Medical Decision Making Lab
Current Research
Meng Li, Helen,
Colby, and Gretchen Chapman
The default effect is the tendency for people to stick with the default
-- the option you will get if you don't specify otherwise. For example, in the US, organ donation has a
default of non-donor: If you don't say
anything, we assume that you don't want to donate your organs. You have to
specify your donor status explicitly (e.g., on your driver's license) if you do
want to donate. But many European
countries have a presumed consent default such that if you don't say anything,
we assume that you do want to be a
donor. If you don't want to donate, you have to specify that explicitly. We are conducting studies to see if the
default effect can be harnessed to nudge people toward the healthier option. In
one study, clinic patients get a letter telling them that they can make an
appointment for a flu shot (default=no appointment) or saying that they have
been automatically scheduled for an appointment which they can cancel
(default=appointment). We then compare vaccination rates in these two groups.
In another study, we are comparing pharmacy customers who are or are not signed
up for automatic prescription refills.
In a third study we are examining the default effect in dietary choices
-- specifically, the type of milk (whole or 2%) that cafes use when making
cappuccinos.
Chapman, G.B., Li, M., Colby, H., & Yoon, H. (2010). Opting in versus opting out of influenza
vaccination. JAMA, 304(1), 43-44.
Electricity
Consumption
Helen Colby and Gretchen
Chapman
How can we encourage people to use less residential electricity? In this study we are observing PSE&G
customer volunteers who either have or don't have a device installed in their
house that allows them to see their moment-to-moment electricity use. We will see whether this type of feedback
helps people to reduce their electricity use.
We are also examining whether feedback that follows principles of
behavioral decision making works better than other types of feedback.
Meng Li and
Gretchen Chapman
How do lay people value human life
when there are not enough health care resources to save everyone? Do they value all lives equally? Do they prioritize people who have many years
left to live because they will gain the most life-years from the intervention (years left)? Do they prioritize young people even if they
don't have many years left to live because they have not yet had their
"fair innings" (years lived)? We find that people use all of these metrics,
and which one they use depends on how you ask the question. The "all lives equal" metric is
advocated more often when people are asked directly about what principle they
support then when asked indirectly to allocate resources across different
groups of people. They are more likely
to use the years left metric if the
question is in the gain frame about saving lives and more likely to use the years lived metric if the question is in
the loss frame about preventing the loss of lives.
Li, M., Vietri, J., Galvani, A., & Chapman, G.B. (2010). How lay
people value life. Psychological Science, 21(2), 263-167.
Time Preferences
Haewon Yoon and Gretchen Chapman
Many
decisions involve trade-offs between immediate outcomes and more delayed
outcomes. Time preference is the extent to which the utility of an outcome is
discounted because of a delay and can be quantified as a discount rate, or the
percent increase in magnitude needed to offset a given delay. For example, if
the annual discount rate were 20%, then $1000 now would be just as attractive
as $1200 to be received in one year. Subjective discount rates can be inferred
from the trade-offs subjects are willing to make between smaller sooner (SS)
and larger later (LL) rewards.
People
sometimes show dynamic inconsistency in their time preferences. For example, in the evening you set the alarm
clock for an early hour because you prefer the long term rewards of a
productive work day (LL) over the shorter term rewards of sleeping in (SS).
However, the next morning when the alarm rings, your preference reverses and
you now prefer sleeping in (SS) over a productive workday (LL).
This
project involves formal computational modeling of the predictions that
different mathematical theories of decision making make about when decision
makers will show dynamic inconsistency.
The project also involves experiments where participants make choices
between sooner and later amounts of money so that we can compare different
methods for measuring temporal discount rates and also to examine how time
preference responses are affected by different ways of posing the question.
Helen Colby and Gretchen Chapman
This project examines
a variety of decision processes that are implicated when people make decisions
about saving or spending money. Many
people spend more and save less than they think they should. One question of
interest is how psychological principles can be used to encourage savings behavior. We especially focus on short-term savings
(e.g., saving up to buy a used car after college graduation). One set of studies found that people are more
willing to forgo discretionary spending in order to put the money toward a
savings goal if the goal is described as broken into subgoals (e.g., save $60
per week for 3 weeks) rather than just one total goal (e.g., save $180). Another set of studies finds that people are
less likely to spend cash on discretionary items if the cash is partitioned into
units the decision maker is reluctant to break, such as a $100 bill or a sealed
envelope containing $100 in smaller bills.
Yes, another study shows that, in a hypothetical scenario, people may
more money toward their credit card bill if the bill is segregated to show
individual items purchased in previous months and the percent yet to be paid
off on each item. In a related set of
studies we examine how making an investment decision for someone else differs
from making an investment decision for yourself.
Colby, H. &
Chapman, G.B. (under review). Savings,
subgoals, and reference points.
Colby, H. &
Chapman, G.B. (under revision). Effects
of asymmetric information in surrogate financial decision making.
Colby, H. &
Chapman, G.B. (under review). Don't break
the $100 bill: Large bills promote savings behavior.
Last updated June 17, 2011.
