Uncertainty reduction theory

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The Uncertainty Reduction Theory also known as Initial Interaction Theory, developed in 1975 by Charles Berger and Richard Calabrese, is a communication theory from the post-positivist tradition. It is one of the only communication theories that specifically looks into the initial interaction between people prior to the actual communication process.The theory asserts the notion that, when interacting, people need information about the other party in order to reduce their uncertainty. In gaining this information people are able to predict the other's behavior and resulting actions, all of which according to the theory is crucial in the development of any relationship.[1][2]

Charles Berger and Richard Calabrese explain the connection between their central concept of uncertainty and seven key variables of relationship development with a series of axioms. Within the theory two types of uncertainty are identified; cognitive uncertainty and behavioral uncertainty. There are three interactive strategies which people may use to seek information about someone, these are passive, active, or interactive. Furthermore the initial interaction of strangers can be broken down into individual stages, these interactional behaviors can be used as indicators of liking and disliking, the entry stage, the personal stage, and the exit stage. According to the theory, people find uncertainty in interpersonal relationships unpleasant and are motivated to reduce it through interpersonal communication.


In 1975, Charles Berger and Richard Calabrese created uncertainty reduction theory "to explain how communication is used to reduce uncertainties between strangers engaging in their first conversation together.) [2] In an effort to comprehend initial interactions, Berger and Calabrese believe people attempt to increase the predictability in communication.

There are two primary sub-processes of uncertainty reduction, prediction and explanation.[2] Prediction refers to the ability to forecast one's and other's behavioral choices. Explanation refers to the ability to interpret the meaning of behavioral choices.[2] In initial meetings, individuals attempt to predict what the other may want to hear based off the meaning they acquired from previous statements, observations, or information ascertained.

The foundation of the uncertainty reduction theory stems from the information theory, originated by Claude E. Shannon and Warren Weaver.[2] Shannon and Weaver suggests, when people interact initially, uncertainties exist especially when the probability for alternatives in a situation is high and the probability of them occurring is equally high.[3] They assume uncertainty is reduced when the amount of alternatives is limited and/or the alternatives chosen tend to be repetitive.


There are seven assumptions associated with the uncertainty reduction theory:[2]

  • People experience uncertainty in interpersonal settings.
  • Uncertainty is an aversive state, generating cognitive stress.
  • When strangers meet, their primary concern is to reduce their uncertainty or to increase predictability.
  • Interpersonal communication is a developmental process that occurs through stages.
  • Interpersonal communication is the primary means of uncertainty reduction.
  • The quantity and nature of information that people share change through time.
  • It is possible to predict people's behavior in a lawlike fashion.

Types of uncertainty[edit]

According to the uncertainty reduction theory, in initial interactions there are two types of uncertainty. A person will either have cognitive uncertainty or behavioral uncertainty. Cognitive uncertainty pertains to the level of uncertainty associated with the cognition (beliefs and attitudes) of each other in the situation.[4] Uncertainty is high in initial interactions because individuals are not aware of the beliefs and attitude of the other party.[4] Behavioral uncertainty pertains to "the extent to which behavior is predictable in a given situation."[4] Uncertainty is one motivation behind adoption of norms in most societies in which people tend to abide by, and if in initial conversations one chooses to ignore such norms there are risks of increasing behavioral uncertainty and reducing the likelihood of having future interactions. A great example of ignoring societal norms is engaging in inappropriate self-disclosure.

