Decision-Making Styles and Intolerance of Uncertainty

Abstract

Intolerance of uncertainty plays a significant role in decision-making by shaping how individuals perceive, interpret, and react to uncertain situations. Consequently, this research seeks to explore the relationship between the five decision-making styles and intolerance of uncertainty. To conduct this study, we utilized the General Decision-Making Style Scale (GDMS) and the Intolerance of Uncertainty Scale (IUS). A total of 131 participants were recruited from a university and other locations through SONA, a software program that helps universities manage research study participation, and social media platforms. The analysis of decision-making styles using a correlogram revealed significant correlations among them, indicating that these styles are not entirely independent. Intuitive decision-making correlated positively with both rational and spontaneous decision-making styles, while dependent decision-making was correlated positively with avoidant decision-making, which also correlated with spontaneous decision-making. These interconnections were accounted for in the regression analyses, ensuring that the relationship of intolerance of uncertainty in each decision-making style was assessed separately. The findings showed that individuals with higher intolerance of uncertainty were more likely to adopt an avoidant decision-making style and less likely to use a rational approach. Additionally, individuals who consider uncertainty “unfair” were more inclined toward dependent and avoidant decision-making styles. Moreover, the findings of this study can help individuals gain insight into their decision-making style and intolerance of uncertainty, enhancing self-awareness and enabling them to recognize their responses to ambiguity while developing strategies for more effective decision-making.

Keywords

decision-making styles decision-making intolerance of uncertainty uncertainty

Decision-making is a fundamental cognitive process that individuals engage in daily, from minor choices like selecting a meal to major life decisions such as career changes or financial investments. At the core of decision-making lies uncertainty—the inability to predict outcomes with absolute certainty. Uncertainty often occurs in situations with limited or unknown information about the expected behavior outcomes (Huettel et al., 2005). While some people are comfortable navigating uncertain situations, others experience significant distress, a characteristic known as intolerance of uncertainty. Intolerance of uncertainty refers to an individual’s excessive tendency to deem it unacceptable for a negative event to occur, regardless of how small the probability of its occurrence may be (Dugas et al., 2001). Intolerance of uncertainty has been linked to many things, like heightened anxiety, avoidance behaviors, and maladaptive coping strategies, all of which can influence the way individuals approach decision-making (Carleton, 2016). Moreover, individuals with a high intolerance of uncertainty make poorer decisions and are more behaviorally inhibited in unpredictable situations compared to those with a low intolerance of uncertainty (Jensen et al., 2014). Additionally, intolerance of uncertainty has been associated with various psychopathologies, including anxiety disorders, obsessive-compulsive disorder, depression, post-traumatic stress disorder, eating disorders, substance use disorders, and personality disorders (Bottesi et al., 2023).

Intolerance of uncertainty is known to impact various aspects of mental health and behavioral inhibition; however, the potential correlation to general behaviors and cognitive processes is worth exploring. The present study explores the correlations between intolerance of uncertainty and different decision-making styles, based on the idea that certain decision-making approaches may be more suited to individuals who seek to minimize or avoid uncertainty. While there are numerous theoretical perspectives on decision-making styles, this study specifically focuses on the General Decision-Making Style (GDMS) framework developed by Scott and Bruce (1995), which was utilized to categorize decision-making into five distinct styles: rational, intuitive, dependent, avoidant, and spontaneous (see Table 1). Each style represents a unique cognitive and emotional approach to processing information and making choices. Rational decision-makers rely on systematic analysis and logical reasoning, whereas intuitive decision-makers trust their instincts and past experiences. Dependent decision-makers seek guidance from others, avoidant decision-makers delay or evade making choices, and spontaneous decision-makers make quick, impulsive decisions without extensive deliberation. While these styles provide a framework for understanding decision-making tendencies, little research has explored how intolerance of uncertainty influences individuals’ preferred decision-making approaches. Understanding the relationship between decision-making styles and intolerance of uncertainty is crucial because it has implications for both psychological well-being and real-world decision-making outcomes. Individuals with high intolerance of uncertainty find it difficult to manage and cope with the negative emotions triggered by uncertainty. They also typically exhibit negative emotional, behavioral, and cognitive responses when faced with uncertain situations (Freeston et al., 1994). Additionally, effectively identifying, managing, and resolving uncertainty is crucial for successful adaptive behavior (Bland & Schaefer, 2012).

Table 1.

