Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire

1. Abstract

The Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire (Peterson & Malhotra, 2023) is a specialized psychometric assessment instrument developed to evaluate consumer cognition, categorization judgments, and affective processing dynamics in response to television commercial executions. Rooted in cognitive categorization theory (Rosch, 1975) and schema congruity models within marketing psychology (Goodstein, 1993; Loken & Ward, 1990), this comprehensive measurement system operationalizes the psychological mechanisms through which an advertisement’s perceived typicality or atypicality governs viewer attention, cognitive elaboration, emotional experience, and brand attitude formation. The scale was established and empirically tested across multiple independent studies involving cross-national consumer cohorts, including rigorous back-translation validation into Russian to ensure cross-cultural semantic equivalence and measurement invariance.

The instrument comprehensively captures multidimensional facets of consumer advertising processing, spanning prior category expectations (positive and negative feeling expectations, ad theme expectations), perceived category congruity (ad match, typicality, representativeness), creative execution appraisals (novelty, uniqueness), viewer processing effort (cognitive elaboration, attention allocation, comprehension effort), and downstream evaluative reactions (ad-evoked positive and negative affect, overall attitude toward the ad [Aad]). Psychometric evaluations demonstrate strong internal consistency across constructs, with Cronbach’s alpha coefficients uniformly exceeding the .76 threshold, reaching upward of .88 on core dimensions. Test-retest reliability over a 60-day interval confirms longitudinal stability, demonstrating stability coefficients averaging .50 for Ad Theme Expectations and .51 for Ad Feelings Expectations (.54 for positive feelings and .44 for negative feelings).

Confirmatory factor analyses (CFA) employing maximum likelihood estimation substantiate the multidimensional architecture of the measurement model, demonstrating that each latent factor explains more than 54% of its indicator variance, with exceptional goodness-of-fit indices (Comparative Fit Index [CFI] = .98, Tucker-Lewis Index [TLI] = .97, and Root Mean Square Error of Approximation [RMSEA] = .07). Nomological and construct validity analyses demonstrate that positive ad-evoked feelings exert a robust positive influence on overall attitude toward the ad (β = .34), whereas negative ad-evoked feelings exert a pronounced negative influence (β = -.26), with cognitive appraisals of social approval motivation contributing significantly (β = .16). Harman’s single-factor diagnostic and confirmatory factor tests confirm that common method variance does not distort parameter estimations. The questionnaire provides an empirically rigorous foundation for consumer psychologists, advertising researchers, and media strategists evaluating the cognitive and emotional processing trajectories elicited by creative broadcast campaigns.

2. Keywords

Ad Typicality, Category Congruity, Schema Incongruity, Creative Advertising Processing, Television Commercial Evaluation, Cognitive Elaboration, Ad-Evoked Feelings, Attitude toward the Ad, Consumer Categorization, Nomological Validity, Psychometric Scale Validation, Advertising Processing Model.

3. Authors

The Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire was formulated, refined, and validated by distinguished scholars in consumer research, marketing strategy, and applied psychometrics:

• Mark Peterson, Ph.D. — Professor of Marketing, whose scholarly investigations center on consumer well-being, marketing communications, sustainable consumption, and international advertising effectiveness.
• Naresh K. Malhotra, Ph.D. — Regents’ Professor Emeritus of Marketing, Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia, United States. Dr. Malhotra is an internationally recognized authority in marketing research methodology, multivariate psychometric modeling, and consumer decision-making. (Email: [email protected]; Correspondence Address: Georgia Institute of Technology, Scheller College of Business, Atlanta, Georgia, United States).

4. Purpose

The primary purpose of the Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire is to provide an empirically validated, theoretically grounded diagnostic tool for measuring how consumers form typicality judgments regarding television advertisements and how these cognitive appraisals dictate cognitive processing depth, affective responses, and evaluative attitudes toward the communication. In modern media environments, television advertisements frequently balance conventional category conventions against creative, unconventional creative executions. While standard executions provide familiar category cues that facilitate immediate schema confirmation, creative executions deliberately violate category conventions to capture viewer attention and disrupt routine processing. Until the development of this unified instrument, marketing psychology lacked an integrated measurement model that linked category-level affective and thematic expectations directly to in-situ ad-evoked experiences and cognitive elaboration metrics.

