Employment self-disclosure rates and rationales of university graduates with learning disabilities.

J Learn Disabil

Department of Educational Technology, Neag School of Education, University of Connecticut, CT, USA.

Published: August 2008

Five hundred graduates with learning disabilities (LD) from three universities in the United States completed a survey related to their postschool employment outcomes and experiences. The present study presents data related to their decisions regarding LD disclosure in employment settings. Although 73% of the respondents reported that the LD affected their job in some way, only 55% reported self-disclosing, and only 12% reported requesting accommodations. Specific reasons for each of these decisions are presented, as are areas in which LD affect work, strategies for dealing with LD in the workplace, and perceptions of the Americans with Disabilities Act. Implications for secondary and postsecondary programs are discussed.

Download full-text PDF

Source
http://dx.doi.org/10.1177/0022219407313805DOI Listing

Publication Analysis

Top Keywords

graduates learning
8
learning disabilities
8
employment self-disclosure
4
self-disclosure rates
4
rates rationales
4
rationales university
4
university graduates
4
disabilities graduates
4
disabilities three
4
three universities
4

Similar Publications

Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.

View Article and Find Full Text PDF

We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.

View Article and Find Full Text PDF

Validation of Machine Learning-assisted Screening of PKC Ligands: PKC Binding Affinity and Activation.

Biosci Biotechnol Biochem

January 2025

Division of Food Science and Biotechnology, Graduate School of Agriculture, Kyoto University, Kyoto, 606-8502, Japan.

Protein kinase C (PKC) is a family of serine/threonine kinases, and PKC ligands have the potential to be therapeutic seeds for cancer, Alzheimer's disease, and human immunodeficiency virus infection. However, in addition to desired therapeutic effects, most PKC ligands also exhibit undesirable pro-inflammatory effects. The discovery of new scaffolds for PKC ligands is important for developing less inflammatory PKC ligands, such as bryostatins.

View Article and Find Full Text PDF

Evaluating amyloid-beta aggregation and toxicity in transgenic Caenorhabditis elegans models of Alzheimer's disease.

Methods Cell Biol

January 2025

Federal University of Santa Maria, Center for Natural and Exact Sciences, Department of Biochemistry and Molecular Biology, Graduate Program in Biological Sciences: Toxicological Biochemistry, Camobi, Santa Maria, RS, Brazil.

Alzheimer's disease (AD) is the leading cause of dementia in the elderly, clinically characterized by memory loss, cognitive decline, and behavioral disturbances. Its pathogenesis is not fully comprehended but involves intracellular depositions of amyloid beta peptide (Aβ) and neurofibrillary tangles of hyperphosphorylated tau. Currently, pharmacological interventions solely slow the progression of symptoms.

View Article and Find Full Text PDF

Enhancing public health outcomes with AI-powered clinical surveillance: Precise detection of COVID-19 variants using qPCR and nanopore sequencing.

J Infect Public Health

January 2025

Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan. Electronic address:

Background: We aimed to evaluate the efficacy of integrating the Varia5 multiplex assay (qPCR) and whole genome sequencing (WGS) for monitoring SARS-CoV-2, focusing on their overall performance in identifying various virus variants.

Methods: This study included 140 naso-pharyngeal swab samples from individuals with suspected COVID-19. We utilized our self-developed Varia5 multiplex assay, which targets five viral genes linked to COVID-19 mutations, in conjunction with comprehensive genomic analysis performed through whole genome sequencing (WGS) using the Oxford Nanopore system.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!