The Decision-Making Styles With Descriptions and Examples

Decision-making style	Description	Example
Rational	Emphasizes a thorough search for and logical evaluation of alternatives.	Choosing a college based on academic programs, location, and cost, rather than solely on popularity or location
Avoidant	Emphasizes postponing and avoiding decisions.	A manager who avoids making a difficult personnel decision, instead of addressing the issue, and hopes it resolves itself.
Dependent	Emphasizes a search for advice and direction from others.	A person constantly asks a partner or friend for advice on what to wear or what to eat, rather than choosing on their own.
Intuitive	Emphasizes a reliance on hunches and feelings.	A gambler might choose a specific number in a lottery because they “felt” it was the winning number, or they might continue betting on a losing streak because they have a “feeling” that they are about to win.
Spontaneous	Emphasizes a sense of immediacy and a desire to get through the decision-making process as soon as possible.	Deciding to eat at a different restaurant for lunch based on a sudden craving.

Decision-making under uncertainty has been extensively studied in behavioral economics. Prospect theory, developed by Kahneman and Tversky (1979), explains that people judge outcomes by comparing them to what they already have or expect, rather than viewing them as absolute gains or losses. For instance, someone who expects a $1,000 bonus but receives only $500 may experience this as a loss, even though they still gained money. A key finding is that potential losses feel more significant than equivalent gains, a tendency known as loss aversion (Kahneman & Tversky, 1979; Tversky & Kahneman, 1992). Prospect theory also shows that people distort probabilities: they give too much weight to unlikely events and too little weight to highly probable ones, which helps explain behaviors such as gambling or buying insurance (Tversky & Fox, 1995). Another important principle is the certainty effect, where individuals disproportionately prefer outcomes that are guaranteed, even when uncertain alternatives could offer a better payoff (Kahneman & Tversky, 1979). In other words, the sense of certainty itself can outweigh logical calculations of value.

When combined with psychological traits like intolerance of uncertainty, cognitive biases become even more pronounced. IU refers to a person’s dispositional difficulty coping with ambiguous or unpredictable outcomes, which can lead to maladaptive coping behaviors in response to uncertainty (Dugas et al., 2001; Freeston et al., 1994; Knowles & Olatunji, 2023). Individuals high in IU often prefer predictable outcomes and avoid uncertain situations to reduce distress, which parallels the certainty effect described in prospect theory: just as people overweight guaranteed outcomes in decision-making, individuals with high intolerance of uncertainty may place extra weight on certain, predictable rewards, even when riskier options could offer greater benefits (Buhr & Dugas, 2009; Knowles & Olatunji, 2023). As a result, they may cling to familiar but suboptimal options, prioritizing short-term relief from uncertainty over long-term gains. For instance, an individual might remain in an unsatisfying relationship because the familiarity of the known partner feels safer than the uncertainty of seeking a new one. Similarly, an employer might promote a less-qualified but familiar employee rather than risk hiring a more qualified but unfamiliar candidate. In this way, intolerance of uncertainty can be understood as a dispositional factor that intensifies the kinds of cognitive biases prospect theory describes, helping to explain why some individuals consistently favor stability and short-term relief over long-term potential gains.

This study aims to explore how intolerance of uncertainty relates to individuals’ decision-making styles and whether certain styles are more strongly associated with higher or lower levels of intolerance of uncertainty. By examining these relationships, this research contributes to a better understanding of how individuals experience and respond to uncertainty when making choices in ambiguous situations. The findings may have practical implications for improving decision-making strategies, particularly for individuals who struggle with uncertainty. Identifying patterns between intolerance of uncertainty and decision-making styles, particularly those that are maladaptive, could help inform interventions aimed at enhancing decision-making confidence, reducing avoidance behaviors, and promoting adaptive coping mechanisms. The findings could also help enhance an individual’s self-awareness, allowing people to recognize how they respond to ambiguous and unpredictable situations.

Method

Sample

In this study, 131 participants were recruited from a university and other cities through SONA, a software program that helps universities manage research study participation, as well as social media platforms like Facebook and Instagram. Of the participants, 28.4% were males, 69.7% were females, and 2.2% were non-binary. The participants’ ages ranged from 18–65+, with the majority falling within the 18–24 age group (66.4%). Some participants were eligible to receive course credit for their involvement. Before participation, all individuals were given an informed consent form and asked to complete a brief demographic questionnaire inquiring about their education level, ethnicity, age, and gender. To take part in the study, participants had to be at least 18 years old.

