Evidence map›Paper›PMID 35579667›Full record

ArticleJournal of occupational rehabilitation2022

Demographic Covariates, Vocational Rehabilitation Services, and Employment Outcomes of Working-Age Adults with Anxiety Disorders: A Multivariate Logistic Regression Analysis.

Cahit Kaya, Kanako Iwanaga, Sharon Hsu, Esra Nur Akpinar, Jill Bezyak, Xiangli Chen, Fong Chan

Abstract read
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Article in Journal of occupational rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Cahit KayaUniversity of Texas-Rio Grande Valley, Edinburg, USA. rehber.cahit@gmail.com.ORCID 0000-0003-0757-320X
Kanako IwanagaVirginia Commonwealth University, Richmond, USA.
Sharon HsuNational Changhua University of Education, Taiwan, Taiwan.
Esra Nur AkpinarHarran University, Sanliurfa, Turkey.
Jill BezyakUniversity of Northern Colorado, Greeley, USA.
Xiangli ChenKessler Foundation, West Orange, USA.
Fong ChanUniversity of Wisconsin-Madison, Madison, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to investigate the relationships between demographic covariates, vocational rehabilitation (VR) services, and employment outcomes of individuals with anxiety disorders. The specific research question for the current study investigate demographic variables and vocational rehabilitation services as predictors of competitive employment outcomes.

methodsData for the present study were extracted from the most recent United States Rehabilitation Service Administration 2018 Case Service Report (RSA-911) data. A purposeful selection, multivariate logistic regression analysis was conducted to examine the case service report data of 9266 individuals with anxiety disorders who received vocational rehabilitation services based on their demographic variables and receipt of VR services.

resultsThe results indicated that African Americans and Latinx, people who have completed high school or more, people who do not receive disability-related benefits, and those who received more vocational rehabilitation services were more likely to be gainfully employed. In addition, receipt of financial support for life crises and occupational credentials (i.e., other services and maintenance services) and vocational rehabilitation counseling and guidance services were significant predictors of employment outcomes. Conversely, receipt of supported employment and transition services were negatively associated with employment outcome.

conclusionsIn the present study, we identified VR services that can improve and risk factors that can impede employment outcomes of people with anxiety disorders. We also identified medical, psychosocial, and vocational interventions that can lessen the effect of anxiety disorders on physical and mental health functioning.

Indexed as

Employment, SupportedRehabilitation, VocationalAdultAnxiety DisordersDemographyHumansLogistic ModelsUnited StatesAnxiety disordersMaintenance servicesOther servicesRehabilitation Service AdministrationVocational rehabilitation

Identifiers

PMID35579667
PMCPMC9112255

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.