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Background And Objectives: Sustained computer and internet use have the potential to help older adults in various aspects of their lives, making predicting sustained use a critical goal. However, some factors related to adoption and use (e.g., computer attitudes) change over time and with experience. To understand these dynamics, the current study modeled changes in constructs related to computer use after initial computer adoption and examined whether these changes predict continued use.
Research Design And Methods: We used data from the computer arm ( = 150, = 76.15) of a 12-month field trial examining the potential benefits of computer use in older adults. Individual differences identified in the technology acceptance literature (perceived usefulness, ease of use, computer interest, computer self-efficacy, computer anxiety, quality of life, social isolation, and social support) were measured before (baseline), during (Month 6), and after the intervention (post-test). Univariate and bivariate latent change score models examined changes in each predictor and their potential causal relationship with use.
Results: Results demonstrated large interindividual differences in the change patterns of individual difference factors examined. Changes in perceived usefulness, perceived ease of use, computer interest, computer self-efficacy, and computer anxiety were but change in use.
Discussion And Implications: Our findings demonstrate the limitation of popular constructs in technology acceptance literature in predicting continued use and point out important gaps in knowledge to be targeted in future investigations.
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http://dx.doi.org/10.1093/geroni/igad029 | DOI Listing |
Comput Biol Med
September 2025
INSIGNEO Institute for in silico medicine, University of Sheffield, UK; School of Mechanical, Aerospace and Civil Engineering, University of Sheffield, UK. Electronic address:
Modelling cardiovascular disease is at the forefront of efforts to use computational tools to assist in the analysis and forecasting of an individual's state of health. To build trust in such tools, it is crucial to understand how different approaches perform when applied to a nominally identical scenario, both singularly and across a population. To examine such differences, we have studied the flow in aneurysms located on the internal carotid artery and middle cerebral artery using the commercial solver Ansys CFX and the open-source code HemeLB.
View Article and Find Full Text PDFBiomacromolecules
September 2025
Department of Chemistry, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea.
Marine biofouling poses significant economic and environmental challenges, highlighting the need for effective antifouling coatings. We report amphiphilic poly(SBMA--EGDEA) copolymer coatings that resist both marine diatom adhesion and sediment adsorption. The coatings were synthesized via surface-initiated ATRP and RAFT polymerization using hydrophilic sulfobetaine methacrylate (SBMA) and hydrophobic ethylene glycol dicyclopentenyl ether acrylate (EGDEA).
View Article and Find Full Text PDFInt J Epidemiol
August 2025
Department of Biostatistics and Informatics, University of Colorado, Aurora, CO, United States.
Background: Existing longitudinal cohort study data and associated biospecimen libraries provide abundant opportunities to efficiently examine new hypotheses through retrospective specimen testing. Outcome-dependent sampling (ODS) methods offer a powerful alternative to random sampling when testing all available specimens is not feasible or biospecimen preservation is desired. For repeated binary outcomes, a common ODS approach is to extend the case-control framework to the longitudinal setting.
View Article and Find Full Text PDFJ Org Chem
September 2025
State Key Laboratory of Fine Chemicals, School of Chemical Engineering, Ocean and Life Sciences, Dalian University of Technology, Panjin 124221, P. R. China.
The Buchwald-Hartwig (B-H) reaction graph, a novel graph for deep learning models, is designed to simulate the interactions among multiple chemical components in the B-H reaction by representing each reactant as an individual node within a custom-designed reaction graph, thereby capturing both single-molecule and intermolecular relationship features. Trained on a high-throughput B-H reaction data set, B-H Reaction Graph Neural Network (BH-RGNN) achieves near-state-of-the-art performance with an score of 0.971 while maintaining low computational costs.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Departments of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, Guangdong, 510630, China, 86 18922109279, 86 20852523108.
Background: Despite the Coronary Artery Reporting and Data System (CAD-RADS) providing a standardized approach, radiologists continue to favor free-text reports. This preference creates significant challenges for data extraction and analysis in longitudinal studies, potentially limiting large-scale research and quality assessment initiatives.
Objective: To evaluate the ability of the generative pre-trained transformer (GPT)-4o model to convert real-world coronary computed tomography angiography (CCTA) free-text reports into structured data and automatically identify CAD-RADS categories and P categories.