Improving Assessment of the Spectrum of Reward-Related Eating: The RED-13

Ashley E Mason, Uku Vainik, Michael Acree, A Janet Tomiyama, Alain Dagher, Elissa S Epel, Frederick M Hecht, Ashley E Mason, Uku Vainik, Michael Acree, A Janet Tomiyama, Alain Dagher, Elissa S Epel, Frederick M Hecht

Abstract

A diversity of scales capture facets of reward-related eating (RRE). These scales assess food cravings, uncontrolled eating, addictive behavior, restrained eating, binge eating, and other eating behaviors. However, these scales differ in terms of the severity of RRE they capture. We sought to incorporate the items from existing scales to broaden the 9-item Reward-based Eating Drive scale (RED-9; Epel et al., 2014), which assesses three dimensions of RRE (lack of satiety, preoccupation with food, and lack of control over eating), in order to more comprehensively assess the entire spectrum of RRE. In a series of 4 studies, we used Item Response Theory models to consider candidate items to broaden the RED-9. Studies 1 and 2 evaluated the abilities of additional items from existing scales to increase the RED-9's coverage across the spectrum of RRE. Study 3 evaluated candidate items identified in Studies 1 and 2 in a new sample to assess the extent to which they accounted for more variance in areas less well-covered by the RED-9. Study 4 tested the ability of the RED-13 to provide consistent coverage across the range of the RRE spectrum. The resultant RED-13 accounted for greater variability than the RED-9 by reducing gaps in coverage of RRE in middle-to-low ranges. Like the RED-9, the RED-13 was positively correlated with BMI. The RED-13 was also positively related to a diagnosis of type 2 diabetes as well as cravings for sweet and savory foods. In summary, the RED-13 is a brief self-report measure that broadly captures the spectrum of RRE and may be a useful tool for identifying individuals at risk for overweight or obesity.

Keywords: assessment; eating behavior; item response theory; obesity; reward-driven eating; reward-related eating; uncontrolled eating.

Figures

FIGURE 1
FIGURE 1
Person-item map and histogram depicting thresholds on the spectrum of reward-related eating (RRE) for Study 1. The histogram at top displays the locations of participants on the latent RRE construct. The top row of the person-item map at bottom depicts the locations of the gaps in coverage of the RRE construct left by the RED-9. The 27 items listed below “thresholds of RED items” are ordered by the average of their thresholds’ values, and colored by the respective scale from which they originate. Circles depict each threshold, i.e., location on the RRE construct where people are most likely to move from one response option to the next. Gray rectangles appear whenever the gap between two consecutive RED-9 item thresholds is wider than 0.29 units. The gray rectangle only highlights parts of the latent trait that are further than 0.29/2 units from any RED-9 threshold. This figure includes the RED-9 items and all items that account for variance in the gap areas. See Supplementary Figure S1 for a figure with all items tested.
FIGURE 2
FIGURE 2
Person-item map and histogram depicting thresholds on the spectrum of RRE for Study 2. See Figure 1 note. Some items are shortened for graphical presentation. This figure includes the RED-9 items and the 37 items that account for variance in the gap areas. See Supplementary Figure S2 for a figure with all items tested.
FIGURE 3
FIGURE 3
Person-item map and histogram depicting thresholds on the spectrum of RRE for Study 3. See Figure 1 note. This figure includes the RED-9 items the 21 items that account for variance in the gap areas. For a graph on all items tested, see Supplementary Figure S3. Stars indicate items selected by authors for inclusion in Study 4.
FIGURE 4
FIGURE 4
Person-item map and histogram depicting thresholds on the spectrum of RRE for Study 4. See Figure 1 note. Bars in darker gray indicate gaps in RRE coverage left by the RED-13. Bars in lighter gray indicate gaps in coverage left by RED-9. Stars indicate items added to the RED-9 to form the RED-13.

