Introduction: The study was conducted in order to investigate the effect of disease-related variables such as socio-demographic characteristics, disease complaints and use of necrosis factor (anti-TNF) on the body image and self-esteem in patients with rheumatoid arthritis.
Method: The data was collected by an Introductory Information Form, Body Image Scale (PfP) BIS and the Coopersmith Self-Esteem Inventory (SEI) in 120 patients with rheumatoid arthritis and in 120 healthy controls. One-way analysis of variance, Tukey HDS analysis, t-test, Kruskal-Wallis test, the Mann-Whitney U test, and Pearson's and Spearman's correlation coefficients were used to compare the data.
Result: 60% of the control group were in the 20-44 year-age group, 75% were women and 30.8% had a bachelor's degree or above, while 60% of patient group were in the 20-44 year-age group, 71.7% were women and 36.7% had a bachelor's degree or higher education level. We observed that the body satisfaction and self-esteem levels were higher in the 20-44 age group, in those with a bachelor's degree or higher education and in the patients who had no additional disease and who did not use anti-TNF. The body satisfaction and self-esteem levels were lower in those who had been receiving treatment for longer than 5 years, who had changes in hands and body, who had gait disturbance and who had changes in family and working life.
Conclusion: The assessment of the psychosocial needs with a holistic approach and training programs for body image and self-esteem would be advisable for patients with rheumatoid arthritis who are aged 45-59 years, who have low self-esteem, who have additional diseases, who use anti-TNF, who have changes in hands and body and who have primary-school education.
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http://dx.doi.org/10.4274/npa.y6195 | DOI Listing |
Sci Rep
January 2025
Division of Cancer Systems Biology, Aichi Cancer Center Research Institute, Nagoya, Aichi, Japan.
This study aimed to address the limitations of conventional methods for measuring skeletal muscle mass for sarcopenia diagnosis by introducing an artificial intelligence (AI) system for direct computed tomography (CT) analysis. The primary focus was on enhancing simplicity, reproducibility, and convenience, and assessing the accuracy and speed of AI compared with conventional methods. A cohort of 3096 cases undergoing CT imaging up to the third lumbar (L3) level between 2011 and 2021 were included.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Marketing, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
A preregistered audit of 600 images by generative AI across 150 different prompts explores the link between humor and discrimination in consumer-facing AI solutions. When ChatGPT updates images to make them "funnier", the prevalence of stereotyped groups changes. While stereotyped groups for politically sensitive traits (i.
View Article and Find Full Text PDFSaudi Med J
January 2025
From the Department of Family and Community Medicine (Alsaidan, Thirunavukkarasu), College of Medicine, Jouf University, Aljouf; and from the Department of Public Health (Alsulami), Maternity and Children Hospital, Makkah, Kingdom of Saudi Arabia.
Objectives: To determine body shape concerns (BSCs), sexual satisfaction, and associated factors in patients with polycystic ovarian syndrome (PCOS).
Methods: Using a structured and validated questionnaire, a cross-sectional survey was carried out at the Maternity and Children's Hospital in Makkah, Saudi Arabia. Data were collected between August 2023 and June 2024.
Comput Biol Med
January 2025
Department of Simulation and Graphics, Faculty of Computer Science, University of Magdeburg, Universitätsplatz 2 39106, Magdeburg, Germany; Department of Computational Medicine, Ilmenau University of Technology, Germany.
Purpose: This paper presents a deep learning-based multi-label segmentation network that extracts a total of three separate adipose tissues and five different muscle tissues in CT slices of the third lumbar vertebra and additionally improves the segmentation of the intermuscular fat.
Method: Based on a self-created data set of 130 patients, an extended Unet structure was trained and evaluated with the help of Dice score, IoU and Pixel Accuracy. In addition, the interobserver variability for the decision between ground truth and post-processed segmentation was calculated to illustrate the relevance in everyday clinical practice.
Expert Rev Mol Diagn
January 2025
Department of Electronics and Communication Engineering, IIITDM Kancheepuram, Chennai, India.
Introduction: Cancer ranks as the second most prevalent cause of death worldwide, responsible for approximately 9.6 million deaths annually. Approximately one out of every six deaths is caused by cancer.
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