METABOLIC STATE ALTERS
ECONOMIC DECISION MAKING
UNDER RISK IN HUMANS – A
CRITIQUE
Symmonds, Emmanuel, Drew, Batterham & Dolan, 2010
OVERVIEW:
METHODS
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19 men with BMI of 22.6±1.7
Anthropometric measurements were taken
Standardisation procedure
Fasting until the next morning
Blood samples were taken to measure glucose, acylghrelin and leptin
• Standardised meal
• Multiple paired lottery choice task
MULTIPLE PAIRED LOTTERY
CHOICE TASK
Symmonds et al. (2010).
OVERVIEW: RESULTS & CONCLUSION
Results:
Risk-taking increases immediately and for up to an
hour after a meal. Correlations with leptin & acylghrelin.
Conclusions:
Risk preferences in humans is affected by metabolic
state.
PROSPECT THEORY
This paper aims to provide a real world application of
Prospect Theory.
Prospect Theory focuses on gains and losses, rather
than on final wealth position (Markowitz, 1952).
Direct analogies from animals' foraging behaviour have
been drawn from Prospect Theory's account
of the relationship between risk-taking and reference
points.
CRITIQUE- PARTICIPANTS
• Small sample size- only 19 participants' data included in
most of the final analyses
• All male sample- could affect risk taking (Wang et al. 2009)
• Participants' nationalities are not known- levels of risk
aversion affected by culture (Weber and Hsee, 1998) (Tse et
al. 1988)
CRITIQUE- PARTICIPANTS
• Volunteer sample
– Greater sociability (Rosenthal, 1965, cited by Schultz, 1969)
– Generalised risk-taking & sociality (Zuckerman & Kuhlman, 2000 )
• Body fat & BMI differences- sample differed significantly from national
average
• No cognitive bias checks in participant selection (Raghunathan & Pham,
1999)
• Age range from 20-46 (Deakin et al, 2004)
CRITIQUE- METHODOLOGY
• Use of standardised meals for varied
participants
– Experience could be positive or negative
– Could be similar to or different from
normal diet
– Different effects on people with different
nutritional needs
CRITIQUE- METHODOLOGY
• Allowed to drink water during fasting period- may
have tried to make themselves feel full
• Not in a controlled environment during fastingtrusting participants not to eat
• Different eating rates among participants- finishing the
meal at different times
CRITIQUE- METHODOLOGY
• Fasting/ Satiated/ Post- satiated conditions occurred in the
same order each time- possibility for practice/fatigue
effects
• Took place over the same time period every day- variation
in mood during this period (Clark et al., 1989)
• Gambles are hypothetical- participants' choices may have
been different if they were actually risking money
CRITIQUE- RESULTS & CONCLUSION
• Significance level used for risk and body fat
correlation unsatisfactory
• Hunger may not directly affect risk. Hunger
may affect mood, which then affects risk,
for example
• Sample size neglect
• Confirmatory bias
– This is where researchers may look for data
to confirm their own beliefs/hypotheses.
POSITIVE METHODOLOGY CRITIQUES
1. Visual Analogue Scales good measure of hunger (Stubbs
et al, 2000)
2. Randomised lottery position to reduce habituation.
3. Same lottery choices across all conditions.
4. Performed an awareness check at debrief.
5. Unlimited time to make lottery decision.
6. Hunger levels underwent significant change.
POSITIVE CONCLUSION CRITIQUES
1. Conclusion adds to field of research by showing
findings not predicted by normative economic
theory.
2. Findings make interesting link under paradigm of
economic prospect theory.
3. Results have important implications to eating
disorders
4. The researchers had no declared competing
interests.
DIRECTIONS FOR FURTHER RESEARCH
1. Conduct study again using mixed gender/ all female
sample. (Dreber, Rand & Wernerfelt et al, 2011)
2. Conduct using larger sample size.
3. A study using recruited participants rather than
volunteers is essential in removing extraneous
variables. (Rosenthal, 1965, cited by Schultz, 1969;
Zuckerman & Kuhlman)
DIRECTIONS FOR FURTHER RESEARCH CONTINUED
4. Environment for fasting element should be more
controlled.
5. Vary time of day in future conditions.
6. Propose non-hypothetical gambling experiment.
REFERENCES
• Clark, L. A., Watson, D., & Leeka, J. (1989) Diurnal Variation in thePositive Affects.
Motivation and Emotion. 13 (3), 205-234
• Deakin, J., Aitken, M., Robbins, T., & Sahakian, B.J., (2004). Risk taking during
decision-making in normal volunteers changes with age. Journal of the
international neuropsychological society. 10 (4), 590-598
• Dreber A., Rand D.G., Wernerfelt, N., Garcia, J.R., Vilar, M.G., Lum, J.K., Zeckhauser,
R.,(2011). Dopamine and risk choices in different domains: Findings among serious
tournament bridge players. Journal of risk and Uncertainty. 43, (1), 19-38
• Human: Teen Brain Wired to Take Risks. Retrieved on 4 November, 2013 from
http://news.discovery.com/human/teenager-brain-risky-behavior.htm
• Kahneman, D., & Tversky, A. ( 1979). Prospect Theory: An Analysis of Decision under
Risk. Econometrica, 47(2), 263-292.
• Raghunathan, R., & Pham, M.T., (1999). All Negative Moods Are Not Equal:
Motivational Influences of Anxiety and Sadness on Decision Making, Organizational
Behaviour and Human Decision Processes. 79, (1) , 56–77
• Schultz, D. P. (1969). The Human Subject in Psychological Research. Psychological
Bulletin, 72(3), 214-228.
REFERENCES
• Stubbs, R.J., Hughes, D.A., Johnstone, A.M., Rowley, E., Reid, C., Stratton, R., Delargy, H.,
King, N., & Blundell, J.E., (2000). The use of visual analogue scales to assess motivation
to eat in human subjects: a review of their reliability and validity with an evaluation of
new hand-held computerized systems for temporal tracking of appetite ratings. British
Journal of Nutrition. 84 (4) p405-415.
• Symmonds M, Emmanuel JJ, Drew ME, Batterham RL, Dolan RJ (2010) Metabolic State
Alters Economic Decision Making under Risk in Humans. PLoS
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Thanos, P. K., Geliebter, A., Biegon, A., & Fowler, J. S. (2009). Evidence of gender
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