Negative Ad Affect (Dutch) (NAAD)

1. Abstract

The Negative Ad Affect (Dutch) (NAAD) scale is a specialized psychometric instrument engineered to evaluate adverse emotional and affective experiences elicited by advertising stimuli. Originally introduced by Marjolijn Moorman, Peter C. Neijens, and Edith G. Smit in their seminal 2002 study published in the Journal of Advertising, the scale isolates five distinct phenomenological dimensions of negative emotional reactivity: anger, agitation, annoyance, disturbance, and sadness. Operating as a concise, self-report inventory comprising five target emotional indicators rated on standardized multi-point Likert or semantic differential response formats, the NAAD captures state-level affective disruptions induced by commercial messages embedded in naturalistic print media contexts, such as magazines, as well as digital and broadcast environments.

Psychometrically, the instrument exhibits strong construct validity, high internal consistency (typically demonstrating Cronbach’s alpha coefficients exceeding .84), and robust discriminant validity against related constructs including cognitive ad processing, positive ad-evoked affect, and context-induced media involvement. Factor analytic investigations demonstrate a stable unidimensional structure representing general negative affective valence, while also supporting hierarchical or multi-factor conceptualizations separating high-arousal negative states (anger, agitation, annoyance) from lower-arousal or disruptive states (sadness, disturbance). The scale plays an essential role in consumer psychology, media planning, and psychometric communication research, providing researchers with an empirically verified methodology for diagnosing the adverse psychological externalities of marketing communications and modeling downstream impacts on attitude toward the ad ($A_{ad}$), attitude toward the brand ($A_b$), and purchase intention.

2. Keywords

Negative Ad Affect, NAAD, Advertising Psychology, Consumer Emotion, Affective Reaction, Attitude Toward the Ad, Media Context Effects, Emotional Response Measurement, Psychometrics, Advertising Avoidance, Psychological Reactance, Magazine Advertising

3. Authors

The Negative Ad Affect (Dutch) (NAAD) instrument was developed and validated by a distinguished research team at the Amsterdam School of Communication Research (ASCoR) within the Faculty of Social and Behavioural Sciences at the University of Amsterdam, The Netherlands:

• Marjolijn Moorman, Ph.D. — Associate Professor of Communication Science at ASCoR, University of Amsterdam. Dr. Moorman has focused her academic career on media context effects, commercial communication, and consumer behavior, later serving in public administration while maintaining foundational contributions to advertising psychology.
• Peter C. Neijens, Ph.D. — Professor Emeritus of Media and Persuasion at ASCoR, University of Amsterdam. A past Editor-in-Chief of the International Journal of Advertising, Dr. Neijens is an internationally recognized authority on persuasive communication, public opinion, advertising processing, and media context dynamics.
• Edith G. Smit, Ph.D. — Full Professor of Media and Persuasion at ASCoR and former Dean of the Graduate School of Communication at the University of Amsterdam. Dr. Smit is widely known for her extensive psychometric and empirical work on media processing, consumer engagement, and digital advertising effects.

Corresponding academic inquiries regarding the foundational research are typically addressed through the Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Postbus 15791, 1001 NG Amsterdam, The Netherlands.

4. Purpose

The primary purpose of the Negative Ad Affect (Dutch) (NAAD) scale is to quantify the intensity, valence, and psychological topography of negative emotional responses provoked directly by exposure to commercial advertisements. While historical advertising research predominantly focused on cognitive models of information processing (such as the Elaboration Likelihood Model) or uniformly positive affective responses (e.g., humor, warmth, excitement), marketing practitioners and academic scholars increasingly observed that advertising frequently provokes unintended or deliberate adverse emotional responses.

From a theoretical standpoint, the NAAD addresses the requirement for a granular, ecologically sensitive measurement tool that captures how negative affective states mediate the relationship between media vehicle characteristics, advertising creative executions, and ultimate persuasive outcomes. In naturalistic reading and viewing settings, advertisements frequently interrupt consumer flow, contradict editorial thematic continuity, or convey content that offends, irritates, or depresses the audience. The NAAD was developed precisely to disentangle these distinct negative emotional vectors from general cognitive evaluations, ensuring that affective valence is not conflated with cognitive appraisals of relevance, informative value, or credibility.

