德国人口的饮食障碍检查-问卷的截止分数
Adrian Meule1,2,3, Anja Hilbert4, Martina de Zwaan5
1Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Munich, Germany.
The International journal of eating disorders
|January 23, 2024
概括
这项研究确定了德国饮食障碍检查问卷 (EDE-Q) 的可靠切断分数. 约2分的得分有效选饮食障碍 (ED) 并评估治疗进展.
科学领域:
- 精神病学是一个精神病学.
- 临床心理学 临床心理学
- 心理测量 心理测量 心理测量
背景情况:
- 饮食障碍检查问卷 (EDE-Q) 是评估饮食障碍 (ED) 症状的关键自我报告措施.
- 现有的EDE-Q的截止分数缺乏一致性,阻碍了其在临床环境和研究中的应用.
- 建立可靠的切断分数对于准确的ED查和治疗评估至关重要.
研究的目的:
- 通过使用大量的,代表性的德国人口样本来推导和验证EDE-Q的可靠切断分数.
- 确定最佳的EDE-Q值,以区分患有ED的人与对照人.
- 在特定ED诊断 (AN,BN,其他EDs) 中调查最佳切断分数的潜在差异.
主要方法:
- 利用接收器操作特征 (ROC) 分析来评估EDE-Q总分的诊断准确性.
- 在住院住院时,比较了一个大型对照组 (n=2519) 与一组ED患者 (n=2038) 的临床组.
- 对神经性厌食症 (AN),神经性嗜食症 (BN) 和其他ED进行了子组分析,包括年龄和性别匹配的比较.
主要成果:
- EDE-Q总分显示了对照组和患者之间的高分辨能力 (AUC>91%).
- 截止分数为1.6对于将一般对照组与患者区分开来是最佳的,特别是那些患有AN的患者.
- 为了区分对照组与患有BN和其他ED的个体,最佳切断分数在1.8到2.4.之间.
结论:
- 获得的EDE-Q截止分数 (1.6-2.4) 提供了用于查EDS和评估德国人口治疗结果的有效工具.
- 对于患有BN和其他ED的人来说,相比患有AN的人,推的切断分数略高一些.
- 这些发现增强了EDE-Q用于流行率估计和治疗监测的临床实用性.
相关概念视频
01:28Anorexia Nervosa
73
Anorexia nervosa is a complex and severe eating disorder characterized by an intense fear of weight gain, an unrelenting pursuit of thinness, and a distorted body image. It often leads to dangerously low body weight relative to an individual's age and height. This disorder is marked by significant physical and psychological consequences, making it one of the most life-threatening psychiatric illnesses.
Symptoms and Physical Effects
Individuals with anorexia nervosa commonly exhibit extreme...
Symptoms and Physical Effects
Individuals with anorexia nervosa commonly exhibit extreme...
73
01:30Bulimia Nervosa
82
Bulimia nervosa is a complex and severe eating disorder characterized by a cyclical pattern of binge-and-purge eating pattern. It generally involves an episode of binge eating, followed by compensatory behaviors such as vomiting, excessive exercise, laxative use, or fasting, to prevent weight gain. Despite often maintaining a normal weight, individuals with bulimia are intensely preoccupied with their body image and harbor an overwhelming fear of gaining weight. This can contribute to the...
82
01:23Binge Eating Disorders
70
Binge eating disorder is a significant mental health condition characterized by recurrent episodes of excessive food consumption within a short period, accompanied by a perceived loss of control over eating behavior. Unlike occasional overeating, binge eating disorder is marked by distressing emotions such as guilt, shame, and anxiety following binge episodes. The disorder affects individuals across different ages and backgrounds, with profound implications for physical and psychological...
70
01:29Assessment of the Gastrointestinal System II: Health Perception Pattern
119
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
119
01:22Self-Report Tests of Personality
353
Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
353
01:00Detection of Gross Error: The Q Test
6.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.1K