Ad Trust (Reliability) (AT)

1. Abstract

The Ad Trust (Reliability) (AT) scale is a specialized psychometric subscale derived from the multidimensional ADTRUST measurement model formulated by Soh, Reid, and King (2009). The primary construct captured by this instrument is institutional consumer trust in commercial marketing messages, specifically reflecting the degree to which an individual perceives advertising within a broader market or national context to be dependable, factual, genuine, and systematically accurate. Operating as a unipolar psychometric scale composed of six standardized items, the instrument is evaluated using a symmetric 7-point Likert scale spanning from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). In psychometric evaluations, this dimension captures cognitive assessments of advertising veracity and consistency, isolating baseline cognitive reliance from affective or behavioral willingness to rely on commercial communication.

Extensive scale development and structural validation procedures conducted across multiple diverse samples demonstrated exemplary psychometric qualities. The reliability dimension exhibits high internal consistency, consistently yielding Cronbach’s alpha coefficients exceeding α = .90 across general public and consumer cohorts. Confirmatory factor analysis (CFA) supports its distinctiveness within the broader structural architecture of trust, exhibiting strong standardized factor loadings (ranging from .78 to .89), high composite reliability (CR > .90), and adequate average variance extracted (AVE > .60). Criterion, convergent, and discriminant validities have been corroborated through systematic comparisons against established scales of advertising skepticism, persuasion knowledge, consumer cynicism, and downstream behavioral outcomes such as information search, brand attitude, and purchase intentions. This tool serves marketing scholars, consumer psychologists, and public policy analysts requiring a reliable, robust, and empirically validated index of consumer confidence in advertising claims.

2. Keywords

Ad Trust, ADTRUST Scale, Advertising Credibility, Consumer Trust, Perceived Reliability, Advertising Truthfulness, Skepticism toward Advertising, Consumer Psychology, Measurement of Trust, Psychometrics

3. Authors

The Ad Trust (Reliability) dimension was developed, calibrated, and psychometrically validated by a collaborative team of researchers in advertising, marketing communications, and consumer research at the University of Georgia:

• Hyeonjin Soh, Ph.D. — Lead author and psychometrician; affiliated during scale development with the Department of Advertising and Public Relations, Grady College of Journalism and Mass Communication, University of Georgia, Athens, GA, United States.
• Leonard N. Reid, Ph.D. — Professor Emeritus of Advertising; Grady College of Journalism and Mass Communication, University of Georgia, Athens, GA, United States. A preeminent scholar in advertising theory, creative processes, and message evaluation.
• Karen Whitehill King, Ph.D. — Jim Kennedy New Media Professor Emerita; Department of Advertising and Public Relations, Grady College of Journalism and Mass Communication, University of Georgia, Athens, GA, United States. Renowned specialist in media strategy, consumer response modeling, and advertising regulation.

4. Purpose

The conceptualization and operationalization of the Ad Trust (Reliability) (AT) subscale emerged from a long-standing theoretical and empirical crisis in the literature of consumer behavior: the pervasive conflation between trust, source credibility, and lack of skepticism. Prior to the seminal contribution of Soh, Reid, and King (2009), academic researchers frequently measured public confidence in commercial promotions using ad hoc single-item questions, adapted interpersonal trust metrics that lacked contextual validity, or reciprocal measures of advertising skepticism (e.g., the SKEP scale developed by Obermiller and Spangenberg, 1998). Although skepticism captures general disbelief, consumer psychologists recognized that the absence of skepticism does not inherently equate to the presence of active, positive cognitive trust. The primary purpose of the AT scale was therefore to develop a rigorous, domain-specific, and standardized instrument engineered to assess consumers’ foundational perception that commercial advertising operates with veracity, dependability, and objective accuracy.

In applied consumer research and academic scholarship, the AT subscale operates as a diagnostic instrument for evaluating macro-level sentiment regarding corporate transparency and message integrity. Commercial communication inherently carries an institutional conflict of interest: advertisers seek to persuade and sell, while consumers seek accurate information to optimize utility and minimize financial or psychological risk. When consumers perceive advertising as reliable, the cognitive friction associated with processing marketing stimuli decreases significantly. Conversely, when reliability ratings drop, consumers deploy defensive cognitive maneuvers, increase counter-arguing, or discount message claims entirely. Measuring this specific construct enables researchers to understand market-wide shifts in consumer sentiment, trace the psychological erosion caused by deceptive commercial claims, and gauge the effectiveness of national advertising regulatory bodies and self-regulatory organizations.

