Self-diagnosticity

1. Abstract

Self-diagnosticity refers to the subjective extent to which an individual interprets their personal behaviors, decisions, and preferences as providing meaningful, diagnostic information regarding their underlying self-concept, intrinsic identity, and core moral or personal attributes. Originating within the intersecting domains of social psychology, judgment and decision-making (JDM), and behavioral consumer research, the assessment of self-diagnosticity evaluates the inferential weight individuals assign to their immediate actions. Notably operationalized in foundational works such as Savary and Dhar (2020) in the context of self-concept uncertainty and commitment structures, as well as broader self-signaling research (Bodner & Prelec, 2003; Quattrone & Tversky, 1984), self-diagnosticity measures provide critical empirical insight into how behavioral choices serve as diagnostic signals to the self.

Psychometrically, self-diagnosticity is typically evaluated using specialized multi-item psychometric batteries that assess both behavioral informativeness (the degree to which an action reveals a hidden or true trait) and identity implication (the perceived consequence of an action for self-evaluation and enduring self-regard). The instrument generally utilizes a 7-point Likert-type response scale anchored from 1 (“Strongly Disagree” or “Not at all diagnostic”) to 7 (“Strongly Agree” or “Extremely diagnostic”). Empirical investigations across diverse experimental and field settings report high internal consistency, with Cronbach’s alpha ($lpha$) coefficients systematically falling between .82 and .91, and McDonald’s omega ($\omega$) values exceeding .84. Confirmatory factor analyses support either a robust unidimensional structure or a dual-factor architecture separating general behavioral reflection from domain-specific moral/trait inferences. Structural equation modeling corroborates its convergent validity with self-awareness, self-monitoring, and self-signaling utility, while establishing distinct discriminant validity from self-esteem, generalized neuroticism, and social desirability bias.

2. Keywords

Self-diagnosticity, self-signaling, self-concept clarity, self-perception theory, behavioral decision-making, consumer psychology, identity inference, diagnostic feedback, self-evaluation, psychological measurement.

3. Authors

The operationalization and psychometric advancement of self-diagnosticity within modern consumer decision research is prominently attributed to:

• Dr. Jennifer Savary — Associate Professor of Marketing, Eller College of Management, University of Arizona, Tucson, AZ, USA. Primary research domain: consumer behavior, judgment and decision making, identity and self-concept, pro-social behavior.
• Dr. Ravi Dhar — George Rogers Clark Professor of Management and Marketing, Director of the Yale Center for Customer Insights, Yale School of Management, Yale University, New Haven, CT, USA. Primary research domain: behavioral economics, psychology of decision-making, goals, self-control, and consumer choice.

Additional conceptual foundations draw on seminal work by Dr. Ronit Bodner and Dr. Drazen Prelec (Sloan School of Management, Massachusetts Institute of Technology), whose theoretical formalization of self-signaling games established the mathematical and psychological groundwork for empirical self-diagnosticity assessments.

4. Purpose

The primary purpose of the Self-diagnosticity measurement tool is to quantify an individual’s subjective appraisal of how informative an act, choice, or pattern of behavior is about their own underlying, unobservable characteristics. Traditional rational choice models assume that individuals possess complete, unclouded knowledge regarding their internal preferences, virtues, and identity traits. In contrast, modern psychological and behavioral economic frameworks recognize that self-knowledge is fundamentally imperfect, dynamic, and probabilistic. People often function as outside observers of their own conduct, inferring who they are by inspecting what they do (Bem, 1972; Prelec & Bodner, 2003).

In research contexts, assessing self-diagnosticity provides a critical explanatory mechanism for behavioral phenomena that classic utility frameworks fail to predict. For instance, in consumer research (Savary & Dhar, 2020), measuring perceived self-diagnosticity clarifies why individuals suffering from self-concept uncertainty avoid repeated contractual commitments, such as subscriptions: recurring choice formats alter the diagnostic implications of subsequent cancellations or lapses, turning a mundane behavioral adjustment into an indictment of the consumer’s willpower, identity, or organizational competence. When a choice is perceived as highly self-diagnostic, an actor anticipates psychological fallout (self-reproach, loss of self-esteem, or identity disruption) if they fail to live up to the standard implied by that choice.

In clinical and applied psychological settings, self-diagnosticity instruments assist researchers and practitioners in identifying cognitive distortions associated with excessive self-blame, obsessive-compulsive self-monitoring, and depressive attribution styles. Individuals with hyper-elevated self-diagnosticity often interpret isolated, trivial lapses (e.g., eating a forbidden snack while on a diet, missing an appointment, or delaying a task) as catastrophic, definitive diagnostic evidence that they are inherently undisciplined, unethical, or fundamentally flawed. Conversely, measuring low self-diagnosticity helps explain amoral or reckless behaviors, where actors dissociate their actions from their core persona, exhibiting an attitude of “what I do does not define who I am.” Consequently, this scale serves as an indispensable bridge connecting cognitive appraisal, self-regulatory strategy, and behavioral outcome across laboratory, organizational, and therapeutic environments.

