Decision-Making Style (Head Vs. Heart) (DMS)

1. Abstract

The Decision-Making Style (Head Vs. Heart) (DMS) scale, developed by psychometricians and consumer psychologists Thomas P. Novak and Donna L. Hoffman (2009), is an empirical psychometric instrument designed to measure the relative primacy of cognition versus affect in discrete decision-making episodes. While earlier psychometric traditions evaluated cognitive styles—such as rational versus intuitive processing—predominantly as enduring, cross-situational personality traits (e.g., Epstein’s Rational-Experiential Inventory), the DMS scale addresses a critical theoretical and methodological gap by operationalizing decision style as an episodic, situation-specific construct. The scale captures the subjective experience of whether an individual relied predominantly on their analytical intellect (“head”) or their emotional, visceral intuition (“heart”) during a targeted choice context.

Structured as a multi-item Likert-type semantic and evaluative inventory, the instrument assesses two focal dimensions: Rational Decision Processing (cognitive, logical, deliberative, and evidence-driven evaluation) and Experiential/Affective Decision Processing (affective, feelings-based, visceral, and holistic appraisal). Psychometric evaluations demonstrate robust structural integrity, yielding Cronbach’s alpha coefficients typically exceeding .85 across both subscales. Confirmatory factor analysis supports a two-factor oblique structure, demonstrating that rational and experiential orientations are not mutually exclusive polar opposites on a single continuum, but rather orthogonal or moderately correlated processing modes capable of operating simultaneously. The scale exhibits exemplary convergent validity with established measures of dispositional thinking styles, pronounced discriminant validity against unrelated personality dimensions, and superior predictive validity regarding post-choice satisfaction, brand engagement, and risk tolerance in task-specific behavioral paradigms. This article provides a comprehensive evaluation of the DMS scale, detailing its theoretical foundation within dual-process theory, psychometric properties, factor structure, scoring mechanics, and extensive empirical applications across cognitive psychology, consumer research, behavioral economics, and clinical judgment.

2. Keywords

Decision-Making Style, Head vs Heart, Dual-Process Theory, Cognitive Experiential Self-Theory, Rational Processing, Affective Processing, Consumer Decision Making, Psychometrics, Situation-Specific Cognition, Intuition, Epistemic Motivation, Heuristic Processing

3. Authors

The Decision-Making Style (Head Vs. Heart) instrument was conceptualized, operationalized, and validated by two leading scholars in consumer psychology, digital environments, and quantitative psychometrics:

• Thomas P. Novak, Ph.D. — Professor of Marketing and Albert O. Steffey Chair in Marketing at the School of Business, George Washington University (formerly at the Owen Graduate School of Management, Vanderbilt University, and the Fox School of Business, Temple University). Novak is renowned for his pioneering structural equation modeling work on flow states, dual-process cognition, and human-computer interactions.
• Donna L. Hoffman, Ph.D. — Louis Rosenfeld Distinguished Scholar and Professor of Marketing at the School of Business, George Washington University. Hoffman is an internationally acclaimed researcher specializing in online consumer behavior, structural psychometric modeling, behavioral analytics, and automated decision environments.

Correspondence regarding the foundational research and methodological framework of the scale was originally routed through the Sloan Center for Internet Retailing, Owen Graduate School of Management, Vanderbilt University, and subsequently maintained at the Center for the Connected Consumer at George Washington University (Washington, D.C., USA).

4. Purpose

The primary purpose of the Decision-Making Style (Head Vs. Heart) scale is to assess, isolate, and quantify the specific processing mode—rational deliberation versus affective intuition—mobilized by an individual during a discrete, real-time or recent decision event. Historically, the field of differential psychology conceptualized thinking styles primarily through trait-based frameworks. Instruments such as the Need for Cognition (NFC) scale (Cacioppo & Petty, 1982), the Faith in Intuition (FI) inventory (Epstein et al., 1996), and the General Decision-Making Style (GDMS) inventory (Scott & Bruce, 1995) treat an individual’s reliance on logic or emotion as a chronically accessible, stable disposition. While these trait instruments provide valuable epidemiological and personality-level profiles, they suffer from a fundamental limitation: they fail to account for situational variance, task complexity, emotional framing, and context-dependent cognitive shifts.

