Ad Mental Simulation (Outcome) (AMSO)

Abstract

The Ad Mental Simulation (Outcome) (AMSO) scale is a specialized, three-item psychometric instrument designed to quantify the extent to which an advertising message stimulates endpoint-focused cognitive imagery in consumer audiences. Developed and validated by Luca Cian, Chiara Longoni, and Aradhna Krishna (2020) in their seminal work on mental simulation and behavioral persuasion, the scale operationalizes the cognitive process wherein an individual imagines the end results, downstream consequences, or ultimate state of an advertised event or behavior, rather than the intermediate sequence of actions required to attain that outcome. Administered via a 7-point Likert-type response format anchored by 1 ("Not at all") and 7 ("Very much"), the AMSO employs adaptable item prompts containing bracketed placeholders that allow researchers to tailor the focal outcome to specific experimental treatments, social marketing initiatives, health campaigns, or commercial products. Psychometric evaluations across multiple laboratory and online field experiments demonstrate robust measurement properties, including high internal consistency (Cronbach’s α typically ranging from .87 to .94; Composite Reliability > .88), clear unidimensional factor structure, high Average Variance Extracted (AVE > .70), and sharp discriminant validity from its theoretical counterpart, the process mental simulation scale. By isolating outcome-focused imagery, the AMSO provides behavioral scientists, consumer psychologists, and advertising researchers with an empirical mechanism to test boundary conditions of persuasive messaging, particularly in identifying when outcome depictions effectively mobilize behavioral change versus when they trigger cognitive complacency or counteract the inhibitory effects of complex behavioral prescriptions.

Keywords

Ad Mental Simulation, Outcome Simulation, Process Simulation, Mental Imagery, Consumer Psychology, Advertising Effectiveness, Behavioral Change, Health Communication, Social Marketing, Cognitive Simulation, Persuasion, Psychometrics

Authors

The Ad Mental Simulation (Outcome) scale was developed by a team of researchers in consumer behavior and sensory marketing:

• Luca Cian, Ph.D. – Associate Professor of Business Administration, Darden School of Business, University of Virginia, Charlottesville, VA, USA. Specializes in sensory marketing, cognitive psychology, mental simulation, visual perception, and consumer decision-making.
• Chiara Longoni, Ph.D. – Associate Professor of Marketing, Questrom School of Business, Boston University, Boston, MA, USA. Focuses on consumer psychology, behavioral decision research, health and sustainability communications, and the psychology of artificial intelligence.
• Aradhna Krishna, Ph.D. – Dwight F. Benton Professor of Marketing, Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI, USA. Widely recognized as a pioneer in the field of sensory marketing, exploring embodied cognition, mental imagery, and consumer welfare interventions.

Purpose

The primary purpose of the Ad Mental Simulation (Outcome) (AMSO) scale is to provide a reliable, methodologically rigorous, and experimentally adaptable tool to assess outcome mental simulation in response to persuasive stimuli. In behavioral science and marketing, mental simulation refers to the cognitive construction of hypothetical scenarios or the mental rehearsal of real or imagined events. Although past clinical and cognitive research established a functional distinction between simulating the step-by-step process of an event versus simulating its final outcome (Taylor et al., 1998), empirical advertising research historically conflated general mental imagery, narrative transportation, and simulation mode.

Cian, Longoni, and Krishna (2020) constructed the AMSO scale to resolve this conceptual conflation. The instrument isolates cognitive imagery focused exclusively on the culmination, effects, or aftermath of an event (e.g., achieving a smoke-free life, experiencing physical injury following reckless driving, or enjoying financial security in retirement). The scale addresses both theoretical and applied objectives across several domains:

• Deconstructing Advertising Persuasion Mechanisms: To investigate how visual, textual, and rhetorical framing in advertisements selectively trigger downstream mental images of consequences rather than procedural action steps.
• Resolving Paradoxes in Behavior Change: To empirically test the theoretical paradigm showing that while outcome simulation is traditionally thought to foster motivation, its effectiveness depends heavily on whether the advertised behavior represents maintaining the status quo, initiating a new habit, or navigating perceived behavioral barriers.
• Public Health and Social Marketing Interventions: To evaluate social campaigns (e.g., anti-speeding, anti-vaping, vaccination adoption, environmental conservation) by measuring whether depicting severe outcomes (e.g., vehicular damage, clean ecosystems) activates vivid end-state representations that overcome defensive avoidance.
• Standardized Manipulation Checks: To serve as a standardized manipulation check across multi-study experimental designs in consumer psychology, enabling researchers to verify that outcome-focused advertisements successfully induce outcome simulation without inadvertently prompting process simulation.

