment, literacy and per capita income are intertwined. However, there seems to be a disconnect between literacy and good living in Nigeria. Purpose: This study investigated the dynamic relationship between poverty, unemployment, literacy and per capita income in Nigeria by examining the impact, shocks and responses among these identified variables. Research methodology: The secondary data on poverty, unemployment and literacy rates were extracted from the National Bureau of Statistics and per capita income was extracted from the World Bank Annual Report. A vector autoregressive (VAR) model of lag order (4) was adopted for the study. Results: The results revealed that poverty rate is an increasing function of unemployment rate and literacy rate and a reducing function of per capita income. The results further showed that dynamics of poverty is affected by shocks in unemployment rate, literacy rate and per capita income. Novelty: Therefore, the study concluded that literacy rate fails as a vital tool for poverty reduction and that the high rate of unemployment results in chronic poverty. The application of VAR to untangle the interrelationship among the variables, without doubt, adds to the literature on the uses of the VAR model.

A 'melanoma mortality belt' of ten U.S. states with the highest melanoma mortality rates.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e21039-e21039
Author(s):  
Alan Geller ◽  
Juliana Berk-Krauss ◽  
David Polsky ◽  
Jennifer Stein
Keyword(s):  
United States ◽  
Unemployment Rate ◽  
Capita Income ◽  
Mortality Rates ◽  
Education Level ◽  
Median Income ◽  
Per Capita Income ◽  
Central United States ◽  
Per Capita ◽  
Melanoma Mortality

e21039 Background: To our knowledge, no study has looked at U.S. melanoma mortality trends by state. We sought to determine the ten states with the highest melanoma mortality rates (per white population) and those with the lowest, as well as any state-wide demographics that could account for these trends. Methods: State melanoma mortality rates were collected from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program and National Program for Cancer Registries. Data on state characteristics were collectied from the Area Health Resource File (AHRF) and the US Census Bureau. We used a regression model to determine associations between melanoma mortality and the state demographic context, such as median income, per capita income, unemployment rate, education level, and rural versus nonrural. We also examined the effect of access to health care resources by looking at density of dermatologists, density of primary care providers, and total number of hospitals. Results: We identified ten states concentrated across the central United States with the highest melanoma mortality rates. Per capita income was the only significant association for melanoma mortality rates (p = 0.0016, 95% CI 6.88 to 18.09). Median income, unemployment rate, education level, rural versus non-rural, health professional density, and unemployment rate were not associated with melanoma mortality rates by state. Conclusions: There exists a ‘melanoma mortality belt’ across the central United States made up of the ten states with the highest melanoma mortality rates. This trend could not be consistently accounted for by state demographics, even socioeconomic status traditionally thought to correlate with mortality. Only one significant association was seen between melanoma mortality rate and per capita income. Our preliminary findings highlight the multifactorial picture of geographic melanoma mortality inequalities in the U.S.

scholarly journals FACTORS INFLUENCING PERSONAL BANKRUPTCY AMONG YOUTH IN MALAYSIA

2021 ◽  
Vol 3 (7) ◽  
pp. 85-91
Author(s):  
Suzana Hassan ◽  
Muhamad Khodri Kholib Jati ◽  
Nurul Huda Md Yatim ◽  
Mohd Azlan Abd Majid
Keyword(s):  
Unemployment Rate ◽  
Financial Literacy ◽  
Capita Income ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Per Capita Income ◽  
Personal Bankruptcy ◽  
Factors Influencing ◽  
Per Capita

The objective of this paper is to explore the factors influencing personal bankruptcy among youth in Malaysia. This paper intended in creating more awareness and give more information to Malaysian about the importance of personal insolvency is due to the increasing of personal insolvency cases from year to year especially in 2016, 2017, and 2018 which involves 290,001, 300,958, and 303,415 cases. Some Malaysian have issues in financial literacy and it will lead to growth in personal bankruptcy cases if there is less initiative to avoid it. Other than that, the objectives of this paper are to discover whether a Non-Performing Loan, unemployment rate, and per capita income affect the bankruptcy cases in Malaysia. This paper using secondary data analysis using time series data yearly starting from 1985 until 2017 and it is consisting of thirty-three observations. The result showed Non-Performing Loan and per capita income are positively significant with personal bankruptcy while positively insignificant with the unemployment rate.

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