Purpose: This study described the use of complementary/alternative medicine (CAM) for arthritis management among community-dwelling older women in urban, suburban, and rural areas.
Data Sources: A descriptive qualitative approach using focus group method was employed. A purposive sample of 50 women ages 66-101 who managed arthritis with CAM participated in eight semistructured focus groups: rural (n=22), suburban (n=17), and urban areas (n=11). Data were transcribed verbatim. Inductive analytic process and computer software were used for data analysis.
Conclusions: A wide variety of self-help CAM were reported. Supplements were the most commonly used CAM across all locations; rural participants reported the greatest variety of CAM use. Physical symptoms, dissatisfaction with conventional medicine, perceived safety and convenience of CAM, and a desire for personal control over one's health motivated CAM use. Most participants did not fully disclose their CAM use to their primary healthcare provider (HCP).
Implications For Practice: Results suggest a strong need for primary HCP to purposely dialogue with their clients on CAM use when designing, organizing, and delivering arthritis care. Information on safe CAM use and greater options for effective arthritis management with CAM are needed. The value of group-based model for treating arthritis deserves further exploration.
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http://dx.doi.org/10.1002/2327-6924.12063 | DOI Listing |
Front Physiol
December 2024
Department of Oral & Maxillofacial Surgery, Shenzhen Stomatology Hospital, Affiliated to Shenzhen University, Shenzhen, Guangdong Province, China.
Introduction: This study aimed to develop a deep learning-based method for interpreting magnetic resonance imaging (MRI) scans of temporomandibular joint (TMJ) anterior disc displacement (ADD) and to formulate an automated diagnostic system for clinical practice.
Methods: The deep learning models were utilized to identify regions of interest (ROI), segment TMJ structures including the articular disc, condyle, glenoid fossa, and articular tubercle, and classify TMJ ADD. The models employed Grad-CAM heatmaps and segmentation annotation diagrams for visual diagnostic predictions and were deployed for clinical application.
Front Robot AI
December 2024
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China.
To address the problems of the labeling curved surfaces vegetable with long label, such as the label wrinkled and the easy detachment, a cam-elliptical gear combined labeling mechanism with an improved hypocycloid trajectory is proposed. Provide the process of the mechanism, and establish a kinematic model of the mechanism. In order to improve the motion performances of the cam-elliptical gear combined labeling mechanism and avoid labels damage, the NSGA-II algorithm is used to optimize the parameters of the mechanism, resulting in 80 sets of Pareto solutions.
View Article and Find Full Text PDFTurk J Med Sci
December 2024
Division of Oncology, Department of Internal Medicine, Altunizade Acıbadem Hospital, İstanbul, Turkiye.
Background/aim: The Memorial Sloan Kettering Cancer Center (MSKCC) nomogram was developed to predict survivorship in gastric cancer patients undergoing R0 resection. This study aimed to evaluate the predictive power of this nomogram in the Turkish patient population.
Materials And Methods: Gastric cancer patients over 18 years of age who were admitted to our clinic between 2000 and 2019 and underwent primary curative surgery and R0 resection were included in the study.
J Prosthet Dent
December 2024
Associate Professor and Department Head, Department of Prosthodontics, University of Ferrara, Ferrara, Italy.
The purpose of this article was to present a novel clinical workflow for the fabrication of complete dentures using computer-aided design and computer-aided manufacturing (CAD-CAM) technology. The dental technique consists of 3 clinical steps and 2 laboratory phases that result in the production of 2 CAD-CAM milled complete denture bases with prefabricated teeth. The integration of analog and digital procedures and materials maximizes their benefits in the planning and fabrication of complete dentures, with the goal of improving clinical outcomes.
View Article and Find Full Text PDFNitric Oxide
December 2024
Key Laboratory for Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China. Electronic address:
Background: Osteocytes are crucial for detecting mechanical stimuli and translating them into biochemical responses within the bone. The primary cilium, a cellular 'antenna,' plays a vital role in this process. However, there is a lack of direct correlation between cilium length changes and osteocyte mechanosensitivity changes.
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