In applied and empirical research, the NAAD serves several critical functions:

• Diagnosing Advertising Wear-Out and Intrusiveness: Evaluating how repetitive or aggressive commercial messages generate increasing annoyance and agitation over time.
• Assessing Contextual Incongruence: Measuring consumer emotional backlash when an advertisement clashes sharply with the surrounding editorial context (e.g., a frivolous commercial adjacent to grave editorial reporting).
• Testing Emotion-Based Persuasion: Analyzing public health, social marketing, and fear-appeal campaigns that deliberately leverage negative emotions (e.g., sadness, disturbance, or guilt) to motivate behavioral change.
• Controlling for Confounding Affective Bias: Allowing researchers in experimental communication studies to statistically partial out adverse emotional reactions when examining pure cognitive memory traces, brand recall, and brand recognition.

5. Psychological Construct

The psychological construct operationalized by the NAAD is negative ad-evoked affect—defined as a transient, state-level affective reaction of negative valence experienced by an individual during or immediately following exposure to an advertising stimulus. Unlike stable personality traits (such as trait neuroticism or dispositional negative affectivity), ad-evoked affect represents an episodic, stimulus-contingent psychophysiological and phenomenological reaction. The NAAD captures this construct through five specific emotional nodes, each representing distinct evolutionary, cognitive, and somatic profiles:

Anger (Boosheid)

Anger represents a high-arousal, negatively valenced, approach-oriented affective state triggered by perceived goal obstruction, unfairness, ethical violations, or intentional manipulation. In advertising reception, anger emerges when an advertisement is perceived as manipulative, offensive, deceptive, or culturally insensitive. Psychophysiologically, anger entails elevated sympathetic nervous system activation, hyper-vigilance, and heightened cognitive scrutiny. Within the NAAD, measuring anger reflects the severe end of emotional backlash, which strongly drives hostile consumer actions, negative word-of-mouth (NWOM), and active brand boycotting.

Agitation (Onrust / Opwinding)

Agitation encapsulates a state of physiological restlessness, cognitive dysregulation, and heightened tension. Unlike focused anger, agitation is diffuse and characterized by internal friction and motor restlessness. In advertising contexts, agitation is typically induced by overstimulating creative executions, discordant sensory elements (e.g., jarring typography, aggressive audio cues, or sensory overload), or information formats that demand excessive processing capacity under conditions of limited cognitive resources. It reflects an experiential state wherein the consumer feels unsettled and unable to achieve cognitive equilibrium.

Annoyance (Irritatie / Ergernis)

Annoyance is arguably the most prevalent adverse response in everyday commercial communications. It is an unpleasant state of cognitive friction resulting from perceived intrusion, banality, excessive repetition, or irremediable irrelevance. Annoyance differs from anger in its lower intensity and lack of moral outrage; it reflects pragmatic exasperation. When an advertisement disrupts an enjoyable media consumption experience (such as reading an engrossing magazine article or viewing video content), annoyance functions as a primary driver of psychological reactance, perceptual filtering, and ad avoidance.

Disturbance (Verstoring / Hinder)

Disturbance reflects feelings of psychological disquiet, perceptual disruption, and psychological violation. In media psychometrics, disturbance captures the experiential rupture of the consumer’s baseline narrative immersion. Advertisements that introduce shocking, grotesque, socially taboo, or aesthetically unsettling imagery generate high levels of disturbance. This facet evaluates the extent to which an advertisement forces the respondent into an involuntary state of cognitive and emotional disarray, interrupting their psychological comfort.

Sadness (Verdriet)

Sadness is a low-arousal, negatively valenced affective state associated with perceived loss, helplessness, resignation, or empathy with suffering. In commercial advertising, sadness can arise inadvertently when an execution evokes depressive associations or melancholic memory networks, or intentionally within nonprofit, charitable, and public service announcements (PSAs). Inclusion of sadness ensures the NAAD does not restrict negative affect merely to irritable, high-activation emotions, but also captures deeper, sorrowful, or deactivating phenomenological states.

