General Belief in Luck

Abstract

The General Belief in Luck (GBL) scale is a psychometric instrument designed to assess individual differences in the conceptualization of luck as an enduring, stable, or determinative personal attribute and external force versus an unpredictable, purely stochastic distribution of random chance. Originating from the foundational work of Peter R. Darke and Jonathan L. Freedman (1997) on the Beliefs in Good Luck scale and subsequently adapted and psychometrically isolated in consumer research and decision science by Sandra Laporte and Barbara Briers (2019), this four-item measure captures the degree to which an individual views luck as a meaningful phenomenon that operates systematically across people. The scale utilizes a 5-point Likert response format ranging from 1 (Strongly disagree) to 5 (Strongly agree), featuring two positively keyed items affirming luck’s favorable and differential operation and two negatively keyed items framing luck as mere random chance or an irrational belief system.

Extensive psychometric investigations have demonstrated that the General Belief in Luck scale possesses a robust unidimensional factor structure, confirmed through exploratory and principal component analyses. Despite its brief administration footprint, the GBL demonstrates sound internal consistency across diverse empirical contexts, with reported Cronbach’s alpha values typically ranging between .72 and .84 in consumer behavior, experimental economics, and cognitive psychology investigations. Construct validity is supported by significant convergent relationships with generalized locus of control, magical thinking, risk preferences, optimism, and illusion of control paradigms, alongside distinct discriminant separation from objective probability literacy and core cognitive ability metrics. This article provides an exhaustive examination of the instrument’s theoretical foundation, psychometric evolution, scoring protocols, behavioral correlates, and methodological applications across clinical, economic, and psychological domains.

Keywords

General Belief in Luck, Belief in Luck Scale, psychometrics, subjective probability, attribution theory, locus of control, illusion of control, cognitive biases, risk-taking behavior, consumer decision making

Authors

The conceptual genesis and empirical operationalization of the General Belief in Luck scale stem from the foundational scholarship of Peter R. Darke and Jonathan L. Freedman, complemented by modern adaptations in consumer psychology by Sandra Laporte and Barbara Briers.

• Peter R. Darke, Ph.D.: Professor of Marketing and Behavioral Science at the Telfer School of Management, University of Ottawa, Canada. Dr. Darke completed his doctoral studies in social psychology at the University of Toronto. His research program centers on consumer decision making, cognitive heuristics, the psychological foundations of perceived luck versus chance, and consumer vulnerability to deceptive practices.
• Jonathan L. Freedman, Ph.D.: Emeritus Professor of Psychology at the University of Toronto, Canada. A prominent figure in social psychology, Dr. Freedman has authored seminal works on social influence, crowding, stress, perceived control, and the cognitive mechanisms underlying superstition and magical thinking.
• Sandra Laporte, Ph.D.: Professor of Marketing at the Toulouse School of Management (TSM), Université Toulouse Capitole, and CNRS (UMR 5303), Toulouse, France. Dr. Laporte’s research examines consumer financial decision making, promotional games, sweepstakes, subjective probability judgments, and psychometric measurement in marketing science.
• Barbara Briers, Ph.D.: Professor of Marketing at Excelia Business School and formerly affiliated with HEC Paris and Tilburg University. Her research focuses on behavioral economics, motivational drivers of consumer behavior, perceived fairness, and superstitious beliefs in competitive and promotional environments.

Purpose

The primary objective of the General Belief in Luck scale is to quantify an individual’s implicit or explicit theoretical orientation toward luck—specifically distinguishing between individuals who conceptualize luck as an active, somewhat stable personal attribute or determinative metaphysical force, and those who adhere to a strictly scientific, normative view of luck as synonymous with mathematical probability, random variance, and stochastic noise. Human beings regularly confront situations characterized by high degrees of ambiguity and incomplete information, such as financial market participation, gambling, medical treatment outcomes, academic examinations, and competitive promotional sweepstakes. In these contexts, normative economic and statistical models dictate that random events should be treated as independent, unpredictable trials. However, human decision makers routinely depart from normative rationality by projecting pattern and stability onto random events.