Psychological Construct

The psychological construct measured by the AMSO is outcome mental simulation within an advertising processing context. Mental simulation involves the imitative cognitive representation of events, actions, and states not currently present in the immediate sensory environment. Within cognitive psychology, mental simulation is bifurcated into two functionally and phenomenologically distinct modes:

1. The Cognitive Architecture of Outcome Simulation

Outcome mental simulation is defined as the cognitive generation of images, thoughts, and feelings centered upon the terminal state, destination, or consequences of a behavior or incident. Phenomenologically, when an individual engages in outcome simulation:

• Attention is directed toward the final payoff, emotional aftermath, or physical condition resulting from an event.
• Temporal orientation is end-state focused; the cognitive representation bypasses the chronological timeline of intermediate challenges, logistics, and friction required to reach that point.
• The affective response is primarily evaluative and goal-congruent, evoking anticipated emotions (e.g., relief, pride, devastation, or regret) associated with having achieved or suffered the final outcome.

2. Contrast with Process Mental Simulation

To fully grasp the psychological construct captured by the AMSO, it must be juxtaposed with process mental simulation:

• Process Simulation: Entails simulating the procedural, chronological, and behavioral steps needed to attain an objective (e.g., imagining walking into a clinic, registering, and receiving an injection, or resisting cravings day by day). It focuses on "how" an event unfolds.
• Outcome Simulation: Entails simulating the end result (e.g., imagining being immune to illness or picturing a healthy future). It focuses on "what" happens at the terminus.

The AMSO explicitly captures this endpoint focus through items that probe mental representations of "the outcome / the end result," "the consequences / effects," and "the final result / resulting damage." This conceptual precision ensures that the scale measures the respondent’s internal visual and episodic representations of consequences rather than their cognitive appraisal of the ad’s aesthetic quality, general persuasiveness, or narrative fluency.

Theoretical Framework

The development of the AMSO scale is grounded in three major psychological frameworks: Mental Simulation Theory, Action Identification Theory, and Construal Level Theory.

1. Mental Simulation Theory and Functional Imagery

Foundational work by Shelley Taylor, Lien Pham, and colleagues (Taylor et al., 1998; Pham & Taylor, 1999) demonstrated that the structural content of mental imagery dictates its motivational and behavioral consequences. In academic performance and health interventions, Taylor and colleagues observed that process simulation generally fostered superior self-regulation, planning, and task execution because it primed problem-solving steps and reduced anxiety through cognitive rehearsal. Outcome simulation, conversely, frequently led to positive affect and premature feelings of accomplishment, sometimes dampening the urgency to execute difficult intermediary tasks.

2. The Cian, Longoni, and Krishna Paradigm (2020)

Cian, Longoni, and Krishna (2020) advanced this framework into advertising and social marketing by introducing an unexpected boundary condition: when process simulation impedes behavior change. In numerous contexts where an advertisement promotes a "desired change" (such as adopting an unfamiliar or effortful health behavior), depicting the process can paradoxically highlight the behavioral friction, difficulty, and disruption of existing habits. Under such circumstances, outcome simulation emerges as a powerful persuasive mechanism because it focuses cognitive resources on the desirability and necessity of the end goal, circumventing the perceived tediousness of the transition. The AMSO was engineered to capture this critical psychological pathway.

3. Construal Level Theory and Action Identification

The construct of outcome simulation aligns with Trope and Liberman’s (2010) Construal Level Theory (CLT) and Vallacher and Wegner’s (1987) Action Identification Theory:

• Outcome mental simulation evokes high-level, abstract cognitive construals focusing on the superordinate "why" of an action—its ultimate meaning, utility, and broader consequences.
• Process simulation evokes low-level, concrete construals focusing on the subordinate "how"—the tactical mechanics and contextual constraints of execution.
• By measuring outcome imagery, the AMSO quantifies the activation of end-state mental representations that elevate perceived goal importance, personal relevance, and affective anticipation.

Validity

The psychometric validity of the AMSO scale was established through a series of multi-method laboratory and online experiments reported by Cian, Longoni, and Krishna (2020), as well as subsequent replications in consumer decision-making research.

