Uncertainty Reduction Theory: 10 Examples and Definition

uncertainty reduction theory examples and definition

Uncertainty Reduction Theory (URT) is a communication theory that focuses on reducing anxiety in social interactions. It explores how communication is used to gain knowledge, create understanding, and reduce uncertainty.

To communicate well, people must have insight into their conversation partner’s background information.

This knowledge enables them to accurately anticipate the other person’s responses and reactions, forming a strong bond over time.

As an example of uncertainty reduction theory, two new acquaintances may build trust by exchanging names and general facts about themselves. In doing so, they each gain insight into the other person’s beliefs, values, and perspectives.

Such practice allows them to understand each other better and predict their behavior in future interactions. As a result of this chance encounter, two relative strangers can now forge an immediate bond of trust and form lasting relationships.

Definition of Uncertainty Reduction Theory

Uncertainty reduction theory, developed in 1975 by Charles Berger and Richard Calabrese, is one of the few communication theories that explicitly considers the initial interaction between people before the actual communication process.

It postulates that when two people first meet, they experience a high level of uncertainty or discomfort due to the unknown.

According to Brunner (2019),

“…uncertainty reduction theory asserts that people need to reduce uncertainty about others by gaining information about them” (p. 208)

This theory suggests that by sharing information about themselves, people can reduce the levels of uncertainty and tension between them to create a more comfortable relationship (Costa, 2015).

So, in simple terms, URT explains how communication is used to reduce the unease experienced between two people when they first meet.

By exchanging information, those involved can build a mutual understanding, which leads to more trust and comfort.

Related Theory: Media Richness Theory

Uncertainty Reduction Theory Examples

  • Introducing Yourself: When two people first meet, they usually introduce themselves to each other. This simple act of exchanging names and basic information helps to create a level of familiarity and comfort between them.
  • Conversation: Engaging in meaningful conversations is another way to reduce uncertainty. People can get to know each other better and gain a deeper understanding by discussing topics of interest.
  • Asking Questions: Asking questions is a great way to learn more about the other person and reduce uncertainty. It could be anything from personal opinions to life experiences. For example, asking someone about their favorite hobby or where they grew up is a great way to reduce tensions.
  • Sharing Personal Facts: Talking about personal experiences, such as schooling, family life, or career goals, can help people to get to know each other better. It can also help them to gain insight into the other person’s values and beliefs.
  • Nonverbal Cues: The way people carry themselves- their facial expressions, body language, posture, etc.- conveys much information about them. By monitoring nonverbal cues, people can understand the other person’s emotions and reactions (see also: high context communication).
  • Making Eye Contact: Eye contact is one of the most potent nonverbal cues people use to communicate with others. Making eye contact during conversations can create a feeling of trust and understanding between people.
  • Body Language: People use body language to display emotions and intentions. Gestures such as smiling, nodding, or putting your hand on someone’s shoulder can help reduce uncertainty and create a feeling of comfort.
  • Small Talk: Making small talk, such as discussing the weather or current events, is another way to reduce uncertainty and create a sense of connection between people. Even though it may seem mundane, this type of conversation can be beneficial for getting to know someone better.
  • Teasing: Teasing is a great way to reduce uncertainty and create a more comfortable relationship. However, ensuring that the teasing isn’t too personal or offensive is essential.
  • Compliments: Complimenting someone on their appearance, work ethic, intelligence, etc., can help to build trust and understanding between two people. People appreciate being recognized and complimented, which helps reduce uncertainty.

Origins of Uncertainty Reduction Theory

The uncertainty reduction theory is based on the information theory developed by Claude Shannon and Warren Weaver in 1948 (Cobley & Schultz, 2013).

Scientists believe that at the initial stage of communication, uncertainty appears due to the expectation of different behaviors of the interlocutor and/or the high probability of using each of the possible behaviors.

According to information theory, uncertainty decreases with a decrease in alternatives and/or with a repeated selection of the same reaction from all possible in a particular situation (Cobley & Schultz, 2013).

URT was proposed in 1975 to explain the behavior patterns of strangers on first contact. Berger and Calabrese noticed that when communicating with strangers, people experience insecurity because they do not know what to expect (Cushman & Kovačic, 1995).

However, with further communication, people receive more information, contributing to the rapid reduction of uncertainty (and, as a side-effect, reduction in likelihood of the false consensus bias).

Initially, the theory was a set of axioms that described the relationship between uncertainty and critical factors in developing relationships. Later, out of 7 fundamental axioms, 20 theorems were formulated by deduction.

Main Types of Uncertainty

According to Berger and Calabrese, the level of uncertainty directly depends on the number of options for the expected actions and reactions. So, they distinguished two main types of uncertainty – cognitive and behavioral.

1. Cognitive Uncertainty

Cognitive uncertainty is associated with the lack of knowledge about the other person. It involves questions such as “Who is this person? What are their values, beliefs, and opinions?” (Costa, 2015).

The degree of cognitive uncertainty involved in the beliefs and attitudes that two parties have towards each other is known as cognitive uncertainty.

