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Regression Analysis01:11

Regression Analysis

6.0K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
6.0K
Stereotype Content Model02:16

Stereotype Content Model

14.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.9K
Traits, Mood, and Subjective Wellbeing01:22

Traits, Mood, and Subjective Wellbeing

126
Subjective well-being (SWB) refers to an individual's self-evaluation of their overall life satisfaction, happiness, and fulfillment. This multifaceted construct is typically assessed by analyzing the balance of positive and negative emotions alongside perceptions of life satisfaction. Personality traits such as neuroticism and extraversion are strongly associated with variations in SWB, offering critical insights into the underlying mechanisms of emotional well-being.
Neuroticism and...
126
Attitudes01:54

Attitudes

29.5K
Attitude is our evaluation of a person, an idea, or an object. We have attitudes for many things ranging from products that we might pick up in the supermarket to people around the world to political policies. Typically, attitudes are favorable or unfavorable: positive or negative (Eagly & Chaiken, 1993). And, they have three components: an affective component (feelings), a behavioral component (the effect of the attitude on behavior), and a cognitive component (belief and knowledge;...
29.5K
Regression Toward the Mean01:52

Regression Toward the Mean

6.5K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.5K
Long-term Depression01:03

Long-term Depression

2.6K
Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Calcium Ion Concentration Mechanism
If over...
2.6K

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相关实验视频

Updated: Sep 8, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

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在基于文本的咨询中评估情绪变化的异质性:隐藏类轨迹分析

Ziru Fu1, Yu Cheng Hsu2, Christian Shaunlyn Chan3

  • 1Department of Social Work and Social Administration, Faculty of Social Sciences, Faculty of Social Sciences, University of Hong Kong, Hong Kong, China (Hong Kong).

Journal of medical Internet research
|September 5, 2025
PubMed
概括

研究人员在网上咨询中发现了三种情绪轨迹:稳定改善,恶化和反弹. 这些模式的早期识别可以增强基于文本的心理健康支持.

关键词:
增长混合模型隐藏类轨迹分析多项逻辑回归情绪分析基于文本的咨询

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科学领域:

  • 数字心理健康
  • 计算社会科学
  • 临床心理学

背景情况:

  • 基于文本的在线辅导正在增长,但其性质在监测用户情绪转变方面存在挑战.
  • 匿名性和文本格式阻碍了个性化干预,可能会影响服务的有效性和用户满意度.

研究的目的:

  • 在线基于文本的辅导中识别寻求帮助者的独特的会议内情感轨迹.
  • 检查与不同情绪轨迹成员关系的关键变量.

主要方法:

  • 在6207个辅导会议中使用增长混合模型 (GMM) 进行潜在类轨迹分析.
  • 通过ChatGPT标记的求助信息的情绪评分被用于轨迹建模.
  • 多项逻辑回归确定了与类成员关系相关的变量.

主要成果:

  • 三个不同的情绪轨迹被确定:稳定改善 (18.9%),恶化 (18.0%),然后反弹 (63.1%).
  • 病情恶化的轨迹与自杀念头,家庭/身体健康问题,及早结束治疗相关.

结论:

  • 在基于文本的在线辅导中存在不同的会议内情感轨迹.
  • 早期识别这些轨迹可以使辅导员能够调整干预措施,提高数字心理健康服务的有效性和满意度.