From an applied research and marketing perspective, the instrument serves several pivotal diagnostic functions:

• Quantifying Category Expectation Baselines: The scale enables investigators to systematically measure prior expectations that consumers hold concerning specific product categories, including the emotional tone (positive vs. negative feeling expectations) and thematic executions (such as physical attractiveness, fun, or functional utility) typically found within commercial broadcasts.
• Assessing Degree of Schema Incongruity: By capturing explicit judgments of ad typicality, representativeness, similarity, and match, the instrument quantifies the exact degree to which a creative commercial aligns with or departs from established product-category exemplars.
• Tracking Cognitive Processing and Elaboration: The questionnaire captures the cognitive effort expended by the viewer, operationalized through self-reported attention allocation, depth of message thought, and comprehension effort required to resolve novel or ambiguous narrative executions.
• Disentangling Affective Trajectories: The model isolates ad-evoked emotional reactions (both positive vitality/cheerfulness and negative skepticism/irritation) from baseline category expectations, enabling researchers to determine whether creative atypicality fosters engagement or triggers cognitive friction and consumer skepticism.
• Evaluating Downstream Communicative Effectiveness: The instrument facilitates path-analytic modeling toward key marketing outcomes, specifically the global Attitude toward the Ad (Aad), which operates as a primary mediating determinant of brand recall, brand attitude, and purchase intentions.

In theoretical and academic research, the questionnaire addresses long-standing questions regarding how schema congruity influences message elaboration. According to Mandler’s (1982) schema congruity framework, moderate schema incongruity stimulates cognitive elaboration and yields positive affective rewards upon cognitive resolution, whereas extreme incongruity may produce cognitive overload, negative affect, and message rejection. By providing granular metrics for typicality, novelty, cognitive effort, and affective balance, this questionnaire equips behavioral researchers with the psychometric precision necessary to empirically map non-linear relationships across advertising environments.

5. Psychological Construct

The psychological architecture measured by the questionnaire captures a sequential, multi-stage information processing network. The instrument breaks down advertising reception into several distinct, intercorrelated psychological constructs:

Category-Level Affective and Thematic Expectations

Before exposure to a specific stimulus, consumers maintain cognitive schemata regarding what constitutes a standard commercial within a given product category (e.g., compact automobiles, financial services, consumer packaged goods). The model delineates three distinct expectation constructs:

• Positive Feeling Expectations: The normative emotional tone consumers expect to experience when viewing commercials within the focal category, measuring dimensions such as vitality, vigor, and cheerfulness (e.g., expecting an automotive ad to be uplifting and dynamic).
• Negative Feeling Expectations: The anticipatory negative affect or consumer defense mechanisms habitually activated within the category, measuring skepticism, critical evaluation, and suspicion regarding commercial claims.
• Theme Expectations (Attractiveness / Social Imagery): The extent to which consumers expect advertisements in the category to leverage specific executional appeals, such as physical attractiveness, sensual aesthetic design, lifestyle prestige, or entertainment value.

Ad Typicality and Category Congruity

Upon viewing a specific commercial, consumers make spontaneous categorization appraisals comparing the perceived stimulus against category prototypes and memory-stored exemplars:

• Ad Typicality and Representativeness: The degree to which the target commercial is perceived as representative, normative, or typical of advertising executions within the product category. Highly typical ads readily conform to existing category norms, whereas atypical executions depart sharply from expected conventions.
• Ad Match: An explicit cognitive judgment assessing whether the brand depiction, underlying narrative themes, and emotional experience delivered by the specific commercial correspond with prior category expectations. When ad match is low, cognitive dissonance or perceived novelty is triggered.

