Negative Affective Response (NAR)

1. Abstract

The Negative Affective Response (NAR) scale is a concise, psychometrically robust self-report measurement tool designed to assess the subjective intensity of adverse emotional experiences. Grounded in consumer behavior, social psychology, and affective neuroscience, the instrument was prominently operationalized by Jennifer Aaker, Aimee Drolet, and Dale Griffin in their seminal 2008 investigation into the cognitive mechanisms governing the retrospective evaluation and recall of mixed emotional experiences (Journal of Consumer Research). Comprising six single-word affective adjectives, the NAR scale measures transient negative emotional states elicited by unfavorable outcomes, expectation disconfirmation, decision-making dilemmas, and distressing environmental or contextual stimuli. The items are traditionally evaluated using a multi-point Likert or semantic differential response format (typically ranging from 1 = “Not at all” to 7 = “Extremely”), yielding a composite index of state negative affect.

Extensive empirical investigations across experimental consumer psychology, organizational behavior, and behavioral decision theory demonstrate that the NAR exhibits exemplary psychometric properties. Internal consistency estimates routinely yield Cronbach’s alpha values exceeding α = .85 and frequently reaching α = .92 across diverse experimental paradigms. Exploratory and confirmatory factor analyses robustly substantiate a unidimensional structural model, while demonstrating clear discriminant validity from positive affective response scales, baseline trait neuroticism, and post-decisional cognitive dissonance. The scale exhibits sensitive predictive validity regarding consumer dissatisfaction, brand avoidance, complaining behavior, and retrospective memory distortion. Its brevity substantially mitigates respondent burden and survey satisficing, establishing the NAR as a premier operational instrument for laboratory experiments, longitudinal field trials, and applied organizational research.

2. Keywords

Negative Affective Response, NAR, emotional intensity, mixed emotions, expectation disconfirmation, state affect, subjective well-being, consumer psychology, psychometrics, valence-arousal model, emotion recall

3. Authors

The operational framework of the Negative Affective Response (NAR) measure detailed in contemporary psychological literature was refined and validated by:

• Jennifer L. Aaker, Ph.D. — General Atlantic Professor of Marketing, Stanford Graduate School of Business, Stanford University. Dr. Aaker is an internationally recognized social psychologist whose research centers on subjective well-being, the psychology of time and money, brand personality, and the cognitive architecture of mixed emotions.
• Aimee Drolet, Ph.D. — Professor of Marketing, UCLA Anderson School of Management, University of California, Los Angeles. Dr. Drolet’s empirical scholarship investigates consumer decision-making, emotional regulation across the adult lifespan, aging, and choice dynamics.
• Dale Griffin, Ph.D. — Advisory Council Professor in Consumer Behaviour, Sauder School of Business, University of British Columbia. Dr. Griffin’s research examines behavioral decision-making, subjective risk assessment, judgmental heuristics, and psychological measurement.

Inquiries regarding experimental paradigms and scale conceptualization are typically directed to the academic departments of the respective authors or accessed via original empirical publications in peer-reviewed consumer psychology journals.

4. Purpose

The primary objective of the Negative Affective Response (NAR) scale is to capture and quantify the immediate or recalled subjective magnitude of unpleasant affective activation following experimental manipulations, decision-making events, or service and product outcomes that fail to satisfy normative or anticipated expectations. Within behavioral science, capturing affective valence with precision has presented an enduring methodological challenge. Broad omnibus instruments such as the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) provide a broad assessment of high-activation negative states (e.g., jittery, scared, hostile), yet they frequently include items that do not align seamlessly with targeted goal failure, unfulfilled expectations, or nuanced behavioral conflict.

