Purpose: This study sought to determine whether the Test of Integrated Language and Literacy Skills (TILLS; Nelson et al., 2016) can accurately identify language disorders in college-aged adults.
Method: Fifty-nine college students between the ages of 18 and 23 years were administered the test battery validated by Fidler et al. (2011) for the diagnosis of language disorders as well as the Identification Core (ID Core) subtests of the TILLS validated for ages 12-18 years. Sensitivity and specificity information was calculated for the TILLS at various cut-scores to determine the diagnostic accuracy of the ID Core for this population. Discriminant function analysis was also performed to determine if sensitivity and specificity could be improved using empirically derived discriminant scores.
Results: The recommended cut-score of 42 for ages 12-18 years underidentified individuals with language disorders in this sample. An adjusted cut-score of 51 maximized sensitivity and specificity to acceptable levels. Discriminant function analysis also yielded acceptable sensitivity and specificity (> 80%).
Conclusion: Using either an adjusted cut-score for the ID Core or weighted discriminant scores, the TILLS can be used to accurately differentiate between college-aged adults with and without language disorders.
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http://dx.doi.org/10.1044/2023_AJSLP-23-00331 | DOI Listing |
Curr Pain Headache Rep
January 2025
Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA, USA.
Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.
Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.
Purpose: Oral health problems in patients with cancer can substantially affect their quality of life, treatment outcomes, and overall nutritional well-being. This study investigated the relationship between nutritional status and self-reported oral health complaints in patients with cancer.
Materials And Methods: A cross-sectional study was conducted among patients with cancer at the King Saud University Medical City Oncology Center in Riyadh, Saudi Arabia.
NeuroSci
January 2025
Department of Neuroscience "Rita Levi Montalcini", University of Turin, 10126 Turin, Italy.
Dementia, including Alzheimer's disease (AD) and frontotemporal dementia (FTD), presents critical challenges for correctional systems, particularly as global populations age. AD, affecting 60-80% of dementia cases, primarily impairs memory and cognition in individuals over 65. In contrast, FTD, rarer than AD but not uncommon in those under 65, affects the frontal and temporal brain regions, leading to deficits in social behavior, language, and impulse control, often resulting in antisocial actions and legal consequences.
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January 2025
ASL Salerno, 84124, Salerno, Italy.
Motor skills in early and middle childhood are essential for physical play, social interactions, and academic development. Children with autism spectrum disorder (ASD) often exhibit atypical sensory responses, which can impact self-care and other developmental areas. This study explores the impact of sensory and motor rehabilitation using a Motor Sensory Room to stimulate motor development in children with ASD.
View Article and Find Full Text PDFSci Prog
January 2025
Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea.
Introduction: The diagnostic boundaries between schizophrenia and bipolar disorder are controversial due to the ambiguity of psychiatric nosology. From this perspective, it is noteworthy that formal thought disorder has historically been considered pathognomonic of schizophrenia. Given that human thought is partially based on language, we can hypothesize that alterations in language may help differentiate between schizophrenia and bipolar disorder.
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