Behavioural decision research Wändi Bruine de Bruin Centre for Decision Research, Leeds University...
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Behavioural decision research
Wändi Bruine de BruinCentre for Decision Research, Leeds University Business School
Department of Engineering and Public Policy, Carnegie Mellon University
Overview
• Introduction to Centre for Decision Research
• Understanding and improving real-world decisions
• Example projects
• Conclusions
Overview
• Introduction to Centre for Decision Research
• Understanding and improving real-world decisions
• Example projects
• Conclusions
• Our Centre for Decision Research aims to understand people’s real-world decisions and test practical strategies for improvement
• We study how individuals make decisions about finance, health, food, sustainability, and so on
• We aim to provide evidence-based advice for practitioners and policy makers
• Our interdisciplinary centre spans the business school, health institute, earth & environment, engineering, transport studies
• Our links include Carnegie Mellon University, RAND Corporation, US Federal Reserve, Dutch Central Bank and others.
Our approach to behavioural decision making
http://www.leeds.ac.uk/decision-research/
Overview
• Introduction to behavioural decision making
• Understanding and improving real-world decisions
• Example projects
• Conclusions
Overview
• Introduction to behavioural decision making
• Understanding and improving real-world decisions
• Example projects
• Conclusions
A challenge for experts
• Experts in different domains aim to understand and improve how people make decisions
• However, experts often – Use wording that is too difficult– Fail to understand the difficulties people
face when making decisions
• As a result, their interventions are often found to be ineffective (if they are tested)
Example: Using difficult wording
Shelter in placeStay inside
Example: Omitting relevant information
Example: Omitting relevant information
1. Expert model: How should people make the decision?– Conduct interdisciplinary literature review – Convene expert panel
2. Lay model: How do people make the decision?– Conduct interviews to identify decision-relevant beliefs,
barriers, and wording– Conduct surveys to examine prevalence of beliefs and
associations with behaviour
3. Intervention: How can we inform people’s decisions? – Address beliefs and skills in wording people understand
4. Evaluation: Does the intervention work?– Randomized controlled study to test effect on
understanding and behaviour
Decision Research Approach
1. Expert model: How should people make the decision?– Conduct interdisciplinary literature review – Convene expert panel
2. Lay model: How do people make the decision?– Conduct interviews to identify decision-relevant beliefs,
barriers, and wording– Conduct surveys to examine prevalence of beliefs and
associations with behaviour
3. Intervention: How can we inform people’s decisions? – Address beliefs and skills in wording people understand
4. Evaluation: Does the intervention work?– Randomized controlled study to test effect on
understanding and behaviour
Modified Decision Research Approach
Overview
• Introduction to behavioural decision making
• Understanding and improving real-world decisions
• Example projects
• Conclusions
Overview
• Introduction to behavioural decision making
• Understanding and improving real-world decisions
• Example projects
• Conclusions
Sexually Transmitted Infections• Goal: To reduce sexually transmitted infections (STIs) in female
adolescents
• Background: Most sex education is ineffective and repeats basic facts
• Interviews and surveys: Female adolescents know about STIs and how to prevent them -- but lack important skills such as how to communicate with their partners
• Intervention: A DVD teaching negotiation skills rather than just basic facts reduced STIs compared to controls
• Take-home message: People may need more than just basic facts
(Bruine de Bruin et al., HIV/AIDS Prevention in Children and Youth, 2007; Downs et al., Social Science & Medicine, 2004)
15
Carbon Capture and Sequestration• Goal: To inform people’s perceptions of CCS
• Background: Public resistance to CCS may stop its widespread deployment
• Interviews and surveys: When people receive information about the risks and benefits of CCS, they focus on its risks and want to discuss alternatives such as wind and solar
• Intervention: Providing about the risks and benefits of all low-carbon electricity generation technologies reduces resistance to CCS
• Take-home message: People may need information about the risks and benefits of all available options
(Fleishman et al., Risk Analysis, 2010; Palmgren et al., Environmental Science and Technology, 2004)
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• Understanding and improving financial decision making by individuals in financial distress (funded by EU Marie Curie Fellowship)
• Understanding public preparedness for extreme weather events (funded by UK Department of Environment, Food, and Rural Affairs)
• Understanding older consumers’ decisions about health and retirement (funded by the US National Institute on Ageing)
• Helping consumers to save electricity through designing better electricity bills and feedback (funded by US Department of Energy)
• Helping kidney patients to make better treatment decisions through decision aids (funded by FIMDM)
Ongoing projects
• People’s decision problems may involve lack of information, lack of other skills, or difficulties in understanding experts’ recommendations, among other things
• Understanding how people make decisions is an important step towards designing effective interventions
• Understanding how people make decisions requires input from multiple academic disciplines and domain experts
Conclusions
Bruine de Bruin, W., Downs, J.S., & Fischhoff, B. (2007). Adolescents’ thinking about the risks and benefits of sexual behavior. In: Lovett, M.C. & Shah, P. (Eds.) Thinking with data. Mahwah, NJ: Erlbaum, pp. 421-439.
Bruine de Bruin, W., Downs, J.S., Fischhoff, B. & Palmgren, C. (2007). Development and evaluation of an HIV/AIDS knowledge measure for adolescents focusing on misunderstood concepts. HIV/AIDS Prevention in Children and Youth, 8, 35-57.
Downs, J.S., Murray, P.J., Bruine de Bruin, W., White, J.P., Palmgren, C. & Fischhoff, B. (2004). Interactive Video Behavioral Intervention to Reduce Adolescent Females' STD Risk: A Randomized Controlled Trial. Social Science & Medicine, 59, 1561-1572.
Fischhoff, B., Downs, J.S. & Bruine de Bruin, W. (1998). Adolescent Vulnerability: A framework for behavioral interventions. Applied and Preventive Psychology, 7, 77-94.
Fischhoff, B., Bruine de Bruin, W., Güvenç, U., Brilliant, L. & Caruso, D. (2006). Analyzing disaster risks and plans: An avian flu example. Journal of Risk and Uncertainty, 33, 131-149.
Fleishman, L., Bruine de Bruin, W., Morgan, M.G. (2010). Informed public preferences for electricity portfolios with CCS and other low-carbon technologies. Risk Analysis, 30, 1399-1410.
Krishnamurti, T., Schwartz, D., Davis, A., Fischhoff, B., Bruine de Bruin, W., Lave, L. & Wang, J. (2012). Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters. Energy Policy, 41, 790-797.
Morgan, M.G., Fischhoff, B., Bostrom, A., & Atman C. Risk communication: The mental models approach. New York, NY: Cambridge University Press.
Palmgren, C., Morgan, M.G., Bruine de Bruin, W. & Keith, D. (2004). Initial public perceptions of deep geological and oceanic disposal of carbon dioxide. Environmental Science & Technology, 38, 6441-6450.
Relevant references