Uncertainty reduction theory

Uncertainty Reduction Theory was introduced in 1975 in a paper entitled Some Exploration in Initial Interaction and Beyond: Toward a Developmental Theory of Interpersonal Communication. This theory, a collaborative effort of Charles R. Berger and Richard J. Calabrese, was proposed to predict and explain relational development (or lack thereof) between strangers.

The scope of the theory is narrowed down to rest on the premise that strangers, upon meeting, go through certain steps and checkpoints in order to reduce uncertainty about each other and form an idea of whether one likes or dislikes the other. To study this phenomenon, the interaction is viewed as going through several stages. Berger and Calabrese also introduce axioms and theorems regarding initial interaction behaviors.

Stages of Relational Development
Berger and Calabrese separate the initial interaction of strangers into 3 stages, the entry stage, the personal stage, and the exit stage. Each category includes interactional behaviors which serve as indicators of liking and disliking.

The entry stage of relational development is characterized by the use of behavioral norms. The contents of the exchanges are often demographic and transactional. Common initial questions are: Where are you from? Or, Do you have any pets? The level of involvement will increase as the strangers move into the second stage (Berger & Calabrese, 99-100).

The second stage, or personal phase, is when strangers begin to explore the attitudes and beliefs of the other. Typically, this stage is entered after the strangers have had several entry stage interactions. One will probe the other for indications of their values, morals and personal issues. Emotional involvement tends to increase as disclosures are made (Berger & Calabrese, 100).

The final stage of interactional development is the exit phase. Here, the former strangers decided if they want to continue to develop a relationship. Any plans for the future are made. If there is not mutual liking, either can choose not to pursue a relationship (Berger & Calabrese, 100).

Understanding the cycle of relational development is key to studying how people seek to reduce uncertainty about others.

Axioms & Theorems
Berger and Calabrese used several studies as a guide to develop the foundations of Uncertainty Reduction Theory. Research and theory development was steeped in the post-positivist tradition, using scientific methodology and deductive reasoning to reach their conclusions (Miller, 176). The results of the studies form the foundation of the theory, seven axioms and 21 theorems. The following are the axioms set forth by Berger and Calabrese in their paper:


 * Axiom 1: Strangers enter an interaction with high levels of uncertainty about the other.  However, as they begin to talk to one another, the level of uncertainty decreases.  In turn, as the uncertainty decreases, the interactants will talk more.
 * Axiom 2: As nonverbal expressive communication increases, uncertainty levels decrease, and vice versa.
 * Axiom 3: High levels of uncertainty prompt strangers to ask more questions of the other.  As uncertainty decreases, so does the posing of questions.
 * Axiom 4: High levels of uncertainty in a relationship lead to less sharing and emotional intimacy.  Low levels of uncertainty allow for more sharing and emotional intimacy.
 * Axiom 5: High levels of uncertainty lead to more symmetrical question exchanges in interaction.  As uncertainty decreases, so does the need for an equal exchange of talk.
 * Axiom 6: Personal similarity will decrease uncertainty about another, while dissimilarity will produce higher levels of uncertainty.
 * Axiom 7: An increase in uncertainty will lead to a decrease in liking.  A decrease in uncertainty will lead to an increase in liking.

Berger and Calabrese formulated the following theorems deductively from their axioms:
 * Theorem 1: The amount of talking and nonverbal communicative expressions are positively related.
 * Theorem 2: The amount of communication and its intimacy level is positively related.
 * Theorem 3: Time spent in interaction and questions posed are inversely related.
 * Theorem 4: Time spent communicating and instance of symmetric exchanges are inversely related.
 * Theorem 5: The amount of communication and liking are positively related.
 * Theorem 6: The amount of communication and personal similarity are positively related.
 * Theorem 7: Nonverbal expressions and intimacy level of conversation are positively related.
 * Theorem 8: Nonverbal expressions and information seeking are inversely related.
 * Theorem 9: Nonverbal expressions and instance of symmetrical exchange are inversely related.
 * Theorem 10: Nonverbal expressions and liking are positively related.
 * Theorem 11: Nonverbal expressions and similarity are positively related.
 * Theorem 12: The level of communication intimacy and information seeking are inversely related.
 * Theorem 13: The level of communication intimacy and instance of symmetrical exchange are inversely related.
 * Theorem 14: The level of communication intimacy and liking are positively related.
 * Theorem 15: The level of communication intimacy and similarity are positively related.
 * Theorem 16: Posing questions and symmetrical exchanges are positively related.
 * Theorem 17: Posing questions and liking are negatively related.
 * Theorem 18: Posing questions and similarity are negatively related.
 * Theorem 19: Instance of symmetrical exchange and liking are negatively related.
 * Theorem 20: Instance of symmetrical exchange and similarity are negatively related.
 * Theorem 21: Similarity and liking are positively related.

Viewed as a whole, the processes of getting to know someone, as well as if there is liking between the two, can be predicted by examining the interactive phenomena through Uncertainty Reduction Theory’s tenets (Berger & Calabrese, 101-109).

Defense
Eleven years after Uncertainty Reduction Theory was introduced, Berger published Uncertain Outcome Values in Predicted Relationships: Uncertainty Reduction Theory Then and Now. His aim was to defend his theory in new contexts and modify it, as necessary. Berger later proposed three types of information seeking behavior, passive (watching the interactant for clues in reactions to stimuli), active (posing questions to other individuals about the interactant), and interactive ( posing direct questions to the interactant) (Miller, 178). Later research by Berger and Bradac (1982) indicated that disclosures by interactants may lead them to be judged as more or less attractive. The judgment will determine whether the judge will continue to reduce their uncertainties or end the relationship. Berger also acknowledges the works of Gundykunst, et al (1985) and Parks & Adelman (1983) to extend Uncertainty Reduction Theory to the realm of more established relationships. Planalp & Honeycutt (1985) studies the introduction of new uncertainty to existing relationships. Their findings indicate that uncertainty in long-term relationships usually impacts negatively on the relationship.

Critique
Uncertainty reduction theory has sparked much discussion in the discipline of communication. Critics have argued that reducing uncertainty is not the driving force of interaction. Michael Sunnafrank's research (1986) indicated that the actual motivation for interaction is a desire for positive relational experiences. Kellerman and Reynolds (1990)pointed out that sometimes there are high level of uncertainty in interaction which no one wants to reduce (Miller, 180-183). Gudykunst (1985) points out that Uncertainty Reduction Theory was formulated to describe the actions and behaviors of middle-class, white strangers in the United States. This is the demographic in the studies Berger and Calabrese used to develop the theory (Gundykunst, 204). Another issue is the scope of the axioms and theorems. If a particular theorem is disproved, it destroys the axiological base upon which it rests.

Contemporary Use
Uncertainty Reduction Theory has been applied to new relationships in recent years. Although it continues to be widely respected as a tool to explain and predict initial interaction events, it is now also employed to study intercultural interaction (Gudykunst et al, 1985), organizational socialization (Lester, 1986), and as a function of media (Katz & Blumer, 1974). Gudykunst argues that is important to test theory in new paradigms, thus adding to its fortitude (Gudykunst, 204).