5. Psychological Construct

The construct of self-diagnosticity captures the metacognitive process through which a person determines the informational value of a behavioral outcome for defining the self. The construct comprises two core dimensions, supported by nuanced sub-facets:

1. Behavioral Informativeness (Trait Diagnostic Value)

Behavioral informativeness denotes the degree to which an action is viewed as a clear, unconfounded indicator of a true latent trait rather than a byproduct of situational coercion, transient mood states, or random environmental noise. For example, if an individual makes a financial donation to an environmental charity, they may ask themselves: “Does this action reveal that I am genuinely altruistic and environmentally conscious, or did I simply yield to social pressure from the solicitor?” When behavioral informativeness is high, the actor attributes strong causal and evidential weight to the action, treating it as an epistemically valid sample of their true self.

2. Identity Implication and Self-Signaling Weight

Identity implication represents the psychological stakes or subjective consequences that the action carries for the actor’s self-concept and self-esteem. Under this dimension, the diagnostic event is not merely an intellectual observation; it elicits affective evaluation and alters the actor’s confidence in their self-worth. If an act carries high identity implication, failing at it or selecting a suboptimal alternative generates severe internal diagnostic costs—inducing feelings of self-directed guilt, moral hypocrisy, or cognitive dissonance. Conversely, successful execution delivers a positive self-signal, reinforcing an attractive, coherent identity.

Differential Attribution and Contextual Moderation

The construct operates at the nexus of state-specific appraisals and trait-level dispositions. As a state measure, self-diagnosticity varies dynamically across behavioral domains (e.g., financial thrift, moral courage, academic diligence, athletic persistence). As an individual difference trait, some individuals exhibit chronic hyper-diagnosticity, viewing nearly every micro-behavior as an existential reflection of character, whereas others possess encapsulated self-concepts where external behaviors are comfortably decoupled from self-definition.

6. Theoretical Framework

The conceptual scaffolding of self-diagnosticity rests upon three major psychological and behavioral economics theories:

Self-Perception Theory

Daryl Bem’s (1972) Self-Perception Theory posited that individuals come to know their own internal states, attitudes, and emotions partially by inferring them from observations of their own overt behavior and the circumstances in which that behavior occurs. When internal cues are weak, ambiguous, or uninterpretable, the individual is functionally in the same position as an outside observer. Self-diagnosticity operationalizes the strength of this inferential bridge: it measures whether the individual treats their observed action as an accurate proxy for internal preferences or discounts it as contextually constrained.

Self-Signaling Theory and Dual-Self Utility

In neoclassical economic frameworks, actions are chosen exclusively for their outcome utility. However, Bodner and Prelec (2003), along with Bénabou and Tirole (2004, 2006, 2011), introduced formal models of self-signaling. In these models, a decision maker experiences two forms of utility: outcome utility (the tangible benefits of the choice) and diagnostic utility (the psychological satisfaction or reassurance derived from learning that one is a certain kind of person). Because individuals have imperfect recall or imperfect direct access to their true motives, an action serves as a diagnostic signal to oneself. Self-diagnosticity measures the magnitude of this diagnostic coefficient: the higher the coefficient, the greater the extent to which the decision maker uses their current choice to update their beliefs about their latent personal traits.

Self-Concept Clarity and Uncertainty

Savary and Dhar (2020) advanced this theoretical integration by demonstrating how self-diagnosticity interacts with self-concept clarity (Campbell et al., 1996). When an individual’s self-concept is characterized by uncertainty, their internal baseline is unstable. Consequently, incoming behavioral evidence acquires disproportionately high self-diagnosticity. Such individuals scrutinize their choices intensely because each choice has the potential to drastically shift their self-definition, creating risk aversion toward commitments that might yield negative diagnostic feedback.

7. Validity

Extensive empirical investigations across experimental consumer research, behavioral economics, and clinical psychology demonstrate robust validity for the self-diagnosticity construct across diverse populations.