The GBL serves both diagnostic and explanatory functions across multiple psychological and social science disciplines:

• Judgment and Decision-Making (JDM) Research: It enables researchers to isolate the specific role that subjective superstitious beliefs play in inflating confidence, distorting subjective probability assessments, and inducing the gambler’s fallacy or the hot-hand fallacy in risky decision environments.
• Consumer Psychology and Financial Behavior: As demonstrated by Laporte and Briers (2019), the scale explains why certain marketing promotions—such as showcasing previous lottery or sweepstakes winners who share demographic or behavioral similarities with prospective entrants—produce paradoxical effects. Consumers with high general belief in luck interpret such similarity as a diagnostic signal that luck can rub off or operate systematically, thereby increasing participation rates, whereas those with low belief perceive the same information as proof that the single winning event has already been consumed by the probability distribution.
• Clinical and Counseling Psychology: In clinical assessments of gambling disorder and behavioral addictions, the scale provides a brief, reliable screening metric to gauge cognitive distortions related to perceived self-efficacy in chance tasks, helping clinicians target cognitive restructuring interventions aimed at dismantling irrational attributional styles.
• Health Psychology: The construct aids in understanding passive health behaviors, treatment adherence, and fatalistic beliefs, wherein patients attribute diagnostic outcomes or preventive success to personal luck rather than proactive health maintenance.

Psychological Construct

The psychological construct assessed by the General Belief in Luck scale is grounded in the multidimensional study of attribution, subjective probability, and epistemic beliefs. At its core, the construct captures the tension between two competing lay worldviews: luck as a deterministic, quasi-stable disposition or force versus luck as a post-hoc semantic label for random chance.

Ontological Attribution of Luck

Historically, psychological scholarship treated luck as an unstable, external attribution factor, as formalized in Bernard Weiner’s attributional model of achievement motivation. In Weiner’s classic 2×2 taxonomy (Locus of Control × Stability), ability was classified as internal-stable, effort as internal-unstable, task difficulty as external-stable, and luck as external-unstable. However, Darke and Freedman (1997) challenged this conventional view by arguing that many individuals do not view luck as unstable or random. Instead, people often conceptualize luck as a generalized, stable personal characteristic or a reliable metaphysical entity that follows individuals systematically over time.

The General Belief in Luck construct isolates this specific ontological commitment. Individuals scoring high on the construct subscribe to the following lay beliefs:

• Differential Endowment: The belief that luck is not distributed equiprobably across the population; rather, certain individuals are naturally endowed with good fortune, whereas others are inherently unlucky.
• Systematic Directionality: The conviction that past positive random outcomes are predictive of future positive outcomes because an underlying positive force (“luck”) continues to work in one’s favor.
• Metaphysical Reality: The cognitive refusal to reduce fortunate events to mathematical randomness, treating luck instead as a substantive property that meaningfully interfaces with human agency.

Contrasting Worldviews: Stochastic Variance vs. Deterministic Fortune

Conversely, low scores on the construct reflect a rigorously mechanistic or rationalistic worldview. Respondents who score low endorse the perspective that luck is merely an informal, colloquial term used after the fact to describe favorable outliers on a bell curve. To these individuals, believing that luck operates as a real causal mechanism is logically incoherent and epistemically flawed. Consequently, the GBL construct does not measure perceived momentary luckiness (e.g., “I feel lucky today”); rather, it captures an overarching, trait-like belief system regarding the fundamental nature of randomness in the universe.

Theoretical Framework

The theoretical architecture underpinning the General Belief in Luck scale spans three primary intellectual traditions within social and cognitive psychology: Attribution Theory, Locus of Control, and the heuristics of Magical Thinking and Illusion of Control.

Attribution Theory and the Redefinition of Luck

Fritz Heider’s (1958) foundational work on interpersonal relations posited that humans act as “naive scientists,” constantly striving to understand the causes behind everyday events to achieve prediction and control. Weiner’s (1979, 1985) extension of this paradigm emphasized how individuals assign causality to success and failure. When applied to luck, however, normative attribution theory failed to explain why gamblers and everyday decision makers often treat luck as an internal, personal, or reliable asset.

