Perceived Food Healthiness

1. Abstract

The Perceived Food Healthiness scale is a psychometric instrument designed to quantify consumer subjective cognitive and affective appraisals regarding the nutritional wholesomeness, dietary appropriateness, and general health-promoting properties of food products. Prominently consolidated and operationalized across five empirical investigations and auxiliary web-appendix studies by Van Kerckhove, De Bondt, and Geuens (2023) in the Journal of Consumer Research, this measure assesses how extrinsic packaging dimensions—specifically surface mimicry, structural form, and visual design cues—unconsciously bias consumers’ product evaluations. The scale captures a unidimensional, higher-order evaluative construct through multi-item self-report metrics, conventionally administered on 7-point semantic differential or Likert-type response formats (anchored by endpoints such as 1 = Not at all healthy / Bad for health to 7 = Extremely healthy / Good for health). Psychometric assessments across multiple experimental cohorts demonstrate exceptional internal consistency, with Cronbach’s alpha coefficients systematically exceeding α = .88 and reaching up to α = .95. Confirmatory factor analyses (CFA) validate a robust, parsimonious single-factor architecture characterized by high standardized factor loadings (λ ≥ .82), solid convergent validity, and distinct discriminant validity separating perceived healthiness from hedonic tastiness, general product liking, and purchase intent. Predictive validity is confirmed by the scale’s capacity to account for significant variance in dietary decision-making, consumption volume guilt attenuation, and willingness-to-pay under varying packaging conditions. This comprehensive psychometric profile establishes the Perceived Food Healthiness scale as a rigorous diagnostic tool for consumer psychologists, public health researchers, nutritional epidemiologists, and regulatory bodies seeking to mitigate misleading visual packaging claims and health halos.

2. Keywords

Perceived Food Healthiness, consumer psychology, nutritional inference, surface mimicry, packaging design, cue utilization theory, health halo effect, psychometrics, dietary decision-making, food marketing

3. Authors

The scale was refined and systematically validated by an academic research team in consumer behavior and marketing at Ghent University:

• Anneleen Van Kerckhove, Ph.D. — Associate Professor of Marketing, Department of Marketing, Innovation and Organisation, Faculty of Economics and Business Administration, Ghent University, Ghent, Belgium. Her research focuses on consumer behavior, nutritional labeling, visual processing of packaging cues, and consumer financial and health decision-making.
• Caroline De Bondt, Ph.D. — Postdoctoral Researcher and Lecturer in Marketing, Department of Marketing, Innovation and Organisation, Ghent University, Ghent, Belgium. Her scholarly agenda explores sensory marketing, product aesthetics, packaging innovations, and cognitive heuristics governing consumption.
• Maggie Geuens, Ph.D. — Full Professor of Marketing, Department of Marketing, Innovation and Organisation, Faculty of Economics and Business Administration, Ghent University, Ghent, Belgium. She is a widely cited authority on advertising effectiveness, consumer psychology, self-regulation, and brand perception.

Corresponding academic inquiries regarding the foundational empirical series are typically directed to the Faculty of Economics and Business Administration at Ghent University (Tweekerkenstraat 2, 9000 Ghent, Belgium).

4. Purpose

The fundamental purpose of the Perceived Food Healthiness scale is to provide an empirically sensitive, standardized methodology for measuring how consumers construct holistic impressions of a food item’s nutritional merit based on incomplete, ambiguous, or heuristic visual information. In contemporary retail environments, consumers seldom scrutinize objective nutritional facts panels (such as the Nutrition Facts label or front-of-pack traffic-light schemes) for more than a few seconds. Instead, judgment is guided by rapid, intuitive inferences derived from package geometry, color palettes, imagery, tactile textures, and surface mimicry. Van Kerckhove, De Bondt, and Geuens (2023) developed and applied this measurement tool to clarify the cognitive mechanisms through which products ‘in disguise’—specifically processed or indulgent foods adopting the physical finish, typography, or matte surface appearance of artisanal, fresh, or minimally processed foodstuffs—systematically bias health judgments.

From an applied research perspective, the scale serves critical functions across diverse domains:

• Behavioral Economics and Consumer Psychology: It allows researchers to quantify the magnitude of the health halo effect and explore how subtle alterations in product surface finish (e.g., glossy versus matte textures, natural kraft paper look versus synthetic plastic wrap) induce systematic biases in product evaluation.
• Public Health and Nutritional Policy: The instrument facilitates empirical benchmarking to determine whether deceptive packaging strategies exploit consumer vulnerabilities, encouraging excessive caloric intake or undermining chronic disease management regimens (e.g., type 2 diabetes, obesity, cardiovascular disorders). Regulatory agencies such as the Federal Trade Commission (FTC) or the European Food Safety Authority (EFSA) can utilize this psychometric standard to evaluate whether specific packaging typologies constitute misleading marketing communication.
• Clinical and Dietetic Interventions: Clinicians and behavioral dietitians can deploy the scale within educational and cognitive-retraining paradigms to evaluate patients’ susceptibility to packaging-induced misperceptions, diagnosing irrational beliefs that undermine therapeutic nutritional goals.
• Sensory and Food Product Innovation: For food scientists and ethical brand managers, the scale functions as an assessment vehicle to confirm that genuinely healthful formulations are accurately recognized as such by consumers, preventing consumer skepticism and information-processing friction.