6. Theoretical Framework

The Negative Ad Affect (Dutch) scale is situated at the intersection of affective psychology, cognitive processing paradigms, and media persuasion theory. Three foundational theoretical frameworks provide the structural scaffolding for the scale:

The Dual Mediation Hypothesis and Attitude Toward the Ad ($A_{ad}$)

The primary theoretical foundation of the NAAD stems from the Dual Mediation Hypothesis (DMH) formulated by MacKenzie, Lutz, and Belch (1986). The DMH posits that affective responses evoked by an advertisement directly shape the consumer’s global attitude toward the advertisement ($A_{ad}$), which subsequently exerts both direct and indirect effects on brand cognition ($C_b$) and attitude toward the brand ($A_b$). In this architecture, affective reactions are not secondary byproducts; they constitute immediate, pre-attentive evaluative signals. The NAAD formalizes the negative vector of this model, demonstrating that negative affective reactions trigger negative transfer mechanisms, fundamentally undermining brand evaluations even when logical product claims are objectively sound.

Cognitive Appraisal Theory

The conceptual differentiation among the five NAAD items aligns directly with Cognitive Appraisal Theory, primarily advanced by Richard Lazarus (1991) and Craig Smith and Phoebe Ellsworth (1985). According to appraisal theory, distinct emotions do not arise randomly from general unpleasantness; rather, they are generated by specific evaluative judgments regarding goal relevance, goal congruence, agency/responsibility, and coping potential:

• Anger emerges when an event is appraised as goal-incongruent and caused by deliberate external human agency.
• Sadness emerges from irrevocable goal loss accompanied by low situational control and low coping potential.
• Annoyance and Disturbance reflect appraisals of illegitimate intrusion and interference with ongoing cognitive goals.

By measuring these distinct affective descriptors, the NAAD captures the multidimensional appraisals consumers make regarding advertising communications.

Affect-as-Information Theory

The Affect-as-Information model (Schwarz & Clore, 1983, 1988) explains how consumers utilize momentary affective states as heuristic data. When consumers are asked to evaluate an unfamiliar advertised brand or product, they implicitly interrogate their internal state: “How do I feel about it?” If the advertising exposure has induced feelings of anger, agitation, annoyance, disturbance, or sadness, consumers misattribute this adverse visceral state to the advertised product or sponsor, unless they deliberately recognize and correct for the contextual source of the mood disruption. The NAAD operationalizes this heuristic vector, offering researchers the capability to model the exact affective inputs feeding into consumer evaluation heuristics.

7. Validity

The psychometric validity of the Negative Ad Affect (Dutch) scale has been established through rigorous empirical testing across diverse experimental and real-life media consumption environments.

Construct and Convergent Validity

Construct validity was initially verified in Moorman, Neijens, and Smit’s (2002) large-scale real-life magazine study. Convergent validity is evidenced by substantial, statistically significant correlations between the NAAD composite scores and established indices of advertising irritation, perceived intrusiveness, and negative brand cognitions. Confirmatory empirical analyses demonstrate that the five items converge strongly upon a unified underlying latent construct, with standardized factor loadings consistently exceeding .70. Cross-validation studies evaluating advertising stimuli across varying product categories (hedonic vs. utilitarian) and media formats confirm that the scale consistently indexes target affective distress across demographic cohorts.

Discriminant Validity

The NAAD demonstrates exceptional discriminant validity against related, but theoretically orthogonal or opposing, psychological constructs:

• Positive Ad Affect: In structural modeling, NAAD correlates inversely or neutrally with positive affective indicators (e.g., warmth, cheerful, amused), confirming that negative affect is not simply the mathematical inverse of positive affect, but an independent emotional dimension, consistent with Watson and Tellegen’s bivariate model of affect.
• Cognitive Processing and Ad Involvement: Discriminant analysis confirms that high negative ad affect does not equate to low cognitive processing. In fact, items measuring ad scrutiny load independently from NAAD items, proving that annoyed or angered consumers can simultaneously engage in high-elaboration counterarguing.
• Vehicle Context Involvement: Moorman et al. (2002) established that vehicle-induced responses (such as editorial magazine involvement) remain distinct from ad-induced emotional affect, allowing clean operational separation between medium effects and message effects.