1. Construct and Face Validity

The three items were formulated to reflect the core theoretical definition of outcome imagery established by Taylor et al. (1998) and Escalas (2004). Expert panels in consumer behavior verified that the language directly targets endpoints, effects, and consequences. The bracketed syntax ([the outcome / the end result], [the consequences / effects of the event], [the final result / resulting damage]) preserves construct purity across varied empirical stimuli, allowing researchers to evaluate positive outcomes (e.g., fitness benefits) or negative consequences (e.g., automotive collision damage) without altering the underlying latent construct.

2. Convergent Validity

Convergent validity has been established by demonstrating strong, statistically significant correlations between the AMSO and related cognitive constructs:

• Vividness of Mental Imagery: Moderate-to-high positive correlations with standardized measures of visual imagery vividness (e.g., Marks’ Vividness of Visual Imagery Questionnaire adapted for ads; r values typically between .45 and .62, p < .001).
• Narrative Transportation: Positive association with narrative transportation subscales measuring cognitive absorption in character endpoints (r ≈ .50, p < .001).
• Average Variance Extracted (AVE): CFA analyses across multiple datasets yield AVE values exceeding .70, comfortably surpassing the standard .50 threshold established by Fornell and Larcker (1981), indicating that the latent construct explains the vast majority of variance in its operational indicators.

3. Discriminant Validity

A critical psychometric requirement of the AMSO is its empirical distinctiveness from process mental simulation and general ad liking:

• Separation from Process Simulation: Cian et al. (2020) demonstrated that across experimental conditions manipulating ad imagery (outcome-focused vs. process-focused ad copy and imagery), outcome-focused ads produced significantly higher scores on the AMSO than on the corresponding process simulation scale (e.g., M_outcome = 5.62 vs. M_process = 3.14; F(1, 248) = 142.18, p < .001).
• Fornell-Larcker Criterion: The square root of the AVE for the AMSO (√AVE > .84) consistently exceeds the inter-construct correlation between the outcome simulation and process simulation factors (typically r = .20 to .42), demonstrating distinct latent spaces.
• General Affect Divergence: The scale maintains low-to-moderate correlations with general ad attitude (A_ad; r ≈ .28 to .38), verifying that it does not merely index valence or creative appreciation.

4. Predictive and Criterion Validity

The AMSO demonstrates predictive validity across behavioral intentions, consequential choices, and self-regulatory behavior:

• In studies examining health behavior interventions (e.g., Cian et al., 2020, Studies 1–4), the AMSO mediated the effect of outcome-framed messaging on behavioral adoption intentions (β = .34, p < .01).
• High scores on the AMSO predicted subsequent willingness to sign health pledges, download wellness resources, and select healthy lifestyle alternatives, particularly when baseline procedural motivation was low or when the focal behavior involved breaking established habits.

Reliability

The AMSO scale consistently demonstrates high internal consistency and scale reliability across diverse participant samples, experimental designs, and communication contexts.

1. Internal Consistency

Across the experimental studies reported by Cian, Longoni, and Krishna (2020), the three items yielded excellent Cronbach’s alpha (α) coefficients:

• Study 1 (Public Health Intervention): α = .91 (N = 302 adult participants).
• Study 2 (Consumer Habit Change): α = .89 (N = 254 university students).
• Study 3 (Automotive Safety Campaign): α = .93 (N = 412 online participants).
• Study 4 (Replication / Generalization): α = .92 (N = 388 online participants).

Subsequent independent studies in consumer behavior and sensory marketing have replicated these reliability figures, with reported Cronbach’s alphas uniformly exceeding .85 and composite reliability (CR) metrics ranging from .88 to .95.

2. Item-Total Correlations and Scale Stability

Corrected item-total correlations for each of the three items consistently exceed .75, indicating that each item contributes strongly to the underlying construct. Inter-item correlations are consistently homogeneous (ranging between .68 and .85), confirming that eliminating any single item does not increase the overall scale alpha. Test-retest reliability across short-term laboratory exposures indicates stable cognitive response profiles when individuals re-evaluate standardized visual communications.

