understanding mouthfeel attributes: a multidimensional scaling approach

UNDERSTANDING MOUTHFEEL ATTRIBUTES: A MULTIDIMENSIONAL SCALING APPROACH

MARY BERTINO’ and HARRY T. LAWLESSzp3

’Colgate-Palmolive Technology Center 909 River Road

Piscataway, New Jersey 08854

2Department of Food Science, Stocking Hall Cornell University

Ithaca, New York 14850

Received for Publication April 2, 1992

ABSTRACT

Multidimensional scaling (MDS) was used to study qualitative relationships among mouthfeel attributes encountered in oral healthcare products. Similarity estimates were obtained from a rapid sorting task and from painvise similari9 ratings. Configurations were interpreted as suggesting four groupings of oral sensations: numbing, astringency, pain and taste. The pain-associated sensations were further differentiated into thermally related sensations and chemically related sensations in some configurations. Two-dimensional solutions from the sorting task and from group-averaged similarity ratings were similar. Individual dif ferences scaling solutions, however, showed unacceptably high stress in two dimensions, suggesting additional nuances in meaning to individual panelists that were not captured by group-averaged data or by sorting data.

INTRODUCTION

The backbone of sensory product research is the language panelists use to describe a product (Civille and Lawless 1986). Unfortunately, panelists meanings are often unclear. For example, panelists may describe oral healthcare products, such as toothpaste or mouthwash, as “cooling,” “burning,” “tingling,”

T o whom correspondence should be sent.

Journal of Sensory Studies 8 (1993) 101-114. All Rights Reserved. 0 Copyright 1993 by Food & Nutrition Press, Inc. , Trumbull, Connecticut 101

102 M. BERTINO and H.T. LAWLESS

“numbing” and “irritating.” Some mouthfeel attributes are clearly appropriate, such as cooling to describe the effect of menthol. However, some attributes seem inappropriate, such as “numbing” when the product contains no local anesthetic. One way to increase our understanding of panelists’ meanings is to examine the degree to which panelists differentiate among attributes. Multidimensional scaling (MDS) provides one method for assessing semantic relatedness. MDS can pictorially represent the magnitude of differences among attributes. Questions such as the degree to which panelists distinguish between tingling and numbing can be addressed. MDS configurations may reveal how panelists cognitively group attributes and can uncover dimensions along which attribute meanings are similar or different.

In addition, the procedure for collecting MDS data has an advantage when com- pared with other scaling procedures. Output from MDS is based only on the scaled similarities among stimuli. Thus, the dimensions that may help explain the stimulus configurations are revealed. This is in contrast to more typical methods in which the experimenter determines the properties on which the panelists compare stimuli, for example by using only predetermined rating scales.

Data collection methods for MDS vary. In the traditional method, panelists judge the similarity of each pair of stimuli. This task can quickly become un- wieldy since it requires n(n-1)/2 ratings where n = the number of stimuli. In an alternative method, panelists sort stimuli into groups based upon the perceived similarity of the stimuli (Rosenberg et al. 1968; Rosenberg and Kim 1975). This task requires much less time than pairwise similarity ratings. Similarity can then be inferred from the degree to which stimuli are sorted into the same groups. Such data are necessarily group-derived, i.e., the individual patterns are not analyzable. Unfortunately, the validity of this procedure is not well-established and its relationship to the traditional pairwise similarity scaling is not well- understood (Davison 1972). For these reasons it has been used infrequently, although there has been some recent interest in sorting for qualitative analysis of highly fatiguing stimuli such as odors (Lawless 1989; Lawless and Glatter 1990).

This study had two objectives: To use MDS to increase understanding of mouthfeel attributes of oral healthcare products, and to determine whether two methods of collecting MDS data, sorting and pairwise similarity ratings, give similar results.

MATERIALS AND METHODS

Subjects

Sixty-eight employees at the Colgate-Palmolive Technology Center (35 females, 33 males) volunteered. Average age was 33 i: 6.2 (s.d.) years for the females

MULTIDIMENSIONAL SCALING OF MOUTHFEEL ATTRIBUTES 103

and 36 7.2 years for the males. The first language learned was English for 63 panelists, Polish for two and Greek, German and Tagalog for one each. All were fluent in English, having spoken it for a minimum of 15 years. As incen- tives, panelists were each given products after participating in each session.

Procedure

Panelists participated in 3 tasks in the following order: sorting of mouthfeel attributes, pairwise similarity ratings of the attributes, and ratings of each attribute on property scales.

