@文章{信息:doi/10.2196/14115，作者=“Ralph-Nearman, Christina和Arevian, Armen C和Puhl, Maria和Kumar, Rajay和Villaroman, Diane和Suthana, Nanthia和Feusner, Jamie D和Khalsa, Sahib S”，标题=“一种新颖的移动工具(Somatomap)来评估身体图像感知试验与时尚模特和非模特:横向研究”，期刊=“JMIR Ment Health”，年=“2019”，月=“10月”，日=“29”，卷=“6”，数字=“10”，页=“e14115”，关键词=“身体图像;身体知觉;身体表征;身体形象障碍;进食障碍;移动健康;心理健康;手机应用程序;背景:一般来说，对身体和外观的扭曲感知是包括神经性厌食症和身体畸形障碍在内的几种精神疾病的核心特征，并在非临床人群中不同程度地发生。然而，鉴于身体形象知觉的主观性和多种表现形式，评估它具有挑战性。 The currently available methods have several limitations including restricted ability to assess perceptions of specific body areas. To address these limitations, we created Somatomap, a mobile tool that enables individuals to visually represent their perception of body-part sizes and shapes as well as areas of body concerns and record the emotional valence of concerns. Objective: This study aimed to develop and pilot test the feasibility of a novel mobile tool for assessing 2D and 3D body image perception. Methods: We developed a mobile 2D tool consisting of a manikin figure on which participants outline areas of body concern and indicate the nature, intensity, and emotional valence of the concern. We also developed a mobile 3D tool consisting of an avatar on which participants select individual body parts and use sliders to manipulate their size and shape. The tool was pilot tested on 103 women: 65 professional fashion models, a group disproportionately exposed to their own visual appearance, and 38 nonmodels from the general population. Acceptability was assessed via a usability rating scale. To identify areas of body concern in 2D, topographical body maps were created by combining assessments across individuals. Statistical body maps of group differences in body concern were subsequently calculated using the formula for proportional z-score. To identify areas of body concern in 3D, participants' subjective estimates from the 3D avatar were compared to corresponding measurements of their actual body parts. Discrepancy scores were calculated based on the difference between the perceived and actual body parts and evaluated using multivariate analysis of covariance. Results: Statistical body maps revealed different areas of body concern between models (more frequently about thighs and buttocks) and nonmodels (more frequently about abdomen/waist). Models were more accurate at estimating their overall body size, whereas nonmodels tended to underestimate the size of individual body parts, showing greater discrepancy scores for bust, biceps, waist, hips, and calves but not shoulders and thighs. Models and nonmodels reported high ease-of-use scores (8.4/10 and 8.5/10, respectively), and the resulting 3D avatar closely resembled their actual body (72.7{\%} and 75.2{\%}, respectively). Conclusions: These pilot results suggest that Somatomap is feasible to use and offers new opportunities for assessment of body image perception in mobile settings. Although further testing is needed to determine the applicability of this approach to other populations, Somatomap provides unique insight into how humans perceive and represent the visual characteristics of their body. ", issn="2368-7959", doi="10.2196/14115", url="http://mental.www.mybigtv.com/2019/10/e14115/", url="https://doi.org/10.2196/14115", url="http://www.ncbi.nlm.nih.gov/pubmed/31469647" }