Rehabilitation-Related Research on Disability and Employer Practices Using Individual-Based National and Administrative Data Sets

Objective:It is useful to examine workplace factors influencing employment outcomes of individuals with disabilities and the interplay of disability, employment-related, and employer characteristics to inform rehabilitation practice.Design:A number of large national survey and administrative data sets provide information on employers and can inform this inquiry.Results:Provides an overview of 9 national survey and administrative data sets that can be used to investigate the impact of employer practices on employment outcomes for individuals with disabilities.Conclusions:Provides specific examples of disability and employment research, which can be performed with these data sets and implications for rehabilitation policy, practice, and research.

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Translating Knowledge Through Blended Learning: A Comparative Analysis of Face-To-Face and Blended Learning Methods

Rehabilitation Research Policy and Education ◽

10.1891/2168-6653.26.4.305 ◽

2012 ◽

Vol 26 (4) ◽

pp. 305-314 ◽

Cited By ~ 1

Author(s):

P Golden Thomas ◽

Karpur Arun

Keyword(s):

Comparative Analysis ◽

Blended Learning ◽

People With Disabilities ◽

Employment Outcomes ◽

Learning Model ◽

Individuals With Disabilities ◽

Face To Face ◽

Traditional Program ◽

Online Tutorials ◽

The Impact

This study is a comparative analysis of the impact of traditional face-to-face training contrasted with a blended learning approach, as it relates to improving skills, knowledge and attitudes for enhancing practices for achieving improved employment outcomes for individuals with disabilities. The study included two intervention groups: one participated exclusively in a half-day traditional face-to-face training program entitled Disability is Diversity; the other participated in both the traditional program and also accessed a series of additional online tutorials to reinforce knowledge translation. The pre-/post-analysis of participants indicated a statistically significant increase in knowledge and intentions of improving employment outcomes for people with disabilities across both groups. A six-month post-training follow-up provided important details about the continued impact of training on improving employment for individuals with disabilities. Specifically, participants who participated in the blended learning model were more likely to advocate the use of leading practices compared to those who attended only the traditional program. Thus, use of a blended learning model appears to increase capacity building of practicing professionals as they approach employment issues for people with disabilities as an issue of diversity, leading toward improved employment outcomes.

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Launching a statewide employment first initiative: Indiana’s work to include coalition

Journal of Vocational Rehabilitation ◽

10.3233/jvr-211133 ◽

2021 ◽

pp. 1-6

Author(s):

Pat Rogan ◽

Susan Rinne

Keyword(s):

Civil Rights ◽

Employment Outcomes ◽

The State ◽

Significant Disabilities ◽

Individuals With Disabilities ◽

Working Age ◽

State Employment ◽

Day Services ◽

Disability Employment ◽

Bureau Of Labor Statistics

BACKGROUND: After decades of local, state and national efforts to increase employment outcomes for individuals with disabilities, progress has been slow, with a mere 17.9% of persons with a disability employed in 2020 compared to 61.8% for persons without a disability (U.S. Bureau of Labor Statistics, February 2021). Individuals with disabilities have demonstrated their abilities and desire to work, including those with significant disabilities, yet our country remains entrenched in outdated and ineffective models of day services (i.e., sheltered workshops, non-work programs) and precious public dollars continue to be used for these services that congregate and segregate individuals, pay subminimum wages, and deny individuals their human and civil rights. OBJECTIVE: The purpose of this article is to describe one state’s efforts to advance employment for working age individuals with disabilities through a statewide Employment First initiative called Work to Include. Indiana is now in its third year of this grassroots initiative driven by a coalition of self-advocates. Major activities of the initiative are discussed, including passing Indiana’s Employment First law, holding statewide Town Hall meetings, establishing 11 local Work to Include teams, developing and implementing a state Employment First plan, launching local and statewide Disability Employment Awareness month campaigns, using social media and webinars to disseminate information, hosting Employment First Summits, and collaborating with employers and state agencies to promote employment outcomes. CONCLUSION: Next steps toward systems change are discussed, including the establishment of an Employment First office at the state and securing an Executive Order from the governor to make the state a model employer.

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Differentiating Incident from Recurrent Stroke Using Administrative Data: The Impact of Varying Lengths of Look-Back Periods on the Risk of Misclassification

Neuroepidemiology ◽

10.1159/000478016 ◽

2017 ◽

Vol 48 (3-4) ◽

pp. 111-118 ◽

Cited By ~ 12

Author(s):

John Mark Worthington ◽

Melina Gattellari ◽

Chris Goumas ◽

Bin Jalaludin

Keyword(s):

Administrative Data ◽

Hospital Admissions ◽

Recurrent Stroke ◽

Haemorrhagic Stroke ◽

Data Sets ◽

South Wales ◽

Look Back ◽

Hospital Administrative ◽

The Impact ◽

Risk Of Misclassification

Background/Aims: Administrative data are widely used to monitor epidemiological trends in stroke and outcomes; yet there is scant empirical guidance on how to best differentiate incident from recurrent stroke. Methods: We identified all hospital admissions in New South Wales, Australia, with a principal stroke diagnosis from July 1, 2013 to June 30, 2014, linked to 12 years of previous admissions. We calculated the proportion of cases identified with a prior stroke to determine the number of years of look-back required to minimise misclassification of incident and recurrent strokes. Results: Using the maximum available look-back period of 12 years, 1,171 out of 8,364 eligible stroke cases (14.0%) had a stroke history. A 1-year look-back period identified only 25.1% of these patients and 1 in 10 stroke cases were misclassified as incident. With a 10-year clearance period, less than 1 in 100 stroke cases were misclassified as incident. The risk of misclassification was lower in patients younger than 65 years and in those with haemorrhagic stroke. Conclusion: Hospital administrative data sets linked to prior admissions can be used to distinguish recurrent from incident stroke. The risk of misclassifying recurrent stroke cases as incident events is negligible with a look-back period of 10 years.