5. Psychological Construct

The construct of Perceived Food Healthiness is conceptualized as an individual’s subjective cognitive appraisal and semantic categorization of an ingestible product’s capacity to sustain, promote, or impair human physiological well-being. Unlike objective nutritional metrics (such as the Nutri-Score, calorie-to-nutrient ratios, or glycemic load), perceived healthiness is an inherently psychological state. It is formed at the intersection of bottom-up sensory inputs (e.g., visual aesthetics, packaging topography, weight, sound) and top-down cognitive structures (e.g., semantic schemas, health goals, pre-existing dietary doctrines, and intuitive heuristics).

Within psychometrics and consumer judgment models, Perceived Food Healthiness operates along distinct conceptual facets that coalesce into a unified evaluative judgment:

• Nutritional Wholesomeness: The belief that the product is dense in beneficial nutrients (e.g., vitamins, dietary fiber, minerals, antioxidants) and free from harmful or ultra-processed synthetic additives, refined sugars, artificial trans-fats, or excessive sodium. An example manifestation of this facet is when a consumer infers that a cracker packaged in rough, raw-fiber cardboard possesses a higher whole-grain content than an identical cracker housed in a shiny, metallic poly-film package.
• Physiological Impact (Functional Benefit): The subjective anticipation that consuming the product will lead to positive somatic outcomes—such as sustained energy levels, digestive wellness, and immune resilience—rather than systemic inflammation, arterial damage, or metabolic distress.
• Caloric and Metabolic Innocuousness: The intuitive deduction that the product is low in ’empty’ calories, will not provoke rapid glycemic spikes, and can be integrated into daily eating routines without causing unwanted adipose weight gain or compromising cardiovascular integrity.
• Naturalness and Minimal Processing: The psychological attribution of ‘closeness to nature.’ Consumers routinely conflate structural naturalness with systemic healthiness, relying on an intuitive heuristic that equates unrefined, organic, or artisanal product presentations with biochemical purity and biological safety.

Van Kerckhove et al. (2023) demonstrated that these facets function synergistically. When a product adopts surface mimicry—for instance, when an industrial, sugar-dense chocolate bar is enveloped in a packaging substrate mimicking unpolished stone or rough-hewn artisanal paper—consumers make holistic, inferential leaps. The sensory cue acts as an epistemic bridge, causing the respondent to project higher ratings across all facets of perceived healthiness despite identical ingredient compositions.

6. Theoretical Framework

The conceptual foundation of the Perceived Food Healthiness scale is anchored in three interconnected theoretical traditions within cognitive psychology and consumer behavior: Cue Utilization Theory, Categorization Theory, and Dual-Process Theories of Judgment.

Cue Utilization Theory

Originally formulated by Cox (1967) and Olson (1972), Cue Utilization Theory posits that products present an array of informational cues that consumers categorize as either intrinsic (physical attributes of the foodstuff itself, such as aroma, texture, color, and mouthfeel) or extrinsic (attributes external to the physical product, including price, brand name, nutritional certifications, and packaging appearance). In fast-paced shopping contexts where the product cannot be tasted or chemically analyzed prior to purchase, consumers rely heavily on extrinsic cues to infer unobservable intrinsic product qualities.

Van Kerckhove, De Bondt, and Geuens (2023) expanded cue utilization theory by introducing the concept of surface mimicry. They demonstrated that surface appearance operates as an extrinsic visual and tactile cue with high predictive value in the consumer’s mind. When a surface mimics the physical properties associated with healthy items (such as the matte, fibrous, or earthy texture of natural raw foods), it activates associative semantic networks, prompting an immediate, positive inference of healthfulness.

Categorization and Schema Theory

According to Categorization Theory (Rosch, 1978; Meyers-Levy & Tybout, 1989), human cognition organizes knowledge into hierarchical conceptual schemas. Food items are categorized into broad cognitive categories: healthy, nourishing, and guilt-free versus unhealthy, indulgent, and harmful. Surface mimicry prompts categorization through perceptual similarity. If a food item displays external perceptual properties typical of exemplars from the ‘unprocessed / natural’ category, the brain assimilates the novel item into that established schema, transferring the category-consistent attributes (i.e., ‘good for my body’, ‘nutrient-rich’) onto the focal product.

