The present research explored the intrinsic relationship of self-reported depressive symptoms and cognitive distortions as proposed by Beck and others. A devised scale of cognitive distortions was correlated with scores on the Beck Depression Inventory for 67 college volunteers. A significant value of 0.59 was found, supporting our hypothesis. There were no sex differences on either scale.
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http://dx.doi.org/10.2466/pr0.1991.68.2.521 | DOI Listing |
J Funct Morphol Kinesiol
January 2025
Department of Medicine and Surgery, Kore University of Enna, 94100 Enna, Italy.
Time estimation was investigated in 24 healthy adults, including 12 women and 12 men, before and after an exhaustive exercise. : We compared the ability of estimating time intervals in the range 1 to 5 s using tasks requiring mental counting and tasks that did not allow it. Time estimation and blood lactate levels were evaluated before and at the end of the exercise.
View Article and Find Full Text PDFActa Neuropsychiatr
January 2025
IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Objective: Time distortions characterise severe mental disorders, exhibiting different clinical and neurobiological manifestations. This systematic review aims to explore the existing literature encompassing experimental studies on time perception in patients with bipolar disorder (BD), considering psychopathological and cognitive correlates.
Methods: Studies using an experimental paradigm to objectively measure the capacity to judge time have been searched for.
Br J Hosp Med (Lond)
December 2024
Department of Clinical Nutrition, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China.
This study expanded the existing literature on obesity and distortion of body image by examining subjective and objective body type among young medical workers, specifically investigating whether fat percentage independently influences body type cognitive bias. We recruited 264 participants (41.29% male, mean age 26.
View Article and Find Full Text PDFFunctional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts.
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