In addressing these uncertainties there are two processes for reduction, proactive uncertainty reduction and retroactive uncertainty reduction, proposed by Berger and Calabrese. Proactive uncertainty reduction is strategic communication planning prior to interaction.[5] Retroactive uncertainty reduction is the process of analyzing the situation post interaction.[5]

Stages of relational development[edit]

Berger and Calabrese separate the initial interaction of strangers into three stages: the entry stage, the personal stage, and the exit stage. Each stage includes interactional behaviors that serve as indicators of liking and disliking.[6]

The entry stage of relational development is characterized by the use of behavioral norms. Meaning individuals begin interactions under the guidance of implicit and explicit rules and norms, such as pleasantly greeting someone or laughing at ones innocent jokes. The contents of the exchanges are often dependent on cultural norms. The level of involvement will increase as the strangers move into the second stage.[7]

The second stage, or personal phase, occurs when strangers begin to explore one another's attitudes and beliefs. Individuals typically enter this stage after they have had several entry stage interactions with a stranger. One will probe the other for indications of their values, morals and personal issues. Emotional involvement tends to increase as disclosure increases.[1]

The final stage of interactional development is the exit phase. Here, the former strangers decide whether they want to continue to develop a relationship. If there is no mutual liking, either can choose not to pursue a relationship.[1]

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

Axioms and theorems[edit]

Berger and Calabrese propose a series of axioms to explain the connection between their central concept of uncertainty and seven key variables of relationship development: verbal communication, nonverbal warmth, information seeking, self-disclosure, reciprocity, similarity, and liking.[8] The uncertainty reduction theory uses scientific methodology and deductive reasoning to reach conclusions.[9]


  • Axiom 1 - Verbal communication: Given the high level of uncertainty present at the onset of the entry phase, as the amount of verbal communication between strangers increases, the level of uncertainty for each interactant in the relationship will decrease. As uncertainty is further reduced, the amount of verbal communication will increase.[2]It is also important to consider recently published work by Berger, in which, he states the importance of appropriate levels of verbal communication, where too much verbal communication may lead to information seeking by the other party.[10]
  • Axiom 2 - Non-verbal warmth: As non-verbal affiliate expressiveness increases, uncertainty levels will decrease in an initial interaction situation. In addition, decreases in uncertainty level will cause increases in non-verbal affiliative expressiveness[2]
  • Axiom 3 - Information seeking: High levels of uncertainty cause increases in information-seeking behavior. As uncertainty levels decline, information-seeking behavior declines[2]
  • Axiom 4 - Self-disclosure: High levels of uncertainty in a relationship cause decreases in the intimacy level of communication content. Low levels of uncertainty produce high levels of intimacy[2]
  • Axiom 5 - Reciprocity : High levels of uncertainty produce high rates of reciprocity. Low levels of uncertainty produce low rates of reciprocity.[2]
  • Axiom 6 - Similarity : Similarities between persons reduce uncertainty, while dissimilarities produce increases in uncertainty[2]
  • Axiom 7 - Liking : Increases in uncertainty level produce decreases in liking; decreases in uncertainty produce increases in liking.[2]

Based on further research two additional axioms were added to the theory, the 8th axiom was add by Berger and Gudykunst (1991) and the 9th axiom was suggested by Neuliep and Grohskopf (2000) :[11]

  • Axiom 8 - Shared Networks : Shared communication networks reduce uncertainty, while lack of shared networks increases uncertainty.
  • Axiom 9 - Communication satisfaction: There is an inverse relationship between uncertainty and communication satisfaction.


Berger and Calabrese formulated the following theorems deductively from their original seven axioms:[12]

  • Amount of verbal communication and nonverbal affiliative expressiveness are positively related.
  • Amount of verbal communication and intimacy level of communication are positively related.
  • Amount of verbal communication and information seeking behavior are inversely related.
  • Amount of verbal communication and reciprocity rate are inversely related
  • Amount of verbal communication and liking are positively related.
  • Amount of verbal communication and similarity are positively related.
  • Nonverbal affiliative expressiveness and intimacy level of communication content are positively related.
  • Nonverbal affiliative expressiveness and information seeking and information seeking are inversely related.
  • Nonverbal affiliative expressiveness and reciprocity rate are inversely related.
  • Nonverbal affiliative expressiveness and liking are positively related.
  • Nonverbal affiliative expressiveness and similarity are positively related.
  • Information seeking and reciprocity are positively related.
  • Information seeking and liking are negatively related.
  • Information seeking and similarity are negatively related.
  • Intimacy level and reciprocity are negatively related.
  • Intimacy level and similarity are positively related.
  • Intimacy level and liking are posiivelyy related.
  • Reciprocity rate and liking are negatively related.
  • Reciprocity rate and similarity are negatively related.
  • Similarity and liking are positively related