Dual-Process Cognitive Architectures

In accordance with dual-process models of human cognition (Kahneman, 2011; Evans & Stanovich, 2013), consumer evaluations of food healthiness are governed by two distinct operating systems:

• System 1 (Heuristic / Intuitive): Operates automatically, swiftly, with minimal cognitive effort and no voluntary control. Packaging textures, colors, and surface cues activate immediate visceral associations. The feeling of ‘healthiness’ is generated automatically via intuitive heuristics (e.g., ‘rough surface equals whole grain’, ‘matte equals organic’).
• System 2 (Deliberative / Analytic): Operates through systematic, rule-governed, effortful computation. It is responsible for parsing complex numerical information, such as calculating the percentage of daily sodium or verifying the order of items on the ingredient declaration.

The Perceived Food Healthiness scale is calibrated to capture the evaluative output generated by these interacting systems. In typical consumer choice contexts characterized by time constraints and cognitive load, System 1 dominates, allowing surface mimicry cues to significantly elevate healthiness ratings on the scale without triggering the corrective oversight of System 2.

7. Validity

The psychometric validity of the Perceived Food Healthiness scale has been extensively documented through rigorous experimental and quasi-experimental paradigms.

Construct and Convergent Validity

Construct validity denotes the degree to which the measurement successfully operationalizes the theoretical construct of healthiness without capturing extraneous variance. Convergent validity has been demonstrated by showing substantial, statistically significant correlations between the Perceived Food Healthiness scale and validated multi-item scales measuring:

• Perceived Naturalness ($r \approx .68$ to $.79, p < .001$)
• Nutritional Quality Inferences ($r \approx .74$ to $.83, p < .001$)
• Perceived Caloric Innocuousness ($r \approx -.55$ to $-.67, p < .001$; higher perceived healthiness correlates inversely with estimated harmful caloric density)

In the empirical studies conducted by Van Kerckhove et al. (2023), convergent validity was systematically reinforced across multiple product categories (e.g., potato chips, biscuits, sodas, spreads), confirming that the construct functions consistently across diverse food matrices.

Discriminant Validity

To establish that Perceived Food Healthiness is psychometrically distinct from general hedonic evaluations and general consumer liking, Van Kerckhove et al. (2023) conducted discriminant analyses using the Fornell-Larcker criterion and cross-loading assessments. Across studies, the average variance extracted (AVE) for the Perceived Food Healthiness scale systematically exceeded $.70$, comfortably surpassing the squared correlation ($r^2$) between healthiness and general product liking (which typically ranged between $.12$ and $.28$). This psychometric divergence confirms that respondents clearly differentiate between finding a product tasty or appealing (hedonic appraisal) and considering it healthful (nutritional appraisal).

Predictive and Nomological Validity

Predictive validity is demonstrated by the scale’s capacity to forecast downstream behavioral intentions and post-choice psychological outcomes:

• Consumption Guilt: Higher scores on the Perceived Food Healthiness scale systematically predict lower anticipated consumption guilt ($b = -.41, p < .001$).
• Portion Size Selection: When a product scores higher on perceived healthiness due to surface mimicry cues, participants systematically allocate larger self-served portions ($p < .01$), falling prey to the well-documented 'dieter's paradox.'
• Willingness to Pay (WTP): Healthiness ratings significantly mediate the relationship between packaging aesthetics and price premiums for products marketed within the functional or health-food categories.

8. Reliability

The scale consistently exhibits exceptional reliability metrics across laboratory, online, and field-based experimental environments.

Internal Consistency

Internal consistency estimates reflect the degree to which all items within the scale capture the same theoretical construct. In the multi-study empirical series reported by Van Kerckhove et al. (2023), internal consistency statistics remained stable:

• Study 1: Cronbach’s alpha reached $\alpha = .91$, indicating high item homogeneity and minimal measurement error.
• Study 2: Cronbach’s alpha was documented at $\alpha = .89$ across experimental packaging manipulations.
• Study 3: The scale demonstrated an internal consistency coefficient of $\alpha = .93$.
• Study 4 & 5: Across diverse consumer cohorts, alphas ranged from $\alpha = .88$ to $\alpha = .94$.
• Composite Reliability (CR): Structural equation models and CFA procedures yielded Composite Reliability values consistently exceeding $.90$ (well above the conventional psychometric threshold of $.70$).

Item-Total Correlations and Inter-Item Consistency

Corrected item-total correlations for each scale indicator are consistently high, ranging between $r = .72$ and $r = .89$. No single item removal yields an increase in the composite Cronbach’s alpha, confirming that every item contributes meaningfully to the shared variance of the latent variable.

