Nearly 70% of Americans are overweight, in large part because of overconsumption of high-calorie foods such as sweets. Reducing sweets is difficult because powerful drives toward reward overwhelm inhibitory control (i.e., the ability to withhold a prepotent response) capacities. Computerized inhibitory control trainings (ICTs) have shown positive outcomes, but impact on real-world health behavior has been variable, potentially because of limitations inherent in existing paradigms, e.g., low in frequency, intrinsic enjoyment, personalization, and ability to adapt to increasing ability. The present study aimed to assess the feasibility, acceptability, and efficacy of a gamified and non-gamified, daily, personalized, and adaptive ICT designed to facilitate weight loss by targeting consumption of sweets. Participants (N = 106) were randomized to one of four conditions in a 2 (gamified vs. non-gamified) by 2 (ICT vs. sham) factorial design. Participants were prescribed a no-added-sugar diet and completed 42 daily, at-home trainings, followed by two weekly booster trainings. Results indicated that the ICTs were feasible and acceptable. Surprisingly, compliance to the 44 trainings was excellent (88.8%) and equivalent across both gamified and non-gamified conditions. As hypothesized, the impact of ICT on weight loss was moderated by implicit preference for sweet foods [F(1,95) = 6.17, p = .02] such that only those with higher-than-average implicit preference benefited (8-week weight losses for ICT were 3.1% vs. 2.2% for sham). A marginally significant effect was observed for gamification to reduce the impact of ICT. Implications of findings for continued development of ICTs to impact health behavior are discussed.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Allom, V., Mullan, B., & Hagger, M. (2016). Does inhibitory control training improve health behaviour? A meta-analysis. Health Psychology Review, 10, 168–186.
Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., Faraji, F., Janowich, J., et al. (2013). Video game training enhances cognitive control in older adults. Nature, 501, 97.
Banse, R., Seise, J., & Zerbes, N. (2001). Implicit attitudes towards homosexuality: Reliability, validity, and controllability of the IAT. Zeitschrift für experimentelle Psychologie, 48, 145–160.
Benikos, N., Johnstone, S. J., & Roodenrys, S. J. (2013). Short-term training in the Go/Nogo task: Behavioural and neural changes depend on task demands. International Journal of Psychophysiology, 87, 301–312.
Best, M., Lawrence, N. S., Logan, G. D., McLaren, I. P., & Verbruggen, F. (2016). Should I stop or should I go? The role of associations and expectancies. Journal of Experimental Psychology: Human Perception and Performance, 42, 115.
Blackburne, T., Rodriguez, A., & Johnstone, S. J. (2016). A serious game to increase healthy food consumption in overweight or obese adults: Randomized controlled trial. JMIR Serious Games, 4, e10.
Boendermaker, W., Prins, P., & Wiers, R. (2013). Documentation of the CityBuilder game. Theoretical background and parameters. Amsterdam: University of Amsterdam.
Bowman, S. A., Clemens, J. C., Martin, C. L., Anand, J., Steinfeldt, L. C., & Moshfegh, A. J. (2017). Added sugars intake of Americans: What we eat in America, NHANES 2013–2014. Maryland: Worldwide Web Site: Food Surveys Research Group.
Dahlin, E., Nyberg, L., Bäckman, L., & Neely, A. S. (2008). Plasticity of executive functioning in young and older adults: Immediate training gains, transfer, and long-term maintenance. Psychology and Aging, 23, 720.
De Koning, L., Malik, V. S., Kellogg, M. D., Rimm, E. B., Willett, W. C., & Hu, F. B. (2012). Sweetened beverage consumption, incident coronary heart disease and biomarkers of risk in men. Circulation, 111, 067017.
Deloitte. (2016). 2016 global mobile consumer survey: US Edition. Retrieved December 10, 2018 from https://www2.deloitte.com/content/dam/Deloitte/us/Documents/technology-media-telecommunications/us-global-mobile-consumer-survey-2016-executive-summary.pdf.
Diabetes Prevention Program Research Group. (2004). Achieving weight and activity goals among diabetes prevention program lifestyle participants. Obesity Research, 12, 1426–1434.