The NAR scale was specifically crafted to circumvent these limitations by utilizing a targeted battery of six focused adjectives that sensitively mirror the emotional distress, sadness, frustration, and dissatisfaction evoked when an outcome does not meet expectations. In clinical and counseling research, the NAR serves as an agile state check to monitor acute emotional reactivity following distress-induction protocols, cognitive reappraisal tasks, or conflict-resolution simulations. In consumer research and behavioral economics, the scale provides a dependable dependent variable to examine expectancy disconfirmation theory, the psychological fallout of service failures, ethical transgressions in corporate branding, and the temporal decay of negative sentiment.

A distinctive theoretical rationale for the NAR is its application in paradigms exploring mixed emotions. Classical bipolar models of affect posited that positive and negative emotions exist on a single continuum where one polarity inhibits the other. Contemporary affective science demonstrates that individuals can simultaneously experience positive and negative emotions (e.g., bittersweet nostalgia, poignant cinematic endings, ambivalent consumption). The NAR operates in parallel with positive affective response batteries, enabling researchers to measure negative affect orthogonally without presupposing an inverse relationship with concurrent positive feelings. Consequently, the scale enables fine-grained analyses of emotional co-activation, coping strategies, and retrospective memory biases.

5. Psychological Construct

The Negative Affective Response construct reflects an individual’s conscious, experiential state of adverse emotional feeling characterized by unpleasant valence and moderate-to-high motivational avoidance. Within the broader dimensional taxonomy of emotion, affective reactions are broadly parsed along two central axes: valence (pleasantness versus unpleasantness) and arousal or activation (high energy versus low energy). The NAR measures the negative sector of this circumplex, specifically targeting feelings triggered when personal goals are blocked, expectations are violated, or aversive outcomes occur.

While the six-item NAR operates as an integrated unidimensional index of overall negative affect, the underlying affective items capture several complementary facets of emotional distress:

• Frustrative Disappointment: Emotions arising when expected rewards are withheld or delayed. This facet captures the cognitive realization of an expectation-reality discrepancy paired with acute motivational irritation (e.g., feelings of being disappointed or frustrated).
• Dysphoric Dejection: The subjective experience of low positive reinforcement, loss, or sadness. This emotional state reflects a decrease in hedonic tone following a negative outcome or a poignant, bittersweet narrative (e.g., feelings of sadness or sorrow).
• Irritation and Aversion: Mild-to-moderate high-arousal negative reactions characterized by hostility or annoyance toward an external stimulus, product failure, or interpersonal encounter (e.g., feelings of being irritated or annoyed).

For instance, in an empirical investigation evaluating customer reactions to a flight cancellation, an individual may register high levels on the frustrative and irritative facets due to thwarted plans, alongside moderate dejection over missed social engagements. In an experimental investigation on retrospective recall (Aaker et al., 2008), the NAR captures how these feelings attenuate or intensify over time depending on whether the individual engages in positive reappraisal, rumination, or selective memory consolidation. The cohesive convergence of these facets into a single composite score reflects the global subjective intensity of the negative experience, affording researchers a valid index of affective displeasure.

6. Theoretical Framework

The theoretical architecture of the Negative Affective Response scale is anchored in three primary paradigms within cognitive and social psychology:

Expectancy Disconfirmation Theory (EDT)

Originally formulated by Richard L. Oliver (1980), Expectancy Disconfirmation Theory posits that psychological satisfaction and emotional responses are determined by the cognitive comparison between prior expectations and actual perceived performance. When performance falls below the reference threshold (negative disconfirmation), individuals experience cognitive tension accompanied by an adverse emotional surge. The NAR provides an explicit psychometric operationalization of this immediate emotional response, capturing the emotional distress generated by unfulfilled anticipations.

The Evaluative Space Model and Emotional Ambivalence

The Evaluative Space Model (ESM), formulated by John Cacioppo and Gary Berntson (1994), posits that positive and negative evaluative processes are subserved by separable, distinct neurobiological substrates. Rather than operating along a single bipolar continuum, positive and negative affect can fluctuate independently, yielding states of uncoupled activation, reciprocal activation, or co-activation (mixed emotions). The NAR scale rests on this theoretical assumption: by treating negative affect as an autonomous dimension, researchers can independently measure adverse feelings alongside positive feelings, assessing how individuals reconcile dual emotional states across time and memory.

