Objectives: To assess the intention of using a Writing Aid software, which integrates four research reporting guidelines (Consolidated Standards of Reporting Trials, Preferred Reporting Items for Systematic Reviews and Meta-Analyses, Strengthening the Reporting of Observational Studies in Epidemiology and STrengthening the Reporting of Observational Studies in Epidemiology-nutritional epidemiology) and their Elaboration & Explanation (E&E) documents during the write-up of research in Microsoft Word compared with current practices.
Design: Two-arms crossover randomised controlled trial with no blinding and no washout period.
Setting: Face-to-face or online sessions.
Participants: 54 (28 in arm 1 and 26 in arm 2) doctoral and postdoctoral researchers.
Interventions: Reporting guidelines and their E&E document were randomly administered as Writing Aid or as Word documents in a single 30 min to 1 hour session, with a short break before crossing over to the other study intervention.
Primary And Secondary Outcomes: Using the Technology Acceptance Model, we assessed the primary outcome: the difference in the mean of intention of use; and secondary outcomes: the difference in mean perceived ease of use and perceived usefulness. The three outcomes were measured using questions with a 7-point Likert-scale. Secondary analysis using structural equation modelling (SEM) was applied to explore the relationships between the outcomes.
Results: No significant difference in reported intention of use (mean difference and 95% CI 0.25 (-0.05 to 0.55), p=0.10), and perceived usefulness (mean difference and 95% CI 0.19 (-0.04 to 0.41), p=0.10). The Writing Aid performed significantly better than the word document on researchers' perceived ease of use (mean difference and 95% CI 0.59 (0.29 to 0.89), p<0.001). In the SEM analysis, participants' intention of using the tools was indirectly affected by perceived ease of use (beta 0.53 p0.002).
Conclusions: Despite no significant difference in the intention of use between the tools, administering reporting guidelines as Writing Aid is perceived as easier to use, offering a possibility to further explore its applicability to enhance reporting adherence.
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http://dx.doi.org/10.1136/bmjopen-2019-030943 | DOI Listing |
PLoS One
January 2025
Institute of Psychiatry, Psychology & Neuroscience at King's College London, London, United Kingdom.
Fluctuation-related pain (FRP) affects more than one third of people with Parkinson's disease (PwP, PD) and has a harmful effect on health-related quality of life (HRQoL), but often remains under-reported by patients and neglected by clinicians. The National Institute for Health and Care Excellence (NICE) recommends The Parkinson KinetiGraphTM (the PKGTM) for remote monitoring of motor symptoms. We investigated potential links between the PKGTM-obtained parameters and clinical rating scores for FRP in PwP in an exploratory, cross-sectional analysis of two prospective studies: "The Non-motor International Longitudinal, Real-Life Study in PD-NILS" and "An observational-based registry of baseline PKG™ in PD-PKGReg".
View Article and Find Full Text PDFCancers (Basel)
December 2024
Science of Functional Recovery and Reconstruction, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8558, Japan.
: Developing high-performance artificial intelligence (AI) models for rare diseases is challenging owing to limited data availability. This study aimed to evaluate whether a novel three-class annotation method for preparing training data could enhance AI model performance in detecting osteosarcoma on plain radiographs compared to conventional single-class annotation. : We developed two annotation methods for the same dataset of 468 osteosarcoma X-rays and 378 normal radiographs: a conventional single-class annotation (1C model) and a novel three-class annotation method (3C model) that separately labeled intramedullary, cortical, and extramedullary tumor components.
View Article and Find Full Text PDFDiagnostics (Basel)
January 2025
Aging + Cardiovascular Discovery Center, Department of Biomedical Education and Data Science, Lewis Katz School of Medicine of Temple University, Philadelphia, PA 19140, USA.
We have demonstrated in human cadavers and canines that nerve transfer to bladder vesical nerve branches is technically feasible for bladder reinnervation after nerve injury. We further clarify here that sacral (S) ventral rami contribute to these vesical branches in 36 pelvic sides (in 22 human cadavers). Gross post-mortem visualization and open anterior abdominal approaches were used, as was micro-CT of sacral nerve bundles, for further confirmation when needed.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Vegetable Crops Department, Faculty of Agriculture, Alexandria University, Alexandria 21545, Egypt.
Soil salinity and the scarcity of freshwater resources are two of the most common environmental constraints that negatively affect plant growth and productivity worldwide. The tomato ( Mill.) plant is moderately sensitive to salinity.
View Article and Find Full Text PDFAdv Skin Wound Care
January 2025
At the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, United States, Adrian Chen, BS, Aleksandra Qilleri, BS, and Timothy Foster, BS, are Medical Students. Amit S. Rao, MD, is Project Manager, Department of Surgery, Wound Care Division, Northwell Wound Healing Center and Hyperbarics, Northwell Health, Hempstead. Sandeep Gopalakrishnan, PhD, MAPWCA, is Associate Professor and Director, Wound Healing and Tissue Repair Analytics Laboratory, School of Nursing, College of Health Professions, University of Wisconsin-Milwaukee. Jeffrey Niezgoda, MD, MAPWCA, is Founder and President Emeritus, AZH Wound Care and Hyperbaric Oxygen Therapy Center, Milwaukee, and President and Chief Medical Officer, WebCME, Greendale, Wisconsin. Alisha Oropallo, MD, is Professor of Surgery, Donald and Barbara Zucker School of Medicine and The Feinstein Institutes for Medical Research, Manhasset New York; Director, Comprehensive Wound Healing Center, Northwell Health; and Program Director, Wound and Burn Fellowship program, Northwell Health.
Generative artificial intelligence (AI) models are a new technological development with vast research use cases among medical subspecialties. These powerful large language models offer a wide range of possibilities in wound care, from personalized patient support to optimized treatment plans and improved scientific writing. They can also assist in efficiently navigating the literature and selecting and summarizing articles, enabling researchers to focus on impactful studies relevant to wound care management and enhancing response quality through prompt-learning iterations.
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