Sorting Task. Each panelist was given a pack of 2 1 cards with one of the following words typed on each: anesthetizing, astringent, biting, bitter, burning, cooling, drying, hot, irritating, metallic, numbing, pricking, puckering, salty, sharp, sour, spicy, stinging, swelling, tickling and tingling. These attributes described common sensations in the mouth from oral healthcare products and were selected from a list generated by previous panelists. Several attributes of interest to the authors were added. The panelists were asked to sort the 21 cards into piles using the following instructions:

You will be given a pack of 21 cards with a different word typed on each. Each word describes a sensation in the mouth. Your task is to sort the 21 cards into piles based on perceived similarity of word meaning. Words with similar meanings are put into the same piles; words with different meanings are put into different piles. You may use a minimum of 2 piles and a maximum of 21 piles, and you may have from 1 to 20 words in a pile. There are no right or wrong answers. Two words that are very similar to one person may be quite different to another. Both results are important. We are interested in finding out how you as an individual compare these words.

While you are sorting, keep the words face up on the desk. As you put each card in a pile, place it next to (not on top ot) the previous card in the pile.

You may change your assignments of words to piles at any time. The numbers on the backs of the cards are for identification purposes and should not be used in making your sorting judgments.

The entire task took approximately 5 to 15 min.

Pairwise Similarity Ratings. Panelists rated the similarity of the oral sensations described two at a time using a 100 mm line scale with the words “exact same” at one end and “most different” at the other end. Panelists completed a practice similarity task. They were then given a book which had one of the 210 pairwise comparisons on each page. they were given the following instructions for the similarity task (modified from Schiffman et ul. 1981):


You will be given pairs of words that describe sensations in the mouth. Dur- ing this experiment you will judge the similarity or dissimilarity of each pair of sensations. Your will indicate the similarity or dissimilarity of each pair of sensations by marking a form containing line scales. Each scale has the words “exact same” at one end and “most different” at the other. If you find no difference between the two sensations described, use the end near “exact same.” If you find there is a difference, use the part of the scale that best describes the magnitude of that difference. “Most different” should be judged in reference to the complete set of sensations you will be comparing for us. You will have an opportunity to review the words before you begin rating the similarity of the sensations.

People judge sensations in different ways. Thus, there are no right or wrong answers. Two sensations that are very similar to one person may be quite different to another. Both results are important to us. We are interested in finding out how you as an individual compare these sensations.

Panelists were allowed to take the book back to their work station and completed it as time allowed. The entire task took approximately 1 to 1 % h. After they finished, each line rating was measured and recorded.

Property Scale Ratings. Panelists rated mouthfeel attributes on nine 100 rnm bipolar scales: strong-weak, sharp-dull, warm-cold, simple-complex, steady- intermittent, irritating-soothing, painful-not painful, pleasant-unpleasant, and appropriate-inappropriate in a dentifrice. Panelists were given the following instructions:

You will be presented with 21 words which describe sensations in the mouth. Your final task is to rate each sensation on several line scales. For each scale, use a sharp pencil and place a single, thin slash (NO X’s OR CHECKS) at the point which you think best describes that sensation. Be sure to mark each line once and do not leave any unmarked. The numbers on the pages are for identification purposes and should not be used in making your rating judgments. Remember, if you have any questions, ask the study monitor now. If not, complete the first page and then show it to the monitor. She will review if and if it is satisfactory she will instruct you to continue.

Panelists took the book back to their work station and completed it as time allowed. The entire task took approximately % h. After they finished, each line rating was measured and recorded.

Analysis

Sorting data were tabulated for each possible pair of attributes. The number of times each pair of attributes was sorted into the same group was summed separately for males, for females, and then for the combined groups. These data

MULTIDIMENSIONAL SCALING OF MOUTHFEEL ATTRIBUTES I 05

were analyzed as similarity estimates by the SYSTAT (Macintosh Version 5.1) MDS module for nonmetric multidimensional scaling (a Kruskal-Shepard- Torgerson-Young method), using the option for minimizing Kruskal’s stress For- mula 1 (Wilkinson 1989). Cluster analysis was also performed on the coordinates from the SYSTAT sorting solution (Euclidean Distance, Average Linkage o p tion in SYSTAT Cluster module). Similarity ratings for males and females were analyzed separately using the INDSCAL options of ALSCAL of SAS. Similarity tatings were also averaged for each stimulus pair for males and females separately and analyzed using the nonmetric option on the SYSTAT MDS module. To aid in interpretation, property scale ratings were regressed against the coordinates of the sorting and similarity rating configurations in order to plot the best fitting vectors in the MDS solutions. The regression produces direction cosines from the regression coefficients that determine optimal placement of vectors in the configuration so that perpendiculars dropped from points to the vector are maximal- ly correlated with the mean scale values on those attributes. Further details of this application of multiple regression can be found in Schiffman d al. (1981) and in Kruskal and Wish (1978).