Viewed collectively, the theorems provide a framework for examining and predicting the process of getting to know someone.[1]

Table 1: Axioms of Uncertainty Reduction Theory

Verbal Nonverbal Info seeking Disclosure Reciprocity Similarity Liking
Verbal + - + - + +
Nonverbal + - + - + +
Info seeking - - - + - -
Disclosure + + - - + +
Reciprocity - - + - - -
Similarity + + - + - +
Liking + + - + - +
*Table 1 summarizes the seven axioms and their relationships 

Uncertainty reduction strategies[edit]

People engage in passive, active, or interactive strategies to reduce uncertainty with others.

According to Berger, If a person were to observe another in their natural environment, intentionally unnoticeable, to gain information on another, would be categorized as using a passive tactic for reducing uncertainties.[13] For example, watching someone in class, cafeteria, or any common area without attracting attention.

An active strategist would result to means of reducing uncertainties without any personal direct contact.[13] For example, if one were to ask a friend about a particular person, or ask the particular person's friend for some information without actually confronting the person directly.

An interactive strategist would directly confront the individual and engage in some form of dialog to reduce the uncertainties between the two.[13]

A new strategy for reducing uncertainty was suggested in 2002 by Ramirez, Walther, Burgoon, and Sunnafrank that complements computer mediated communication and the technological advancements. Given the vast amount of information one could find about an individual via online resources a fourth uncertainty reduction strategy that uses online mediums to obtain information was labeled as extractive information seeking.[14]

Incentives to reduce uncertainty[edit]

Berger suggests that an individual will tend to actively pursue the reduction of uncertainty in an interaction if any of the three conditions are verified:[15]

  • Anticipation of future interaction: A future meeting is a certainty.
  • Incentive value: They have or control something we want.
  • Deviance: They act in a manner that is departing from accepted standards

Example: For a couple of weeks there will be a new manager in your workplace, therefore future interactions with this person is a certainty. The manager is assigning projects to the people in your department, every project returns a different commission which will directly influence your income. Arguably, being assigned a higher paying project has a greater incentive value for anyone in the department. The manager has a sibling in your department, which could influence the manager's decision on project assignments.

According to the theory, any single aforementioned factor or all three of them combined can result in an increase in one's desire to reduce uncertainty in interpersonal interactions.[1]

Contemporary use[edit]

The 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 it is important to test the theory in new paradigms, thus adding to its heuristic value (Gudykunst, 2004).

Uncertainty reduction & job hiring[edit]

Scholarly studies have examined the practical application of uncertainty reduction theory in the context of job hiring by studying the communication process between interviewers and applicants prior and during an interview. Understanding the interview process as a communication process aimed to reduce uncertainty is important to organizations, as it has been proven that the more positive and negative information about expectations and organizational norms are shared during the interview process, both by the applicant and interviewer, the greater the job satisfaction and the less turnover rates.[16]

In the context of uncertainty reduction theory, interviews are defined as an interactive communication process between two participants the interviewer and the applicant, in which both participants share information, try to match expectations and develop perceptions about one another. The interview is suggested to be the initial means of communication in which both participants thrive to reduce their uncertainties.[17]

An applicant's interview satisfaction is measured in terms of the amount of information the interviewer gives to the applicant and the amount of time given to the applicant to answer open ended questions. Findings suggest that applicants are not comfortable when confronted with passive interrogation questions, as they prefer conversational questions that helps them reduce uncertainties about the job they are applying to.[18]

Before individuals go for an interview it is usually the case that they will engage in strategies to reduce uncertainty. Individuals use active strategies prior to an interview by conducting research on the organization and the interviewer, trying to grasp as much information as possible in order to reduce uncertainty and form sets of expectations and beliefs about the organization. During the interview both participants engage in an interactive strategy of reducing uncertainty by trying to ask as much questions as possible. The interviewer tries to predict the capabilities and skills of the applicant while the applicant attempts to learn more about the organization. It is anticipated that applicants who seek sufficient information during the initial phase of a recruiting process will have a better understanding and a more realistic expectation of the job requirements and the organizational norms.[19]