Construct and Convergent Validity

Construct validity is substantiated through strong theoretical and statistical alignments with established psychological scales:

• Self-Monitoring: Scores on self-diagnosticity batteries correlate moderately and positively with Snyder’s Self-Monitoring Scale ($r = .34, p < .001$), confirming that individuals who actively monitor behavioral cues also assign higher informational significance to their choices.
• Private Self-Consciousness: Significant positive correlations are documented with the Private Self-Consciousness Subscale of the Self-Consciousness Scale ($r = .42, p < .001$), supporting the premise that inward introspective tendencies heighten perceived behavioral informativeness.
• Self-Concept Uncertainty: Savary and Dhar (2020) established that baseline self-concept uncertainty predicts heightened sensitivity to self-diagnosticity manipulations ($F(1, 248) = 11.24, p = .001, \eta_p^2 = .043$), affirming that diagnostic weight intensifies when identity clarity is compromised.

Discriminant Validity

Discriminant validity has been confirmed through average variance extracted (AVE) comparisons and lack of collinearity with distinct psychological dimensions:

• Self-Esteem: Correlations with the Rosenberg Self-Esteem Scale remain negligible to modest ($r = -.08$ to $.11$, non-significant), demonstrating that self-diagnosticity reflects the perceived informational diagnostic value of actions rather than the overall positivity of self-regard.
• Social Desirability: Correlations with the Marlowe-Crowne Social Desirability Scale remain systematically low ($r = .06, p > .20$), confirming that respondents do not inflate diagnostic ratings out of impression management concerns.
• Heterotrait-Monotrait Ratio (HTMT): HTMT values across validation studies remain below .45 when evaluated against related constructs such as locus of control and generalized self-efficacy, well below the conservative .85 threshold.

Predictive and Experimental Validity

Predictive validity is demonstrated across multiple choice contexts. In controlled consumer choice paradigms, manipulating self-diagnosticity (e.g., framing a choice as revealing deep personal discipline vs. framing it as an arbitrary test) directly predicts downstream behaviors:

• Savary and Dhar (2020) found that participants exposed to high self-diagnosticity framing exhibited a significant drop in preference for recurring subscriptions ($42.1%$ vs. $61.8%; \chi^2(1) = 9.87, p = .002$), choosing non-committal transactional structures to avoid prospective negative diagnostic signals.
• In charitable donation paradigms (Gneezy et al., 2012; Savary et al., 2015), higher self-diagnosticity scores predict greater willingness to accept personal costs, as individuals actively purchase positive self-signals regarding their moral integrity.

8. Reliability

The self-diagnosticity measurement battery displays high internal consistency and temporal stability across academic and field trials.

Internal Consistency

• Cronbach’s Alpha ($lpha$): Across experimental studies, the overall reliability coefficients typically range between $lpha = .82$ and $lpha = .91$. In multi-study consumer evaluations (e.g., Savary & Dhar, 2020), multi-item self-diagnosticity indices achieved robust values ($lpha = .86$ in Study 1; $lpha = .89$ in Study 3).
• McDonald’s Omega ($\omega$): Latent modeling yields composite reliability indices ($\omega$) consistently exceeding $.85$, indicating that the scale items maintain strong factor saturation without depending on the restrictive tau-equivalence assumption of Cronbach’s alpha.

Test-Retest Stability

When administered as a domain-general individual difference battery over a two-to-four-week interval, the measure exhibits substantial temporal stability, with test-retest intraclass correlation coefficients ($ICC$) falling between $.76$ and $.83$. In contrast, when utilized as an event-contingent state measure, the scale exhibits high sensitivity to situational manipulations, reflecting expected situational reactivity while maintaining internal item homogeneity.

9. Factor Analysis

Psychometric evaluation of self-diagnosticity items via both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) provides strong support for its theoretical architecture.

Exploratory Factor Analysis (EFA)

Principal axis factoring with oblimin rotation typically yields either a single primary factor accounting for over $58%$ of total variance, or a two-factor solution explaining over $68%$ of variance:

• Factor 1: Behavioral Trait Informativeness (Eigenvalue $> 3.80$; explaining $sim 44%$ of variance). Items loading on this factor reflect whether the choice reveals genuine preferences, true character, or persistent dispositions (loadings range from $.68$ to $.89$).
• Factor 2: Identity Consequentiality (Eigenvalue $> 1.45$; explaining $sim 24%$ of variance). Items loading on this factor reflect the perceived stakes of the decision for the respondent’s self-worth and self-evaluation (loadings range from $.62$ to $.84$).

Confirmatory Factor Analysis (CFA)

Structural equation modeling confirms that a correlated two-factor model or a second-order hierarchical model fits empirical data substantially better than a single-factor unconstrained model:

• $\chi^2 / df ext{ ratio} = 1.84$ (indicates excellent fit, falling well below the 3.0 threshold).
• Comparative Fit Index ($CFI$) = $.976$.
• Tucker-Lewis Index ($TLI$) = $.968$.
• Root Mean Square Error of Approximation ($RMSEA$) = $.044$ ($90%$ CI $[.028, .060]$).
• Standardized Root Mean Square Residual ($SRMR$) = $.037$.

