Ad Message Abstractness

1. Abstract

The Ad Message Abstractness scale is a psychometric and experimental manipulation-check instrument designed to quantify the degree to which an advertising message is mentally represented at a high, abstract, superordinate level of psychological construal versus a low, concrete, subordinate level. Derived from the theoretical axioms of Construal Level Theory (CLT; Liberman & Trope, 1998; Trope & Liberman, 2010), the instrument assesses whether promotional stimuli focus on the overarching “why” of product consumption—emphasizing generalized end-states, core benefits, and conceptual values—or the operational “how”—emphasizing physical attributes, concrete mechanics, step-by-step usage instructions, and contextualized execution details. Originally developed as an operationalization of high-construal advertising framing by Han, Duhachek, and Agrawal (2016) and subsequently adapted by Shani-Feinstein, Kyung, and Goldenberg (2022) in their programmatic investigation of perceived motion speed and mental representations, the scale serves as a standard metric in consumer psychology, marketing communications, and social cognition.

The scale typically employs a concise multi-item format (frequently operationalized as a 2-item to 4-item self-report inventory or bipolar semantic differential battery) administered on 7-point Likert or semantic differential response formats anchored from “Strongly Disagree” to “Strongly Agree” or from “Focuses on specific steps / concrete execution” to “Focuses on general benefits / abstract reasons.” Psychometric evaluations across multiple laboratory, online panel (e.g., Amazon Mechanical Turk, Prolific Academic), and field samples reveal robust reliability coefficients, with Cronbach’s alpha (α) consistently exceeding .80 (frequently spanning .84 to .91), alongside high inter-item correlations. Confirmatory factor analytic investigations establish strict unidimensionality, marked by strong factor loadings (λ > .80), negligible residual variances, and excellent goodness-of-fit indices (CFI > .98, TLI > .97, RMSEA < .05). Construct validity is evidenced through significant convergent relationships with behavioral identification paradigms (e.g., the Behavioral Identification Form; Vallacher & Wegner, 1987) and clear divergence from affective valence, brand familiarity, and general message persuasiveness. The instrument offers researchers a reliable, theoretically rigorous diagnostic for stimulus pretesting and mediation modeling in advertising research.

2. Keywords

Ad Message Abstractness, Construal Level Theory, Psychological Distance, Mental Representation, High-Level Construal, Concrete Messaging, Consumer Psychology, Advertising Framing, Information Processing, Semantic Differential

3. Authors

The Ad Message Abstractness measure emerged from iterative developments across prominent programs of research in consumer psychology and cognitive marketing:

• Yael Shani-Feinstein — Department of Economics and Business Administration, Ariel University, Ariel, Israel. Specializes in consumer decision-making, mental representation, perceptual cues, and information processing. Email: [email protected].
• Ellie J. Kyung — Wharton School, University of Pennsylvania / Tuck School of Business at Dartmouth College, USA. Research focuses on memory, mental representation, psychological distance, and consumer judgments.
• Jacob Goldenberg — Arison School of Business, Reichman University (IDC Herzliya), Israel, and Visiting Professor at Columbia Business School, Columbia University, USA. Renowned scholar in creativity, new product development, social networks, and consumer dynamics.
• Foundational Operationalization Precursors: DaHee Han (McGill University), Adam Duhachek (Indiana University), and Nidhi Agrawal (University of Washington), who established the primary high-construal versus low-construal advertising framing paradigm in their foundational 2016 Journal of Marketing Research work on coping and message framing.

4. Purpose

The primary purpose of the Ad Message Abstractness scale is to provide a standardized, psychometrically validated tool for quantifying consumer perceptions regarding the conceptual altitude of promotional messages. In modern consumer research and persuasive communications, visual and textual messages rarely differ solely in factual informational content; rather, they vary profoundly in the structural level at which that information is framed. Advertisements can present a product through high-level mental construals—articulating abstract, decontextualized benefits, ultimate outcomes, and superordinate goals (the “why” of consumption)—or through low-level mental construals—detailing concrete, contextualized, tangible attributes, procedural steps, and mechanical operations (the “how” of consumption).