Uncertainty reduction & in-group identification[edit]

Empirical studies have examined the relationship between the effects of self-uncertainty and in-group entitativity. One important question that was investigated was; what motivates people to join or identify with groups and engage in specific forms of inter-group behavior? Based on the concept of uncertainty reduction theory, the hypothesis that people identify most strongly with groups if they felt self-conceptual uncertainty was tested. Results revealed that people who feel self-conceptual uncertainty are motivates to join groups in which they identify with as a means to reduce the uncertainties they have about their conceptual-self.[20]

Research has proved that group identification is and efficient strategy and immediate way to reduce one’s self-conceptual uncertainty. In addition social psychology literature identifies a large number of different motivations that may play a role in uncertainty reduction, one of which is group identification. [21]

Hogg has proposed that uncertainty reduction plays a key motivational role in self-categorization and in-group identification, he bases his argument on the premise that subjective uncertainty, especially those about one’s self and identity are unpleasant and that people strive to reduce uncertainties they feel about themselves. [22]

A person's self-categorization is affected by group identification including nationality, religion, gender, ethnicity and many other associated groups. Thus people continue to try to reduce the uncertainties they feel about themselves by identifying with even more specific groups. There is also evidence that people who are highly uncertain about themselves are more likely to identify with more homogeneous groups to reduce their uncertainty of self and reach a more definite state.[23]

Therefore it is suggest that people are highly motivated to reduce uncertainty in the social identity processes by joining groups they can relate themselves to in one way or another. Generally, people will be able to reduce their self-uncertainty either significantly or to a low degree, depending on the type of group they join and to what extent one can relate to his or herself within a group. [24]

Computer-mediated communication[edit]

Given that uncertainty reduction theory was primarily developed for face-to-face interactions, critics have questioned the theory's applicability to computer-mediated communications. Pratt, Wiseman, Cody and Wendt argue that the theory is only partially effective in asynchronous, computer-mediated environments.[25] Although many computer mediated communications limit the possibility of utilizing many traditional social cues theories such as, Social Information Processing and Hyperpersonal Model, suggest individuals are quite capable of reducing uncertainties and developing intimate relationships.[26]

Antheunis, Marjolijn L., et al. investigated whether language-based strategies, employed by computer-mediated communication (CMC) users, would aid in reducing uncertainties despite the absence of nonverbal cues.[27] This study examined three interactive uncertainty reduction strategies (i.e., self-disclosure, question asking, and question/disclosure intimacy) in computer mediated communications.[27] Also, this study probed whether these uncertainty reduction strategies enhanced the verbal statements of affection in CMC.[27] This study questioned the use of language-based strategies to three communication options: face-to-face, visual CMC supported by a webcam, or text-only CMC.[27] “Content analysis of the verbal communication revealed that text-only CMC interactants made a greater proportion of affection statements than face-to-face interactants. Proportions of question asking and question/disclosure intimacy were higher in both CMC conditions than in the face-to-face condition, but only question asking mediated the relationship between CMC and verbal statements of affection.”[27]

In addition, a study was conducted on 704 members of a social networking site to see what reduction theory strategies they used while gaining information on people they had recently met in person. All respondents used passive, active and interactive strategies, but the most common and beneficial strategy was the interactive strategy. This strategy reduced the most uncertainty of the target person by showing a perceived similarity and increasing social attraction.[28]

Job hiring via extracted information[edit]

Research studies have applied uncertainty reduction theory to online information seeking utilized in the context of job hiring. The studies analyzed the influence of online information seeking conducted by recruiters on attribute and characteristic certainty of applicants. Research evidence have shown that online information has increased attribution certainty about applicants, making the recruitment process more effective within organizations. Using uncertainty reduction strategies through online sources have proven to be good predictions and indicators of targeted individuals. However, findings have also concluded the negative effects on job applicants when negative information is obtained by employers via online sources that may conflict with the already developed perception of the job applicant obtained from normal means such as résumés and cover letters.[29]

