Dual process models point towards an interaction between topdown control and bottom-up influences.

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3 Dual process models point towards an interaction between topdown control and bottom-up influences. Research suggests obesity is linked to low self-control combined with high reward sensitivity. Childhood obesity is linked to low inhibitory control and greater activation of neural reward centres in response to food cues. Higher inhibitory control is linked to greater consumption of fruit and vegetables among children. Can interventions help develop inhibitory control capacity?

4 New approaches to healthy eating are looking at targeting the brain s response to food via a computer game instead of telling people what to do. Inhibitory control training (ICT): Go/No-Go task Healthy foods = Go Unhealthy foods = No-Go Successful inhibition required Decreases intake Increases healthy choice, decreases unhealthy choice And even leads to weight loss in adults

5 One study found an effect on sweets and chocolate intake (non-food control task) p =.117 p =.008 p =.554 Studies run by Exeter 3 undergraduates 2 investigated effects on food choice and produced 1 inconsistent results (50/50 food control task). 0 Study 1 Study 2 Study 3 Active Control

6 To measure changes in food choice, a pretraining choice task was added. To compare across studies, a non-food control task was included. To check hypothetical vs. real measures, a real food choice was added. Active Food Control Non-Food Control

7 Phase 1: Random allocation Hypothetical food task Hunger scale Break (5-10 days) Phase 2: Go/No-Go training Hypothetical food task Hunger scale Real food choice

8 Proportion of HF chosen of total choices N = 81; 45 male (A = 29; FC = 25; NFC = 27) ANCOVA controlling for pre-training choices as a covariate Average proportion of Healthy Foods Chosen Pre Post Outcome expressed as a proportion due to pretraining errors Active Food Control Non-food

9 Proportion of HF chosen of total choices N = 81; 45 male (A = 29; FC = 25; NFC = 27) Pre-training HF choice (covariate) = F 1,77 = 60.77, p < Average proportion of Healthy Foods Chosen Pre Post Condition = F 2,77 = 5.17, p = A vs. FC: p =.012 A vs. NFC: p =.005 FC vs. NFC: p = Active Food Control Non-food

10 Proportion of HF chosen of total choices N = 81; 45 male (A = 29; FC = 25; NFC = 27) Change from pre- to posttraining: Average proportion of Healthy Foods Chosen Pre Post A = t 28 = -4.79, p <.001, Cohen s d z =.89, JSZ B = FC = p =.477, d z =.14, JSZ B = NFC = p=.353, d z =.18, JSZ B = Active Food Control Non-food

11 Real food choice N = 69; 38 male (A = 25; FC = 21; NFC = 23) Average number of Healthy Foods Chosen Real vs. Card Choices correlated well = r s =.661, p < Condition on choice (Kruskal-Wallis) = x 2 2 = 4.76, p =.047; (one-sided test) Active Column1 Food Control Non-Food Control

12 Real food choice N = 69; 38 male (A = 25; FC = 21; NFC = 23) Average number of Healthy Foods Chosen Planned comparisons (Mann-Whitney) A vs. NF: U = 188.5, p = All other comparisons: p > Active Column1 Food Control Non-Food Control

13 Participants in the active group chose the greatest number of healthy foods. This was due to an increase in healthy food choice from pre- to posttraining. 50/50 food response task may not be appropriate for control groups.

14 No measure of absolute liking for foods (e.g., was it a decrease in unhealthy or an increase in healthy?) No change data for real food task. No follow-up data to test longevity of effects.

15 Does 50/50 food response training lead to change in real food measures? What are the mechanisms of such training? Can training effects withstand the effects of advertising on intake? How does it work? STOP Automatic inhibition? Stimulus devaluation? Both? Advertising is particularly problematic when it comes to children s energy-dense food intake. Can inhibitory control training compete?

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17 Boyland, E. J., & Halford, J. C. (2013). Television advertising and branding. Effects on eating behaviour and food preferences in children. Appetite, 62, Bruce, A. S., Holsen, L. M., Chambers, R. J., Martin, L. E., Brooks, W. M., Zarcone, J. R., Butler, M.G. & Savage, C. R. (2010). Obese children show hyperactivation to food pictures in brain networks linked to motivation, reward and cognitive control. International Journal of Obesity, 34(10), Bunge, S. A., Dudukovic, N. M., Thomason, M. E., Vaidya, C. J., & Gabrieli, J. D. (2002). Immature frontal lobe contributions to cognitive control in children: evidence from fmri. Neuron, 33(2), Folkvord, F., Veling, H., & Hoeken, H. (2016). Targeting Implicit Approach Reactions to Snack Food in Children: Effects on Intake. Children s Reactivity to Embedded Food Cues in Advergames, 163. Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), Jones, A., Di Lemma, L. C., Robinson, E., Christiansen, P., Nolan, S., Tudur-Smith, C., & Field, M. (2016). Inhibitory control training for appetitive behaviour change: A meta-analytic investigation of mechanisms of action and moderators of effectiveness. Appetite, 97, Lawrence, N. S., Hinton, E. C., Parkinson, J. A., & Lawrence, A. D. (2012). Nucleus accumbens response to food cues predicts subsequent snack consumption in women and increased body mass index in those with reduced self-control. Neuroimage, 63(1), Lawrence, N. S., O'Sullivan, J., Parslow, D., Javaid, M., Adams, R. C., Chambers, C. D.,... & Verbruggen, F. (2015). Training response inhibition to food is associated with weight loss and reduced energy intake. Appetite, 95, 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(4), 389. Public Health England (2014). National Diet and Nutrition Survey: Results from Years 1-4 (combined) of the Rolling Programme (2008/ /12): Executive summary. Accessed online: (February, 2016) Public Health England (2015). Making the case for tackling obesity; why invest? (Powerpoint slides). Accessed online: (March, 2016) Riggs, N., Chou, C. P., Spruijt-Metz, D., & Pentz, M. A. (2010). Executive cognitive function as a correlate and predictor of child food intake and physical activity. Child Neuropsychology, 16(3), Stiles, K. (2015), Trash the Treats: The Effects of the Go/No-Go Paradigm on Children s Food Preferences. (Unpublished undergraduate dissertation). University of Exeter, Devon. Veling, H., Aarts, H., & Stroebe, W. (2013). Using stop signals to reduce impulsive choices for palatable unhealthy foods. British journal of health psychology, 18(2),