Literature DB >> 23175601

Direct comparison of the generalized Visual Analog Scale (gVAS) and general Labeled Magnitude Scale (gLMS).

John E Hayes1, Alissa L Allen, Samantha M Bennett.   

Abstract

Hundreds of studies have used the generalized Labeled Magnitude Scale (gLMS) to collect intensity data. Recent work on generalized affective scales like the Labeled Affective Magnitude (LAM) scale and Labeled Hedonic Scale (LHS) suggest a substantial proportion of participants fail to use the entire range of generalized scales, marking only at the adjective labels. This categorical behavior (i.e., clustering) is not limited to affective ratings, as it is well known anecdotally among users of the gLMS. One way to stop this behavior would be to retain a generalized top anchor and cross modal orientation procedure while stripping away the internal adjectives. Several published studies have already used this variant, the generalized Visual Analog Scale (gVAS). Because there are no reports directly comparing the gVAS and gLMS head to head, we did so in two experiments. In Experiment 1, participants (n=87) were randomized to 1 of 3 conditions to test effects of scaling instructions and scale structure. In Experiment 2, participants (n=58) assessed perceived ease of use and resolving power for each scale in a two-session crossover design. gLMS data showed evidence of categorical behavior, while gVAS data did not. Explicitly instructing participants to rate between adjectives did not reduce this behavior. The gLMS was easier to use according to participants, but resulted in non-normal data due to clustering near the adjective labels. gVAS data did not show categorical behavior, as there are no adjectives to cluster around, but the gVAS sacrifices semantic information about the magnitude of response. Regardless of scale type, participants felt the cross-modal orientation procedure helped them understand how to use the scale. Both scales were able to discriminate between sucrose samples in a concentration series. Relative tradeoffs between the two methods suggest the choice of one scale over the other depends on the specific goals and context of the project.

Entities:  

Year:  2012        PMID: 23175601      PMCID: PMC3501107          DOI: 10.1016/j.foodqual.2012.07.012

Source DB:  PubMed          Journal:  Food Qual Prefer        ISSN: 0950-3293            Impact factor:   5.565


  18 in total

Review 1.  Comparing sensory experiences across individuals: recent psychophysical advances illuminate genetic variation in taste perception.

Authors:  L M Bartoshuk
Journal:  Chem Senses       Date:  2000-08       Impact factor: 3.160

2.  Adaptation-level vs. the relativity of judgment.

Authors:  S S STEVENS
Journal:  Am J Psychol       Date:  1958-12

3.  A complex relationship among chemical concentration, detection threshold, and suprathreshold intensity of bitter compounds.

Authors:  Russell S J Keast; Jessica Roper
Journal:  Chem Senses       Date:  2007-01-13       Impact factor: 3.160

4.  Derivation and evaluation of a labeled hedonic scale.

Authors:  Juyun Lim; Alison Wood; Barry G Green
Journal:  Chem Senses       Date:  2009-11       Impact factor: 3.160

Review 5.  Psychophysics of sweet and fat perception in obesity: problems, solutions and new perspectives.

Authors:  Linda M Bartoshuk; Valerie B Duffy; John E Hayes; Howard R Moskowitz; Derek J Snyder
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-07-29       Impact factor: 6.237

6.  Aging is associated with increased Weber ratios for caffeine, but not for sucrose.

Authors:  M M Gilmore; C Murphy
Journal:  Percept Psychophys       Date:  1989-12

7.  Measurement of mood.

Authors:  A K Zealley; R C Aitken
Journal:  Proc R Soc Med       Date:  1969-10

8.  A JND-scale/category-scale convergence in taste.

Authors:  R L McBride
Journal:  Percept Psychophys       Date:  1983-07

Review 9.  Individual responder analyses for pain: does one pain scale fit all?

Authors:  Raymond A Dionne; Linda Bartoshuk; Jeffrey Mogil; James Witter
Journal:  Trends Pharmacol Sci       Date:  2005-03       Impact factor: 14.819

10.  Associations between taste genetics, oral sensation and alcohol intake.

Authors:  Valerie B Duffy; Julie M Peterson; Linda M Bartoshuk
Journal:  Physiol Behav       Date:  2004-09-15
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  38 in total

1.  Older US adults like sweetened colas, but not other chemesthetic beverages.

Authors:  Madison R Wierenga; Ciera R Crawford; Cordelia A Running
Journal:  J Texture Stud       Date:  2020-07-29       Impact factor: 3.223

2.  A sipometer for measuring motivation to consume and reward value of foods and beverages in humans: Description and proof of principle.

Authors:  P S Hogenkamp; A Shechter; M-P St-Onge; A Sclafani; H R Kissileff
Journal:  Physiol Behav       Date:  2017-01-13

3.  Reliability and responsiveness of virtual portion size creation tasks: Influences of context, foods, and a bariatric surgical procedure.

Authors:  Jeon D Hamm; Jany Dotel; Shoran Tamura; Ari Shechter; Musya Herzog; Jeffrey M Brunstrom; Jeanine Albu; F Xavier Pi-Sunyer; Blandine Laferrère; Harry R Kissileff
Journal:  Physiol Behav       Date:  2020-06-06

4.  Gender differences in the influence of personality traits on spicy food liking and intake.

Authors:  Nadia K Byrnes; John E Hayes
Journal:  Food Qual Prefer       Date:  2015-06-01       Impact factor: 5.565

Review 5.  Evaluation of Sweetener Synergy in Humans by Isobole Analyses.

Authors:  M Michelle Reyes; Stephen A Gravina; John E Hayes
Journal:  Chem Senses       Date:  2019-10-17       Impact factor: 3.160

6.  Polymorphisms in TRPV1 and TAS2Rs associate with sensations from sampled ethanol.

Authors:  Alissa L Allen; John E McGeary; John E Hayes
Journal:  Alcohol Clin Exp Res       Date:  2014-09-25       Impact factor: 3.455

7.  Regional differences in suprathreshold intensity for bitter and umami stimuli.

Authors:  Emma L Feeney; John E Hayes
Journal:  Chemosens Percept       Date:  2014-12       Impact factor: 1.833

8.  Personality factors predict spicy food liking and intake.

Authors:  Nadia K Byrnes; John E Hayes
Journal:  Food Qual Prefer       Date:  2012-10-04       Impact factor: 5.565

9.  Behavioral measures of risk tasking, sensation seeking and sensitivity to reward may reflect different motivations for spicy food liking and consumption.

Authors:  Nadia K Byrnes; John E Hayes
Journal:  Appetite       Date:  2016-04-29       Impact factor: 3.868

10.  Bitterness of the non-nutritive sweetener acesulfame potassium varies with polymorphisms in TAS2R9 and TAS2R31.

Authors:  Alissa L Allen; John E McGeary; Valerie S Knopik; John E Hayes
Journal:  Chem Senses       Date:  2013-04-18       Impact factor: 3.160

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