Writing tasks that encourage an appreciation of body functionality can improve women's body image and may buffer against negative effects of idealised media exposure. However, no research has examined whether these tasks can serve as a coping strategy after idealised exposure. To this end, young adult women (N = 217, M = 21.63) recruited from an Australian university and general community completed a writing task after idealised media exposure, with state body image measures taken at baseline, post-exposure, and post-task. Women were randomly allocated to one of three writing tasks and asked to appreciate their body functionality, to focus on the previously viewed images (rumination), or to describe a frequently travelled route (distraction). Improvements on outcome measures were equally found across both the functionality and distraction condition. Only body appreciation uniquely improved in the functionality condition. The functionality task was rated more helpful but also more challenging. These findings add to the evidence base regarding the usefulness of functionality-based writing tasks for improving women's body image. They can offer immediate benefits when experiencing body image distress, as can distraction, and future research should explore their utility in driving more sustained and deeper ways of engaging with one's body long-term.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.bodyim.2024.101782 | 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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!