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相关概念视频

Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about the way you...
Bullying02:04

Bullying

A modern form of aggression is bullying. As you learn in your study of child development, socializing and playing with other children is beneficial for children’s psychological development. However, as you may have experienced as a child, not all play behavior has positive outcomes. Some children are aggressive and want to play roughly. Other children are selfish and do not want to share toys. One form of negative social interactions among children that has become a national concern is bullying.
Deindividuation00:57

Deindividuation

Deindividuation is a form of social influence on an individual’s behavior such that the individual engages in unusual or non-normal behavior while in a group setting. Why? Because in these group settings, the individual no longer sees themselves as an individual anymore, disinhibiting their behavior and personal restraint.

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使用机器学习和网络分析,在青少年自我伤害行为中识别基于的风险网络.

Zheng Zhang1, Honghui Chen2,3, Yanyue Ye1

  • 1Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.

Translational psychiatry
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概括

青少年自我伤害行为 (SIB) 是由诸如孤独,焦虑和互联网成等因素预测的. 了解这些相互关联的风险是早期干预和预防策略的关键.

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科学领域:

  • 精神病学是一个精神病学.
  • 心理学 心理学 心理学
  • 公共卫生 公共卫生

背景情况:

  • 青少年自我伤害行为 (SIB) 影响全球13.7%,需要早期识别和干预,以防止自杀和自我伤害.
  • 对SIB日益增长的认识凸显了对强大的预测机制的迫切需要.

研究的目的:

  • 使用精神病学网络理论探索青少年SIB的多维风险因素.
  • 通过整合网络分析和机器学习来开发精确的风险评估方法.

主要方法:

  • 在中国调查了2047名青少年 (年龄11-17岁),分析了19个生理,心理和社会变量.
  • 应用机器学习,网络分析和重法 (EWM) 进行风险评估.

主要成果:

  • 确定了关键的风险因素:孤独,ADHD症状,上网成,焦虑,抑郁,对孤独的亲和,自闭症特征和欺凌.
  • 揭示了这些因素相互作用的复杂网络结构,直接和间接地影响SIB.
  • 电子商务管理,网络分析和机器学习集成提供了更精确的青少年SIB风险评估.

结论:

  • 调查结果为SIB的因果机制提供了洞察力,强调相互关联的风险因素.
  • 强调针对青少年SIB的有针对性的预防和干预策略的重要性.
  • 综合方法为评估青少年SIB风险提供了更准确的方法.