Materials

A Google Form survey was created, featuring three distinct questionnaires: a demographic questionnaire, the Intolerance of Uncertainty Scale (Buhr & Dugas, 2002), and the General Decision-Making Style Scale (Scott & Bruce, 1995). The Intolerance of Uncertainty Scale (Buhr & Dugas, 2002) consists of 27 questions. It assesses an individual’s responses to uncertainty, ambiguous situations, and the future using a 5-point Likert scale ranging from (1 = “not characteristic of me”) to (5 = “entirely characteristic of me”). This scale was utilized as both a unifactorial and bifactorial tool, measuring two factors: negative behavioral and self-referent implications of uncertainty, and the belief that uncertainty is unfair and detrimental.

Additionally, the General Decision-Making Style Scale (Scott & Bruce, 1995) is a 25-question assessment that measures an individual’s approach to decision-making on a Likert scale ranging from (1 = “strongly disagree”) to (5 = “highly agree”). Higher scores in each subscale (the sum of the items) mean that this style is used more frequently. This scale encompasses five decision-making styles: rational, intuitive, dependent, avoidant, and spontaneous, which will be employed to categorize participants. It is important to note that while the scale can assign a specific “preferred” decision-making style to each individual, it also measures the continuous levels of each style. Instead of assuming that each person has only one decision-making style, we can assess the extent to which they rely on each style.

Design

The Google Form survey included an informed consent form, a brief 4-question demographic questionnaire, the Intolerance of Uncertainty Scale (Buhr & Dugas, 2002), and the General Decision-Making Style Scale (Scott & Bruce, 1995). Following its creation, the survey was tested by the researchers and approved by the Institutional Review Board (IRB). This study aimed to obtain a sample that was as representative as possible by recruiting participants not only through the university’s research participation platform (SONA) but also through social media platforms to maximize reach. It is important to acknowledge that potential sources of bias and sample inconsistencies may still be present. In particular, social media recruitment may introduce bias, as online platforms often create environments where individuals interact with others who share similar views and experiences, which can limit the diversity of responses. The data was measured using a correlogram and a multiple linear regression. The survey typically took up to 30 minutes to complete.

Results

The decision-making scale used in this study allows for the assessment of both overall intolerance of uncertainty and two theoretically distinct sub-factors that capture different aspects of intolerance of uncertainty. Factor 1 (F1) reflects the negative behavioral and self-referential effects of uncertainty, while Factor 2 (F2) represents the belief that uncertainty is unfair and harmful. In the analyses below, the relationships between decision-making styles and intolerance of uncertainty scores were examined. First, we present an exploration of the internal structure of the two surveys, focusing on identifying and controlling for cases of non-independence amongst subfactors.

Independence of Factors within Each Scale

Our original analysis plan was to assess relationships among the 5 decision styles and the three uncertainty scores (total intolerance, F1, and F2), but we needed to assess whether the subfactors were sufficiently independent of each other. First, we conducted both exploratory and confirmatory factor analysis on the uncertainty scores. In brief, the subfactors F1 and F2 were highly correlated with each other (r (129) = .77) and the total uncertainty score (F1: r (129) = .95; F2: r (129) = .94), and showed significant covariance with each other from the confirmatory factor analysis (see Appendix A for details). Consequently, we did not treat total intolerance, F1, F2 as independent scale factors. However, we still wanted to capture the conceptual difference between the two factors, so we calculated an F2 Dominance Score, calculated as F2 minus F1 for each participant. The F2 dominance score indicates the extent to which an individual is more concerned with the perceived unfairness of uncertainty (F2) relative to the behavioral consequences of uncertainty (F1); with higher values reflecting more importance for unfairness than behavioral consequences. This F2 dominance score was largely independent of the total uncertainty score (r (129) = .17, p = .08, see upper left of Figure 1), allowing us to simultaneously evaluate the total intolerance of uncertainty and the relative importance of each factor without the problem of high covariance.

Next, we assessed the independence of the subfactors from the General Decision-Making Styles survey. Figure 1 shows a correlogram displaying the correlations within and across subfactors of the two self-report surveys. The General Decision-Making Styles (GDMS) inventory was originally developed and validated as a set of distinct yet related decision-making styles (Scott & Bruce, 1995). Scott and Bruce emphasized that while each style represents a unique approach to decision-making, individuals may exhibit a combination of styles, indicating that the subscales are mostly independent but not mutually exclusive. Later research supports treating the GDMS subscales as separable constructs and also emphasizes that they are not rigid categories, as individuals often display overlapping styles when making decisions (Loo et al., 2000; Thunholm, 2004).