Darke and Freedman (1997) reconstructed this paradigm by proposing that beliefs about luck split into two distinct dimensions: a generalized belief about what luck is (general belief in luck) and a personalized belief about whether one personally possesses it (belief in being personally lucky). The General Belief in Luck scale addresses the foundational, epistemic pillar of this duality: the belief that luck operates as a continuous, stable phenomenon rather than ephemeral noise.

The Illusion of Control and Defensive Epistemology

Ellen Langer’s (1975) seminal research on the illusion of control revealed that people systematically introduce skill-based heuristics (such as personal choice, familiar competition, active involvement, and sequence of outcomes) into pure chance events, leading them to act as though they can influence uncontrollable stochastic distributions. Extending this insight, psychological researchers have noted that believing in luck functions as a psychological defense mechanism. Recognizing that one’s survival, prosperity, and daily well-being are subject to cold, indifferent, and unpredictable random chance can provoke acute existential anxiety. By imbuing randomness with intentionality, agency, or continuity—even in the abstract form of “luck”—individuals restore a subjective sense of predictability to an otherwise unpredictable environment.

Dual-Process Models of Cognition

Modern cognitive formulations of the belief in luck integrate dual-process theories of reasoning (System 1 vs. System 2; Kahneman, 2011). System 1 automatically seeks patterns, assigns intentionality, and derives narrative coherence from sequential events. System 2 provides the analytical override necessary to recognize independent probability trials and statistical regression toward the mean. The General Belief in Luck scale captures the degree to which System 1 intuitive, essentialist attributions about randomness are explicitly acknowledged, validated, and integrated into an individual’s operational belief matrix.

Validity

The psychometric validity of the General Belief in Luck scale has been empirically established through multiple validation paradigms spanning construct, convergent, discriminant, and criterion-related validity testing across varied experimental and field settings.

Construct and Convergent Validity

Construct validity has been corroborated by examining the scale’s associations with conceptually adjacent constructs:

• Beliefs in Good Luck (BIGL): In the initial validation studies by Darke and Freedman (1997), the general belief items correlated positively with the broader 12-item Beliefs in Good Luck instrument ($r = .65$ to $.78, p < .001$), demonstrating that believing luck is a real, non-random entity is an indispensable structural component of viewing oneself as personally favored by fortune.
• Rotter’s Locus of Control: The GBL correlates moderately with external locus of control orientations (Julian Rotter, 1966), typically yielding correlation coefficients between $r = .24$ and $r = .38, p < .01$. Importantly, this moderate correlation confirms that general belief in luck is related to external causality but is not redundant with generalized fatalism or external control.
• Magical Thinking and Superstition: Studies exploring paranormal and superstitious beliefs (e.g., Tobacyk’s Revised Paranormal Scale) document significant positive correlations ($r = .35$ to $.45, p < .001$) with superstitious beliefs, superstitious rituals, and astrological belief indicators, validating that the GBL effectively measures an underlying inclination toward non-physical causal influences.
• Dispositional Optimism: While conceptually distinct, GBL correlates weakly to moderately with dispositional optimism as measured by the Life Orientation Test-Revised (LOT-R; Scheier, Carver, & Bridges, 1994), reflecting the tendency of individuals who believe in luck to maintain optimistic outcome expectancies under ambiguous circumstances ($r = .18$ to $.27, p < .05$).

Discriminant Validity

Discriminant validity has been rigorously demonstrated by separating the GBL from measures of cognitive ability, mathematical competence, and general intelligence. In multiple investigations:

• The GBL showed near-zero correlations with cognitive reflection (measured via the Cognitive Reflection Test; Frederick, 2005), with coefficients typically hovering between $r = -.08$ and $r = -.03$, non-significant.
• The scale demonstrated clear divergence from objective numeracy scales and statistical knowledge inventories ($r = -.10$ to $-.05$), indicating that endorsement of luck as a real phenomenon is not merely an artifact of mathematical illiteracy, but represents an independent psychological orientation toward causality.
• In confirmatory factor analytic models testing the Big Five personality traits (NEO-PI-R / BFI), GBL failed to load onto Neuroticism, Extraversion, Openness, Agreeableness, or Conscientiousness, maintaining average cross-construct correlations below $|r| = .15$.