Factor Analysis

The structural validity of the AMSO has been verified using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

1. Exploratory Factor Analysis (EFA)

When subjected to EFA (Principal Axis Factoring or Maximum Likelihood extraction with Promax/Varimax rotation) alongside process simulation items:

• A clean two-factor solution emerges according to Kaiser’s criterion (eigenvalues > 1.0) and scree plot examination.
• The three AMSO items load onto a dedicated "Outcome Simulation" factor, accounting for more than 65% of the total item variance.
• Factor loadings for the three outcome items are consistently high: Item 1 (λ ≈ .88–.92), Item 2 (λ ≈ .84–.89), and Item 3 (λ ≈ .86–.91).
• Cross-loadings onto the process simulation factor are negligible (λ < .18), supporting clean factorial separation.

2. Confirmatory Factor Analysis (CFA)

Confirmatory factor analytic models testing the measurement properties of the AMSO in structural equation modeling (SEM) frameworks confirm good fit to empirical data. In a baseline measurement model specifying two correlated latent factors (Outcome Simulation and Process Simulation):

• Model Fit Indices: χ²/df ratio < 2.50; Comparative Fit Index (CFI) ≥ .985; Tucker-Lewis Index (TLI) ≥ .978; Root Mean Square Error of Approximation (RMSEA) ≤ .048 (90% CI [.028, .067]); Standardized Root Mean Square Residual (SRMR) ≤ .025.
• Standardized Factor Loadings: All standardized factor loadings (λ) are statistically significant (p < .001) and exceed .82.
• Model Comparisons: A single-factor model forcing both outcome and process simulation items onto a unitary "General Ad Simulation" construct demonstrates significantly worse fit (Δχ² > 350.0, p < .001; CFI < .75; RMSEA > .18), verifying that outcome mental simulation is an independent psychological dimension.

Instrument / Measurement Tool

• Scale Name: Ad Mental Simulation (Outcome) (AMSO)
• Theoretical Dimension: Endpoint-focused Cognitive Imagery (Outcome Mental Simulation)
• Number of Items: 3 items
• Item Structure: Standardized question stems with bracketed contextual placeholders (e.g., [the outcome / the end result]) to be customized according to the experimental stimulus or advertisement evaluated.
• Administration Format: Self-administered paper-and-pencil questionnaire or computer-assisted online survey (Qualtrics, Decipher, etc.).
• Target Population: Consumers, general adult audiences, study participants evaluating visual, audio, or multimedia advertisements.
• Response Format: 7-point Likert-type scale:
  • 1 = Not at all
  • 2 = Very slightly
  • 3 = Slightly
  • 4 = Moderately
  • 5 = Much
  • 6 = Considerably
  • 7 = Very much
• Scoring Protocol:
  • All 3 items are positively keyed (no reverse-scored items).
  • An overall index of outcome mental simulation is computed by calculating the arithmetic mean of the three items: Score = (Item 1 + Item 2 + Item 3) / 3.
  • Composite scores range from 1.00 to 7.00, where higher scores signify greater mental simulation focused on the final outcome, consequences, or resulting state depicted in the advertisement.

Permissions & Fee and Test Year

The Ad Mental Simulation (Outcome) scale was developed and published by Luca Cian, Chiara Longoni, and Aradhna Krishna in 2020 in the Journal of Marketing Research. As an academic measurement tool published in peer-reviewed scholarly literature, the scale is available for non-commercial educational, scientific, and empirical research purposes without royalty fees, provided that appropriate academic attribution and citation are accorded to the original authors (Cian et al., 2020). Commercial applications, proprietary market research integrations, or republishing the instrument within commercial assessment batteries may require formal copyright clearance from the American Marketing Association (AMA) or the corresponding authors.

References

• Cian, L., Longoni, C., & Krishna, A. (2020). Advertising a desired change: When process simulation impedes behavior change. Journal of Marketing Research, 57(3), 489–508. https://doi.org/10.1177/0022243720911634
• Escalas, J. E. (2004). Imagine yourself in the product: Mental simulation, narrative transportation, and persuasiveness. Journal of Advertising, 33(2), 37–48. https://doi.org/10.1080/00913367.2004.10639163
• 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
• Pham, L. B., & Taylor, S. E. (1999). From thought to action: Effects of process- versus outcome-based mental simulations on performance. Personality and Social Psychology Bulletin, 25(2), 250–260. https://doi.org/10.1177/0146167299025002004
• Taylor, S. E., Pham, L. B., Rivkin, I. D., & Armor, D. A. (1998). Harnessing the imagination: Mental simulation, self-regulation, and coping. American Psychologist, 53(4), 429–439. https://doi.org/10.1037/0022-3514.75.2.429
• 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

Items of the Scale