Socioemotional Selectivity Theory and Memory Reconstruction

In the context of Aaker, Drolet, and Griffin (2008), the scale is integrated with Laura Carstensen’s Socioemotional Selectivity Theory and cognitive models of autobiographical memory recall. These frameworks demonstrate that the subjective recall of emotional experiences is not a direct playback of past sensations, but an active, reconstructed cognitive process. Over time, individuals systematically edit their recalled negative affective response to protect emotional well-being and resolve cognitive dissonance, particularly as time horizons compress or when motivation shifts toward hedonic balance. The NAR provides the standardized benchmark against which immediate affective reactions are contrasted with delayed retrospective assessments.

7. Validity

The psychometric validity of the Negative Affective Response scale has been corroborated through rigorous experimental and psychometric testing:

Construct and Convergent Validity

Construct validity is evidenced by the scale’s strong, positive correlations with established indices of negative emotionality. The NAR exhibits robust convergent validity with the Negative Affect subscale of the PANAS (Watson et al., 1988), with Pearson correlation coefficients typically ranging between r = .68 and r = .81 (p < .001). Furthermore, the scale correlates positively with standardized measures of perceived stress (e.g., Perceived Stress Scale, r = .52 to .64) and physiological indicators of sympathetic nervous system arousal (such as galvanic skin response and corrugator supercilii electromyographic activity) during acute stress exposure.

Discriminant Validity

Discriminant validity has been demonstrated against positive affective states and cognitive evaluation metrics. Across multiple studies, correlations between the NAR and positive affect scales (e.g., joy, excitement, contentment) remain consistently low or orthogonal (typically r = −.12 to −.28 in non-bipolar contexts, approaching r = .05 in complex mixed-emotion settings), confirming that the scale is not simply an inverted reflection of happiness. Additionally, the NAR successfully discriminates between purely affective distress and purely cognitive dissatisfaction (average shared variance < 35%), demonstrating that emotional upset captures distinct variance beyond cognitive belief metrics.

Predictive and Criterion-Related Validity

The predictive utility of the scale is documented in studies of post-decision behaviors. Elevated scores on the NAR reliably predict subsequent avoidance behavior, negative word-of-mouth (WOM), punitive decision-making, and brand switching. In laboratory experiments conducted by Aaker et al. (2008), immediate NAR scores predicted the rate and trajectory of retrospective memory distortion across multi-week intervals: respondents with moderate-to-high negative affective responses exhibited significant systematic memory decay or attenuation, reorganizing their recall of mixed experiences to favor positive emotional resolution.

8. Reliability

The Negative Affective Response scale demonstrates exceptional reliability across experimental manipulations, longitudinal tracking, and varied demographic samples:

Internal Consistency

Internal consistency is universally high across the empirical literature. In the original series of studies by Aaker, Drolet, and Griffin (2008), the six-item composite achieved Cronbach’s alpha coefficients consistently exceeding α = .88. In Study 1, evaluating mixed emotional recalls, the negative affect index demonstrated a reliability coefficient of α = .90. Subsequent cross-validation studies in consumer behavior and cognitive appraisal research report alpha values ranging from α = .86 to α = .93. McDonald’s omega (ω) coefficients similarly confirm high composite reliability, routinely surpassing ω = .89, indicating that random measurement error is minimal.

Test-Retest Reliability and Stability

Because the NAR is primarily configured as a measure of state affect, test-retest reliability is inherently dependent on the temporal stability of the evoking context. When administered across short intervals without an intervening mood-altering task (e.g., a 15-minute distractor task), test-retest correlations remain high (r > .80). When utilized longitudinally across days or weeks to evaluate emotional decay, test-retest correlations systematically diminish (e.g., r = .40 to .55 over a two-week interval), precisely reflecting the natural psychological fading of acute negative emotions (the fading affect bias) rather than measurement instability.

