The performance of older adults and depressed people on linear order reasoning is hypothesized to be best explained by different theoretical models. Whereas depressed younger adults are found to be impaired in generative inference making, older adults are well capable of making such inferences but exhibit problems with working memory (Experiments 1 and 2). Restriction of the available study time impairs reasoning by nondepressed control participants and. as such, proves to be a good model of older adults' but not depressed participants' limitations (Experiment 3). These results are replicated comparing depressed and older participants with a control group in the same study, providing increased power and linking the results to additional control measures of processing speed and working memory (Experiment 4).
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http://dx.doi.org/10.1037/0096-3445.133.2.237 | DOI Listing |
Eur J Radiol
January 2025
Department of Radiology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Neurodevelopment and Cognitive Disorders, China. Electronic address:
Objective: To explore the clinical value of combining split-bolus contrast injection with dual-energy CT(DECT) scanning technology in pediatric computed tomography urography (CTU) imaging.
Methods: A total of 128 children aged 0-17 years were prospectively selected and randomly assigned to three groups: A, B, and C. For Group A, a high-pitch flash mode was employed, where a single bolus of contrast agent was followed by four-phase scanning (noncontrast, cortex, medulla, and excretory phases).
Menopause
January 2025
National Institute of Health, Cheongju, Republic of Korea.
Objectives: We examined the health-related quality of life (HRQoL) during menopause transition (MT) among middle-aged Korean women.
Methods: This cross-sectional study comprised 2,290 middle-aged women who completed web-based questionnaires between 2020 and 2022. Based on self-reported menstrual cycle patterns, menopause status was classified as premenopausal, early or late transition, or postmenopausal.
J Med Internet Res
January 2025
Department of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Background: Despite the increasing popularity of electronic devices, the longitudinal effects of daily prolonged electronic device usage on brain health and the aging process remain unclear.
Objective: The aim of this study was to investigate the impact of the daily use of mobile phones/computers on the brain structure and the risk of neurodegenerative diseases.
Methods: We used data from the UK Biobank, a longitudinal population-based cohort study, to analyze the impact of mobile phone use duration, weekly usage time, and playing computer games on the future brain structure and the future risk of various neurodegenerative diseases, including all-cause dementia (ACD), Alzheimer disease (AD), vascular dementia (VD), all-cause parkinsonism (ACP), and Parkinson disease (PD).
JMIR Res Protoc
January 2025
Department of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, United States.
Background: Low back pain (LBP) is highly prevalent and disabling, especially in agriculture sectors. However, there is a gap in LBP prevention and intervention studies in these physically demanding occupations, and to date, no studies have focused on horticulture workers. Given the challenges of implementing interventions for those working in small businesses, self-management offers an attractive and feasible option to address work-related risk factors and manage LBP.
View Article and Find Full Text PDFJMIR Cancer
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.
Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.
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