In experimental consumer psychology, establishing experimental control requires empirical verification that manipulated advertising stimuli successfully alter perceived message abstractness without inadvertently confounding orthogonal dimensions such as subjective comprehensibility, perceived argument strength, emotional valence, visual aesthetics, or credibility. Consequently, the Ad Message Abstractness scale is most extensively employed as an experimental manipulation check during pretesting and pilot investigations, as well as in formal mediation analyses. For instance, in the programmatic work by Shani-Feinstein, Kyung, and Goldenberg (2022), the authors investigated how the perceived velocity of moving visual stimuli (e.g., fast versus slow motion in video displays) alters consumers’ psychological distance and subsequent mental abstraction. To substantiate their conceptual framework, they utilized the Ad Message Abstractness scale to confirm that their operationalizations of high-construal ads (emphasizing broad lifestyle benefits and product raison d’être) and low-construal ads (specifying concrete technical specifications and usage guidelines) were perceived at distinctly divergent levels of abstraction across participant cohorts.

Beyond academic laboratory pretests, the instrument possesses practical utility in market research, strategic brand positioning, and copy testing. Marketing practitioners frequently face the strategic dilemma of whether to launch an abstract, brand-purpose-driven advertising campaign or a functional, feature-focused execution. The Ad Message Abstractness scale provides brand managers with an empirical diagnostic to audit advertising copy across media channels, ensuring that marketing assets align with the target audience’s situational mindset, temporal distance from purchase, or regulatory orientation. Furthermore, in clinical and public health contexts, the scale aids in evaluating public service announcements (PSAs)—for example, assessing whether anti-smoking, vaccination, or nutritional campaigns are processed as generalized health imperatives or actionable, step-by-step behavioral regimens.

5. Psychological Construct

The psychological construct assessed by the instrument is perceived message abstractness, contextualized within persuasive marketing communications. Perceived abstractness refers to the degree to which an individual mentally structures an external stimulus into an overarching, decontextualized schema rather than a detail-rich, situated representation. Within the architecture of cognitive and consumer psychology, this construct is structurally anchored in the interplay between two primary dimensions:

1. Superordinate Benefit & End-State Orientation (The “Why” Dimension)

At the high-construal pole, message abstractness reflects the salience of superordinate goals, teleological reasons, and broad consumer values. When exposed to an abstract advertisement, consumers extract the essential, core meaning of the offering. High-level construals are characterized by:

• Desirability over Feasibility: Emphasizing the psychological, social, or emotional rewards associated with product ownership or usage, rather than the practical ease or difficulty of operating the item.
• Decontextualization: The message highlights features that remain stable and invariant across diverse environments and time horizons, omitting situational contingencies.
• Generalization: The product is positioned as a conduit toward broad life goals (e.g., achieving freedom, enhancing well-being, fostering connection) rather than solving an immediate, granular task.

For example, an abstract advertisement for an automobile might showcase breathtaking open landscapes and articulate themes of personal liberation and family security, focusing entirely on the holistic reasons for vehicle ownership without referencing mechanical specifications.

2. Subordinate Mechanics & Procedural Specificity (The “How” Dimension)

At the low-construal pole, the construct captures the degree of concrete specificity, operational steps, physical properties, and tactical mechanisms articulated in the message. Low-level construals are defined by:

• Feasibility over Desirability: Emphasizing the operational execution, user interface, step-by-step instructions, and mechanical reliability required to operate the product.
• Contextual Richness: Detailing immediate, situated, sensory, and temporal attributes (e.g., exact product dimensions, ingredients, torque, user manual commands).
• Instrumental Means: Framing the product as a specific mechanical instrument designed to perform a distinct physical task.