Novak and Hoffman (2009) developed the DMS scale to rectify this methodological imbalance. The instrument provides researchers and practitioners with an episodic measurement tool that specifically indexes the actualized processing style deployed in response to concrete environmental stimuli, consumption choices, ethical dilemmas, or clinical situations. By measuring both the “Head” (analytical, systematic, calculating logic) and the “Heart” (gut feelings, emotional resonance, hedonic impulses), the DMS allows for the empirical examination of “cognitive fit” or regulatory congruence. Theoretical paradigms suggest that optimal decision quality, emotional well-being, and post-decisional satisfaction occur when an individual’s chronic disposition matches the task demands and the chosen situational processing mode.

In academic and applied research, the DMS scale serves several distinct purposes:

• Experimental Psychology: Capturing state-level manipulation checks following cognitive load, emotional priming, or mindfulness interventions designed to alter analytic versus intuitive reasoning.
• Consumer Behavior and Marketing: Explaining why consumers oscillate between utilitarian product evaluations (functional attributes, price-per-unit metrics) and hedonic consumption (aesthetic attraction, brand love, symbolic identification).
• Behavioral Economics and Financial Choice: Quantifying how emotional states bias risk perception, prospect evaluation, and portfolio allocation compared to disciplined mathematical calculations.
• Medical and Health Decision-Making: Evaluating whether patients and healthcare providers select treatment protocols based on statistical survival rates and clinical trial data (“Head”) or anecdotal patient narratives and visceral fear (“Heart”).
• Clinical and Counseling Contexts: Assisting clinicians in diagnosing dysfunctional cognitive processing, such as emotional over-reactivity in anxiety disorders or hyper-rational detachment in obsessive-compulsive tendencies, within specific interpersonal confrontations.

5. Psychological Construct

The psychological construct underlying the DMS scale centers on the structural and functional duality of human mental processing during choice tasks. Rather than treating decision-making style as a monolithic, bipolar continuum—where reliance on reason necessarily extinguishes feeling—the DMS operationalizes “Head” and “Heart” as two independent, highly articulated cognitive-affective systems capable of concurrent activation.

The “Head” Dimension: Rational, Analytic Cognition

The “Head” dimension reflects the activation of conscious, controlled, effortful, rule-governed, and linguistically mediated thinking. When an individual approaches a decision via the Head, their mental operations are characterized by:

• Systematic Attribute Decomposition: Breaking down complex alternatives into discrete, measurable components (e.g., comparing technical specifications, monetary costs, warranty lengths).
• Logical Coherence and Deductive Validity: Ensuring that conclusions follow logically from established premises and that choices adhere to normative economic principles, such as transitivity and cost-benefit optimization.
• Epistemic Verification: Requiring objective, empirical evidence and empirical validation before forming a preference, intentionally suppressing gut inclinations that lack substantive justification.
• High Cognitive Resource Expenditure: Relying heavily on working memory, central executive functioning, and focused attention, making this mode vulnerable to cognitive depletion, time constraints, and information overload.

For example, a consumer purchasing a vehicle using predominantly “Head” processing will construct a comparative spreadsheet, assess fuel efficiency ratings, calculate long-term depreciation, and read independent crash-test evaluations, consciously insulating themselves from the emotional allure of vehicle styling or brand prestige.

The “Heart” Dimension: Experiential, Affective Processing

Conversely, the “Heart” dimension captures the operation of experiential, holistic, associative, emotionally driven, and pre-reflective cognition. Grounded in somatic cues and emotional associations, this dimension entails:

• Holistic and Gestalt Evaluation: Appraising choices as integrated wholes rather than dissecting them into isolated parameters, responding to the overall “feel” or aesthetic harmony of the target.
• Affective Primacy and Somatic Markers: Utilizing immediate emotional reactions (joy, dread, excitement, relief) as valid informational inputs. As posited by Antonio Damasio’s somatic marker hypothesis, bodily sensations guide choice behavior rapidly prior to conscious deliberation.
• Intuitive and Associative Processing: Accessing deep-seated experiential schemas, narrative memories, and implicit heuristic associations stored in long-term memory without conscious retrieval effort.
• Speed and Cognitive Automaticity: Functioning effortlessly with minimal demand on executive working memory, allowing individuals to navigate decisions swiftly even under conditions of high stress or cognitive distraction.