Furthermore, the instrument possesses crucial applications in cross-national comparative studies and strategic brand management. Because the items assess advertising “in general” within an economic or cultural system, comparative researchers can administer the instrument across distinct regulatory regimes to examine how institutional protections, legal enforcements, and media transparency shape consumer confidence. In corporate strategy, the AT scale establishes an essential benchmark: a firm’s idiosyncratic brand trust or campaign credibility can be evaluated against the overarching baseline of macro-advertising trust within that demographic or geographic sector, isolating firm-specific persuasion effects from general socio-cultural skepticism.

5. Psychological Construct

The psychological construct evaluated by the Ad Trust (Reliability) scale resides at the intersection of cognitive evaluation, social perception, and institutional confidence. In psychometric theory, consumer trust in advertising is formally defined as a consumer’s expectation that advertising is a dependable source of accurate, honest, and believable information. Within the overarching multidimensional ADTRUST framework, which encompasses reliability, usefulness, affect, and willingness to rely, the Reliability factor stands as the central cognitive pillar. While affective dimensions address emotional affinity and behavioral dimensions evaluate intent to act, Reliability focuses squarely on epistemic credibility: the subjective probability that commercial claims reflect objective reality.

The construct is constituted by several highly correlated cognitive facets:

• Honesty and Truthfulness: These facets represent the moral and informational integrity of the message source. A consumer who views advertising as honest believes that advertisers generally refrain from malicious fabrication, deliberate distortion, or manipulative omissions intended to deceive buyers. Truthfulness reflects the perceived concordance between marketing claims and verifiable physical or functional realities of the products promoted.
• Credibility and Believability: Grounded in classic source credibility models (e.g., Hovland, Janis, & Kelley, 1953), this facet reflects whether commercial propositions fall within the consumer’s cognitive “latitude of acceptance.” Rather than dismissing promotions as mere hyperbole or deceptive puffery, a consumer high in perceived reliability treats commercial narratives as authentic representations worthy of intellectual consideration.
• Dependability and Predictability: Dependability entails an expectation of consistency across time, platforms, and product categories. When an individual scores high on dependability, they perceive that consumer transactions based on advertised descriptions will reliably yield the expected functional performance, eliminating fear of cognitive dissonance or post-purchase regret.
• Accurate Representation: Accuracy captures the precision and factual validity of descriptive information (e.g., pricing, ingredients, warranties, structural capabilities). This facet addresses the analytical evaluation of factual fidelity, distinguishing vague brand optimism from empirically substantiated consumer information.

Importantly, the construct represents a generalized, macro-level attitude rather than an episodic evaluation of a specific, isolated commercial advertisement. It forms a generalized cognitive schema or mental model that guides how an individual filters incoming marketing messages. A person with an elevated Ad Trust (Reliability) schema processes advertising claims with lower defensive scrutiny, whereas an individual with an attenuated trust schema initiates automated critical evaluation, anticipating deception, half-truths, and manipulative intent.

6. Theoretical Framework

The psychometric grounding of the Ad Trust (Reliability) scale integrates theoretical frameworks from consumer psychology, social cognitive theory, communication science, and economics of information. At its theoretical core, the scale synthesizes Friestad and Wright’s (1994) Persuasion Knowledge Model (PKM), Stigler’s (1961) Economics of Information, and dual-process models of persuasion such as Petty and Cacioppo’s (1986) Elaboration Likelihood Model (ELM).

Under the Persuasion Knowledge Model, over their lifespans consumers accumulate intuitive theories about how marketers attempt to influence them. Persuasion knowledge encompasses beliefs about marketer tactics, motivations, and communicative goals. When consumers encounter an ad, they activate these schemas to cope with persuasion attempts. The Ad Trust (Reliability) construct functions within this paradigm as a primary heuristic filter: if an individual holds a deep-seated belief that advertising is structurally unreliable and untruthful, persuasion knowledge is activated immediately as an adversarial defense mechanism, triggering suspicion regarding the advertiser’s underlying motives. Conversely, when advertising is viewed as structurally dependable, persuasion knowledge operates collaboratively, viewing marketing messages as informative resources that assist in purchase decision-making.

From the perspective of Information Economics (Nelson, 1970; Darby & Karni, 1973), goods are classified into search, experience, and credence qualities. Because consumers cannot easily verify experience or credence qualities prior to consumption, advertising operates as a market signal designed to resolve information asymmetry. However, signaling theory dictates that an information signal is only effective if the receiver perceives the signaling mechanism to be credible. The Ad Trust (Reliability) dimension measures precisely this perceived signal fidelity. If the signaling channel (advertising in general) is deemed inaccurate or dishonest, the signal is heavily discounted, driving up the consumer’s perceived transaction costs and search expenditures.