Creative Execution Appraisals

Closely linked to atypicality is the perceived creativity of the commercial execution. Creativity in advertising psychometrics requires both divergence (novelty) and meaningful relevance:

• Novelty and Uniqueness: The perceived freshness, originality, and unconventional nature of the creative approach, measuring whether the execution diverges from formulaic industry approaches.

Cognitive Processing Effort (Elaboration)

When an advertisement diverges from normative expectations, consumers cannot rely on passive, heuristic processing. Instead, atypicality triggers active cognitive processing:

• Attention Allocation: The conscious focusing of perceptual and cognitive resources onto the television commercial during exposure.
• Message Elaboration (Thought Depth): The extent to which the viewer generates active cognitive thoughts, counterarguments, or associative connections concerning the commercial’s thematic proposition.
• Comprehension Effort: The subjective cognitive strain or problem-solving effort expended to decipher the narrative structure, humor, metaphor, or conceptual punchline of the commercial execution.

Ad-Evoked Affect and Attitude toward the Ad (Aad)

Processing trajectories culminate in immediate affective and evaluative end-states:

• Ad-Evoked Positive Feelings: Discrete positive emotional states generated in direct response to the commercial (e.g., feeling active, cheerful, alive).
• Ad-Evoked Negative Feelings: Discrete negative affective responses provoked by the commercial execution, including irritation, annoyance, suspicion, or critical skepticism.
• Ad Motivation (Social Approval Cognitions): Specific cognitive inferences regarding whether owning or using the advertised brand satisfies psychological needs for social status, peer acceptance, and impression management.
• Attitude toward the Ad (Aad): A global, enduring evaluative predisposition toward the commercial execution, characterized by overall favorability, liking, and perceived commercial quality.

6. Theoretical Framework

The Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire is theoretically grounded at the intersection of cognitive psychology, social categorization theory, and advertising information processing models.

Cognitive Categorization and Prototype Theory

The foundation of the typicality construct stems from Eleanor Rosch’s prototype theory of cognitive categorization (Rosch, 1975). According to prototype models, cognitive categories (such as “compact car television advertisements”) are not organized around rigid, binary logical rules; rather, they are structured around a central prototype or a collection of salient exemplars that exhibit family resemblance. Category members vary along a continuous spectrum of typicality or graded category membership. In consumer psychology, Loken and Ward (1990) established that typicality judgments strongly govern consumer preferences, cognitive accessibility, and recall.

Building on these categorization foundations, Goodstein (1993) demonstrated that consumers hold well-defined cognitive schemas for television commercials across specific product categories. When an ad contains executional cues (e.g., standard voiceover, predictable demonstration, familiar product setting) that match the prototype, typicality ratings are high, allowing consumers to process the advertisement through top-down, schema-driven heuristic pathways. When executional cues deviate, the commercial is appraised as atypical, disrupting automatic cognitive processing and compelling bottom-up, data-driven processing.

Schema Incongruity and Processing Elaboration

The processing dynamics captured by the questionnaire are guided by Mandler’s (1982) schema congruity theory, further refined within consumer behavior by Meyers-Levy and Tybout (1989). Mandler posited that when an incoming stimulus perfectly conforms to an activated schema (congruity), cognitive processing proceeds effortlessly, resulting in mild, predictable positive affect but low cognitive elaboration. When a stimulus deviates moderately from expectations (moderate incongruity), it triggers cognitive arousal and a conscious search for meaning. If the individual successfully resolves the incongruity (e.g., understanding the unexpected creative twist or metaphorical humor in an automobile commercial), the cognitive resolution yields psychological pleasure and intense positive affect.

However, when an advertisement presents severe incongruity that cannot be assimilated into existing schemas, the cognitive system experiences cognitive overload, leading to frustration, skepticism, and negative affective reactions. The Peterson and Malhotra (2023) measurement model captures this delicate interplay by simultaneously measuring perceived typicality, cognitive effort (attention, thought depth, comprehension effort), and discrete affective reactions.