For example, an individual selecting an apartment via “Heart” processing will decide within seconds of crossing the threshold because the space feels “warm, welcoming, and like home,” disregarding structural imperfections or slightly higher rent that a rational analysis would flag as problematic.

Orthogonality and the Dynamics of Fit

A critical nuance of the construct formulated by Novak and Hoffman is the orthogonal independence of these two modes. A decision-maker can experience:

1. High Head / Low Heart: Purely detached, analytical, mechanistic decisions (e.g., executing a routine index-fund rebalancing).
2. Low Head / High Heart: Purely affective, impulsive, hedonic decisions (e.g., purchasing a luxury fashion accessory on impulse).
3. High Head / High Heart: Dialectical, integrated decisions where intense emotional passion is accompanied by exhaustive research and strategic planning (e.g., selecting a life partner, founding an entrepreneurial venture).
4. Low Head / Low Heart: Apathetic, habitual, or low-involvement choices characterized by inertia (e.g., repurchasing the same brand of household paper towels).

6. Theoretical Framework

The theoretical architecture of the Decision-Making Style (Head Vs. Heart) scale is anchored in the convergence of multiple cognitive and social psychological paradigms, most notably Dual-Process Theories of judgment and Seymour Epstein’s Cognitive-Experiential Self-Theory (CEST).

Cognitive-Experiential Self-Theory (CEST)

Epstein (1990, 1994, 2003) posited that human beings process information through two parallel, interacting systems: the Rational System and the Experiential System. The rational system is uniquely human, analytical, slow, deliberate, language-based, and affect-free; it operates through logical rules and requires conscious intentionality. In contrast, the experiential system is evolutionary ancient, continuous with non-human animals, rapid, automatic, holistic, pre-conscious, and closely tied to the hedonic principle (the pursuit of pleasure and avoidance of pain). Novak and Hoffman adapted CEST’s foundational insights but addressed a major theoretical tension: CEST historically measured these systems as trait-level personal dispositions (via the Rational-Experiential Inventory). Novak and Hoffman extended CEST by demonstrating that environmental cues, task properties, and momentary emotional states activate situational manifestations of these two systems, necessitating state-level psychometric measurement.

System 1 and System 2 Dual-Process Architecture

The scale integrates modern dual-process models articulated by cognitive theorists such as Daniel Kahneman, Amos Tversky, Keith Stanovich, and Jonathan Evans. Under this architecture:

• System 1 (Heuristic / Intuitive / Heart): Characterized by autonomous execution, low working-memory demand, associative networks, and affective valuation. It produces rapid behavioral intuitions without cognitive strain.
• System 2 (Analytic / Deliberative / Head): Characterized by cognitive decoupling, mental simulation, hypothetical thinking, executive override, and algorithmic computation. It can interrogate, validate, or override the instinctual outputs generated by System 1.

The DMS scale explicitly measures the subjective salience and behavioral deployment of System 1 versus System 2 operations within a discrete choice context, operationalizing the degree to which an individual permits System 1 affect to drive choice versus mobilizing System 2 executive resources to steer the outcome.

The Affect-as-Information and Somatic Marker Hypotheses

The theoretical framework also draws upon Norbert Schwarz and Gerald Clore’s (1983, 2003) Affect-as-Information heuristic and Antonio Damasio’s (1994) Somatic Marker Hypothesis. These frameworks argue that feelings do not merely distort rational thought; rather, affect serves as a sophisticated, efficient computational mechanism that provides rapid diagnostic information regarding the valence, safety, and personal relevance of complex stimuli. The “Heart” dimension of the DMS scale captures the respondent’s deliberate utilization of these affective signals as legitimate decision criteria, formalizing the theoretical recognition that feeling-based choices represent an authentic, structured mode of cognitive appraisal rather than random noise or irrational cognitive failure.

7. Validity

The psychometric validity of the Decision-Making Style (Head Vs. Heart) scale has been extensively demonstrated across numerous empirical studies involving diverse experimental contexts, consumption choices, and decision environments.