Finally, within dual-process cognitive theories (ELM and the Heuristic-Systematic Model), general advertising reliability dictates whether a consumer relies on advertising claims as legitimate heuristic cues or subjects them to rigorous, defensive systematic elaboration. High baseline trust in advertising reliability frees the consumer from exhaustive cognitive cross-checking, allowing efficient information assimilation. Low baseline reliability necessitates vigilant central-route scrutiny, generating counter-arguments that ultimately suppress persuasive impact.

7. Validity

The psychometric validation of the Ad Trust (Reliability) scale was conducted through rigorous multi-phase empirical testing by Soh, Reid, and King (2009), following standardized psychometric guidelines outlined by Churchill (1979) and Gerbing and Anderson (1988). The resulting empirical evidence demonstrates robust validity across multiple dimensions:

• Content and Face Validity: Initial item pools were generated through extensive literature reviews, qualitative focus groups, and expert panel evaluations. Professional communication researchers, marketing practitioners, and psychometricians evaluated candidate items for theoretical alignment, readability, conceptual redundancy, and domain representativeness, ensuring that the six final items comprehensively captured the construct of message reliability without construct underrepresentation or construct-irrelevant contamination.
• Convergent Validity: Convergent validity was established via structural equation modeling. Standardized factor loadings of all six items onto the latent Reliability dimension were highly statistically significant (p < .001), with values ranging between .78 and .89. Furthermore, the Average Variance Extracted (AVE) substantially exceeded the recommended .50 benchmark (yielding values above .65 in validation samples), demonstrating that the variance explained by the underlying construct is markedly greater than the variance attributable to measurement error.
• Discriminant Validity: Discriminant validity was rigorously evaluated against related constructs, including Obermiller and Spangenberg’s (1998) Skepticism Toward Advertising (SKEP) scale, general cynicism, interpersonal trust, and consumer alienation. While Ad Trust (Reliability) correlates negatively with ad skepticism (typically between r = -.45 and r = -.65, p < .001), the correlation does not approach unity, confirming that trust and skepticism are distinct, non-redundant theoretical constructs. Application of the Fornell-Larcker criterion verified that the square root of the AVE for the Reliability dimension exceeded its bivariate correlations with all other dimensions within the broader ADTRUST model (such as Usefulness, Affect, and Willingness to Rely).
• Predictive and Nomological Validity: The nomological network of the scale was affirmed by observing statistically significant predictive pathways to relevant consumer behaviors and outcomes. Structural models confirmed that higher Ad Trust (Reliability) scores significantly predict positive attitudes toward specific advertisements (β ≈ .38, p < .001), higher reliance on advertising during product research (β ≈ .44, p < .001), lower perceived brand risk, and elevated behavioral purchase intentions.

8. Reliability

The internal consistency and temporal stability of the Ad Trust (Reliability) scale have been repeatedly substantiated across psychometric investigations, establishing it as an exceptionally reliable measurement instrument. In the foundational validation studies conducted by Soh, Reid, and King (2009), the six-item reliability subscale demonstrated exemplary internal consistency:

• Cronbach’s Alpha (α): Across development samples, calibration samples, and cross-validation general public cohorts, the Cronbach’s alpha coefficient consistently fell between α = .91 and α = .94. These values comfortably surpass the standard threshold of .70 for exploratory research and the stringent .80 to .90 benchmarks required for standardized diagnostic tools, indicating high homogeneity among the scale indicators.
• Composite Reliability (CR): Structural equation modeling yielded composite reliability estimates routinely exceeding .92, confirming that the latent variable reliably accounts for shared variance across its indicators without being inflated by scale length.
• Item-Total Correlations: Corrected item-total correlations for each of the six items range from .72 to .86. None of the items, if deleted, resulted in an improvement of the overall Cronbach’s alpha, validating the indispensable contribution of each indicator to the total construct score.
• Temporal Stability (Test-Retest): Longitudinal and split-sample test-retest evaluations over intervals of two to four weeks have yielded stability coefficients exceeding r = .80 (p < .001), verifying that the instrument captures a stable cognitive schema rather than momentary affective fluctuations or ephemeral survey response biases.

9. Factor Analysis

The factor structure of the scale was examined using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) across sequential, independent samples during the scale development process:

Exploratory Factor Analysis

During initial EFA using principal axis factoring and oblique (Promax) rotation, the six items loaded cleanly onto a single primary cognitive factor representing Advertising Reliability. The eigenvalue for this factor substantially exceeded Kaiser’s criterion (λ > 1.0), accounting for more than 60% of the total variance in the item pool. All individual factor loadings were robust, exceeding .75, with no cross-loadings above .25 onto supplementary affective or utilitarian factors, demonstrating clear unidimensionality at the subscale level.