References

    1. American Psychological Association (2000). Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR. Arlington, VA: American Psychiatric Association Publishing.
    1. Arnold J. B. (2013). ggthemes: Extra Themes, Scales and Geoms for ggplot. R Package Version.
    1. Baker F. B. (2001). The Basics of Item Response Theory. Second Edition. College Park, MD: ERIC Publication.
    1. Boswell R. G., Kober H. (2016). Food cue reactivity and craving predict eating and weight gain: a meta-analytic review. Obes. Rev. 17 159–177. 10.1111/obr.12354
    1. Buhrmester M., Kwang T., Gosling S. D. (2011). Amazon’s mechanical turk a new source of inexpensive, yet high-quality, data? Perspect. Psychol. Sci. 6 3–5. 10.1177/1745691610393980
    1. Burgess E. E., Turan B., Lokken K. L., Morse A., Boggiano M. M. (2014). Profiling motives behind hedonic eating: preliminary validation of the Palatable Eating Motives Scale. Appetite 72 66–72. 10.1016/j.appet.2013.09.016
    1. Camilli G. (1994). Teacher’s corner: origin of the scaling constant d = 1.7 in item response theory. J. Educ. Behav. Stat. 19 293–295. 10.3102/10769986019003293
    1. Cooper M. L. (1994). Motivations for alcohol use among adolescents: development and validation of a four-factor model. Psychol. Assess. 6 117–128. 10.1037/1040-3590.6.2.117
    1. Čukić I., Mõttus R., Realo A., Allik J. (2016). Elucidating the links between personality traits and diabetes mellitus: examining the role of facets, assessment methods, and selected mediators. Pers. Individ. Dif. 94 377–382. 10.1016/j.paid.2016.01.052
    1. Dalton M., Finlayson G., Hill A., Blundell J. (2015). Preliminary validation and principal components analysis of the Control of Eating Questionnaire (CoEQ) for the experience of food craving. Eur. J. Clin. Nutr. 69 1313–1317. 10.1038/ejcn.2015.57
    1. Daubenmier J., Moran P. J., Kristeller J., Acree M., Bacchetti P., Kemeny M. E., et al. (2016). Effects of a mindfulness-based weight loss intervention in adults with obesity: a randomized clinical trial. Obesity 24 794–804. 10.1002/oby.21396
    1. Davis C. (2013). From passive overeating to “food addiction”: a spectrum of compulsion and severity. ISRN Obes. 2013:435027 10.1155/2013/435027
    1. Epel E., Tomiyama A. J., Mason A., Laraia B. A., Hartman W., Ready K., et al. (2014). The reward-based eating drive scale: a self-report index of reward-based eating. PLoS ONE 9:e101350 10.1371/journal.pone.0101350
    1. Fleiss J. L. (1971). Measuring nominal scale agreement among many raters. Psychol. Bull. 76 378–382. 10.1037/h0031619
    1. Forman E. M., Butryn M. L., Juarascio A. S., Bradley L. E., Lowe M. R., Herbert J. D., et al. (2013). The mind your health project: a randomized controlled trial of an innovative behavioral treatment for obesity. Obesity 21 1119–1126. 10.1002/oby.20169
    1. French S. A., Mitchell N. R., Finlayson G., Blundell J. E., Jeffery R. W. (2014). Questionnaire and laboratory measures of eating behavior. Associations with energy intake and BMI in a community sample of working adults. Appetite 72 50–58. 10.1016/j.appet.2013.09.020
    1. Gearhardt A., Corbin W. R., Brownell K. D. (2009). Preliminary validation of the Yale Food Addiction Scale. Appetite 52 430–436. 10.1016/j.appet.2008.12.003
    1. Gearhardt A., Corbin W. R., Brownell K. D. (2016). Development of the Yale Food Addiction Scale Version 2.0. Psychol. Addict. Behav. 30 113–121. 10.1037/adb0000136
    1. Goodman J. K., Cryder C. E., Cheema A. (2013). Data collection in a flat world: the strengths and weaknesses of mechanical turk samples. J. Behav. Decis. Mak. 26 213–224. 10.1002/bdm.1753
    1. Gormally J., Black S., Daston S., Rardin D. (1982). The assessment of binge eating severity among obese persons. Addict. Behav. 7 47–55. 10.1016/0306-4603(82)90024-7
    1. Hair J., Tatham R., Anderson R., Black W. (1998). Multivariate Data Analysis, 5th Edn London: Prentice-Hall.
    1. Harris P. A., Taylor R., Thielke R., Payne J., Gonzalez N., Conde J. G. (2009). Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 42 377–381. 10.1016/j.jbi.2008.08.010
    1. Hu L., Bentler P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. Multidiscip. J. 6 1–55. 10.1080/10705519909540118
    1. Kenny D. (2014). SEM: Fit (David A. Kenny). Available at: [accessed February 16, 2017].
    1. Kittur A., Chi E. H., Suh B. (2008). “Crowdsourcing user studies with Mechanical Turk,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, 453–456. 10.1145/1357054.1357127
