Twenty-five undergraduate students were instructed to feign believable impairment following a brain injury from a car accident and 27 students were told to perform like they had recovered from such an injury. Three forced-choice tests, the Test of Memory Malingering (TOMM), Victoria Symptom Validity Test (VSVT), and Word Memory Test (WMT) were given. Test-taking strategies were evaluated by means of a questionnaire given at the end of the test session. The results revealed that all the tasks differentiated between groups. Using conventional cut-scores, the WMT proved most efficient while the VSVT captured the most participants in the definitive below-chance category. Individuals instructed to feign injury were more likely to prepare prior to the experiment, with feigning of memory loss as the most frequently reported strategy. Regardless, preparation effort did not translate into believable performance on the tests.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1076/clin.16.4.495.13909 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Negative association between 15 obesity- and lipid-related indices and testosterone in adult males: a population based cross-sectional study.
Lipids Health Dis
January 2025
Department of Urology, Qilu Hospital of Shandong University, 107 Wenhuaxi Road Jinan, Shandong, 250012, People's Republic of China.
Background: An association exists between obesity and reduced testosterone levels in males. The propose of this research is to reveal the correlation between 15 indices linked to obesity and lipid levels with the concentration of serum testosterone, and incidence of testosterone deficiency (TD) among adult American men.
Methods: The study utilized information gathered from the National Health and Nutrition Examination Survey (NHANES) carried out from 2011 to 2016.
Warrick score in rheumatoid-arthritis interstitial lung disease: a promising tool for assessing the extent and progression of lung involvement.
Adv Rheumatol
January 2025
Division of Rheumatology, Department of Internal Medicine, Kocaeli University Faculty of Medicine, İzmit, Kocaeli, 41380, Turkey.
Background: The clinical manifestations and course of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) exhibits considerable heterogeneity. In this study, we aimed to explore radiographic progression over a defined period, employing the Warrick score as a semi-quantitative measure in early RA-ILD, and to assess the associated risk factors for progression.
Methods: RA-ILD patients underwent consecutive Warrick scoring based on initial high-resolution computed tomography (HRCT) at diagnosis and the first follow-up.
A multicenter study of neurofibromatosis type 1 utilizing deep learning for whole body tumor identification.
NPJ Digit Med
January 2025
Neurofibromatosis Type 1 Center and Laboratory for Neurofibromatosis Type 1 Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.
View Article and Find Full Text PDFMachine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007-2016.
Sci Rep
January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Kunming Children's Hospital, Kunming, Yunnan, China.
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS.
View Article and Find Full Text PDFAutomated mechanical ventilator design and analysis using neural network.
Sci Rep
January 2025
School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India.
Mechanical ventilation is the process through which breathing support is provided to patients who face inconvenience during respiration. During the pandemic, many people were suffering from lung disorders, which elevated the demand for mechanical ventilators. The handling of mechanical ventilators is to be done under the assistance of trained professionals and demands the selection of ideal parameters.
View Article and Find Full Text PDFWant 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!