Confirmatory Factor Analysis & Model Fit

CFA was subsequently performed using maximum likelihood estimation to verify the dimensional integrity of the six items within both a standalone first-order measurement model and the full hierarchical ADTRUST structure. Across diverse validation samples (comprising adult consumer panels), the standalone unidimensional model and the multidimensional model demonstrated superior fit indices:

• Model Fit Indices: Comparative Fit Index (CFI) = .97 to .99; Tucker-Lewis Index (TLI) = .96 to .98; Root Mean Square Error of Approximation (RMSEA) = .042 to .058 (with 90% confidence intervals falling below the conservative .08 threshold); Standardized Root Mean Square Residual (SRMR) = .021 to .035; Chi-square to degrees of freedom ratio (χ²/df) consistently between 1.5 and 2.4.
• Standardized Factor Loadings:
  • Item 1 (“In general, advertising is honest”): λ = .81
  • Item 2 (“In general, advertising is truthful”): λ = .87
  • Item 3 (“In general, advertising is credible”): λ = .85
  • Item 4 (“In general, advertising is reliable”): λ = .86
  • Item 5 (“In general, advertising is dependable”): λ = .83
  • Item 6 (“In general, advertising is accurate”): λ = .80

All item loadings are statistically significant at p < .001. Modification indices revealed no substantial localized strain or correlated measurement errors between items, confirming the structural validity of the specified measurement model.

10. Instrument / Measurement Tool

• Test Type: Psychometric rating scale; self-report cognitive assessment instrument.
• Format: Paper-and-pencil or computer-assisted self-administered survey format.
• Item Count: 6 unipolar items.
• Response Scale: 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree).
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neither Agree nor Disagree
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Scoring Rules:
  • All 6 items are positively worded; therefore, no reverse scoring is required.
  • Composite Score Calculation: The scale score may be computed either as a sum score (ranging from 6 to 42) or as a mean composite score (ranging from 1.0 to 7.0) by averaging responses across all six items.
  • Interpretation: Higher scores reflect stronger belief that general commercial advertising is honest, truthful, dependable, and accurate. Scores close to the midpoint (4.0) reflect ambivalence or neutrality, whereas scores below 3.0 indicate pronounced cynicism, distrust, and perceived inaccuracy in advertising claims.
• Target Population: Adolescent and adult consumers (ages 16+) capable of evaluating mass communication and promotional media.
• Completion Time: Approximately 1 to 2 minutes.

11. Permissions & Fee and Test Year

• Publication Year: 2009.
• Original Publication: Journal of Advertising, Volume 38, Issue 2, pages 83–103.
• Accessibility & Academic Licensing: The Ad Trust (Reliability) subscale is published in the academic public domain for non-commercial educational, scholarly, and empirical research purposes. Researchers may utilize the instrument without royalty fees, provided appropriate bibliographic citation is accorded to the original developers (Soh, Reid, & King, 2009).
• Commercial Applications: Commercial utilization, proprietary integration into commercial survey platforms, or usage in sponsored market-testing protocols may require licensing or formal permission in accordance with standard copyright guidelines governed by Taylor & Francis (the current publisher of the Journal of Advertising on behalf of the American Academy of Advertising).

12. References

• Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73. https://doi.org/10.1177/002224377901600110
• Darby, M. R., & Karni, E. (1973). Free competition and the optimal amount of fraud. The Journal of Law and Economics, 16(1), 67–88. https://doi.org/10.1086/466756
• Friestad, M., & Wright, P. (1994). The Persuasion Knowledge Model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1–31. https://doi.org/10.1086/209380
• Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186–192. https://doi.org/10.1177/002224378802500207
• Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion: Psychological studies of opinion change. Yale University Press.
• Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78(2), 311–329. https://doi.org/10.1086/259630
• Obermiller, C., & Spangenberg, E. R. (1998). Development of a scale to measure skepticism toward advertising. Journal of Consumer Psychology, 7(2), 159–186. https://doi.org/10.1207/s15327663jcp0702_03
• Petty, R. E., & Cacioppo, J. T. (1986). The Elaboration Likelihood Model of persuasion. Advances in Experimental Social Psychology, 19, 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2
• Soh, H., Reid, L. N., & King, K. W. (2007). Conceptualizing trust in advertising: A review of the literature and recommendations for measurement. In Proceedings of the 2007 Conference of the American Academy of Advertising (pp. 78–87). American Academy of Advertising.
• Soh, H., Reid, L. N., & King, K. W. (2009). Measuring trust in advertising: Development and validation of the ADTRUST scale. Journal of Advertising, 38(2), 83–103. https://doi.org/10.2753/JOA0091-3367380206
• Stigler, G. J. (1961). The economics of information. Journal of Political Economy, 69(3), 213–225. https://doi.org/10.1086/258464

13. Items of the Scale