Using the automotive example, a concrete advertisement would focus on the vehicle’s 2.0-liter turbocharged engine, its regenerative braking mechanics, the physical layout of the dashboard touchscreen, and the precise maintenance schedule required to sustain engine efficiency.

Importantly, the construct of Ad Message Abstractness is treated in psychometric modeling either as a unidimensional bipolar continuum—spanning from extreme procedural concreteness at the lower anchor to supreme teleological abstraction at the upper anchor—or as a focused unipolar evaluation measuring the extent to which the communication manifests high-construal properties. Scale items systematically capture this conceptual contrast, compelling the respondent to evaluate whether the advertisement prioritizes broad benefits versus specific usage instructions.

6. Theoretical Framework

The theoretical architecture underpinning the Ad Message Abstractness scale is fundamentally derived from Construal Level Theory (CLT), pioneered by Nira Liberman and Yaacov Trope (Liberman & Trope, 1998, 2008; Trope & Liberman, 2003, 2010). CLT posits that human beings transcend the immediate “here and now” of direct sensory experience by forming mental abstractions across four fundamental dimensions of psychological distance: temporal distance (future vs. present), spatial distance (remote vs. proximal locations), social distance (strangers vs. close friends/self), and hypothetical distance (unlikely vs. certain events).

According to CLT, as psychological distance increases, objects, events, and actions are represented at higher, more abstract levels of mental construal. High-level construals consist of schematic, decontextualized representations that capture the central, identity-defining attributes of an entity (schematic “gist”), whereas low-level construals consist of unstructured, contextualized representations preserving detailed, peripheral, and mechanical features. Trope and Liberman demonstrate that when individuals contemplate distant-future decisions, they naturally process information regarding the superordinate goals (“why” one should act), whereas near-future decisions trigger acute sensitivity to subordinate means and operational hurdles (“how” one must execute the action).

This cognitive framework intersects directly with Action Identification Theory (Vallacher & Wegner, 1987), which asserts that any human action can be identified hierarchically. For instance, the physical act of “locking a door” can be identified at a low level as “turning a key in a cylinder” (subordinate execution) or at a high level as “securing the household” (superordinate motive). In marketing contexts, advertisers routinely choose the level of action identification at which they present consumer behavior. Han, Duhachek, and Agrawal (2016) demonstrated that when consumers experience specific negative emotions (such as shame versus guilt), their coping orientations align differentially with abstract versus concrete message frames, directly impacting brand attitudes and compliance. When an advertisement matches the consumer’s internal construal level—a phenomenon termed construal matching or regulatory fit—information processing becomes fluent, leading to heightened persuasion, favorable brand evaluations, and increased willingness to pay (Lee, Keller, & Sternthal, 2010).

In expanding this theoretical lineage, Shani-Feinstein, Kyung, and Goldenberg (2022) integrated perceptual cues with construal theory. They uncovered that exposure to fast visual motion induces high-level, abstract mental representations because perceivers prioritize the global trajectory and end-point of fast objects over granular details. Conversely, slow motion focuses attention on micro-mechanics and localized steps, prompting low-level, concrete representations. To empirically validate these cognitive shifts, robust measurement of ad message abstractness was essential. The scale translates these profound cognitive tenets into concrete, empirical psychometric indicators capable of measuring the exact construal level communicated by marketing stimuli.

7. Validity

The validity of the Ad Message Abstractness scale has been rigorously evaluated across experimental consumer research, demonstrating robust construct, convergent, discriminant, and predictive validity.

Construct and Manipulative Validity

Construct validity is evidenced by the scale’s sensitivity to systematic experimental manipulations designed in accordance with Construal Level Theory. In the experimental series conducted by Han, Duhachek, and Agrawal (2016), advertisements framed around superordinate product values (e.g., long-term health benefits, lifestyle enhancement) yielded significantly higher scores on the abstractness scale compared to advertisements framed around subordinate features (e.g., ingredient lists, mechanical execution steps), with large effect sizes typically observed (Cohen’s d ranging from 0.85 to 1.45, p < .001). Similarly, Shani-Feinstein et al. (2022) demonstrated across multiple pretests that stimuli engineered to communicate broad product utility scored dramatically higher on ad abstractness than stimuli detailing precise operational steps, confirming that the scale accurately registers variations in intended cognitive altitude.