In our dataset, intercorrelations among decision styles (Figure 1 lower right) were generally moderate to small, consistent with the view that the subscales represent largely distinct patterns of decision-making. The correlogram revealed four significant correlations: the intuitive decision-making style was positively correlated with both the rational (r (129) = 0.42, p < 0.5) and spontaneous decision-making styles (r (129) = 0.35, p < 0.05), the dependent decision-making style was positively correlated with the avoidant decision-making style (r (129) = 0.51, p < 0.05), and the avoidant decision-making style was positively correlated with the spontaneous decision-making style (r (129) = 0.26, p < 0.05). Creating composite scores among these 5 factors, like we did with the F2 dominance score, was not straightforward, so we controlled for these moderate dependencies in the regression analyses below, allowing us to evaluate the connection between intolerance of uncertainty and each distinct decision-making style, independent of the other styles’ influence.

As with any self-report instrument, the GDMS assesses the decision-making style individuals report using, which may not accurately reflect the one they actually employ in real-world contexts. Nonetheless, the GDMS provides a validated and widely used framework for assessing individual differences in decision-making tendencies, and our analytic approach reduces and controls for non-independence amongst the subfactors.

Total Intolerance of Uncertainty

We analyzed the relationship between uncertainty intolerance and decision-making styles, while controlling for non-independence of the decision-making styles, using multiple linear regression (Table 2). For total intolerance of uncertainty, the results indicate two statistically significant associations: the rational decision-making style shows a negative association (b = −0.518, SE = 0.1818, t = −2.85, p < .01), whereas the avoidant decision-making style shows a positive association (b = 0.532, SE = 0.1453, t = 3.66, p < .001). Therefore, individuals with a higher total intolerance of uncertainty were more likely to engage in avoidant decision-making and less likely to adopt a rational decision-making approach.

Factor 2 Dominance

As a reminder, the factor 2 dominance score was created to control for the high correlations between the F1 and F2 subfactors in the intolerance of uncertainty scale. Conceptually, this score reflects a person’s tendency to care more about the unfairness of uncertainty compared to the behavioral consequences of it. The linear regression with F2 dominance score and decision-making styles (Table 2) showed that both dependent and avoidant decision-making styles were positively associated with factor 2 dominance (b = 1.448, SE = 0.3929, t = 3.68, p < .001; b = 1.507, SE = 0.3461, t = 4.35, p < .001). This means that individuals who were more troubled by the unfairness of uncertainty, regardless of their overall intolerance of it, were more likely to engage in both dependent and avoidant decision-making.

Discussion

The present study investigated the relationship between intolerance of uncertainty and the five decision-making styles identified by the General Decision-Making Style Scale (Scott & Bruce, 1995): rational, intuitive, dependent, avoidant, and spontaneous. The findings reveal how different levels of intolerance toward uncertainty correlate with individuals’ decision-making styles.

Key Findings and Interpretation

The results showed several significant correlations between intolerance of uncertainty and decision-making styles. Notably, individuals with a higher total intolerance of uncertainty were more likely to use avoidant decision-making styles. This means they tend to delay or evade making decisions when faced with ambiguous or uncertain situations. This approach to decision-making could increase and prolong discomfort, as avoiding making a decision prevents a person from quickly resolving the uncertainty. This finding aligns with previous research and supports two out of the four-factor structures of the Intolerance of Uncertainty Scale (Buhr & Dugas, 2002), indicating that individuals with intolerance for uncertainty often struggle to take action and tend to avoid decision-making in uncertain situations (Buhr & Dugas, 2002). These avoidant individuals may feel heightened discomfort when confronted with uncertainty, leading them to postpone choices to escape the associated stress and cognitive burden.

In contrast, individuals who exhibited lower levels of intolerance of uncertainty favored a rational decision-making style. This suggests that rational decision-makers may be more comfortable processing uncertainty through logical analysis and systematic evaluation, enabling them to navigate the emotional distress typically associated with uncertain situations. This finding supports existing literature indicating that rational decision-makers are more likely to take a deliberate and logical approach to decision-making, which would inherently slow the decision process and thus prolong the experience of uncertainty (Scott & Bruce, 1995).

Further analysis examining the two factors of the Intolerance of Uncertainty Scale (Buhr & Dugas, 2002) revealed that individuals who scored higher on Factor 2, which reflects the belief that uncertainty is unfair and spoils everything, also exhibited higher use of both dependent and avoidant decision-making styles. This pattern suggests that individuals who perceive uncertainty as negative may become reliant on others for guidance or choose to avoid decisions altogether in an attempt to minimize the perceived personal threat.