Construct Validity

Construct validity was initially established by Novak and Hoffman (2009) across several large-scale multi-method studies. By contrasting task-induced conditions (e.g., priming analytic focus via mathematical calculations versus priming affective focus through emotional storytelling), the authors demonstrated that the DMS subscales respond dynamically and systematically to external situational pressures. When participants are instructed to evaluate choices based on factual merits, scores on the Rational (Head) subscale increase significantly, while scores on the Experiential (Heart) subscale decrease. Conversely, when instructed to trust their instincts and feelings, the pattern reverses predictably, confirming that the scale accurately tracks the intended psychological states.

Convergent Validity

Convergent validity has been repeatedly substantiated by examining correlations between the state-level DMS and established trait-level measures of thinking style:

• The DMS Head subscale correlates positively and moderately with trait Need for Cognition (r ranging from .38 to .52, p < .001) and the Rational scale of Epstein’s REI, confirming that individuals with chronic rational dispositions are more prone to mobilizing state-level cognitive deliberation during specific tasks.
• The DMS Heart subscale exhibits robust positive correlations with the Faith in Intuition scale (r ranging from .41 to .58, p < .001) and measures of emotional expressivity and affective reactivity.

Importantly, these correlations remain moderate rather than extremely high, proving that while trait tendencies influence state deployment, the DMS captures unique variance attributable to the specific decision environment that trait scales fail to explain.

Discriminant Validity

Discriminant validity was verified using Fornell-Larcker criteria and average variance extracted (AVE) comparisons. In confirmatory factor models, the AVE for both the Head and Heart factors routinely exceeds the squared correlation between the two latent constructs (which typically fluctuates between r = -.15 and r = .25 depending on task complexity), confirming their statistical orthogonality. Furthermore, the DMS subscales display negligible or non-significant correlations with unrelated personality dimensions such as general intelligence (IQ), social desirability response bias (e.g., the Marlowe-Crowne Social Desirability Scale), and broad Big Five traits such as Neuroticism or Extraversion, confirming that the tool measures decision processing style rather than general emotional stability or sociability.

Predictive and Criterion Validity

The scale exhibits exceptional predictive validity across a spectrum of behavioral and psychological outcomes:

• Post-Choice Regret and Satisfaction: Novak and Hoffman (2009) demonstrated that the congruence (fit) between a consumer’s chronic thinking style, the situational context, and their DMS score strongly predicts subjective satisfaction. When an individual uses “Head” processing for a utilitarian product (e.g., insurance, washing machine) and “Heart” processing for a hedonic product (e.g., perfume, artwork), post-purchase satisfaction is maximized and cognitive dissonance is minimized.
• Price Sensitivity and Value Trade-offs: High “Head” scores predict rigorous price sensitivity, intense comparison shopping, and accurate recall of functional attributes. In contrast, high “Heart” scores predict willingness to pay price premiums based on brand resonance and aesthetic allure.
• Information Search Trajectories: In digital search environments, higher “Head” ratings correlate with increased page views, longer dwell times on technical documentation, and structured keyword querying, whereas higher “Heart” ratings correlate with image-centric browsing, video engagement, and rapid checkout decisions.

8. Reliability

The Decision-Making Style (Head Vs. Heart) scale possesses high internal consistency, stability, and scale homogeneity across diverse demographic segments and experimental implementations.

Internal Consistency

In the foundational validation samples reported by Novak and Hoffman (2009), comprising over 1,200 participants across multiple laboratory experiments and field surveys, the subscales demonstrated strong internal consistency:

• Rational (Head) Processing Subscale: Cronbach’s alpha coefficients regularly ranged from α = .86 to α = .92. Composite reliability (CR) indices calculated via structural equation modeling typically exceeded .89, with average variance extracted (AVE) values surpassing .60, indicating that the latent construct accounts for the majority of the variance in the manifest items.
• Experiential/Affective (Heart) Processing Subscale: Cronbach’s alpha coefficients ranged from α = .84 to α = .91, with composite reliability (CR) exceeding .88 and AVE values regularly above .58.

Subsequent independent replications in consumer marketing, organizational behavior, and behavioral finance have corroborated these figures. For example, cross-cultural studies utilizing translated versions of the instrument in Western Europe and East Asia report Cronbach’s alphas consistently remaining above the conventional .80 benchmark for both dimensions.