    1. Lai J. S., Eton D. T. (2002). Clinically meaningful gaps. Rasch Meas. Trans. 15 850.
    1. Lowe M. R. (2003). Self-Regulation of Energy Intake in the Prevention and Treatment of Obesity: Is It Feasible? Obes. Res. 11 44S–59S. 10.1038/oby.2003.223
    1. Lowe M. R., Butryn M. L., Didie E. R., Annunziato R. A., Thomas J. G., Crerand C. E., et al. (2009). The Power of Food Scale. A new measure of the psychological influence of the food environment. Appetite 53 114–118. 10.1016/j.appet.2009.05.016
    1. Mason A., Epel E. S., Aschbacher K., Lustig R. H., Acree M., Kristeller J., et al. (2016). Reduced reward-driven eating accounts for the impact of a mindfulness-based diet and exercise intervention on weight loss: data from the SHINE randomized controlled trial. Appetite 100 86–93. 10.1016/j.appet.2016.02.009
    1. Mason A., Laraia B. A., Daubenmier J., Hecht F. M., Lustig R. H., Puterman E., et al. (2015a). Putting the brakes on the “drive to eat”: pilot effects of naltrexone and reward based eating on food cravings among obese women. Eat. Behav. 9 53–56. 10.1016/j.eatbeh.2015.06.008
    1. Mason A., Lustig R., Brown R., Acree M., Bacchetti P., Moran P., et al. (2015b). Acute responses to opioidergic blockade as a biomarker of hedonic eating among obese women enrolled in a mindfulness-based weight loss intervention trial. Appetite 91 311–320. 10.1016/j.appet.2015.04.062
    1. Meule A., Hermann T., Kübler A. (2014). A short version of the Food Cravings Questionnaire-Trait: the FCQ-T-reduced. Front. Psychol. 5:190 10.3389/fpsyg.2014.00190
    1. Mietus-Snyder M. L., Lustig R. H. (2008). Childhood obesity: adrift in the “limbic triangle”. Annu. Rev. Med. 59 147–162. 10.1146/annurev.med.59.103106.105628
    1. Neuwirth E. (2014). RColorBrewer: ColorBrewer Palettes. 2014. R package version 1.1-2.
    1. O’Neil P. M., Theim K. R., Boeka A., Johnson G., Miller-Kovach K. (2012). Changes in weight control behaviors and hedonic hunger during a 12-week commercial weight loss program. Eat. Behav. 13 354–360. 10.1016/j.eatbeh.2012.06.002
    1. Partchev I. (2004). A Visual Guide to Item Response Theory. Available at:
    1. Price M., Higgs S., Lee M. (2015). Self-reported eating traits: underlying components of food responsivity and dietary restriction are positively related to BMI. Appetite 95 203–210. 10.1016/j.appet.2015.07.006
    1. R Core Team (2013). R: A Language and Environment for Statistical Computing. Available at:
    1. Revelle W. (2014). The Personality Project: An Introduction to Psychometric Theory. In Chapter 8: An Introduction to Psychometric Theory with Applications in R. The Personality Project. Available at:
    1. Rosseel Y. (2012). Lavaan. An R package for structural equation modeling. J. Stat. Softw. 48 1–36. 10.18637/jss.v048.i02
    1. Skinner B. F. (1963). Operant behavior. Am. Psychol. 18 503–515. 10.1037/h0045185
    1. Stunkard A. J., Messick S. (1985). The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J. Psychosom. Res. 29 71–83. 10.1016/0022-3999(85)90010-8
    1. Vainik U., Mõttus R., Allik J., Esko T., Realo A. (2015a). Are trait–outcome associations caused by scales or particular items? Example analysis of personality facets and BMI. Eur. J. Pers. 29 622–634. 10.1002/per.2009
    1. Vainik U., Neseliler S., Konstabel K., Fellows L. K., Dagher A. (2015b). Eating traits questionnaires as a continuum of a single concept. Uncontrolled eating. Appetite 90 229–239. 10.1016/j.appet.2015.03.004
    1. van Strien T., Frijters J. E. R., Bergers G. P. A., Defares P. B. (1986). The Dutch Eating Behavior Questionnaire (DEBQ) for assessment of restrained, emotional, and external eating behavior. Int. J. Eat. Disord, 5 295–315. 10.1002/1098-108X(198602)5:2<295::AID-EAT2260050209>;2-T
    1. Visscher T. L. S., Viet A. L., Kroesbergen H. T., Seidell J. C. (2006). Underreporting of BMI in adults and its effect on obesity prevalence estimations in the period 1998 to 2001. Obesity 14 2054–2063. 10.1038/oby.2006.240
    1. Wickham H. (2009). ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer Science & Business Media; 10.1007/978-0-387-98141-3
    1. Wirth R., Edwards M. C. (2007). Item factor analysis: current approaches and future directions. Psychol. Methods 12 58–79. 10.1037/1082-989X.12.1.58

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