Post on 14-Apr-2017
T I HO M I RA TO M O VAM S C HE ALT H P S Y CHO L O G Y
Associations Between Health Behaviours and Executive
Function:An Exploratory Study
Background (1)Good intentions- Poor behaviour
Previous research suggests that most of the general population are aware of the benefits of maintaining a healthy diet (Adriaanse et al., 2011; O’Brien & Davies, 2007). However, although many people do intend to follow a healthy, balanced diet, few of them turn their intentions into actual behavior (Kumanyika et al., 2000).
So what differentiates those that do achieve their goal-directed intentions?
One of the factors found to be involved in the successful execution of health-related behaviours and behaviour change is executive function (EF; Williams & Thayer, 2009).
behaviourintentions X
Background (2)What is EF
EF has been identified as the set of neurocognitive processes responsible for the planning, initiation, and maintenance of complex goal-directed action (Riggs et al., 2011).
Although EF has an underlying unitary quality, it also has correlated (but dissociable) subfunctions:
Two options exist for measuring EF:
Miyake et al. (2000)
1. Mental Flexibility
2. Working Memory
3. Inhibition
Objective Neuropsychological
TestsSelf-Reports
Background (3)
InhibitoryControl
Mental Flexibility
Working Memory
Poor DietaryBehaviour (e.g. high-calorie snacking)
Allan, Johnston & Campbell (2010; 2011)
Nederkoorn, et. al. (2010)
Allom & Mullan(2014)
Hofmann, Friese, & Roefs(2009)
Good Dietary Behaviour (e.g. F & V consumption)
Allan, Johnston & Campbell (2011)
Allom & Mullan(2014)
EFGoal
Aims
1. To identify which facets of EF are significantly associated with two key types of dietary behaviour:
2. To see if individuals with more efficient performance on objective EF tests are more likely than those with weak EF to adhere to their stated diet intentions over 48 hours
Hypotheses: 1. Inhibitory control is negatively ≈ with unhealthy snacking (better inhibitory control >> snacking)
2. Mental Flexibility is positively ≈ with F&V consumption (better mental flexibility >> F & V consumption)
3. Working Memory: participants with a superior WM performance consume high-calorie snacks and F&V.
Methods (1)
Design:
a cross-sectional, observational study investigating the associations between EF and dietary behaviour with a nested prospective component exploring whether EF predicts adherence to dietary intentions over 48 hours.
55 healthy adults (Females: 32 ; Age: Mean= 25.98, SD= 8.09; BMI: Mean = 22.68, SD = 3.58)
Inclusion criteria:
Intentions to eat healthily Being fluent in English
Methods (3)
Intention Behaviour
Mea
sure
s
Baseline After 48 hours
“ How many snacks/ F&V do you expect to consume tomorrow?”
“ How many snacks/ F&V did you consume yesterday/ the day before yesterday?”
Analysis Plan (1)
Measuring the Association between EF & Diet
Spearman’s Rank Correlation matrix: EF measures vs Dietary Behaviour
Multiple Regressions, controlling for age, gender, BMI, & years of education
Stroop Colour Word Interference Test (Inhibitory Control) ≈ FFQ (Snacks)
Verbal Fluency- Category Switching (Mental Flexibility) ≈ FFQ (F&V)
Tower Task (Working Memory) ≈ FFQ (Snacks) & FFQ (F&V)
Concordance between BRIEF-A & D-KEFS
Analysis Plan (2)
Intention-Behaviour Gap
Subtract Behaviour from Intention
Multiple Regression
1. Inhibitory Control performance predicted the size of the I – B gap for unhealthy snacking
2. Mental Flexibility performance predicted the size of the I- B gap for F&V consumption
3. Working Memory performance predicted the size of the I-B gap for unhealthy snacking + F& V consumption
Discussion (1)
Link to Dual Process Models (Strack & Deutsch, 2006): EF- an important component of the Reflective System
Link to Temporal Self-Regulation Theory (Hall & Fong (2007; 2015): EF directly associated with behaviour AND the intention-behaviour gap
Discuss the results in light of existing literature (e.g. Allom & Mullan, 2014)
Strengths Limitations
Use of objective measures
Validated measure of diet
The first study to assess all core facets of EF
Discussion (2)
Convenience sample ×
Small sample (n= 55) ×
Correlational nature of the data ×
Discussion (3)
Future Directions
Future studies could look at how EF relates to other processes known to influence the successful execution of health-related behaviours and behaviour change, such as self-efficacy and perceptions of control
Several variables which could have influenced the intention behaviour measure performance were not recorded or controlled for=> day of the week ( If “tomorrow” is Saturday/Sunday people might be more inclined on snacking than on days from the usual working week, i.e. Monday to Friday).
References
Adriaanse, M. A., Vinkers, C. D., De Ridder, D. T., Hox, J. J., & De Wit, J. B. (2011). Do implementation intentions help to eat a healthy diet? A systematic review and meta-analysis of the empirical evidence. Appetite, 56(1), 183-193.
Allan, J. L., Johnston, M., & Campbell, N. (2010). Unintentional eating. What determines goal-incongruent chocolate consumption?. Appetite, 54(2), 422-425.
Allan, J. L., Johnston, M., & Campbell, N. (2011). Missed by an inch or a mile? Predicting the size of intention–behaviour gap from measures of executive control. Psychology & Health, 26(6), 635-650.
Allom, V., & Mullan, B. (2014). Individual differences in executive function predict distinct eating behaviours. Appetite, 80, 123-130.
Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis-Kaplan executive function system: Technical manual. Psychological Corporation.
Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). Test review behavior rating inventory of executive function. Child Neuropsychology, 6(3), 235-238.
Hofmann, W., Friese, M., & Roefs, A. (2009). Three ways to resist temptation: The independent contributions of executive attention, inhibitory control, and affect regulation to the impulse control of eating behavior. Journal of Experimental Social Psychology, 45(2), 431-435.
References
Kumanyika, S. K., Bowen, D., Rolls, B. J., Van Horn, L., Perri, M. G., Czajkowski, S. M., & Schron, E. (2000). Maintenance of dietary behavior change. Health Psychology, 19(1S), 42.
Masson, L. F., McNeill, G., Tomany, J. O., Simpson, J. A., Peace, H. S., Wei, L., ... & Bolton-Smith, C. (2003). Statistical approaches for assessing the relative validity of a food-frequency questionnaire: use of correlation coefficients and the kappa statistic. Public health nutrition, 6(03), 313-321.
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive psychology, 41(1), 49-100.
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.O'Brien, G., & Davies, M. (2007). Nutrition knowledge and body mass index. Health education research, 22(4), 571-575.
Riggs, N. R., Huh, J., Chou, C. P., Spruijt-Metz, D., & Pentz, M. A. (2012). Executive function and latent classes of childhood obesity risk. Journal of behavioral medicine, 35(6), 642-650.
Williams, P. G., & Thayer, J. F. (2009). Executive functioning and health: Introduction to the special series. Annals of Behavioral Medicine, 37(2), 101-105.