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Related Concept Videos

Sources of Self-Esteem III: Social Comparison01:27

Sources of Self-Esteem III: Social Comparison

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Social comparison plays a fundamental role in the evaluation of personal success and self-worth. Rather than assessing our achievements in isolation, we interpret their significance relative to personal goals and critically in comparison to the performance of others. A grade of B in a mathematics exam might elicit pride if one's expectation was a C, yet result in disappointment if an A was anticipated or if peers achieved superior results. These comparative evaluations illustrate how both...
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Protecting Self-Esteem01:27

Protecting Self-Esteem

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Self-esteem, a central component of psychological well-being, is actively maintained through various cognitive and behavioral strategies. Individuals employ specific mechanisms to preserve a positive self-concept and mitigate threats to their self-worth, particularly in contexts involving social evaluation or personal feedback. Four primary techniques are commonly used to sustain self-esteem.Manipulating AppraisalsOne prominent strategy involves manipulating appraisals from others. Individuals...
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Benefits of Self-Esteem01:25

Benefits of Self-Esteem

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Self-esteem—an individual's overall evaluation of their worth—plays a complex role in psychological functioning and well-being. It is often associated with many positive traits, such as confidence, optimism, and perseverance. Individuals with high self-esteem typically experience better sleep, manage peer pressure more effectively, and report greater life satisfaction. Conversely, low self-esteem has been consistently linked with increased risks of depression, anxiety, and poor...
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Self-Evaluation: Self-Enhancement and Self-Verification03:00

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Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
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Sources of Self-Esteem II: Performance Feedback01:24

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Self-esteem is intricately tied to our perception of competence and our ability to exert control over our lives. One of the primary sources of this perception is performance feedback — the ongoing evaluation of our actions in terms of success and failure. According to Franks and Marolla (1976), people derive self-worth from experiencing themselves as causal agents, capable of achieving goals and overcoming obstacles. This process nurtures a critical component of self-esteem:...
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The Sense of Self: Reflected Self-Appraisal and Social Comparison02:57

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According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...
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Leveraging Reddit data for Context-enhanced Synthetic Health Data Generation to Identify Low Self Esteem.

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    This study introduces a novel framework to create synthetic clinical notes from social media data, improving the detection of low self-esteem (LoST) and other psychosocial risks in patients.

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    Area of Science:

    • Computational linguistics
    • Clinical psychology
    • Artificial intelligence in healthcare

    Background:

    • Low self-esteem (LoST) is a significant risk factor for depressive disorders, often undetected in clinical settings.
    • Existing structured tools for self-esteem assessment have limited clinical use, leaving LoST indicators in unstructured clinical notes.
    • Developing natural language processing (NLP) models for LoST detection is hindered by the scarcity of annotated clinical data and privacy concerns with LLM-driven labeling.

    Purpose of the Study:

    • To develop a novel framework for generating context-enhanced synthetic clinical notes from social media narratives.
    • To evaluate the utility of small language models in identifying expressions of low self-esteem within these synthetic notes.
    • To offer a scalable and privacy-preserving solution for synthetic data generation for early detection of psychosocial risks.

    Main Methods:

    • A novel framework was developed to generate context-enhanced synthetic clinical notes from social media (Reddit) data.
    • Small language models were evaluated for their ability to detect low self-esteem indicators.
    • A mixed-method evaluation framework assessed structure, readability, linguistic diversity, and contextual fidelity of synthetic notes.

    Main Results:

    • Synthetic clinical notes generated from social media data can effectively augment scarce clinical corpora.
    • NLP models trained on synthetic data show comparable or superior performance to those trained on real data.
    • The framework demonstrates the potential for translating social media mental health signals into clinically actionable insights.

    Conclusions:

    • The proposed framework offers a scalable, privacy-preserving method for generating synthetic clinical data for psychosocial risk detection.
    • This approach facilitates the early identification of patients at risk for conditions like low self-esteem.
    • It provides a pathway for leveraging readily available online data to enhance clinical NLP applications for mental health.