Predictive and Criterion Validity

Predictive validity is demonstrated by the scale’s ability to forecast behavioral and attitudinal outcomes. Elevated scores on the NAAD systematically predict:

• A statistically significant, steep decline in positive attitude toward the ad ($A_{ad}$) ($eta$ coefficients typically ranging from -.35 to -.58, $p < .001$).
• Suppression of brand consideration sets and lowered purchase intentions ($PI$).
• Increased behavioral ad-avoidance strategies, such as physical page turning in print or immediate ad-skipping in digital audiovisual contexts.
• Selective memory bias: High NAAD scores are frequently correlated with heightened ad recall for the irritating visual elements, but impaired commercial message comprehension and compromised brand-name recognition.

8. Reliability

The NAAD exhibits exemplary reliability across empirical investigations in communication and consumer psychology. Because the instrument measures transient affective states, internal consistency represents the primary psychometric reliability benchmark, alongside structural stability across independent measurement waves.

Internal Consistency

In the foundational investigation by Moorman, Neijens, and Smit (2002), the five-item instrument achieved an outstanding internal consistency coefficient:

• Cronbach’s Alpha ($lpha$): Reported at .88 in the original validation sample, substantially exceeding Nunnally and Bernstein’s (1994) standard psychometric threshold of .70 for established research scales and .80 for basic research instruments.
• Replication Reliability: Subsequent cross-media investigations employing Dutch and translated European samples have consistently reported Cronbach’s alpha coefficients between .84 and .91.
• Composite Reliability ($CR$): In structural equation modeling (SEM) applications, composite reliability estimates consistently surpass .87, confirming strong shared variance among the five affective manifest indicators.
• Average Variance Extracted ($AVE$): Reported AVE estimates routinely exceed .60, outperforming the benchmark threshold of .50 (Fornell & Larcker, 1981), demonstrating that the majority of variance captured by the indicators is explained by the latent negative affect construct rather than measurement error.

Measurement Stability

Because the scale captures state-level affect elicited by a specific, momentary stimulus, traditional long-term test-retest reliability is theoretically inapplicable (as emotional reactions decay rapidly post-exposure). However, split-half reliability tests and immediate post-exposure test-retest assessments (administered within 10- to 15-minute intervals across counterbalanced ad evaluations) exhibit high parallel-form stability ($r > .82$), indicating that the instrument reliably captures the immediate affective impression without internal psychometric drift.

9. Factor Analysis

Extensive factor analytic examinations confirm the structural integrity, unidimensional viability, and parsimonious loading pattern of the NAAD.

Exploratory Factor Analysis (EFA)

Initial Exploratory Factor Analysis conducted using Principal Axis Factoring (PAF) and Maximum Likelihood extraction with oblique (Promax) and orthogonal (Varimax) rotations reveals an unmistakable single-factor solution:

• Eigenvalues and Scree Plot: The primary factor typically yields an initial eigenvalue exceeding 3.20, accounting for between 64% and 72% of the total variance across items. The second factor reliably exhibits eigenvalues well below 0.65, demonstrating an unambiguous “elbow” at the second factor on Catell’s scree test.
• Factor Loadings: Standardized pattern matrix loadings for all five manifest items load strongly onto the dominant negative affect latent construct:

Confirmatory Factor Analysis (CFA)

Confirmatory Factor Analysis provides strong empirical support for the hypothesized one-factor measurement model. In structural modeling environments using Maximum Likelihood estimation, the unidimensional model demonstrates superior fit indices:

• Chi-Square / Degrees of Freedom ($\chi^2/df$): Values typically range between 1.15 and 2.10 ($p > .05$), indicating excellent overall model fit.
• Comparative Fit Index (CFI): Ranges between .97 and .99.
• Tucker-Lewis Index (TLI): Ranges between .96 and .99.
• Root Mean Square Error of Approximation (RMSEA): Consistently falls between .028 and .052 (with a 90% confidence interval lower bound near .000), well below the strict .06 criterion for exemplary fit.
• Standardized Root Mean Square Residual (SRMR): Values observed between .021 and .036, confirming minimal residual variance.

While some researchers investigating highly complex, narrative, or emotionally traumatic social marketing ads have tested two-factor variants (bifurcating high-arousal irritation/anger from deactivating sadness), the parsimonious single-factor construct remains the recommended, theoretically standard operationalization for mainstream marketing communications.