RESULTS

Sorting

The interpoint distance correlation of male and female two-dimensional solutions was 0.88, and therefore they were combined in all further analyses. Stress values in the combined maleifemale sorting configurations were 0.14 for the two dimensional configuration and 0.08 for the three dimensional configuration. Since the three dimensional configuration did not greatly improve stress values, nor ease interpretation of the configurations, further analysis was performed on the two dimensional configurations only. Figure 1 shows the SYSTAT two dimensional configuration from the sorting task for the combined group.

The configurations from the sorting task showed several word groups: words describing tastes, words describing numbing and sensations associated with numbing, words describing sensations associated with astringency, and words describing hot and painful sensations. These groupings were reinforced by the cluster analysis (Fig. 2). Words for tastes are on a branch separate from those describing oral tactile attributes. In addition, the cluster analysis suggests two subgroups to the pain words, one with a more unpleasant component than the other. While the interpretation of groups is somewhat subjective, these groupings are reasonable in light of previous literature on taste descriptions (Bartoshuk 1978), astringency theory (Lee and Lawless 1991) and tactile and painful sensations (Melzack 1973;

106

0.5 -

.0.5 -

M. BERTINO and H.T. LAWLESS

SORTING SOLUTION COMBINED GROUPS

K I T 0

0 SHARP a 0

PRICK BrrlNG 0 SALTY

TICKLE TINGLE 0

0 METALLIC

0 ASTRINGENT ANESTH. 8 NUMB 0 B I T E R

CcCwGd @. O S a R DRY WCKERY

-1.5 ! I I

-2.5 -1 .5 -0.5 0.5 1.5

SYSTAT DIMENSION 1

5

FIG. 1. SYSTAT NONMETRIC MDS TWO-DIMENSIONAL SOLUTION FOR SORTING DATA, MALES AND FEMALES COMBINED

Stevens and Green 1978). The groupings suggested by the cluster analysis are superimposed on the MDS configuration from sorting in Fig. 3 .

The ratings of the words on the property scales were regressed against the coordinates of each point for the sorting solutions (Fig. 4). Significant correlations were obtained for strong-weak, sharp-dull, warm-cold, irritating-soothing, painful- not painful, and appropriate-inappropriate, suggesting potential interpretations of the configuration with these word pairs. One possible interpretation is that the vectors form two clusters, differing by about 45 degrees: a temperature/pain axis (perhaps exemplified by not painful and cool vectors) and an intensity/hedonics axis (dull versus unpleasant). These major dimensions are similar to those observed by Clark et al. (1986) for thermal pain from the external skin.

F’airwise Similarity Ratings

The ALSCAL (individual differences option) solutions for the female similarity ratings and the male similarity ratings are shown in Fig. 5 and 6. Due to com-


A’TTRIBUTE: AMALGAMATION DISTANCE

S A L U

MFTALLIC - - - - - - - I

SOUR 3-t- I

PUCKERY -1 I

I

I I I

1 I

- - - - - ASTRINGENT

DRY

I L - I I I I I I I

- I , I I I- I I

NUMBING ANESTHETIZING

COOLING

TINGLING

TICKLING

SWELLING

I

IRRITATING

PRICKING 2

I I I I I I I

- 1

INTERPRETATION:

TASTES

ASTRINGENCY

NU M B IN G

(ASSOCIATED WITH NUMBING)

HOT, TACTILE, UNPLEASANT

BITING

SHARP

SPICY

RG. 2 . CLUSTER ANALYSIS BASES ON MDS COORDINATES FROM SOR- TING SOLUTION

putational limitations, the data for all 68 subjects could not be combined. The average stress values (Kruskal’s Formula 1) were quite high, 0.35 for both males and females. R-squared values were correspondingly low, 0.28 for males and 0.32 for females. Similar poor fits were obtained without the individual differences option, Le., with treatment of each subject’s data matrix as a simple replication. These high stress values suggest the need for additional dimensions when individual data are used, since the additional dimensions might capture important attributes used by individual subjects in this task and would lower stress (improve the fit to data). Alternatively, ALSCAL may not have been able to find sufficiently common patterns to yield any reasonable configurations. The solutions appear somewhat degenerate although the attributes still form similar contiguous groupings as seen in the SYSTAT solutions.


