Comparison of affective rating scales and their relationship to variables reflecting food consumption

Autor: Sari Ollila, Sirpa Tuomi-Nurmi, Hely Tuorila, Anna Huotilainen, Nina Urala, Liisa Lähteenmäki
Jazyk: angličtina
Rok vydání: 2008
Předmět:
Zdroj: Tuorila, H, Huotilainen, A, Lähteenmäki, L, Ollila, S, Tuomi-Nurmi, S & Urala, N 2008, ' Comparison of affective rating scales and their relationship to variables reflecting food consumption ', Food Quality and Preference, vol. 19, no. 1, pp. 51-61 . https://doi.org/10.1016/j.foodqual.2007.06.007
Popis: A consumer panel ( n = 669) rated ten familiar and unfamiliar (ethnic, nutritionally modified, functional) foods, with food names as stimuli, using 7 categories for pleasantness (“very unpleasant”–“very pleasant”) and liking (”not at all”–“very much”), reported use frequencies (“never”–“2–4 times a day”) and likelihood of buying (“very unlikely”–“very likely”). On average, pleasantness was rated 0.48 units higher than liking. For well-liked and familiar foods, liking was linearly correlated with pleasantness while, at low levels of affection for unfamiliar foods, the relationship was curvilinear. Gender, education or food orientations (food neophobia, general health interest) did not interact with scale usage. However, older respondents (>55 years) rated pleasantness, on average, similarly to the young, but tended to rate liking lower. For most foods, frequency of use and likelihood of buying were curvilinearly related to affective ratings, the former mainly described by exponential and the latter by cubic equations. On average, linear predictive equations explained 27.8% (pleasantness) or 28.1% (liking) of use frequency, and 29.8% (pleasantness) or 45.2% (liking) of likelihood of buying. Addition of the most appropriate curvilinearity term(s) improved the average prediction 5.9%, 4.3%, 2.3%, and 2.0%, respectively. In conclusion, careful consideration of the instruments is required in the interpretation of affective ratings and their relationship to consumption.
Databáze: OpenAIRE