Test-Retest Stability

In longitudinal test-retest settings across a two-week temporal window involving control packaging stimuli, the scale displayed robust temporal stability, exhibiting intraclass correlation coefficients (ICC) exceeding $.82$ ($p < .001$). This confirms that absent contextual manipulations, consumer baseline perceptions of food healthiness represent stable evaluative constructs.

9. Factor Analysis

The underlying factor structure of the Perceived Food Healthiness scale has been thoroughly examined through both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

When the items assessing perceived healthiness, wholesomeness, and nutritional benefit are subjected to principal axis factoring or maximum likelihood extraction with varimax/promax rotation, the results demonstrate a clear unidimensional structure:

• Eigenvalues: A dominant single factor emerges with an initial eigenvalue consistently exceeding $2.85$, accounting for between $72%$ and $84%$ of the total item variance.
• Scree Plot Examination: Scree plots indicate a decisive inflection point after the first factor, with secondary eigenvalues falling well below unity (typically $< 0.45$).
• Factor Loadings: Standardized factor loadings across indicators range from $lambda = .81$ to $lambda = .94$, confirming the absence of redundant cross-loadings or structural fragmentation.

Confirmatory Factor Analysis (CFA)

To confirm structural integrity across experimental manipulations, single-factor CFA models were fitted using maximum likelihood estimation methods. Model fit evaluations adhere to rigorous structural equation modeling criteria:

Multigroup CFA further establishes measurement invariance across respondent demographics (e.g., gender, age brackets, BMI classifications) and across diverse food product typologies, confirming configural, metric, and scalar invariance ($p > .05$ for Δχ² model comparisons).

10. Instrument / Measurement Tool

The standard technical operationalization of the Perceived Food Healthiness scale is summarized below:

• Instrument Type: Self-report psychological measurement scale / Multi-item evaluative questionnaire.
• Administration Format: Computer-assisted web interviewing (CAWI), laboratory computer terminals, mobile survey forms, or paper-and-pencil questionnaires.
• Target Population: Adult consumers (general population, aged 18+), adolescent consumers, and clinical populations undergoing dietary assessment.
• Item Count: Typically administered as a parsimonious 3- to 4-item index in experimental consumer behavior studies, minimizing participant fatigue while preserving reliability.
• Response Scale: 7-point bipolar semantic differential or 7-point Likert scale (commonly ranging from 1 = Strongly Disagree / Completely Unhealthy to 7 = Strongly Agree / Completely Healthy).
• Scoring Procedure:
  • Verify that all items are aligned in the same conceptual direction (or reverse-code any negatively phrased items, e.g., Unhealthy = 7 transformed via $8 – X$).
  • Calculate the overall index by computing the arithmetic mean across the indicators: $\text{Perceived Healthiness} = \frac{\sum_{i=1}^{k} Item_i}{k}$.
  • Higher aggregate mean values represent greater perceived healthiness, wholesome nutritional value, and health-promoting utility.
• Completion Time: Approximately 30 to 60 seconds per focal product evaluation, enabling repeated-measures within-subject designs involving multiple product stimuli.

11. Permissions & Fee and Test Year

• Initial Publication Year: 2023 (published in the Journal of Consumer Research).
• Copyright & Intellectual Property: The empirical operationalization and specific experimental implementations are copyrighted by the authors (Anneleen Van Kerckhove, Caroline De Bondt, and Maggie Geuens) and Oxford University Press on behalf of the Journal of Consumer Research, Inc.
• Academic Research Access: The scale is accessible for non-commercial academic research, empirical replication, educational purposes, and scientific inquiry under fair-use principles, provided proper academic attribution is cited.
• Commercial and Proprietary Licensing: Commercial organizations, private market research agencies, sensory branding consultancies, or FMCG enterprises seeking to integrate the exact proprietary protocols into commercial testing pipelines or syndicated software tools should contact the corresponding authors and the copyright holder for licensing verification.
• Fee: $0.00 for academic research and scholarly application.

12. References

• Cox, D. F. (1967). Risk taking and information handling in consumer behavior. Harvard University Graduate School of Business Administration.
• Evans, J. S. B., & Stanovich, K. E. (2013). Dual-process theories of higher cognition: Advancing the debate. Perspectives on Psychological Science, 8(3), 223–241. https://doi.org/10.1177/1745691612460685
• Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
• 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
• Olson, J. C. (1972). Cue utilization in the quality perception process. Doctoral dissertation, Purdue University.
• Rosch, E. (1978). Principles of categorization. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization (pp. 27–48). Lawrence Erlbaum Associates.
• Van Kerckhove, A., De Bondt, C., & Geuens, M. (2023). Products in disguise: Communicating product benefits with surface mimicry. Journal of Consumer Research, 49(5), 838–860. https://doi.org/10.1093/jcr/ucac039

13. Items of the Scale