Drewnowski, A. (1997). Taste preferences and food intake. Annual Review of Nutrition, 17, 237–253.
Drewnowski, A., Darmon, N., & Briend, A. (2004). Replacing fats and sweets with vegetables and fruits—A question of cost. American Journal of Public Health, 94, 1555–1559.
Drewnowski, A., & Greenwood, M. (1983). Cream and sugar: Human preferences for high-fat foods. Physiology & Behavior, 30, 629–633.
Egloff, B., & Schmukle, S. C. (2002). Predictive validity of an implicit association test for assessing anxiety. Journal of personality and social psychology, 83, 1441.
Feskanich, D., Rimm, E. B., Giovannucci, E. L., Colditz, G. A., Stampfer, M. J., Litin, L. B., et al. (1993). Reproducibility and validity of food intake measurements from a semiquantitative food frequency questionnaire. Journal of the American Dietetic Association, 93, 790–796.
Freund, A. M., & Hennecke, M. (2012). Changing eating behaviour vs. losing weight: The role of goal focus for weight loss in overweight women. Psychology & Health, 27, 25–42.
Friese, M., Hofmann, W., & Wänke, M. (2008). When impulses take over: Moderated predictive validity of explicit and implicit attitude measures in predicting food choice and consumption behaviour. British Journal of Social Psychology, 47, 397–419.
Giel, K. E., Speer, E., Schag, K., Leehr, E. J., & Zipfel, S. (2017). Effects of a food-specific inhibition training in individuals with binge eating disorder—Findings from a randomized controlled proof-of-concept study. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity, 22, 345–351.
Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the implicit association test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85, 197.
Guerrieri, R., Nederkoorn, C., & Jansen, A. (2012). Disinhibition is easier learned than inhibition. The effects of (dis)inhibition training on food intake. Appetite, 59(1), 96–99.
Hartmann-Boyce, J., Jebb, S. A., Fletcher, B. R., & Aveyard, P. (2015). Self-help for weight loss in overweight and obese adults: Systematic review and meta-analysis. American Journal of Public Health, 105, e43–e57.
Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4, 162–176.
Hofmann, W., Friese, M., & Wiers, R. W. (2008). Impulsive versus reflective influences on health behavior: A theoretical framework and empirical review. Health Psychology Review, 2, 111–137.
Houben, K. (2011). Overcoming the urge to splurge: Influencing eating behavior by manipulating inhibitory control. Journal of Behavior Therapy and Experimental Psychiatry, 42, 384–388.
Houben, K., Havermans, R. C., Nederkoorn, C., & Jansen, A. (2012). Beer à No-Go: Learning to stop responding to alcohol cues reduces alcohol intake via reduced affective associations rather than increased response inhibition. Addiction, 107, 1280–1287.
Houben, K., & Jansen, A. (2011). Training inhibitory control. A recipe for resisting sweet temptations. Appetite, 56, 345–349.
Houben, K., & Jansen, A. (2015). Chocolate equals stop. Chocolate-specific inhibition training reduces chocolate intake and go associations with chocolate. Appetite, 87, 318–323.
Hu, F. B. (2013). Resolved: There is sufficient scientific evidence that decreasing sugar-sweetened beverage consumption will reduce the prevalence of obesity and obesity-related diseases. Obesity Reviews, 14, 606–619.
Hu, F. B., Rimm, E., Smith-Warner, S. A., Feskanich, D., Stampfer, M. J., Ascherio, A., et al. (1999). Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. The American Journal of Clinical Nutrition, 69, 243–249.
Jansen, A., Nederkoorn, C., van Baak, L., Keirse, C., Guerrieri, R., & Havermans, R. (2009). High-restrained eaters only overeat when they are also impulsive. Behaviour Research and Therapy, 47, 105–110.
Johnstone, S. J., Roodenrys, S. J., Johnson, K., Bonfield, R., & Bennett, S. J. (2017). Game-based combined cognitive and neurofeedback training using focus pocus reduces symptom severity in children with diagnosed AD/HD and subclinical AD/HD. International Journal of Psychophysiology, 116, 32–44.
