New Food Imagery Scale Measures How Vividly You Can Picture Taste, Smell and Texture

Close your eyes and try to imagine the smell of onions caramelising in a pan, or the exact crunch of a thin-cut potato chip between your teeth. For some people, those mental pictures are startlingly real; for others, they barely register at all. That gap in the mind’s eye has long fascinated psychologists, because mental imagery shapes sensory expectations, cravings, liking and ultimately what and how much we eat. Yet the tools available to measure it have been surprisingly ill-suited to the task. Now, a team of researchers led by Mei Peng of the Sensory Neuroscience and Nutrition Lab at the University of Otago, working with colleagues at the University of Auckland and Charles Spence of the Crossmodal Research Laboratory at the University of Oxford, has built and rigorously tested a purpose-made instrument: the Food Imagery Scale, or FIS, published as an open-access research article in BMC Psychology.

The problem the researchers set out to solve was one of fit. Existing imagery questionnaires tend to be modality-specific, probing only how vividly people visualise objects or conjure smells in isolation, or they rely on generic prompts that were never designed with eating in mind. Food, however, is an inherently multisensory experience. A single bite of chocolate recruits orthonasal smell as the aroma drifts up from the plate, retronasal smell as volatile compounds travel from the back of the mouth, basic taste qualities such as sweetness and bitterness, the mechanical feel of texture, and the visual appearance of the food itself. A measure that captures only one of these channels risks missing the very individual differences that matter most for eating behaviour research, from craving susceptibility to appetite control.

The project began with a preliminary item-generation study designed to identify foods and drinks with distinct, recognisable sensory characteristics. The goal was to source items that would reliably evoke each sensory channel, so that a participant rating their mental image of brewed coffee, for example, would be engaging the olfactory system rather than guessing at a vague, undifferentiated food memory. The final scale asks respondents to imagine 25 items across five domains: smell, flavour, taste, texture and appearance. Each item is rated from zero, meaning no image at all, to ten, meaning an image as clear and vivid as real life. The published version includes prompts such as imagining the smell of freshly baked bread and cinnamon rolls, the flavour of parmesan cheese and dark chocolate, the bitterness of coffee, the sourness of a lemon, ice cream melting in the mouth, and the look of a red apple or a scoop of ice cream.

With the item pool in hand, the team subjected the scale to a four-experiment validation programme involving well over a thousand participants in total. Experiment 1, with 354 participants, used exploratory factor analysis and parallel analysis, two statistical techniques for uncovering the latent structure underlying a set of questionnaire items, to refine the pool and examine internal consistency. The results supported a correlated five-factor solution, meaning the data were best explained by five related but separable dimensions corresponding to the five sensory channels. The fit statistics were strong: a root mean square residual of 0.023, a root mean square error of approximation of 0.065, and a comparative fit index of 0.962, alongside high internal consistency, indicating that items within each factor measured the same underlying trait coherently.

Reliability over time is just as important as internal structure, and here the team turned to Experiment 2. Eighty-three participants completed the scale twice, three to four weeks apart, allowing the researchers to compute a test–retest reliability coefficient. The total score achieved an intraclass correlation of 0.75, with a 95 percent confidence interval ranging from 0.62 to 0.82. In practical terms, this means a person’s standing on the scale is reasonably stable over a month, which is precisely what one would expect if the instrument is measuring a genuine trait, a stable disposition of the mind, rather than a fleeting mood or situational appetite. For a tool intended to characterise individual differences in eating-related cognition, that temporal stability is a foundational credential.