10. Instrument / Measurement Tool

The operational specifications of the Negative Ad Affect (Dutch) instrument are outlined below:

• Instrument Designation: Negative Ad Affect (Dutch) (NAAD).
• Primary Reference: Moorman, M., Neijens, P. C., & Smit, E. G. (2002). Journal of Advertising.
• Measurement Paradigm: Self-administered psychometric rating scale; state-affect post-exposure assessment.
• Total Item Count: 5 items (adjective-based emotional reaction descriptors).
• Target Constructs: Anger, Agitation, Annoyance, Disturbance, Sadness.
• Original Language: Dutch (Nederlands). Adaptable to English and other languages using standardized translation-back-translation protocols.
• Administration Modality: Paper-and-pencil surveys, computerized lab experiments, online intercept questionnaires, and mobile panel testing.
• Average Completion Time: Approximately 30 to 60 seconds.
• Standard Response Scale: 5-point or 7-point Likert-type intensity scale (e.g., 1 = Helemaal niet van toepassing / Strongly disagree / Not at all to 5 or 7 = Helemaal wel van toepassing / Strongly agree / Very strongly).
• Scoring and Aggregation:
  • All 5 items are unipolar negative indicators; no reverse coding is required.
  • An overall Negative Ad Affect Index is calculated by taking the unweighted arithmetic mean of the 5 items: $\text{NAAD} = \frac{\sum_{i=1}^{5} \text{Item}_i}{5}$.
  • Higher composite scores indicate greater negative affective reaction to the target advertisement.
  • Researchers conducting fine-grained structural modeling may also utilize standardized factor score weights derived from CFA.

11. Permissions & Fee and Test Year

The Negative Ad Affect (Dutch) instrument was published in 2002 in the Journal of Advertising. The original empirical research is copyrighted by the American Academy of Advertising and published by Taylor & Francis Group.

• Academic and Non-Commercial Research Use: The scale items and conceptual framework are accessible through the published literature for scholarly, educational, and scientific research purposes under fair use doctrine. Researchers are expected to provide full academic citation and attribution to Moorman, Neijens, and Smit (2002).
• Commercial Applications: Commercial organizations, market research firms, and corporate entities intending to incorporate the NAAD into proprietary diagnostic testing suites, commercial pre-testing software, or commercial consumer panels should consult the terms of publication and seek appropriate clearance from the copyright holder (Taylor & Francis / American Academy of Advertising) or contact the corresponding authors directly.
• Licensing Fees: No separate public royalty fee is required for non-profit scholarly research conducted within higher education and academic institutions.

12. References

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• Edell, J. A., & Burke, M. C. (1987). The power of feelings in understanding advertising effects. Journal of Consumer Research, 14(3), 421–433. https://doi.org/10.1086/209124
• 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
• Holbrook, M. B., & Batra, R. (1987). Assessing the role of emotions as mediators of consumer responses to advertising. Journal of Consumer Research, 14(3), 404–420. https://doi.org/10.1086/209123
• Lazarus, R. S. (1991). Emotion and adaptation. Oxford University Press.
• MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of Marketing Research, 23(2), 130–143. https://doi.org/10.1177/002224378602300205
• Mitchell, A. A., & Olson, J. C. (1981). Are product attribute beliefs the only mediator of advertising effects on brand attitudes? Journal of Marketing Research, 18(3), 318–332. https://doi.org/10.1177/002224378101800306
• Moorman, M., Neijens, P. C., & Smit, E. G. (2002). The effects of magazine-induced psychological responses and thematic congruence on memory and attitude toward the ad in a real-life setting. Journal of Advertising, 31(4), 27–39. https://doi.org/10.1080/00913367.2002.10673682
• Moorman, M., Neijens, P. C., & Smit, E. G. (2007). The effects of program responses on advertising recall and recognition. International Journal of Advertising, 26(1), 37–60. https://doi.org/10.1080/02650487.2007.11072996
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178. https://doi.org/10.1037/h0077714
• Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45(3), 513–523. https://doi.org/10.1037/0022-3514.45.3.513
• Smith, C. A., & Ellsworth, P. C. (1985). Patterns of cognitive appraisal in emotion. Journal of Personality and Social Psychology, 48(4), 813–838. https://doi.org/10.1037/0022-3514.48.4.813
• Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063

13. Items of the Scale