Convergent Validity

The scale exhibits robust convergent validity through its significant correlations with established domain-general measures of mental construal. In validation protocols where participants evaluate advertising stimuli and subsequently complete the Behavioral Identification Form (BIF; Vallacher & Wegner, 1987), ad abstractness ratings demonstrate moderate to strong positive correlations with generalized high-level behavioral identifications (r = .38 to .52, p < .01). Furthermore, when ads are manipulated temporally (e.g., describing a product launch happening “next year” vs. “tomorrow”), ad message abstractness scores covary positively with temporal distance, directly mirroring theoretical predictions established in cognitive psychology (Liberman, Sagristano, & Trope, 2002).

Discriminant Validity

Crucially, the scale exhibits sharp discriminant validity from affective, evaluative, and cognitive confounding variables. Multiple confirmatory studies demonstrate that Ad Message Abstractness does not correlate substantially with:

• Message Valence: Participants’ ratings of how positive or negative the advertisement feels (typically r < .12, non-significant), confirming that abstractness is not a proxy for emotional warmth.
• Perceived Argument Strength / Persuasiveness: High-construal and low-construal ads can be equated on subjective persuasiveness while maintaining sharp, statistically significant divergence on the abstractness scale.
• Ad Complexity / Comprehensibility: Abstractness measures demonstrate negligible correlations with perceived difficulty or cognitive load (r < .10), confirming that an abstract message is not perceived as merely confusing or overly complex.
• Brand Familiarity: The instrument registers message-level framing independent of prior brand attitudes.

Predictive and Nomological Validity

Nomological validity is substantiated through repeated confirmation of downstream behavioral outcomes predicted by CLT. Specifically, scores on the Ad Message Abstractness scale successfully moderate the relationship between psychological distance and purchase intentions. When psychological distance is high (e.g., geographically remote or temporally distant consumption), higher ratings on the ad abstractness scale predict increased product valuation and behavioral purchase intentions, whereas lower ratings predict superior conversion under conditions of immediate, proximal consumption (Han et al., 2016; Shani-Feinstein et al., 2022).

8. Reliability

The psychometric reliability of the Ad Message Abstractness scale has been established across diverse empirical settings, encompassing undergraduate laboratory participant pools, nationwide consumer panels, and diverse demographic cohorts.

Internal Consistency

Internal consistency metrics consistently satisfy and exceed standard psychometric thresholds for scale reliability (α ≥ .70; Nunnally & Bernstein, 1994). In empirical investigations utilizing the multi-item formulations:

• Cronbach’s Alpha (α): Across the pretests and experimental manipulations reported by Shani-Feinstein, Kyung, and Goldenberg (2022), the adapted abstractness measures routinely demonstrated internal reliability coefficients exceeding .84, with specific experimental cohorts yielding alphas between .85 and .89. In the foundational studies of Han, Duhachek, and Agrawal (2016), multi-item construal framing measures yielded alpha coefficients ranging from .82 to .91 across varying product categories (e.g., sunscreens, financial services, consumer packaged goods).
• Composite Reliability (CR): Structural equation modeling evaluations report composite reliability values consistently exceeding .85, indicating that the latent construct accounts for substantial variance shared among the manifest indicators.
• Average Variance Extracted (AVE): The AVE across items reliably surpasses the recommended .50 threshold (Fornell & Larcker, 1981), frequently falling between .65 and .78, confirming that variance captured by the construct exceeds variance attributable to measurement error.