Test-Retest Stability vs. State Sensitivity

Because the DMS is deliberately engineered as a situation-specific (state-level) instrument, conventional test-retest reliability across long time intervals must be interpreted with theoretical caution. When the exact same decision context is evaluated over a brief temporal window (e.g., 48 to 72 hours), test-retest reliability is high (r > .80), indicating stable recall of the cognitive and affective processes utilized during that event. However, when measured across differing decision tasks (e.g., buying a car versus choosing an evening movie), cross-situational correlations drop to modest levels (r = .25 to .40). This variability does not represent measurement unreliability; rather, it provides vital empirical evidence of the scale’s high sensitivity to situational variance, fulfilling its design goal of detecting state-dependent cognitive shifts rather than static trait inertia.

9. Factor Analysis

The latent structure of the Decision-Making Style (Head Vs. Heart) scale has been thoroughly tested using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) within structural equation modeling (SEM) frameworks.

Exploratory Factor Analysis (EFA)

Initial exploratory factor analyses utilizing principal axis factoring and maximum likelihood estimation with oblique rotations (Promax and Oblimin) consistently extract two distinct, dominant eigenvalues exceeding Kaiser’s criterion of 1.0 (scree plot analyses confirm a clear two-factor elbow). The two factors correspond cleanly to the theoretical dimensions:

• Factor 1 (Head / Rationality): Explains approximately 32% to 38% of the total variance, with all rational, analytic, and logical items loading cleanly (λ ≥ .70) and displaying negligible cross-loadings on the alternative factor (λ ≤ .20).
• Factor 2 (Heart / Experientiality): Explains an additional 24% to 30% of the total variance, capturing all affective, intuitive, and feeling-based items with primary factor loadings exceeding .68 and minimal cross-loadings.

Confirmatory Factor Analysis (CFA) and Model Fit

To establish structural validity, Novak and Hoffman (2009) evaluated competing structural models via CFA using maximum likelihood estimation in AMOS and LISREL. They compared three alternative structural specifications:

1. Single-Factor Unidimensional Model: All items loading onto a single general decision-making factor (or a bipolar Head-vs-Heart continuum). This model showed exceptionally poor fit (χ²/df > 8.5, CFI < .70, TLI < .65, RMSEA > .14), demonstrating conclusively that Head and Heart are not opposite ends of a single continuum.
2. Two-Factor Orthogonal Model: Rational and Experiential dimensions constrained to be completely uncorrelated (r = .00). This model displayed acceptable fit, but was statistically inferior to the oblique specification.
3. Two-Factor Oblique Model: Rational and Experiential dimensions specified as distinct, correlated latent factors. This model consistently provided superior, outstanding fit across all calibration and validation samples:

The fit indices for the two-factor oblique model regularly achieve exemplary thresholds in published literature:

• Chi-Square to Degrees of Freedom Ratio (χ²/df): Ranging between 1.45 and 2.10 (well below the conservative threshold of 3.0).
• Comparative Fit Index (CFI): .96 to .98 (exceeding the .95 gold standard).
• Tucker-Lewis Index (TLI): .95 to .97.
• Root Mean Square Error of Approximation (RMSEA): .038 to .052 (with 90% confidence intervals entirely below .06).
• Standardized Root Mean Square Residual (SRMR): .032 to .045.

Item standardized factor loadings (λ) across CFA models are uniformly strong and statistically significant (p < .001), typically spanning from .72 to .89. The latent factor correlation between the Head and Heart constructs generally hovers near zero or reveals a weak negative correlation (r = -.08 to -.22) in complex choice scenarios, confirming that these two processing systems are structurally independent and functionally decoupled in human cognition.

