Uncertainty Reduction Theory

Published on October 21, 2011
by The Glaring Facts

Uncertainty Reduction Theory – Charles R. Burger

Initial interactions between strangers are characterized by information seeking in order to reduce uncertainty. Uncertainty is reduced as levels of self-disclosure, nonverbal warmth, and similarity increase.

  • When people interact, they will act to reduce the uncertainty about the other person, seeking ways to predict their behavior. This is particularly true when they first meet and they do not know one another. The most common way of reducing uncertainty is via information-seeking, questioning the other person, for example about their background. We start with the opening small-talk before moving on to the meat of the conversation. Other approaches are to find out indirectly about the person (e.g. by asking a friend) or to passively observe them.
    • e.g. Upon meeting someone who sits next to you in a class, you begin to ask questions about that person in order to reduce uncertainty. Chances are high that they will reciprocate and seek to reduce uncertainty as well.

Quick overview:

Objectivist theory –> has hypothesis, uses quantitative methods

  • How do people cope with new interpersonal situations? What people do and how they cope with new relationships.
  • People are like scientists, trying to predict others’ behaviour. What’s going to happen next, what’s the person going to do? How are we going to get along with this person?

Uncertainty

  • Icky
  • Influences our communication. A negative force in reduction theory.
  • Our motive to decrease our uncertainty goes up
    • Anticipation of future interaction. If you’re expecting to see him/her again later, you’ll be fighting that uncertainty.
    • Incentive value. Does that person have something you’ll like? Is this person rewarding. Social Exchange theory.
    • Deviance Peaks our curiosity.

Uncertainty Reduction

  • The process of using communication to gather information about someone to improve your ability to explain and predict their behaviour (towards you).
  • Eight axioms describe how uncertainty relates to other variables.

Selected Axioms

  • #3 More uncertainty = more information seeking. If you have lower levels of uncertainty, you can predict rather accurately.
  • #6 More similarity = Less uncertainty. The more you see you have in common with the other person, teh less uncertainty you’ll perceive of the other person. If you two feel you have some common ground, you will have less uncertainty.
  • #7 More uncertainty = Less talking. If you have higher uncertainty, you will like the other person less. A lot of ppl disagree with. The intriguing stranger, people who like mystery.

Information Seeking Strategies

  • Passive strategy would just be to watch them, would be to see them. Who they talk to, who they hang out with. Observe them.
  • Active strategy. Ask other people about the target uncertainty.
  • Interactive strategy

Weaknesses

  • Complex: 28 theorems is not parsimonious.
  • Fails to predict reliably
  • Conclusions appear mundane (Eidenmuller)

Strengths

  • Explanatory Power
  • Practical utility: suggestions to negotiate first encounters.
  • Heuristic: Interesting theory has led to a lot of research and new theories.

Events that increase uncertainty (romantic relationships)

  • Meeting someone new, spending time apart, a betrayal, your friends say you spend too much time w/ partner.
  • Relational uncertainty: confidence in your perception of a romantic relationship (Knobloch & Solomon). It might affect the ongoing relationships.
  • Moderately intimate relationships have highest relational uncertainty.

Problematic Integration Theory

  • Probability: How likely is it?
  • Evaluation: Is it Good or Bad?
    • Likelihood of an occurance = value. Whether it’s good or bad, sometimes they work together.
  • Easy Integration.
    • Good + Likely
  • Probability and Evaluation diverge: Likely & Negative or Unlikely & Positive. It’s likely to happen and it’s negative. Super unlikely but it’s positive. Divergence between our evaluation and probability.
  • Ambiguity: Can’t Predict what’s going to happen. Makes it really hard if you would like to do something but you couldn’t predict how it would run.
  • Ambivalence: Conflicting evaluation. You have either two positive or negative. You have two jobs both look good but it’s hard to decide between them. Sometimes we like uncertainty.
    • E.G. We don’t like negative news, maybe the test was wrong..maybe you don’t have this disease. We would want to increase your uncertainty to help you progress in an illness.

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