Experiment 3 then put the five-factor structure to a stricter test. Using a new sample of 393 participants, the researchers applied confirmatory factor analysis, a method that tests a predefined structure rather than letting one emerge from the data, and examined correlations with established questionnaires of visual and olfactory imagery vividness. The five-factor structure replicated cleanly, with a chi-squared statistic of 503.15 on 265 degrees of freedom, comparative and Tucker–Lewis fit indices both at 0.998, RMSEA of 0.048 and a standardised root mean square residual of 0.040. The convergent validity results were particularly elegant. The appearance factor correlated most strongly with visual imagery vividness, at a Spearman coefficient of 0.47, while the smell factor correlated most strongly with olfactory imagery vividness, at 0.51, both highly statistically significant. In other words, the food-specific channels behave as they should: they align with their general-domain counterparts without collapsing into them, suggesting the FIS captures something genuinely food-tuned.

The final and arguably most consequential experiment addressed the question that motivated the whole project: does food imagery vividness relate to actual eating-related tendencies? Experiment 4 recruited 781 participants and examined criterion-related associations with trait food craving, the dispositional tendency to experience intense desires for specific foods. After adjusting for covariates, the researchers found small but reliable positive associations for two of the sensory channels. Smell imagery vividness correlated with trait food craving at r = 0.110, significant at p = 0.002, and flavour imagery showed an association of r = 0.080, significant at p = 0.026. The effect sizes are modest, as is typical for single-trait predictors of complex behaviour, but their pattern is telling: the chemosensory channels, smell and flavour, the ones most intimately tied to the reward and pleasure of eating, are the ones that link to craving.

That pattern has intriguing implications. Flavour, as the scale clarifies for respondents, refers to the combined in-mouth experience arising primarily from taste and retronasal smell, distinct from the basic taste qualities of sweetness, sourness, saltiness, bitterness and umami. If people who more vividly imagine smells and flavours also report stronger trait cravings, vivid multisensory imagery may act as a kind of mental rehearsal of eating, priming desire before any food is present. This connects to a broader literature in which imagery is understood to function as a weak form of perception, recruiting overlapping neural machinery. It also opens practical questions for interventions: if imagery vividness shapes craving, techniques that modulate imagery, from vividness training to competing-task strategies that load the sensory systems and blunt craving episodes, could be tailored according to an individual’s FIS profile.

The authors are careful about the boundaries of what they have established. They note that future work should establish the scale’s incremental predictive validity, that is, whether it predicts eating outcomes better than general imagery measures already exist, and should test its cross-cultural generalisability, since foods like miso soup, soy sauce and roast dinners carry very different familiarity across populations, and food familiarity is known to shape both imagery and craving. The project was funded by a grant from the Royal Society of New Zealand through the Marsden Fund, with the design, conduct, analyses and interpretation conducted independently of the sponsor, and the work received ethics approval from the University of Otago Human Ethics Committee.

Even with those caveats, the arrival of a reliable, food-specific, multisensory imagery measure is a notable addition to the psychologist’s toolkit. For decades, eating behaviour research has had to borrow instruments built for other purposes, averaging across senses that food never treats separately. The FIS treats the imagined meal as what it actually is, a symphony of smell, flavour, taste, texture and sight, and offers researchers a way to ask not just whether a person thinks vividly, but whether their culinary imagination in particular runs hot. Given the scale’s documented psychometric credentials across four experiments and more than 1,600 participants, and its open-access availability, it seems likely to find its way into studies of craving, dietary choice, appetite and sensory science for years to come.

Subject of Research: Development and validation of a self-report scale measuring trait vividness of multisensory food imagery for eating behaviour research

Article Title: Developing and validating the Food Imagery Scale: a trait measure of multisensory food imagery for eating behaviour research

Article References: Peng, M., McCormack, J., Golo, S., Hames, M., Roberts, R., & Spence, C. (2026). Developing and validating the Food Imagery Scale: a trait measure of multisensory food imagery for eating behaviour research. BMC Psychology. https://doi.org/10.1186/s40359-026-05526-x

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05526-x

Keywords: mental imagery, food imagery, eating behaviour, food craving, psychometrics, sensory perception, flavour, olfaction, questionnaire validation, BMC Psychology, Developing, validating