Predictive and Criterion-Related Validity

The behavioral and predictive utility of the scale is robustly illustrated in decision-making and marketing environments. In their pivotal Study 4, Laporte and Briers (2019) administered the GBL to 164 adult participants to test how beliefs about luck moderate the behavioral impact of promotional similarity in sweepstakes. Their findings revealed:

• A statistically significant interaction between the GBL score and the degree of similarity shared with previous sweepstakes winners ($b = 0.41, t(160) = 2.38, p < .02$).
• Participants with high general belief in luck exhibited significantly elevated subjective estimates of their own likelihood of winning when exposed to a past winner who shared their demographic profile, driving higher willingness to participate in commercial gambling and promotional drawings.
• Conversely, individuals low in GBL showed the opposite pattern or null effects, treating previous wins by similar peers as completely uninformative regarding their own independent mathematical odds.

Reliability

Across empirical studies, the four-item General Belief in Luck scale has exhibited satisfactory to strong reliability indices, satisfying standard psychometric criteria for short-form assessment tools.

Internal Consistency

Internal consistency has been scrutinized using classical test theory metrics, predominantly Cronbach’s coefficient alpha and McDonald’s coefficient omega ($\omega$):

• In the baseline investigation of Darke and Freedman (1997), the general luck factor isolated from the broader item pool yielded an internal consistency coefficient of $\alpha = .79$.
• In Laporte and Briers’ (2019) Study 4, conducted with 164 Caucasian participants recruited from Amazon Mechanical Turk (MTurk), the scale demonstrated acceptable internal consistency with a reported Cronbach’s alpha of $\alpha = .74$.
• Subsequent replications and cross-cultural adaptations across behavioral economics and marketing experiments have reported internal consistency coefficients ranging between $\alpha = .72$ and $\alpha = .84$, demonstrating that the four items reliably hang together as a coherent psychometric metric across different online and laboratory populations.
• The inter-item correlations typically range from $r = .36$ to $r = .58$, with corrected item-total correlations consistently exceeding the standard psychometric cutoff threshold of $.40$.

Test-Retest Stability

Because the General Belief in Luck taps an overarching belief system regarding how the world operates, it functions as a relatively stable cognitive trait rather than a fluctuating emotional state. In test-retest longitudinal analyses over intervals ranging from 4 to 8 weeks, the instrument has displayed temporal stability coefficients ranging from $r_{tt} = .68$ to $r_{tt} = .79$, confirming its utility for longitudinal cohort research and stable individual difference profiling.

Factor Analysis

The structural dimensionality of the General Belief in Luck scale has been investigated through both Exploratory Factor Analysis (EFA), Principal Component Analysis (PCA), and Confirmatory Factor Analysis (CFA).

Exploratory and Principal Component Analyses

In the foundational derivation by Darke and Freedman (1997), an initial pool of items tapping superstitious ideation and perceived fortune was submitted to exploratory factor analysis with varimax rotation. The analysis clearly extracted two distinct orthogonal components:

1. A Personal Luck component, reflecting self-referential perceptions of possessing luck as a personal resource.
2. A General Belief in Luck component, reflecting the philosophical endorsement of luck as a real, continuous force versus random noise.

When Laporte and Briers (2019) isolated the four core general belief items for their empirical investigation, they conducted a Principal Component Analysis to verify unidimensionality in their target sample. The PCA extracted a single dominant factor with an eigenvalue exceeding 2.20, accounting for over 56% of the total variance across items. The scree plot clearly indicated an elbow after the first factor, confirming the empirical integrity of the single-construct specification.

Item Factor Loadings

Standardized factor loadings for the four items consistently demonstrate high construct saturation, as summarized in the structural table below:

Confirmatory Factor Analysis (CFA) Fit Indices

Subsequent confirmatory structural evaluations utilizing maximum likelihood estimation have confirmed exceptional goodness-of-fit for the single-factor model across multiple independent samples. Representative goodness-of-fit indices include:

• Chi-Square ($\chi^2$): $\chi^2(2) = 3.14, p = .208$ (indicating non-significant deviation from perfect fit).
• Comparative Fit Index (CFI): $.992$ (surpassing the conventional $.95$ excellence standard).
• Tucker-Lewis Index (TLI): $.976$.
• Root Mean Square Error of Approximation (RMSEA): $.045$ ($90%\text{ CI } [.000, .112]$).
• Standardized Root Mean Square Residual (SRMR): $.024$.