10. Instrument / Measurement Tool

The Decision-Making Style (Head Vs. Heart) scale is administered as an episodic, self-report psychometric instrument. Its operational structure, administrative parameters, and scoring conventions are outlined below:

• Instrument Designation: Decision-Making Style (Head Vs. Heart) Scale (DMS).
• Target Domain: Situation-specific cognitive and affective processing in choice tasks.
• Test Format: Paper-and-pencil or computer-assisted self-administered questionnaire (web surveys, mobile lab experiments).
• Administration Time: Approximately 3 to 5 minutes to complete, making it highly suitable for post-experimental checks or multi-wave survey protocols.
• Item Inventory: Comprises multi-item batteries measuring the situation-specific rational (“Head”) processing and situation-specific experiential (“Heart”) processing, typically deployed as paired semantic differentials or Likert-type agreement scales.
• Response Format: Typically administered using a 7-point Likert-type scale ranging from 1 (“Strongly Disagree” / “Not at all”) to 7 (“Strongly Agree” / “Completely”), or 7-point bipolar semantic differential anchors (e.g., “Relying completely on logic” [1] to “Relying completely on feelings” [7] when assessing single-item indices, or paired construct statements for multi-item subscales).
• Target Reference Framing: Instructions explicitly prompt the respondent to focus on a specific decision just made or recently executed (e.g., “Thinking back to the choice you just completed, please indicate how you made your decision…”).
• Scoring Architecture:
  • Head (Rational) Score: Calculated as the unweighted arithmetic mean of all items loading on the Rational Decision Processing subscale. Higher scores indicate deeper analytical, calculated, and evidence-based scrutiny.
  • Heart (Affective) Score: Calculated as the unweighted arithmetic mean of all items loading on the Experiential Decision Processing subscale. Higher scores denote stronger reliance on emotional impulses, intuitive hunches, and visceral feelings.
  • Relative Processing Differential Index (Optional): In comparative designs, researchers compute a standardized difference score (Z_Head − Z_Heart) or an absolute ratio to locate the respondent along an operational continuum of cognitive dominance.

11. Permissions & Fee and Test Year

The Decision-Making Style (Head Vs. Heart) scale was officially introduced and published in 2009 by Thomas P. Novak and Donna L. Hoffman in the Journal of Consumer Research (Volume 36, Issue 1, pages 56–72). The work was supported in part by academic research grants from the Sloan Center for Internet Retailing at Vanderbilt University.

Licensing and Academic Usage:

• Academic and Non-Commercial Research: The scale is widely considered an open-access psychometric instrument for non-profit academic research, university dissertations, and scientific investigation. Qualified researchers may utilize, adapt, and administer the scale items published within the 2009 Journal of Consumer Research article without paying licensing royalties, provided that rigorous academic attribution is cited in resulting manuscripts, theses, and presentations.
• Commercial Applications: Commercial consulting firms, market research agencies, corporate training programs, and proprietary software developers seeking to integrate the scale into monetized diagnostic platforms, recruitment pipelines, or commercial consumer tracking systems must seek appropriate copyright clearance from the copyright holder, Oxford University Press (on behalf of the Journal of Consumer Research, Inc.), and consult the original authors regarding proprietary rights.

12. References

The theoretical foundations, validation procedures, and empirical applications of the Decision-Making Style (Head Vs. Heart) scale are anchored in the following seminal academic publications:

• Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116–131. https://doi.org/10.1037/0022-3514.42.1.116
• Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. New York: G.P. Putnam’s Sons.
• Epstein, S. (1990). Cognitive-experiential self-theory. In L. A. Pervin (Ed.), Handbook of personality: Theory and research (pp. 165–192). New York: Guilford Press.
• Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49(8), 709–724. https://doi.org/10.1037/0003-066X.49.8.709
• Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. (1996). Individual differences in intuitive-experiential and analytical-rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390–405. https://doi.org/10.1037/0022-3514.71.2.390
• Evans, J. S. B., & Stanovich, K. E. (2013). Dual-process theories of higher cognition: Advancing the debate. Perspectives on Psychological Science, 8(3), 223–241. https://doi.org/10.1177/1745691612460685
• Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.
• Novak, T. P., & Hoffman, D. L. (2009). The fit of thinking style and situation: New measures of situation-specific experiential and rational cognition. Journal of Consumer Research, 36(1), 56–72. https://doi.org/10.1086/596026
• Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45(3), 513–523. https://doi.org/10.1037/0022-3514.45.3.513
• Scott, S. G., & Bruce, R. A. (1995). Decision-making style: The development and assessment of a new measure. Educational and Psychological Measurement, 55(5), 818–831. https://doi.org/10.1177/0013164495055005017
• Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 23(5), 645–665. https://doi.org/10.1017/S0140525X00003435

13. Items of the Scale