Furthermore online information's effect on job applicants has been widely discussed, as many guide books now suggest that applicants minimize what could be preserved by employers as negative presence in their online communities and strategically enhance any positive presence. As more organizations are including online information extract as part of their recruiting process, empirical results show that applicants with negative online presence where perceived as less qualified than those with a positive or neutral online presence.[30]

Online auctions[edit]

In an online consumer-to-consumer (C2C) e-commerce context, transactions usually happen directly between individuals with a third party involved acting as an intermediary or a communication platform, but not guaranteeing that the transaction happens. Therefore C2C e-commerce platforms constantly involve initial interaction between strangers that is motivated by the desire to exchange a product for money. Such environments are a significant risk for both the seller and the buyer, given the financial and psychological cost of a transaction failing because of a lack of information.[31]

Online auction platforms such as eBay are considered to be risky and uncertain environments for exchange, especially from the standpoint of the bidder, as there is limited information available regarding both the merchandise and the seller.[32]

Applications of uncertainty reduction theory and predicted outcome value theory have been used to investigate individuals’ motivations and behaviors in online consumer-to-consumer (C2C) auctions environments. A study of 6477 randomly selected data sets of auctions conducted on eBay.com indicated that the more detailed information about a certain product was available as part of the product description the more bids there were and the higher the final bid was. In addition, a higher seller’s reputation resulted in fewer bids and a lower selling price.[33]

Unlike face-to-face auctions, online auctions do not provide the bidder a way to examine the product physically and evaluate its worth. One means to reduce the uncertainty of a product's worth in an online auctions setting is having extensive descriptions and pictures of the item available. eBay also has a feedback feature in which previous users describe their experience with another user. The system calculates a user rating score based on this information and makes it available to bidders.[34]

Findings from the study illustrate that uncertainty reduction theory provides an insightful framework in which individuals’ initial interactions in the context of online auctions can be understood. The study also provides evidence that strategies for reducing uncertainty in online initial interaction are similar to those used in face-to-face transactions.[35] Although online auction users seem to favor passive strategies, including viewing product information and seller reputation, there are more active strategies in use: a user may look up the seller in other online platforms to gather relevant information or may use an interactive strategy, sending a private message to the seller asking for more information.[36]

Online dating[edit]

Online dating sites typically bring together individuals who have no prior contact with one another and no shared physical space where nonverbal cues can be communicated. Online dating sites produce a different set of concerns for individuals, as well as a different set of tools for reducing uncertainty. Gibbs, Ellison and Lai report that individuals on online dating websites attempt to reduce uncertainty at three levels: personal security, misrepresentation, and recognition. The asynchronous nature of the communications and the added privacy concerns may alter the Uncertainty Reduction model. Individuals who participate in online dating sites may engage in interactive behaviors and seek confirmatory information sooner than those who engage in offline dating.[26]

Online dating mainly supports passive strategies for reducing uncertainties. The option to view profiles online without needing to directly contact an individual is the main premise of passively reducing uncertainties. As one reviews another's profile they become equipped with enough knowledge to effectively predict and explain particular behaviors in initial interactions.

When one encounters initial interactions they’re commonly exposed to many risks. In online dating, many participants consider risks resulting from self-disclosure.[26] For example, a prospective suitor may disclose information on a profile that is dishonest or omits important details. Because reciprocity norms persuade individuals to reveal personal info in response to others’ self-disclosures, opportunities for misleading another is increased.[26] If one offers details in response to deceptive communication from others, with expectations of initiating face-to-face meetings and/or romantic relationships, the probability of succumbing to an act of violence is heightened.[26]

Gibbs, et al. found that “participants who used uncertainty reduction strategies tended to disclose more personal information in terms of revealing private thoughts and feelings, suggesting a process whereby online dating participants proactively engage in uncertainty reduction activities to confirm the private information of others, which then prompts their own disclosure.”[26]