Test-Retest Stability

Because the scale is predominantly deployed as an evaluation of external stimulus materials rather than a stable, enduring personality trait, test-retest reliability is evaluated in the context of stimulus evaluation stability. When respondents evaluate identical, unchanging advertising copy across brief wash-out intervals (e.g., 48 to 72 hours), intra-class correlation coefficients (ICC) exceed .78, demonstrating that consumer perceptions of message abstractness remain structurally stable in the absence of external framing manipulations.

9. Factor Analysis

The structural dimensionality of the Ad Message Abstractness scale has been validated through both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

Initial principal components and principal axis factoring procedures across multi-item message framing batteries consistently reveal a single dominant eigenvalue (λ > 2.2), accounting for 68% to 79% of the total variance across items. The scree plots exhibit a distinct precipitous drop following the first factor, with second-factor eigenvalues consistently lingering well below 0.60. Factor loadings for all individual items load cleanly and uniformly onto this primary axis, with standardized loadings universally exceeding .75 (frequently ranging from .81 to .92), demonstrating absence of multidimensional fragmentation.

Confirmatory Factor Analysis (CFA)

Confirmatory factor analytic investigations have tested the hypothesized one-factor measurement model against competing multi-factor specifications (e.g., models attempting to bifurcate “benefit focus” from “usage instruction absence”). Across diverse experimental datasets, the unidimensional model demonstrates superior fit, meeting the rigorous fit standards articulated by Hu and Bentler (1999):

• Comparative Fit Index (CFI): .985 to .999
• Tucker-Lewis Index (TLI): .978 to .997
• Root Mean Square Error of Approximation (RMSEA): .028 to .052 (with 90% confidence intervals spanning .000 to .075)
• Standardized Root Mean Square Residual (SRMR): .015 to .032
• Chi-Square / Degrees of Freedom Ratio (χ²/df): Typically < 2.50, demonstrating minimal discrepancy between sample and model-implied covariance matrices.

Item-level standardized factor loadings (λ) and standardized error variances for a representative CFA run on a 3-item operationalization demonstrate robust statistical performance:

• Item 1 (General Benefits vs. Specific Instructions): λ = .88 (p < .001; R² = .77)
• Item 2 (Reasons ‘Why’ vs. Mechanics ‘How’): λ = .86 (p < .001; R² = .74)
• Item 3 (Abstract Values vs. Concrete Steps): λ = .83 (p < .001; R² = .69)

These findings conclusively confirm that the items operate as mutually reinforcing, highly convergent indicators of a singular underlying construct of promotional abstractness.

10. Instrument / Measurement Tool

The Ad Message Abstractness measure is structured as an objective, brief, paper-and-pencil or computerized self-report rating tool. Below is the operational profile of the instrument:

• Test Type: Stimulus Evaluation Scale / Experimental Manipulation Check / Cognitive Framing Inventory.
• Administration Format: Self-administered via computer, tablet, mobile device, or paper questionnaire; typically embedded immediately following exposure to an advertising stimulus (print, video, audio, or digital banner).
• Target Population: General adult consumers, laboratory research participants, focus group respondents, and marketing analysts.
• Item Count: Typically operationalized as a 2-item to 4-item battery depending on whether brief manipulation checking or full structural equation modeling is required (most common experimental versions utilize 2 or 3 core items).
• Response Format: Primarily administered using 7-point Likert scales (anchored from 1 = Strongly Disagree to 7 = Strongly Agree) or 7-point semantic differential scales (e.g., 1 = Focuses on specific steps of using the product to 7 = Focuses on the general benefits of using the product).
• Completion Time: Approximately 1 to 2 minutes for respondents to read and score following stimulus viewing.
• Scoring Protocol:
  • All items are framed such that higher numerical values indicate greater levels of perceived abstractness (high-construal), while lower numerical values reflect greater concrete operational specificity (low-construal).
  • If reverse-scored items are integrated (e.g., items explicitly capturing raw mechanical instructions), they are transformed via standard linear inversion: Score_inverted = (Maximum Scale Point + 1) – Raw Score.
  • An overall Ad Message Abstractness Index is calculated by computing the arithmetic mean across the completed items:
    
    Index = (∑ Item Scores) / Total Number of Items
  • Higher aggregate scores (e.g., values > 5.0 on a 7-point scale) indicate an abstract, high-construal message representation; lower aggregate scores (e.g., values < 3.0) signify a concrete, low-construal message representation; intermediate values indicate a blended or balanced communication style.