The Dual-Mediation and Affective Response Paradigms

The model incorporates the Elaboration Likelihood Model (Petty & Cacioppo, 1986) and dual-mediation models of advertising effectiveness (MacKenzie, Lutz, & Belch, 1986). In high-elaboration scenarios stimulated by creative atypicality, both cognitive responses (social approval motivation cognitions) and affective responses (positive vs. negative ad-evoked feelings) directly determine Attitude toward the Ad (Aad). The theoretical paradigm recognizes that affect is not a unidimensional continuum, but rather comprises distinct positive and negative emotional subsystems that can operate concurrently (Watson, Clark, & Tellegen, 1988). By separating expectations from actual ad-evoked emotions, the framework isolates the net change in affective states produced by creative television advertising executions.

7. Validity

The psychometric integrity of the Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire was rigorously validated across three empirical studies by Peterson and Malhotra (2023), confirming robust construct, convergent, discriminant, and nomological validity.

Convergent and Discriminant Validity

Construct validity was established following the classical multitrait-multimethod principles formalized by Campbell and Fiske (1959) and the modern variance-extracted criteria outlined by Fornell and Larcker (1981):

• Convergent Validity: In confirmatory factor analytic models, all standardized factor loadings were statistically significant (p < .001), with each latent construct accounting for more than 54% of its corresponding indicator variance (average variance extracted [AVE] > .54), meeting and surpassing recommended thresholds (Hair et al., 2019).
• Discriminant Validity: Discriminant validity among the latent constructs was demonstrated by confirming that the squared correlation between any pair of constructs was substantially smaller than the average variance extracted by each individual construct. In addition, the constructs of Feeling Expectations (anticipatory baseline) and Ad-Evoked Feelings (in-situ response) demonstrated clear empirical separation despite sharing semantic descriptors, confirming that participants accurately differentiated between their general expectations of television advertising and their immediate emotional responses to the viewed commercial.

Nomological and Predictive Validity

Nomological validity was empirically demonstrated through structural equation modeling, testing the theoretical linkages among typicality judgments, cognitive appraisals, emotional experiences, and evaluative outcomes:

• Positive Ad-Evoked Feelings → Attitude toward the Ad: Demonstrating powerful nomological alignment, positive ad-evoked feelings exerted a substantial and statistically significant positive contribution to Attitude toward the Ad (β = .34, p < .01).
• Negative Ad-Evoked Feelings → Attitude toward the Ad: Conversely, negative ad-evoked feelings (critical skepticism, suspicion) exerted a pronounced negative impact on Attitude toward the Ad (β = -.26, p < .01).
• Advertising Cognition (Social Approval Motivation) → Attitude toward the Ad: In support of cognitive response theory, cognitive appraisals that the advertised brand satisfies social approval motives contributed positively and significantly to Attitude toward the Ad (β = .16, p < .05), directly replicating foundational findings by Peterson and Malhotra (1998).

Common Method Variance (CMV) Diagnostics

Because multiple constructs were collected via self-report within identical testing sessions, common method variance was rigorously tested using Harmon’s one-factor test as well as confirmatory multi-trait tests (Podsakoff & Organ, 1986). In tests evaluating Positive and Negative Feeling Expectations alongside Ad-Evoked Feelings, an unconstrained single-factor model demonstrated unacceptable fit, whereas a multi-factor specification consistently extracted distinct, clean factors with no excessive cross-loadings. Feeling expectation items loaded exclusively onto expectation factors, and ad-evoked items loaded cleanly onto emotion factors, confirming that CMV did not compromise parameter validity.

8. Reliability

The reliability of the Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire has been corroborated through evaluations of both internal consistency and temporal test-retest stability across multiple independent validation samples.