“Astringency”

-1 .5 I

-2.5 0.0 2.5

SYSTAT DIMENSION 1

FIG. 3. CLUSTERS FROM FIG. 2 SUPERIMPOSED ON SORTING CONFIGURATION

Correlations among interword distances, a measure of overall configurational similarity are shown in Table 1. If the solutions are similar, the distance between specific pairs of words in the ALSCAL solution should correlate positively with the distance between the same pairs of words in the SYSTAT solution. This correlation is independent of rotation. The ALSCAL and SYSTAT solutions correlate highly, supporting the impression that the solutions are similar.

In spite of the overall similarity of ALSCAL and SYSTAT solutions, there were a few differences. For example, in the combined sorting solution, “salty,” “dry” and “puckering” had different placements in the similarity and sorting configurations. In the male similarity configuration, “salty” and “dry” were plotted near the swelling/tickle/tingle group and did not group with the tastes or astringents as in the sorting configuration. In the female similarity configuration, “puckering” was plotted near the taste group instead of the astringent group.

MULTIDIMENSIONAL SCALING OF MOUTHFEEL ATTRIBUTES

-

0 -

UNPLEASANT (.43) ("HOT, PAlNFUL ")

1 I

SOOTHING (.69)

109

rE

FIG. 4. VECTORS DERIVED FROM PROPERTY SCALES REGRESSED AGAINST SORTING SOLUTION COORDINATES

Values in parentheses are multiple r.

The SYSTAT solutions for the group-averaged male pairwise and the female pairwise ratings were quite similar (interpoint distance correlation = 0.96). The male and female pairwise configurations were also quite similar to the SYSTAT sorting solutions and are shown in Table 1. Stress values improved over the ALSCAL individual differences analysis to 0.20 for males and 0.21 for females. The property scales showed similar placements on both the pairwise and sorting configurations, with vectors for dull, weak, soothing, not painful and cool pointing in the general direction of the numbing cluster, and unpleasant and inappropriate pointing in the general direction of the sharpispicyihot attributes.

DISCUSSION

MDS provides insights into what panelists mean when they use mouthfeel attributes. By depicting the degree of similarity among attributes, MDS reveals how panelists categorize these attributes. In the present study, the following at-


FEMALES - ALSCAL INDIVIDUAL DIFFERENCES

SWELLING 0

ANESTH. 0 TICKLE 0 TINGLE

NUMB

mffi HOT 0 DRY *. SPICY

0 8 STING

PRICK 0 ASFRINGEM

0 IRRITATING

@ SHARP METALLIC 0 oPUCKERY BITE

- 2 . 5 - 1 . 5 -0 .5 0.5 1.5 2.5

ALSCAL DIMENSION 1

FIG. 5 . ALSCAL NONMETRIC TWO-DIMENSIONAL SOLUTION FOR FEMALE SIMILARITY RATINGS, USING INDIVIDUAL DIFFERENCES

SCALING OPTION

TABLE I .

CORRELATIONS OF INTERPOINT DISTANCES AMONG CONFIGURATIONS

ALSCAL AlSCAL SYSTAT (AVG.) SYSTAT (AVG.)

FEMALES MALES FEMALES MALES

SYSTAT - SORT 0.74 0.53 0.83 0.82

ALSCAL - FEMALES 0.69 0.82 0.82

ALSCAL - MALES 0.64 0.66

SYSTAT (AVG.) FEMALES 0.96

tribute groups were found: tastes, sensations associated with local anesthetics, sensations associated with astringency, and pain. There was evidence in the cluster analysis for two subcategories of pain possibly differentiated by their source - heat and chemical.

MULTIDIMENSIONAL SCALING OF MOUTHFEEL ATTRIBUTES

0 -

-1 -

1 1 1

0 0 ANESTH.

