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Related Concept Videos

Social Exchange Theory02:06

Social Exchange Theory

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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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We typically love the people with whom we form relationships, but the type of love we have for our family, friends, and lovers differs. Robert Sternberg (1986) proposed that there are three components of love: intimacy, passion, and commitment. These three components form a triangle that defines multiple types of love: this is known as Sternberg’s triangular theory of love. Intimacy is the sharing of details and intimate thoughts and emotions. Passion is the physical attraction—the...
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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
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Confidence Coefficient01:24

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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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Updated: Jul 16, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
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The value of connections.

Vanessa Rossetto Marcelino1

  • 1Melbourne Integrative Genomics, School of Biosciences and Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia.

Elife
|September 19, 2023
PubMed
Summary

High levels of self-feeding gut bacteria signal poor gut health. This finding highlights a new indicator for assessing the gut microbiome

Keywords:
bacteriacomputational biologyecologygastrointestinal disordersgut microbiomehumaninflammatory bowel diseasemetabolismmicrobial ecologysystems biology

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Area of Science:

  • Microbiology
  • Gastroenterology
  • Human Health

Background:

  • The gut microbiome plays a crucial role in human health.
  • Understanding microbial metabolic capabilities is key to assessing gut health.
  • Certain bacteria possess the ability to synthesize their own nutrients.

Discussion:

  • Elevated abundance of autotrophic (self-feeding) bacteria correlates with detrimental gut conditions.
  • This suggests a shift in microbial community structure indicative of dysbiosis.
  • Further research is needed to elucidate the precise mechanisms linking these bacteria to poor health outcomes.

Key Insights:

  • A high proportion of gut bacteria capable of producing their own food is a significant indicator of compromised gut health.
  • This metabolic characteristic can serve as a novel biomarker for gut dysbiosis.
  • The study identifies a specific bacterial trait linked to negative health status.

Outlook:

  • Future studies should explore therapeutic interventions targeting these self-feeding bacteria.
  • Developing diagnostic tools based on this indicator could revolutionize gut health assessment.
  • Longitudinal studies will be essential to confirm the causal relationship and predictive value.