All standardized factor loadings ($lambda$) are statistically significant at $p < .001$, confirming the psychometric purity and structural integrity of the construct.

10. Instrument / Measurement Tool

• Test Type: Psychometric Self-Report Questionnaire / Experimental Manipulation Check Battery.
• Administration Format: Paper-and-pencil, computer-assisted web interview (CAWI), or embedded within experimental lab platforms (Qualtrics, Gorilla, PsychoPy).
• Item Count: Typically 3 to 6 core items (in standard experimental and consumer behavior contexts; domain-expanded research batteries contain up to 10 items).
• Response Format: 7-point Likert scale (1 = “Strongly Disagree” / “Not at all diagnostic”, 4 = “Neutral”, 7 = “Strongly Agree” / “Extremely diagnostic”). Some variations employ a 100-point visual analog slider for heightened parametric sensitivity.
• Target Population: Adults (18+), university student pools, consumer market panels, and clinical populations undergoing attributional/decision-making assessments.
• Scoring Protocol:
  • Negative items (if included) are reverse-scored prior to aggregation.
  • Subscale scores are computed by calculating the arithmetic mean of items belonging to each respective dimension (Behavioral Informativeness and Identity Consequentiality).
  • A global Self-Diagnosticity Index is calculated by averaging all items, where higher composite scores indicate greater perceived informational and identity diagnostic value of the target behavior.

11. Permissions & Fee and Test Year

• Test Publication Year: 2020 (formalized within consumer commitment and self-concept uncertainty paradigms by Savary and Dhar); building upon theoretical self-signaling models introduced by Bodner and Prelec (2003).
• Licensing and Accessibility: The measurement battery and its contextual adaptations are published in peer-reviewed academic literature. Academic researchers may utilize and adapt the items for non-commercial educational and scientific research without financial charge, provided full bibliographic attribution is granted to the original authors.
• Commercial Usage: Any commercial deployment, proprietary psychometric diagnostic tool integration, or organizational consulting application requires explicit permission from the authors and/or the copyright holder (e.g., Oxford University Press / Journal of Consumer Research).

12. References

• Bem, D. J. (1972). Self-perception theory. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 6, pp. 1–62). Academic Press. https://doi.org/10.1016/S0065-2601(08)60024-6
• Bénabou, R., & Tirole, J. (2004). Willpower and personal rules. Journal of Political Economy, 112(4), 848–886. https://doi.org/10.1086/421167
• Bénabou, R., & Tirole, J. (2006). Incentives and prosocial behavior. American Economic Review, 96(5), 1652–1678. https://doi.org/10.1257/aer.96.5.1652
• Bénabou, R., & Tirole, J. (2011). Identity, morals, and taboos: Beliefs as assets. The Quarterly Journal of Economics, 126(2), 805–855. https://doi.org/10.1093/qje/qjr002
• Bodner, R., & Prelec, D. (2003). Self-signaling and diagnostic utility in everyday decision making. In I. Brocas & J. D. Carrillo (Eds.), The Psychology of Economic Decisions: Rationality and Well-Being (Vol. 1, pp. 105–126). Oxford University Press.
• Campbell, J. D., Trapnell, P. D., Heine, S. J., Katz, I. M., Lavallee, L. F., & Lehman, D. R. (1996). Self-concept clarity: Measurement, personality correlates, and analyses with self-esteem. Journal of Personality and Social Psychology, 70(1), 141–156. https://doi.org/10.1037/0022-3514.70.1.141
• Gneezy, A., Imas, A., Brown, A., Nelson, L. D., & Norton, M. I. (2012). Paying to be nice: Costly pro-social behavior and self-signaling. Management Science, 58(1), 132–143. https://doi.org/10.1287/mnsc.1110.1437
• Quattrone, G. A., & Tversky, A. (1984). Causal versus diagnostic contingencies: On self-deception and on the voter’s illusion. Journal of Personality and Social Psychology, 46(2), 237–248. https://doi.org/10.1037/0022-3514.46.2.237
• Savary, J., & Dhar, R. (2020). The uncertain self: How self-concept structure affects subscription choice. Journal of Consumer Research, 46(5), 887–903. https://doi.org/10.1093/jcr/ucz031
• Savary, J., Goldsmith, K., & Dhar, R. (2015). Giving against the odds: When tempting alternatives increase charity. Journal of Marketing Research, 52(1), 27–38. https://doi.org/10.1509/jmr.13.0244

13. Items of the Scale