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Just About Right Scales

Last modified at 2/2/2021 3:28 PM by Maren Johnson
Just about right (JAR) scales measure the appropriateness of the level of a specific attribute, and are used to determine the optimum levels of attributes in a product1. In consumer testing of packaged goods, consumers are often asked whether a sensory characteristic of a product (e.g., saltiness) is too high, too low, or just about right. Such “attribute diagnostics” are included to assist researchers in understanding why consumers like or dislike a product and to guide product development efforts aimed at increasing consumer acceptability.
While there are many variations of JAR scales, such scales typically consist of five or seven points, ranging from too little to too much for a given characteristic2. One end point is labeled as “much too little”, the other end point as “much too much” and the middle point as “just right” or “just about right”3. There are many variations of JAR scales. The most prevalent for is a 5 point category scale where categories are labeled (e.g. not nearly salty enough, not salty enough, just about right, too salty, much too salty). However, an unstructured line scale anchored with “not nearly sweet enough” at the left, “just right” at the center, and “much to sweet” at the right was used to optimize sweetness in lemonade4,5.
Although JAR scales have been criticized on several grounds, including that these diagnostic questions place too great a demand on consumers to know what they ideally would like and that consumers have to have a consensus understanding of the attributes in question1, they continue to be extremely popular, both among sensory and market research professionals. The JAR and hedonic scales information can be combined to provide directional information for product reformulation or optimization, but analysis of the JAR data can pose some problems. A Combination of the Stuart-Maxwell frequency test and the McNemar test for JAR data has been recommended to test difference between products1. A popular way of data interpretation is given by Penalty Analysis.


1 Lawless HT, Heymann H 1998. Sensory evaluation of food: principles and practices. Aspen Publishers, Inc. Gaithersburg, Maryland.
2 Meullenet JF, Xiong R and Findlay C. 2007. Multivariate and probabilistic analyses of sensory science problems. 256p. IFT Press. Blackwell Publishing, Ames, IA.
3 Anon. 2003. Triangle plots: graphic display of “Just right” scale data. Research on Research 56.
4 Johnson L and Vickers Z 1987. Avoiding the centering bias or range effect when determining an optimum level of sweetness in lemonade. Journal of Sensory Studies. 2(4):283-292.
5 Vickers Z 1988. Sensory specific satiety in lemonade using a just right scale for sweetness. Journal of Sensory Studies. 3(1):1-8.

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