Jones, A., Di Lemma, L. C., Robinson, E., Christiansen, P., Nolan, S., Tudur-Smith, C., et al. (2016). Inhibitory control training for appetitive behaviour change: A meta-analytic investigation of mechanisms of action and moderators of effectiveness. Appetite, 97, 16–28.
Jones, A., Hardman, C. A., Lawrence, N., & Field, M. (2017). Cognitive training as a potential treatment for overweight and obesity: A critical review of the evidence. Appetite, 124, 50–67.
Kühn, S., Lorenz, R. C., Weichenberger, M., Becker, M., Haesner, M., O’Sullivan, J., et al. (2017). Taking control! Structural and behavioural plasticity in response to game-based inhibition training in older adults. NeuroImage, 156, 199–206.
Lawrence, N. S., O’Sullivan, J., Parslow, D., Javaid, M., Adams, R. C., Chambers, C. D., et al. (2015). Training response inhibition to food is associated with weight loss and reduced energy intake. Appetite, 95, 17–28.
Little, R., & Yau, L. (1996). Intent-to-treat analysis for longitudinal studies with drop-outs. Biometrics, 52, 1324–1333.
Logan, G. D., Schachar, R. J., & Tannock, R. (1997). Impulsivity and inhibitory control. Psychological Science, 8, 60–64.
Lumsden, J., Edwards, E. A., Lawrence, N. S., Coyle, D., & Munafò, M. R. (2016). Gamification of cognitive assessment and cognitive training: A systematic review of applications and efficacy. JMIR Serious Games, 4, e11.
Metcalfe, J., & Mischel, W. (1999). A hot/cool-system analysis of delay of gratification: Dynamics of willpower. Psychological Review, 106, 3.
National Center for Health Statistics. (2013–2014). National health and nutrition examination survey data. Retrieved December 10, 2018 from https://www.cdc.gov/nchs/fastats/obesity-overweight.html.
Nederkoorn, C., Houben, K., Hofmann, W., Roefs, A., & Jansen, A. (2010). Control yourself or just eat what you like? Weight gain over a year is predicted by an interactive effect of response inhibition and implicit preference for snack foods. Health Psychology, 29, 389.
Nederkoorn, C., Smulders, F. T., Havermans, R. C., Roefs, A., & Jansen, A. (2006). Impulsivity in obese women. Appetite, 47, 253–256.
Nosek, B. A., Greenwald, A. G., & Banaji, M. R. (2005). Understanding and using the Implicit Association Test: II. Method variables and construct validity. Personality and Social Psychology Bulletin, 31, 166–180.
Peeters, K., Van Leemputte, F., Fischer, B., Bonini, B. M., Quezada, H., Tsytlonok, M., et al. (2017). Fructose-1, 6-bisphosphate couples glycolytic flux to activation of Ras. Nature Communications, 8, 922.
Pew Research Center. (2017). Record shares of Americans now own smartphones, have home broadband. Retrieved December 10, 2018 from http://www.pewresearch.org/fact-tank/2017/01/12/evolution-of-technology/.
Poppelaars, A., Scholten, H., Granic, I., Veling, H., Johnson-Glenberg, M. C., & Luijten, M. (2018). When winning is losing: A randomized controlled trial testing a video game to train food-specific inhibitory control. Appetite, 129, 143–154.
Porter, L., Bailey-Jones, C., Priudokaite, G., Allen, S., Wood, K., Stiles, K., et al. (2018). From cookies to carrots; The effect of inhibitory control training on children’s snack selections. Appetite, 124, 111–123.
Preuss, H., Pinnow, M., Schnicker, K., & Legenbauer, T. (2017). Improving inhibitory control abilities (ImpulsE)—A promising approach to treat impulsive eating? European Eating Disorders Review, 25, 533–543.
Prins, P. J., Dovis, S., Ponsioen, A., Ten Brink, E., & Van der Oord, S. (2011). Does computerized working memory training with game elements enhance motivation and training efficacy in children with ADHD? Cyberpsychology, Behavior, and Social Networking, 14, 115–122.
Schonberg, T., Bakkour, A., Hover, A. M., Mumford, J. A., Nagar, L., Perez, J., et al. (2014). Changing value through cued approach: An automatic mechanism of behavior change. Nature Neuroscience, 17, 625–630.