Early interactions are particularly uncertain due to a lack of understanding regarding the other party’s beliefs or feelings.

2. Behavioral Uncertainty

Behavioral uncertainty is associated with difficulty predicting how the other person will act or react in certain situations.

It involves questions such as “What will they do? How will they respond to my actions?” (Costa, 2015).

The degree of behavioral uncertainty is based on the number of alternative ways an individual can behave in a given situation. Early interactions are particularly uncertain due to a lack of experience with the other person. 

7 Key Axioms of Uncertainty Reduction Theory

Uncertainty reduction theory (URT) has seven fundamental axioms that describe the connection between communication and uncertainty (Floyd et al., 2017).

  1. Verbal Communication: As the level of uncertainty between strangers begins to transition into an entry phase, verbal communication will likely increase. This decrease in tension for each individual involved further encourages conversation between them. Thus, with a reduced sense of apprehension comes more talk and dialogue amongst parties.
  • Non-Verbal Communication: Nonverbal communication, such as facial expressions and gestures, is also essential in reducing uncertainty. When non-verbal affiliative expressiveness rises, uncertainty levels in a primary interaction situation will plummet.
  • Information Seeking: At the onset of any conversation, questions are exchanged to gain clarity and understanding. When there is a high degree of uncertainty present, more queries will be posed as a means to acquire additional information. As levels of ambiguity decline, so does the need for questioning behaviors.
  • Intimacy Level: When people experience a higher level of doubt, there is an observable decrease in the intimacy of their discourse. On the other hand, when uncertainty levels are low, one can notice an increase in closeness within the communication.
  • Reciprocity: When there is an abundance of doubt, the rate of mutual action increases. Conversely, when uncertainty is low, this leads to a lower level of reciprocity.
  • Similarity: When we find similarities between people, it boosts our confidence and decreases doubt. On the other hand, when there is dissimilarity among us, uncertainty increases. Thus, differences in one another lead to a heightened sense of unpredictability, while similarities make us more comfortable (which is explained by the affinity bias).
  • Liking: As the level of uncertainty rises, people’s overall liking for something decreases. On the other hand, as levels of uncertainty fall over time, likability increases in response.

Drawing on their seven original axioms, Berger and Calabrese developed the following set of theorems. These theorems explain how uncertainty is reduced in interpersonal communication.

Benefits of Uncertainty Reduction Theory

URT has several benefits for both individuals and groups in interpersonal communication. They include improved understanding, increased trust, and more explicit expectations.

  • Improved Understanding: By utilizing this theory, people can transcend the uncertainty associated with communication and better predict the behavior of others. Furthermore, it provides them with a deeper understanding of how their own actions may be interpreted in any given situation.
  • Increased Trust: When two individuals are more familiar with each other, the likelihood of establishing trust is amplified. By quelling any sense of uncertainty and mystery between them, one can safely assume that confidence will grow as a result. Thus, reducing doubt leads to an increase in faith among both parties.
  • Clearer Expectations: As people get to know each other better, they are able to establish more precise expectations. It will help them steer clear of potential future disagreements since they understand what actions and attitudes should be anticipated from the other person.

So, URT helps people to better understand and interact with each other. Besides, it also helps them to develop a sense of trust and form clearer expectations. It, in turn, leads to more effective communication, which benefits both parties.


Uncertainty reduction theory proposes that the more conversation exchanges occur between interactants, the lower the uncertainty. 

By engaging in discourse, they gain knowledge and insight, which reduces unease or trepidation. In essence, the key to lowering ambiguity lies in the communication itself!

This theory was initially proposed by Jurgen Habermas and further developed by Charles Berger and Richard Calabrese to explain how individuals can reduce the uncertainty they experience when engaging in interpersonal communication.

URT has numerous benefits for interpersonal communication, including increased understanding, trust, and clear expectations. Ultimately, URT explains why communication is necessary for successful relationships between individuals.

Read Next: Interpersonal Communication Examples


Brunner, B. R. (2019). Public relations theory: Application and understanding. John Wiley & Sons, Inc.

Cobley, P., & Schulz, P. (2013). Theories and models of communication. Walter De Gruyter.

Costa, C. (2015). Uncertainty reduction and game communication: How does uncertainty reduction theory come into play? https://minds.wisconsin.edu/bitstream/handle/1793/77916/Costa2015.pdf?sequence=1&isAllowed=y

Cushman, D. P., & Kovačic, B. (1995). Watershed research traditions in human communication theory. N.Y. State University of New York Press.

Floyd, K., Schrodt, P., Erbert, L. A., & Trethewey, A. (2017). Exploring communication theory: Making sense of us. Routledge.

Viktoriya Sus

Viktoriya Sus (MA)

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Viktoriya Sus is an academic writer specializing mainly in economics and business from Ukraine. She holds a Master’s degree in International Business from Lviv National University and has more than 6 years of experience writing for different clients. Viktoriya is passionate about researching the latest trends in economics and business. However, she also loves to explore different topics such as psychology, philosophy, and more.

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This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

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