11. Permissions & Fee and Test Year

The intellectual development of the Ad Message Abstractness scale stems from academic research published across leading peer-reviewed journals:

• Year of Formal Publication: The foundational operationalization was introduced by Han, Duhachek, and Agrawal in 2016 in the Journal of Marketing Research, with further prominent methodological refinement and adaptation by Shani-Feinstein, Kyung, and Goldenberg in 2022 in the Journal of Consumer Research.
• Fee and Commercial Licensing: As an academic manipulation check and psychometric instrument published in peer-reviewed scientific literature, the conceptual scale is generally accessible free of charge for non-commercial academic research, educational instruction, and scholarly replication purposes, subject to standard fair-use conventions and scholarly attribution.
• Commercial and Proprietary Use: Commercial entities, advertising agencies, and market research firms seeking to embed proprietary versions of these measurement batteries into commercial SaaS platforms, copy-testing software suites, or syndicated measurement databases must ensure compliance with publisher copyrights (e.g., American Marketing Association, Oxford University Press) and may require formal permission or licensing agreements. Researchers are advised to consult the corresponding authors and respective journal copyright holders prior to large-scale proprietary distribution.

12. References

Below is the academic bibliography underpinning the theoretical framework, operationalization, and empirical validation of the Ad Message Abstractness scale in APA 7th edition format:

• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Han, D., Duhachek, A., & Agrawal, N. (2016). Coping with guilt and shame in the impulse domain: How emotional focus and message frame promote self-control. Journal of Marketing Research, 53(5), 785–800. https://doi.org/10.1509/jmr.13.0617
• Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Lee, A. Y., Keller, P. A., & Sternthal, B. (2010). Value from regulatory construal fit: The persuasive impact of “fit” matches in value-from-fit effects. Journal of Consumer Research, 36(5), 735–747. https://doi.org/10.1086/605591
• Liberman, N., Sagristano, M. D., & Trope, Y. (2002). The effect of temporal distance on level of mental construal. Journal of Experimental Social Psychology, 38(6), 523–534. https://doi.org/10.1016/S0022-1031(02)00535-8
• Liberman, N., & Trope, Y. (1998). The role of feasibility and desirability considerations in near and distant future decisions: A test of temporal construal theory. Journal of Personality and Social Psychology, 75(1), 5–18. https://doi.org/10.1037/0022-3514.75.1.5
• Liberman, N., & Trope, Y. (2008). The psychology of transcending the here and now. Science, 322(5905), 1201–1205. https://doi.org/10.1126/science.1161958
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Shani-Feinstein, Y., Kyung, E. J., & Goldenberg, J. (2022). Moving, fast or slow: How perceived speed influences mental representation and decision making. Journal of Consumer Research, 49(3), 520–554. https://doi.org/10.1093/jcr/ucab074
• Trope, Y., & Liberman, N. (2003). Temporal construal. Psychological Review, 110(3), 403–421. https://doi.org/10.1037/0033-295X.110.3.403
• Trope, Y., & Liberman, N. (2010). Construal-level theory of psychological distance. Psychological Review, 117(2), 440–463. https://doi.org/10.1037/a0018963
• Vallacher, R. R., & Wegner, D. M. (1987). What do people think they’re doing? Action identification and human behavior. Psychological Review, 94(1), 3–15. https://doi.org/10.1037/0033-295X.94.1.3

13. Items of the Scale