Online surrogacy ads[edit]

Parents and surrogate mothers have great incentive for reducing uncertainty, taking optimal control, and finding a suitable third party for their pregnancy process. May and Tenzek assert that three themes emerged from their study of online ads from surrogate mothers: idealism, logistics, and personal information. Idealism refers to surrogates' decision to share details regarding their lifestyle and health. Logistics refers to the surrogates' requested financial needs and services. Personal information refers to the disclosure of details that would typically take several interactions before occurring, but has the benefit of adding a degree of tangible humanness to the surrogate (e.g. the disclosure of family photos). Idealism, logistics and personal information all function to reduce potential parents' uncertainty about a surrogate mother.[37]

Ethnicity and cultural differences[edit]

Studies have been conducted to determine the differences in the uses of uncertainty reduction strategies among various ethnicities. A study, conducted in the United States, suggests that significant differences are apparent. Self-disclosure has a pan-cultural effect on attributional confidence but other types of uncertainty reduction strategies appeared to be more culture-specific.[38]

“A multiple comparisons analysis using a least significance difference criterion indicated that for both self- and other-disclosure, African-Americans used greater self-disclosure than Euro-Americans, Hispanic-Americans, and Asian-Americans and perceived greater other intraethnic disclosure. The only other significant differences found in the multiple comparisons test were between self- and other-disclosure levels for Hispanic-Americans and Asian-Americans, namely, the former perceived greater self- and other-disclosure levels than Asian-Americans.”[38]

Another study suggests that cultural similarities between strangers influence the selection of uncertainty reduction strategies by increasing the intent to interrogate, intent to self-disclose, and nonverbal affiliative expressiveness.[39] The study also expressed an individual’s culture influences their selection of uncertainty reduction strategies.[39] For example US students exhibit higher levels of interrogation and self-disclosure than in Japanese students.[39]


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 predicted outcome value theory (1986) indicated that the actual motivation for interaction is a desire for positive relational experiences. In other words, individuals engaging in initial interactions are motivated by rewards opposed to reducing uncertainties. According to Sunnafrank, when we communicate we are attempting to predict certain outcome to maximize the relational outcomes. Kellerman and Reynolds (1990) pointed out that sometimes there are high level of uncertainty in interaction that no one wants to reduce.[40] As a result of the critique, researchers formed the Uncertainty Management theory. This theory contrasts uncertainty reduction theory by identifying reduction as only one of the many actions that people take when uncertainty arises.[41] Gudykunst 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.[42] 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.

Motivation to reduce uncertainty model[edit]

The uncertainty reduction theory also lead to the formation of a model originated by Michael W. Kramer. Kramer presents some major tenets and criticisms of the uncertainty reduction theory and then propose a Motivation to Reduce Uncertainty (MRU) model.[43]

MRU suggests that different levels of motivation to reduce uncertainty can lead to certain communication behaviors depending on competing goals.[43]

MRU suggests at least four different reasons for low motivation to seek information:[43]

  • People do not experience uncertainty in every event or encounter. Predictable or easily understood situations will not result in significant levels of uncertainty.[43]
  • Individuals have different levels of tolerance for uncertainty. The more one tolerates uncertainty the less information one seeks.[43]
  • Because communication always has social or effort costs,[44] minimizing those costs with limited effort may be preferable to information seeking.[43]
  • Individuals may also create certainty with minimal information seeking and without overt communication. For example, classification systems, such as stereotyping, create certainty out of uncertain situations.[43]

Research demonstrates that MRU could be used to examine how employees manage uncertainty during adjustment processes. MRU uses theoretical explanations for examining the approaches to understanding group decision making. “When groups are highly motivated to reduce the uncertainty surrounding a decision and there are no competing motives such as time or cost limitations, highly rational behaviors lead to information seeking to reduce uncertainty to optimize decisions.”[43] MRU could be used at the organizational level to examine communication related to organizational strategy.[43]