Internal Consistency Reliability

All latent constructs within the measurement model demonstrate robust internal consistency. Across empirical studies, Cronbach’s alpha coefficients uniformly surpassed the conventional .70 psychometric standard (Nunnally & Bernstein, 1994):

• Positive Feeling Expectations: α ≥ .76
• Negative Feeling Expectations: α ≥ .78
• Theme Expectations (Attractiveness): α ≥ .79
• Ad Match / Typicality Subscale: α ≥ .82
• Positive Ad-Evoked Feelings: α ≥ .84
• Negative Ad-Evoked Feelings: α ≥ .81
• Ad Motivation (Social Approval Cognitions): α ≥ .83
• Attitude toward the Ad (Aad): α ≥ .88

Composite reliability (CR) indices calculated within confirmatory factor modeling frameworks similarly ranged from .80 to .91, indicating that indicator variables uniformly capture their designated latent constructs with minimal measurement error.

Test-Retest Reliability and Temporal Stability

A critical psychometric hallmark of the model is its demonstration of temporal stability for category-level expectation schemas. In a 60-day longitudinal retest study conducted among consumer cohorts, the average Pearson correlation coefficient confirmed significant temporal consistency:

• Ad Theme Expectations: r = .50 (p < .001) over a 60-day interval.
• Ad Feelings Expectations: r = .51 (p < .001) overall; with positive feeling expectations demonstrating r = .54 (p < .001) and negative feeling expectations demonstrating r = .44 (p < .001).

These longitudinal correlations confirm that product-category advertising schemas represent relatively enduring cognitive structures in consumer semantic memory, providing a dependable baseline against which specific television commercials are evaluated.

9. Factor Analysis

The structural dimensionality of the questionnaire was examined through both exploratory factor analysis (EFA) during preliminary calibration phases and confirmatory factor analysis (CFA) for formal structural testing, adhering to rigorous psychometric best practices (Gerbing & Anderson, 1988; Hair et al., 2019).

Confirmatory Factor Model Structure

Confirmatory factor models were estimated using maximum likelihood parameter estimation in LISREL and AMOS. In accordance with Gerbing and Anderson’s (1988) two-step modeling procedure, the measurement model was evaluated independently of the structural path model to establish unidimensionality for each hypothesized construct. Each indicator loaded cleanly and significantly on its assigned factor, with standardized factor loadings ranging from .68 to .92 (p < .001). Furthermore, each latent construct accounted for more than 54% of the total variance in its respective indicator set, confirming strong factor extraction and indicator convergence.

Model Fit Indices

The goodness-of-fit evaluation revealed that the measurement model conformed exceptionally well to the empirical covariance matrix across independent participant samples. Key goodness-of-fit statistics include:

• Comparative Fit Index (CFI): .98 (exceeding the conventional .95 threshold for exemplary model fit).
• Tucker-Lewis Index (TLI / NNFI): .97 (confirming outstanding relative fit compared to the null baseline model).
• Root Mean Square Error of Approximation (RMSEA): .07 (90% confidence interval: [.054, .082]), falling comfortably within the recognized acceptable range (≤ .08) for well-fitting psychometric models.
• Standardized Root Mean Square Residual (SRMR): .048 (well below the .08 cutoff, indicating minimal residual error).

Alternative nested structural specifications (such as collapsing positive and negative affect into a single bipolar factor or collapsing category expectations and ad-evoked experiences into singular dimensions) yielded statistically significant degradations in Chi-square (Δχ² tests, p < .001) and poor fit indices, confirming the theoretical and empirical necessity of the multi-factor, dual-system structure.

10. Instrument / Measurement Tool

The instrument is structured as a multidimensional self-report inventory suitable for laboratory experiments, media testing panels, and consumer surveys. A concise technical overview of the measurement tool is presented below:

• Instrument Name: Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire
• Test Type: Multi-item Self-Report Survey / Experimental Measurement Battery
• Total Number of Items: 14 core processing and evaluative items (augmented by 8 category-expectation baseline indicators)
• Administration Format: Paper-and-pencil, computer-assisted personal interviewing (CAPI), or web-based online survey platforms
• Target Population: General consumer adult population (ages 18 and older, including young adults 18–29)
• Available Languages: English, Russian (validated via rigorous back-translation and cross-cultural consensus procedures)
• Core Dimensions / Subscales:
  • Ad Typicality & Category Congruity: Evaluates perceived typicality, representativeness, similarity, and ad match (Items 1–5).
  • Creative Execution & Novelty: Evaluates perceived creativity, novelty, and uniqueness (Items 6–8).
  • Cognitive Processing Effort (Elaboration): Captures self-reported attention allocation, depth of thought, and comprehension effort (Items 9–11).
  • Affective Reaction & Attitude toward the Ad (Aad): Measures overall reaction, liking, appeal, and ad-evoked positive/negative emotional tone (Items 12–14).
• Response Scale and Format:
  • The “Ad Match” construct is operationalized using agree-disagree scales.
  • Subscale indicators utilize semantic-differential and anchored bipolar response options spanning 5-point to 7-point formats (e.g., Not at all typical – Very typical, Unfavorable – Favorable).
• Scoring and Computational Rules:
  • Items are grouped into distinct subscales evaluating Ad Typicality, Category Congruity, and Processing Responses (Cognitive Effort, Affective Reaction). Ratings are averaged within subscales.
  • Subscale scores are calculated as the unweighted arithmetic mean of their constituent item ratings. Higher numerical scores reflect higher levels of the respective construct (e.g., higher perceived typicality, greater cognitive elaboration, or more favorable attitude toward the ad).
  • No reverse scoring is applied to standard congruence or positive affect items; negative affect items are computed as an independent negative-feeling index rather than an inverted positive scale.

11. Permissions & Fee and Test Year

The Ad Typicality Judgments and Creative Television Ad Processing–Model Questionnaire was formally published in its validated structure in 2023 by Dr. Mark Peterson and Dr. Naresh K. Malhotra in the International Journal of Advertising.

• Publication Year: 2023
• Copyright & Intellectual Property: Copyright © 2023 Advertising Association; published by Taylor & Francis Informa UK Limited.
• Access Fee: There is no fee required for non-commercial academic research and scholarly educational use. Academic researchers may employ and administer the measurement model without royalty obligations.
• Permissions Information: Researchers planning commercial testing, proprietary advertising tracking, or commercial software integration must contact the publisher (Taylor & Francis / Routledge) or the corresponding author (Dr. Naresh K. Malhotra, Georgia Institute of Technology: [email protected]) to secure formal permissions.

12. References

The conceptualization, development, and validation of the measurement tool are supported by the following foundational academic literature:

• Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. https://doi.org/10.1037/h0046016
• 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
• Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186–192. https://doi.org/10.1177/002224378802500207
• Goodstein, R. C. (1993). Category-based applications and extensions in advertising: Motivating more extensive ad processing. Journal of Consumer Research, 20(1), 87–99. https://doi.org/10.1086/209335
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
• Loken, B., & Ward, J. (1990). Alternative approaches to understanding the determinants of typicality. Journal of Consumer Research, 17(2), 111–126. https://doi.org/10.1086/208542
• 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
• Mandler, G. (1982). The structure of value: Accounting for taste. In M. S. Clark & S. T. Fiske (Eds.), Affect and cognition: The seventeenth annual Carnegie symposium on cognition (pp. 3–36). Lawrence Erlbaum Associates.
• Meyers-Levy, J., & Tybout, A. M. (1989). Schema congruity as a basis for product evaluation. Journal of Consumer Research, 16(1), 39–54. https://doi.org/10.1086/209192
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Peterson, M., & Malhotra, N. K. (1998). Determinants of attitude toward the ad for compact automobile commercials. Journal of Current Issues & Research in Advertising, 20(2), 43–58. https://doi.org/10.1080/10641734.1998.10505082
• Peterson, M., & Malhotra, N. K. (2023). Ad typicality judgments in the processing of creative television ads. International Journal of Advertising: The Review of Marketing Communications, 42(2), 288–316. https://doi.org/10.1080/02650487.2022.2129331
• Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, 19, 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2
• Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. https://doi.org/10.1177/014920638601200408
• Rosch, E. (1975). Cognitive representations of semantic categories. Journal of Experimental Psychology: General, 104(3), 192–233. https://doi.org/10.1037/0096-3445.104.3.192
• 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