Schulze, M. B., Manson, J. E., Ludwig, D. S., Colditz, G. A., Stampfer, M. J., Willett, W. C., et al. (2004). Sugar-sweetened beverages, weight gain, and incidence of type 2 diabetes in young and middle-aged women. JAMA, 292, 927–934.
Spierer, L., Chavan, C., & Manuel, A. L. (2013). Training-induced behavioral and brain plasticity in inhibitory control. Frontiers in Human Neuroscience, 7, 427.
Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8, 220–247.
Subar, A. F., Kirkpatrick, S. I., Mittl, B., Zimmerman, T. P., Thompson, F. E., Bingley, C., . . . Potischman, N. (2012). The automated self-administered 24-hour dietary recall (ASA24): A resource for researchers, clinicians, and educators from the national cancer institute. Journal of the Academy of Nutrition and Dietetics, 112, 1134–1137. https://doi.org/10.1016/j.jand.2012.04.016.
Tsai, A. G., & Wadden, T. A. (2009). Treatment of obesity in primary care practice in the United States: A systematic review. Journal of General Internal Medicine, 24, 1073–1079.
Turton, R., Bruidegom, K., Cardi, V., Hirsch, C. R., & Treasure, J. (2016). Novel methods to help develop healthier eating habits for eating and weight disorders: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews, 61, 132–155.
Unity3D Game Engine. (2016). Unity. Retrieved December 10, 2018 from http://unity3d.com.
US Department of Health & Human Services. (2017). Dietary guidelines for Americans 2015–2020. New York: Skyhorse Publishing Inc.
Van Schie, S., & Boendermaker, W. (2014). Measuring attentional bias towards alcohol in adolescents using motivating game elements. Unpublished master’s thesis.
Veling, H., Aarts, H., & Papies, E. K. (2011). Using stop signals to inhibit chronic dieters’ responses toward palatable foods. Behaviour Research and Therapy, 49, 771–780.
Veling, H., Lawrence, N. S., Chen, Z., van Koningsbruggen, G. M., & Holland, R. W. (2017). What is trained during food go/no-go training? A review focusing on mechanisms and a research agenda. Current Addiction Reports, 4, 35–41.
Veling, H., van Koningsbruggen, G. M., Aarts, H., & Stroebe, W. (2014). Targeting impulsive processes of eating behavior via the internet. Effects on body weight. Appetite, 78, 102–109.
Verbeken, S., Braet, C., Goossens, L., & Van der Oord, S. (2013). Executive function training with game elements for obese children: A novel treatment to enhance self-regulatory abilities for weight-control. Behaviour Research and Therapy, 51, 290–299.
Vinogradov, S., Fisher, M., & de Villers-Sidani, E. (2012). Cognitive training for impaired neural systems in neuropsychiatric illness. Neuropsychopharmacology, 37, 43–76.
World Health Organization. (2015). Sugar intake for adults and children: Guideline. http://www.who.int/nutrition/publications/guidelines/sugars_intake/en. Accessed May 10, 2016.
The authors would like to thank Cara Dochat, Valerie Everett, and Jerry Martin for their help coordinating the study, and Michael Wagner, Travis Chandler, Josh Korn, Ricardo Concha, and Rachel Buttry for their help creating and maintaining the project’s graphics and code.
This study was funded by the National Cancer Institute (R21CA191859; PI: E Forman).
Conflict of interest
Evan Forman declares that he has no conflict of interest. Stephanie Manasse declares that she has no conflict of interest. Diane Dallal declares that she has no conflict of interest. Rebecca Crochiere declares that she has no conflict of interest. Caitlin Loyka declares that she has no conflict of interest. Meghan Butryn declares that she has no conflict of interest. Adrienne Juarascio declares that she has no conflict of interest. Katrijn Houben declares that she has no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Human and animal rights and Informed consent
All procedures followed were in accordance with ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Forman, E.M., Manasse, S.M., Dallal, D.H. et al. Computerized neurocognitive training for improving dietary health and facilitating weight loss. J Behav Med 42, 1029–1040 (2019). https://doi.org/10.1007/s10865-019-00024-5
- Inhibitory control training
- Health behavior
- Weight loss