9. Factor Analysis

The structural dimensionality of the Negative Affective Response scale has been evaluated via both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA):

Exploratory Factor Analysis (EFA)

Principal axis factoring and maximum likelihood extractions with both varimax (orthogonal) and promax (oblique) rotations consistently identify a single dominant factor with an eigenvalue substantially greater than 1.00 (frequently exceeding 3.80). The first factor typically accounts for 62% to 75% of the total variance across the item pool. The scree plot clearly displays a sharp elbow after the initial factor, confirming the unidimensionality of the construct. All six single-word adjectives exhibit robust factor loadings on this single construct, with standardized loadings universally exceeding .70 and frequently surpassing .85.

Confirmatory Factor Analysis (CFA)

Structural equation modeling and CFA substantiate the one-factor measurement model. Fit indices across diverse empirical samples consistently satisfy rigorous psychometric cutoffs (Hu & Bentler, 1999):

• Comparative Fit Index (CFI): .96 to .99
• Tucker-Lewis Index (TLI): .95 to .98
• Root Mean Square Error of Approximation (RMSEA): .038 to .062 (90% CI [.020, .078])
• Standardized Root Mean Square Residual (SRMR): .022 to .039
• Model Chi-Square (χ²/df): Ratios consistently fall between 1.20 and 2.40, indicating acceptable model fit.

Alternative two-factor models (e.g., separating low-arousal dejection from high-arousal irritation) do not yield significant improvements in fit and suffer from high factor inter-correlations (r > .85), thereby supporting the parsimonious, standardized single-factor model.

10. Instrument / Measurement Tool

The Negative Affective Response scale is designed for efficient, low-burden administration in laboratory, online, and field environments:

• Instrument Type: Self-administered state affective rating inventory.
• Item Format: Six single-word emotional adjectives capturing diverse manifestations of negative valence.
• Response Scale: Typically administered using a 7-point Likert scale (1 = “Not at all” to 7 = “Extremely” / “Very strongly”), although 5-point and 9-point numeric variations are also employed in specific experimental contexts.
• Administration Time: Approximately 30 to 60 seconds, minimizing participant fatigue and experimental attrition.
• Scoring Procedure:
  • All six items are scored positively toward the negative construct (no reverse scoring is necessary).
  • An overall Negative Affective Response index is calculated by computing the unweighted arithmetic mean across the 6 items (scores range from 1.00 to 7.00).
  • Alternatively, a sum score (ranging from 6 to 42) can be utilized for structural equation modeling or path analysis. Higher scores signify greater negative affective intensity.

11. Permissions & Fee and Test Year

The operational form of the Negative Affective Response scale was introduced in 2008 in the Journal of Consumer Research by Jennifer Aaker, Aimee Drolet, and Dale Griffin. As an academic psychometric battery published in peer-reviewed scholarly literature, the scale is generally accessible for non-commercial academic, educational, and scientific research without licensing fees, provided appropriate scholarly citation is attributed to the original authors and the journal publication. Commercial applications, proprietary brand tracking, or inclusion within copyrighted commercial diagnostic platforms may require formal permission from the copyright holder (the Journal of Consumer Research / Oxford University Press). Researchers are encouraged to review relevant institutional guidelines and consult the published work for specific experimental implementation details.

12. References

• Aaker, J., Drolet, A., & Griffin, D. (2008). Recalling mixed emotions. Journal of Consumer Research, 35(2), 268–278. https://doi.org/10.1086/588570
• Cacioppo, J. T., & Berntson, G. G. (1994). Relationship between attitudes and evaluative space: A critical review, with emphasis on the separability of positive and negative substrates. Psychological Bulletin, 115(3), 401–423. https://doi.org/10.1037/0033-2909.115.3.401
• Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity. American Psychologist, 54(3), 165–181. https://doi.org/10.1037/0003-066X.54.3.165
• 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
• Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405
• 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