Objectives: We piloted a computerised cognitive training battery in a group of participants with Parkinson's disease without dementia to investigate the relevance of the training to daily life and the feasibility and the acceptability of the tasks. Previous studies of CT have had limited success in the benefits of training, extending to improvements in everyday function. By taking a pragmatic approach and targeting training to the cognitive skills affected by Parkinson's disease (planning, attention, and recollection), whilst using tasks that emulated real-life scenarios, we sought to understand whether participants perceived the training to be effective and to identify the elements of the training that elicited beneficial effects.
Methods: Four participants completed a cognitive training session comprising three distinct tasks 5 days a week over two weeks. Participants completed baseline questionnaires examining health-related quality of life, everyday cognition, and apathy before the training period, after the last session, and two weeks after the last session. An interview was held after participants had completed the training.
Results: The findings indicated that participants felt the training was acceptable, enhanced their awareness, and encouraged them to monitor their thinking abilities. The group interview indicated that the training was feasible; participants felt the tasks had potential to improve everyday performance, but more supporting information should be provided to facilitate this transfer. Responses to the questionnaires reflected these findings, indicating improvement for some participants' cognition and quality of life. Objective measures supported the subjective reports; there were improvements in some but not all domains. Performance on the planning and recollection tasks improved over the training period, and the evidence for improvement on the attention task was mixed.
Conclusion: This study has found that pragmatic computer-based training with real-life outcomes is both feasible and acceptable and should be evaluated more extensively using controlled methods.
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http://dx.doi.org/10.1155/2019/5258493 | DOI Listing |
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Neurovascular Research Laboratory, Faculty of Life Sciences and Education, University of South Wales, Pontypridd, UK.
To what extent sildenafil, a selective inhibitor of the type-5 phosphodiesterase modulates systemic redox status and cerebrovascular function during acute exposure to hypoxia remains unknown. To address this, 12 healthy males (aged 24 ± 3 y) participated in a randomized, placebo-controlled crossover study involving exposure to both normoxia and acute (60 min) hypoxia (Fi = 0.14), followed by oral administration of 50 mg sildenafil and placebo (double-blinded).
View Article and Find Full Text PDFJ Hand Surg Eur Vol
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View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Chemical Engineering, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan.
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, leading to a scarcity of high-quality activation energy data. In this work, we explore and compare three innovative approaches (transfer learning, delta learning, and feature engineering) to enhance the accuracy of activation energy predictions using graph neural networks, specifically focusing on methods that incorporate low-cost, low-level computational data.
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