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)

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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