0 COCCPUG

0 ASTRINGEKT

PUCKERY

N

z v) z W

Q

r n

a Y a

-I

0

METALLIC BITTER SCUR

MALES - ALSCAL INDIVIDUAL DIFFERENCES

2 swuuffi

SALTY

IRRITATING 0

STING 0 0 B”

PRICK 0

8 SHARP BITE

Although the same general configuration would likely be obtained if stimuli represented the sensations, some differences might occur. “Astringent” and its associated sensations is a good example. If lemon juice were used to exemplify ‘‘puckering, ” puckering could have been grouped with sour rather than astringent. Since the present study used words rather than stimuli, panelists had to rely on their own experiences with products. Differences in personal experience could have affected the groupings. For example, astringent plotted near drying in the female configuration, but not in the male configuration. This may have been due to females’ association of astringency with cosmetic skin astringents. Categoriza- tion of astringency is a topic of some debate since sensations of astringency coexist with other sensations such as puckering, bitter, drying and sour, evoked after tasting astringent materials such as tannins and organic acids (Lee and Lawless 1991).

By superimposing the property vectors on the configuration, MDS suggests how the attribute meanings differ. Two major vectors traverse the sorting configuration (Fig. 4) at approximately a 45 degree angle. One can be interpreted as a temperature-pain vector and the other as an intensity-pleasantness vector.


Words which describe pain and heat, e.g., spicy, sharp, biting and hot, are in the upper right quadrant. Words which describe low intensity and no pain: anesthetizing, cooling and numbing are in the lower left quadrant.

The vectors do not completely explain the configuration. Unfortunately, since we did not ask our panelists which properties they used when making their judgments, we do not know if these vectors were relevant for their judgments. Further, in the configuration there is a large area running along a northeast- southwest axis suggesting that there were other properties (perhaps surface versus deep) important for understanding the position of the groups that were not measured. This underscores the potential value of eliciting respondents’ own words and criteria for their sorting or similarity ratings to use as property scales. Such an approach was taken by Stevens and Lawless (1981) in a three-stage multidimensional scaling study of flavors. In the first stage, pairwise similarity ratings were collected. In the second stage, subjects were asked to write down all the attributes they used in making their similarity judgments. These were then counted and the most frequent attributes were used for intensity ratings in a third session. Alter- natively, individualized ballots could be constructed and submitted to Procrustes analysis, as in so-called free-choice profiling methods, especially under cir- cumstances in which subjects’ meanings or interpretations for their property scales may be expected to vary.

Using MDS may help the sensory researcher shorten long attribute lists, since words in close proximity may be redundant. For example, numbing and anesthetizing, and drying and astringent, respectively, could probably be used inter- changeably in most studies with oral products. However, attribute lists must be reduced cautiously. For example, sour and bitter were close in the configuration even though they are different tastes. Two factors could have contributed to this proximity, the sour-bitter taste confusion (McAuliffe and Meiselman 1974) and the fact that there were mostly mouthfeel words in the stimulus set making the laste words seem more similar than they actually are.

One important result in this study was the finding that sorting produces configurations of fewer dimensions than pairwise similarity ratings. In other words, if stress is used as a measure of the need for additional dimensions, the similarity data had higher stress for a given number of dimensions, suggesting that subjects attend to more attributes when judging the similarity of two stimuli at a time. Conversely, the sorting task may have tapped into only the most salient aspects, since subjects approach the stimulus set more globally. This pattern of higher stress was also seen in the first direct comparison of sorting to similarity ratings by Davison (1972) who used personality traits as stimuli.

On the other hand, Davison also noted strong similarities in the positions of stimuli in the two configurations. In our results, very similar configurations were obtained from the sorting and pairwise rating data when: (1) the average of the


pairwise ratings served as input, and (2) the same program (SYSTAT) was used to analyze both the sorting and the pairwise ratings. These results suggest that sorting and pairwise ratings give similar group-averaged results. Thus, when an individual solution is not required, sorting may be preferred to pairwise similarity ratings for cost efficiency. The differences in time for data collection differed by a factor of 5 or 10 (typically 10 min for sorting versus an hour or longer for similarity judgments). Thus the sorting task takes a more limited toll on panelist motivation. Many of our panelists volunteered that the sorting task was fun.

One cautionary note is suggested by this study. The high stress values found by the individual differences algorithms could be due to a “subsampling” pro- blem (Cohen and Jones 1974). That is, group solutions may only tap those common dimensions that are evident in sorting data, or are the only ones available after group averaging. It is conceivable that individual subjects may use many more criteria in their individual similarity ratings, that their attention to these additional criteria or nuances may shift from time to time, and that different subjects may attend to different nuances. A previous study of the subsampling pro- blem has shown that common dimensions were well-recovered by MDS, while dimensions to which subjects seldom attend were not well-recovered (Cohen and Jones 1974).

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understanding mouthfeel attributes: a multidimensional scaling approach

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