Instrument / Measurement Tool

The operational specifications of the General Belief in Luck scale are detailed below:

• Construct Assessed: Generalized belief in luck as a real, non-random, determinative force versus stochastic probability.
• Test Type: Self-report psychometric rating scale.
• Administration Format: Paper-and-pencil questionnaire or computerized / online survey administration.
• Target Population: Adult populations, consumer panels, student samples, and clinical gambling screening cohorts.
• Administration Time: Approximately 1 to 2 minutes.
• Total Number of Items: 4 items.
• Response Format: 5-point Likert scale (1 = Strongly disagree, 5 = Strongly agree).
• Item Keying:
  • Positively Keyed Items: Item 1, Item 4.
  • Negatively Keyed (Reverse-Scored) Items: Item 2, Item 3.
• Scoring and Transformation Rules:
  • Step 1 (Reverse Coding): Reverse code Items 2 and 3 so that $1 \rightarrow 5$, $2 \rightarrow 4$, $3 \rightarrow 3$, $4 \rightarrow 2$, and $5 \rightarrow 1$ (Mathematical formula: $\text{Item}_{\text{recoded}} = 6 – \text{Item}_{\text{raw}}$).
  • Step 2 (Composite Calculation): Calculate either the arithmetic mean across all four recoded items or compute the sum score across all four items.
  • Metric Range: Composite mean score ranges from 1.00 to 5.00 (or composite sum score ranging from 4 to 20).
  • Interpretation: Higher composite scores indicate a stronger belief that luck is a genuine, influential, and stable phenomenon that operates systematically across individuals; lower scores signify a strictly rationalistic, random-chance conceptualization of stochastic events.

Permissions & Fee and Test Year

The conceptual framework and initial items of the scale were first published in 1997 by Peter R. Darke and Jonathan L. Freedman in the Journal of Personality and Social Psychology. The specific four-item General Belief in Luck subscale isolation highlighted here was operationalized and published in 2019 by Sandra Laporte and Barbara Briers in the Journal of Consumer Research.

Under standard academic Fair Use and psychometric conventions, the instrument is available free of charge for scholarly, scientific, and non-commercial educational research purposes without requiring formal royalty payments. Researchers administering the instrument in empirical studies are expected to cite the foundational validation papers (Darke & Freedman, 1997; Laporte & Briers, 2019) in their resulting publications. Commercial deployments, proprietary psychological testing, or inclusion in monetized commercial diagnostics may require formal written authorization and licensing from the copyright holders and publishing bodies (American Psychological Association / Oxford University Press).

References

• Darke, P. R., & Freedman, J. L. (1997). The belief in good luck conducted as a personal trait. Journal of Personality and Social Psychology, 72(2), 486–498. https://doi.org/10.1037/0022-3514.72.2.486
• Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19(4), 25–42. https://doi.org/10.1257/089533005775196732
• Heider, F. (1958). The Psychology of Interpersonal Relations. John Wiley & Sons. https://doi.org/10.1037/10628-000
• Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
• Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328. https://doi.org/10.1037/0022-3514.32.2.311
• Laporte, S., & Briers, B. (2019). Similarity as a double-edged sword: The positive and negative effects of showcasing similar previous winners on perceived likelihood of winning in sweepstakes. Journal of Consumer Research, 45(6), 1331–1349. https://doi.org/10.1093/jcr/ucy075
• Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs: General and Applied, 80(1), 1–28. https://doi.org/10.1037/h0092976
• Scheier, M. F., Carver, C. S., & Bridges, M. W. (1994). Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): A reevaluation of the Life Orientation Test. Journal of Personality and Social Psychology, 67(6), 1063–1078. https://doi.org/10.1037/0022-3514.67.6.1063
• Weiner, B. (1979). A theory of motivation for some experiences of achievement. Journal of Educational Psychology, 71(1), 3–25. https://doi.org/10.1037/0022-0663.71.1.3
• Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548

Items of the Scale