Working memory (WM) training has gained interest due to its potential to enhance cognitive functioning and reduce symptoms of mental disorders. Nevertheless, inconsistent results suggest that individual differences may have an impact on training efficacy. This study examined whether individual differences in training performance can predict therapeutic outcomes of WM training, measured as changes in anxiety and depression symptoms in sub-clinical and healthy populations. The study also investigated the association between cognitive abilities at baseline and different training improvement trajectories. Ninety-six participants (50 females, mean age = 27.67, SD = 8.84) were trained using the same WM training task (duration ranged between 7 to 15 sessions). An algorithm was then used to cluster them based on their learning trajectories. We found three main WM training trajectories, which in turn were related to changes in anxiety symptoms following the training. Additionally, executive function abilities at baseline predicted training trajectories. These findings highlight the potential for using clustering algorithms to reveal the benefits of cognitive training to alleviate maladaptive psychological symptoms.
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http://dx.doi.org/10.1007/s00426-022-01728-1 | DOI Listing |
BMC Med Educ
December 2024
Department of Orthopedics, Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, 151203, India.
Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning to create diverse content, enabling personalized learning, enhancing resource accessibility, and facilitating interactive case studies. This narrative review explores the integration of generative artificial intelligence (AI) into orthopedic education and training, highlighting its potential, current challenges, and future trajectory.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Obstetrics, Division of Obstetrics and Gynecology, Oslo University Hospital Rikshospitalet, Oslo, Norway.
Preeclampsia is a pregnancy disorder with substantial perinatal and maternal morbidity and mortality. Pregnant women at risk of preeclampsia would benefit from early detection for follow-up, timely interventions and delivery. Several attempts have been made to identify protein biomarkers of preeclampsia, but findings vary with demographics, clinical characteristics, and time of sampling.
View Article and Find Full Text PDFChild Abuse Negl
December 2024
Instituto Universitário de Lisboa (ISCTE-IUL), CIS-IUL, Lisboa, Portugal.
Background: Youth in residential care (RC) reveal high-risk trajectories, which require upholding their rights and providing them with opportunities to participate.
Objective: We aimed to identify staff profiles focused on their perceptions of participation and the association with sociodemographic variables.
Participants And Setting: This study included quantitative analysis of qualitative data collected from 87 professionals in the RC (M = 38.
Public Health
December 2024
Department of Data Science, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, India. Electronic address:
Objectives: Stillbirths, the tragic loss of a baby before or during delivery, presents a profound global health concern. Investigating the diverse causes and risk factors is essential to develop targeted interventions, enhance perinatal care, and reduce the incidence of this devastating outcome. The aim of this study was to identify the causes and possible risk factors of stillbirths in India.
View Article and Find Full Text PDFJ Robot Surg
December 2024
Department of Thyroid Surgery, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, P. R. China.
Since its introduction, robotic surgery has experienced rapid development and has been extensively implemented across various medical disciplines. It is crucial to comprehend the advancements in research and the evolutionary trajectory of its thematic priorities. This research conducted a bibliometric analysis on the literature pertaining to robotic surgery, spanning the period from 2014 to 2023, sourced from the Web of Science database.
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