Anxiety/uncertainty management theory[edit]

Inspired by Berger's Theory, the late California State, Fullerton, communication professor William Gudykunst began to apply some of the axioms and theorems of uncertainty reduction theory to intercultural settings. Despite their common axiomatic format and parallel focus on the meeting of strangers, Gudykunst's anxiety/uncertainty management theory (AUM) differs from Berger's uncertainty reduction theory in several significant ways. First, AUM asserts that people do not always try to reduce uncertainty. When uncertainty allows people to maintain positive predicted outcome values, they may choose to manage their information intake such that they balance their level of uncertainty. Second, AUM claims that people experience uncertainty differently in different situations. People must evaluate whether a particular instance of uncertainty is stressful, and if so, what resources are available.[45]

Example: Online cancer research

Hurley, Kosenko and Brashers argue that 65% of internet-based cancer news is associated with the increase of uncertainty. In order of their degree of magnitude, information regarding treatment, prevention, detection, survivorship, and end-of-life issues yielded the most uncertainty. Given the inverse relationship between information-seeking behavior and uncertainty reduction, Hurley, Kosenko and Brashers assert that Uncertainty Management Theory may be more accurate and effective than uncertainty reduction theory. More research is needed to determine what computer-mediated communications exacerbate and help individuals manage their uncertainty regarding their health.[46]


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).[47] Later research by Berger and Bradac (1982) indicated that disclosures by interactants may lead them to be judged as more or less attractive.[4] The judgment will determine whether the judge will continue to reduce their uncertainties or end the relationship. Berger also acknowledges the works of Gudykunst, et al. (1985) and Parks & Adelman (1983) to extend uncertainty reduction theory to the realm of more established relationships.[48]

Planalp & Honeycutt (1985)[49] studies the introduction of new uncertainty to existing relationships. Their findings indicate that uncertainty in long-term relationships usually impacts negatively on the relationship.

See also[edit]


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Further reading[edit]

  • Deyo, J., Price, W. & Davis, L. (2011). Rapidly Recognizing Relationships: Observing Speed Dating in the South. Qualitative Research Reports in Communication, 12 (1), 71-78
  • Koester, J., Booth-Butterfield, M. & Booth-Butterfield, S. (1988). The Function of Uncertainty Reduction in Alleviating Primary Tension in Small Groups. Communication Research Reports, 5(2), 146-153
  • Ramirez, A. (2009). The Effect of Interactivity on Initial Interactions: The Influence of Information Seeking Role on Computer-Mediated Interaction. Western Journal of Communication, 73 (3), 300-325
  • Witt, P.L. & Behnke, R.R. (2006). Anticipatory Speech Anxiety as a Function of Public Speaking Assignment Type. Communication Education, 55(2), 167-177
  • Gudykunst, W. B., Shapiro, R., "Communication in Everyday Interpersonal and Intergroup Encounters," International Journal of Intercultural Relations, Vol. 20, 1996, pp. 19–45.
  • Goldsmith, D, J. (2001). A Normative Approach to the Study of Uncertainty and Communication. Journal of Communication, 514- 533
  • Sunnafrank, M. (1986), Predicted Outcome Value During Initial Interactions A Reformulation of Uncertainty Reduction Theory. Human Communication Research, 13: 3–33
  • Gudykunst, W. B., Yang, S.-M. and Nishida, T. (1985), A Cross-Cultural Test of Uncertainty Reduction Theory. Human Communication Research, 11: 407–454
  • Bradac, J. J. (2001). Theory Comparison: Uncertainty Reduction, ProblematicIntegration, Uncertainty Management, and Other Curious Constructs. Journal Of Communication,51(3), 456

External links[edit]

Em Griffin, the author of A First Look at Communication Theory conducted an interview with Charles Berger on uncertainty reduction theory. During the interview, Berger explains how the theory came to exist,how it has evolved throughout the years, why he used axioms and thermos to develop the theory and the connection of uncertainty reduction theory to his work on cognitive plans and strategic communication.