The correlogram analysis (Figure 1) also provided insights into how different decision-making styles relate to one another. Rational and intuitive styles were positively correlated, indicating that individuals who rely on logic may also incorporate elements of intuition when making decisions. This aligns with Scott and Bruce (1995), suggesting that decision-making strategies are not always mutually exclusive, but rather can complement one another. Additionally, avoidant decision-making was positively correlated with both dependent and spontaneous styles, indicating that individuals who avoid decisions may also be prone to either impulsively making decisions or heavily leaning on others for support. This is supported by Gambetti et al. (2008), who also found a positive correlation between avoidant decision-making and both dependent and spontaneous decision-making styles. Moreover, the correlation between avoidant and spontaneous decision-making styles is also supported by Bavolar and Orosová (2015), who found a positive relationship between these two styles. However, Bavolar and Orosová (2015) found a negative correlation between avoidant and dependent decision-making styles. This contrasts with the findings of the present study, which showed a positive correlation. Lastly, the intuitive and spontaneous decision-making styles were positively correlated, indicating that intuitive individuals tend to make decisions quickly when facing time pressure and are more likely to rely on their intuition (Gambetti et al., 2008; Spicer & Sadler-Smith, 2005).

Theoretical Contributions

The present findings contribute to the theoretical understanding of decision-making by providing correlational support for the notion that decision-making styles are distinct yet interrelated constructs. Consistent with Scott and Bruce (1995), Thunholm (2004), Loo et al. (2000), Gambetti et al. (2008), and Bavolar and Orosová (2015), the correlations observed between certain decision-making styles (e.g., rational-intuitive, dependent-avoidant, intuitive-spontaneous, avoidant-spontaneous) indicate that individuals often employ overlapping cognitive and emotional strategies rather than relying exclusively on a single style. This supports a multidimensional view of decision-making, emphasizing the flexibility and context-dependent nature of cognitive approaches to uncertainty.

Furthermore, this study supports existing theoretical models of intolerance of uncertainty by highlighting its association with specific decision-making tendencies. The relationship between higher intolerance of uncertainty and avoidant decision-making, as well as lower intolerance of uncertainty and rational decision-making, is consistent with existing literature. Research suggests that individuals who have difficulty with uncertainty are more likely to engage in avoidance behaviors. In contrast, individuals who are less affected by intolerance of uncertainty may feel more comfortable using logical analysis to approach problems instead of avoiding them. This leads to improved decision-making strategies in uncertain situations (Buhr & Dugas, 2002; Jensen et al., 2014; Scott & Bruce, 1995). Importantly, a unique aspect of this study that adds nuance to the theoretical models of intolerance of uncertainty is the use of a factor-specific F2-dominance score, which reveals that individuals who perceive uncertainty as unfair are particularly prone to dependent and avoidant decision-making. This finding contributes to theoretical models of intolerance of uncertainty by showing that it is specific cognitive appraisals of uncertainty, such as perceiving it as unfair, rather than general intolerance alone, that may be linked to greater reliance on dependent and avoidant decision-making behaviors.

Finally, these results align with concepts from behavioral economics, such as the certainty effect described in prospect theory by Kahneman and Tversky (1979). Individuals with high intolerance of uncertainty tend to prefer predictable outcomes and avoid ambiguous options, reflecting the certainty effect, in which people favor guaranteed outcomes even when they are not the most advantageous. By linking a dispositional factor such as intolerance of uncertainty to decision-making styles, these findings suggest a theoretical bridge between research on individual differences and behavioral economics, highlighting how personality traits may influence responses to ambiguity.

Implications for Practice

A potential benefit of this study includes giving individuals insight into their decision-making style and intolerance of uncertainty. This knowledge can enhance self-awareness, allowing people to recognize how they respond to ambiguous and unpredictable situations, and helping them develop strategies for more effective decision-making. For example, individuals with a high intolerance of uncertainty who tend to avoid decisions might benefit from cognitive-behavioral techniques to tolerate ambiguity, gradually expose themselves to uncertain situations, and develop structured decision-making strategies to manage stress. Furthermore, encouraging these individuals to adopt a quicker or more proactive decision-making style, such as intuitive or rational approaches, may help reduce their discomfort by minimizing the time they spend facing the uncertainty they find difficult to tolerate.