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Australia’s State Specific and Regional Migration Schemes: exploring permanent and temporary skilled migration outcomes in South Australia

Australian Population Studies ◽

10.37970/aps.v3i2.50 ◽

2019 ◽

Vol 3 (2) ◽

pp. 16-28

Author(s):

George Tan ◽

Andreas Cebulla ◽

Anna Ziersch ◽

Andrew Taylor

Keyword(s):

South Australia ◽

Employment Outcomes ◽

Regional Migration ◽

Factors Influencing ◽

Employment Factors ◽

To Come ◽

The University ◽

Temporary Migrants ◽

The Impact ◽

Skilled Migrant

Background Recent concerns about population growth and its consequences in Sydney and Melbourne have added momentum to the debate on ways to achieve a more even geographic distribution of population. However, there is little contemporary evidence about the impact of regionally-focused immigration policies in delivering positive migrant outcomes and easing pressures in major cities.Aims The aim of this paper is to compare migration, employment and settlement outcomes between permanent and temporary skilled migrants to South Australia (SA) as well as the factors influencing migrants’ decisions to move into and out of the State. Data and methods Data in this paper draws on the South Australian General Skilled Migrant survey of State-sponsored skilled migrants conducted by The University of Adelaide in 2015. Results Lifestyle and employment factors were important in decisions to come to, stay or leave SA. Permanent migrants were more likely to choose SA as a destination because it was perceived as a good place to raise a family, while temporary migrants were more likely to cite employment. Temporary visa holders had relatively poor employment outcomes. Conclusions Temporary and permanent visa holders experienced different settlement and employment outcomes, demonstrating that a more detailed understanding of migrant characteristics and outcomes may be useful in designing and evaluating regionally-focused migration initiatives.

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How to Psychologically Minimize Scratching Impulses

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000183 ◽

2014 ◽

Vol 222 (3) ◽

pp. 140-147 ◽

Cited By ~ 5

Author(s):

Ariane Sölle ◽

Theresa Bartholomäus ◽

Margitta Worm ◽

Regine Klinger

Keyword(s):

Cognitive Processes ◽

Placebo Effect ◽

Psychological Factors ◽

Pharmacological Treatments ◽

Physiological Basis ◽

Psychological Mechanisms ◽

Physical Complaints ◽

Factors Influencing ◽

The Impact ◽

Placebo Model

Research in recent years, especially in the analgesic field, has intensively studied the placebo effect and its mechanisms. It has been shown that physical complaints can be efficiently reduced via learning and cognitive processes (conditioning and expectancies). However, despite evidence demonstrating a large variety of physiological similarities between pain and itch, the possible transfer of the analgesic placebo model to itch has not yet been widely discussed in research. This review therefore aims at highlighting potential transfers of placebo mechanisms to itch processes by demonstrating the therapeutic issues in pharmacological treatments for pruritus on a physiological basis and by discussing the impact of psychological mechanisms and psychological factors influencing itch sensations.

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The Long-Term Impact of Disability, Employment, and Marital Status Shocks: Evidence from Matched Administrative Data

SSRN Electronic Journal ◽

10.2139/ssrn.3315584 ◽

2019 ◽

Author(s):

Owen Haaga ◽

Richard Warren Johnson

Keyword(s):

Marital Status ◽

Administrative Data ◽

Long Term Impact ◽

Disability Employment

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Art Creation as an Instrument in Education of Individuals with Disabilities

Lifelong Learning ◽

10.11118/lifele2016060156 ◽

2016 ◽

Vol 6 (1) ◽

pp. 56-69

Author(s):

Pavel Sochor

Keyword(s):

Art Education ◽

Inclusive Education ◽

Outsider Art ◽

Individuals With Disabilities ◽

Artistic Style ◽

Models Of Disability ◽

Art Brut ◽

Mainstream Society ◽

The Impact

Theoretical study deals with approaches towards art education of individuals with disabilities. Arts and Education are crucial cultural components and significantly affect the quality of life of people with disabilities in our society. Nowadays both components may serve to promote the ideas od lifelong inclusive education. Intervention in education is influenced by models of disability concepts reflecting different approaches. Art therapy and approach presenting the impact of disability on the basis of social reality is confronted with the presentation of disabled artist´s personality and his diversity. Unique environment of art education centres and art studios provides opportunity for cultivation of personality of a person with disability. The establishment of author with a disablity in artistic style art brut and outsider art in mainstream society can be considered as a form of socialization.

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Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

Journal Of Big Data ◽

10.1186/s40537-021-00488-w ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Yahya Albalawi ◽

Jim Buckley ◽

Nikola S. Nikolov

Keyword(s):

Social Media ◽

Deep Learning ◽

Comprehensive Evaluation ◽

Classification Problem ◽

Data Sets ◽

Word Embeddings ◽

Data Set ◽

Lower Accuracy ◽

Health Related ◽

The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

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