Furthermore, the present study’s findings suggest that individuals with higher intolerance of uncertainty are more likely to adopt avoidant and dependent decision-making styles, meaning they may delay decisions or rely heavily on others when facing ambiguity. In high-stakes professions, such as healthcare, aviation, emergency response, or finance, these tendencies can reduce efficiency, slow critical decision-making, and increase the likelihood of errors or overly cautious decisions. For example, avoiding a necessary decision or constantly seeking reassurance may delay time-sensitive actions or lead to ineffective outcomes. By systematically assessing decision-making styles and intolerance of uncertainty levels, training programs could identify individuals at risk of these patterns and provide targeted interventions, such as structured decision-making strategies or techniques to tolerate uncertainty, which encourage more rational or adaptive approaches. Understanding this link between intolerance of uncertainty and decision-making styles can therefore help improve performance, reduce errors, and enhance outcomes in professions where effective decision-making under uncertainty is critical.

Limitations/Future Directions

While this study provides important insights, several limitations should be acknowledged. The study sample mainly included young adults aged 18-24, predominantly female, which limits the generalizability of the findings. Additionally, self-report measures, while convenient, are subject to social desirability bias and participants’ ability to accurately assess their own decision-making tendencies. One other limitation in this study is that data was collected via online self-report without explicit safeguards to detect automated messages (i.e., bots). Although no anomalous response patterns were observed, future studies should incorporate attention checks and bot-detection procedures to further strengthen data integrity. Future studies could also benefit from incorporating behavioral decision-making tasks or longitudinal designs to capture how intolerance of uncertainty and decision-making styles evolve over time. Finally, it would also be valuable to explore whether a causal relationship exists between decision-making styles and intolerance of uncertainty. For instance, if individuals were trained to adopt more rational or intuitive decision-making approaches, their intolerance of uncertainty might decrease. Or, if we employed an experimental design that systematically manipulated uncertainty, we could determine if there was a causal effect on the adoption of different decision-making styles.

Conclusion

This study focuses on the associations between intolerance of uncertainty and individual decision-making styles. It emphasizes the importance of recognizing personal traits within decision-making processes. By understanding these relationships more deeply, we can help individuals develop adaptive strategies for dealing with uncertain situations, ultimately enhancing both personal and professional decision-making outcomes.

Footnotes

ORCID iD

Sara Valentin

Ethical Considerations

This study received ethical approval from the Missouri Western State University IRB (#63) on 10/15/2024.

Consent to Participate

Respondents gave written consent before starting the survey.

Author contributions

Conceptualization: Sara Valentin; Methodology: Sara Valentin; Formal analysis and investigation: Sara Valentin, Corey White; Writing - original draft preparation: Sara Valentin; Writing - review and editing: Corey White; Supervision: Corey White

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available through this link

Author Biographies

Sara Valentin conducted this research as an undergraduate independent research project in psychology under the mentorship of Corey White. Her research interests are in cognitive psychology and neuropsychology.

Corey White, Ph.D., Professor of Psychology, Missouri Western State University, St. Joseph, Missouri, USA.

Appendix

Table 2.

Multiple Linear Regression

	Total uncertainty
	Estimate	Std. Error	t value	Pr (>\|t\|)
(Intercept)	3.2458	4.5130	0.719	0.473,335
Intuitive	0.3317	0.2201	1.507	0.134,244
Dependent	−0.1578	0.1650	−0.957	0.340,642
Rational	−0.5182	0.1818	−2.851	0.005098	**
Avoidant	0.5317	0.1453	3.659	0.000371	***
Spontaneous	−0.2079	0.1700	−1.223	0.223,692

	F2 dominance
	Estimate	Std. Error	t value	Pr (>\|t\|)
(Intercept)	1.7467	10.7493	0.162	0.871,178
Intuitive	0.1392	0.5242	0.265	0.791,076
Dependent	1.4475	0.3929	3.684	0.000339	***
Rational	0.7731	0.4330	1.786	0.076575
Avoidant	1.5068	0.3461	4.353	2.75e-05	***
Spontaneous	0.4490	0.4050	1.109	0.269,599

Significant Beta Weights from Regression Analyses.

[*p < .05 **p < .01 ***p < .001].

Note. Multiple linear regression depicting the correlation between decision-making styles and intolerance of uncertainty.

Figure 1.

Correlogram. Note. Correlogram showing the correlations among F2 Dominance, Total Uncertainty, and the different Decision-Making Styles. Creating the F2-dominance score eliminated significant correlations among the subfactors for the intolerance of uncertainty scale (gray box, upper left). There were also significant correlations among decision styles (dashed black box, lower right), which were controlled for with regression analysis (see text). * indicates the correlation was significant at the p < .05 level

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