BEHAVIORAL ECONOMICS FOR DUMMIES
Behavioral Economics For Dummies. That is all.
Hat tip: http://xkcd.com/1022/
BEHAVIORAL ECONOMICS FOR DUMMIES
Behavioral Economics For Dummies. That is all.
Hat tip: http://xkcd.com/1022/
HOW DO PEOPLE MAKE DECISIONS WHEN TIME IS LIMITED, INFORMATION UNRELIABLE, AND THE FUTURE UNCERTAIN?
A new reader on heuristics, Heuristics: The Foundations of Adaptive Behavior, has just been released. Full disclosure, your Decision Science News editor is author on two of the book’s chapters:
Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.). (2011). Heuristics: The Foundations of Adaptive Behavior. New York: Oxford University Press.
How do people make decisions when time is limited, information unreliable, and the future uncertain?
Based on the work of Nobel laureate Herbert Simon and with the help of colleagues around the world, the Adaptive Behavior and Cognition (ABC) Group at the Max Planck Institute for Human Development in Berlin has developed a research program on simple heuristics, also known as fast and frugal heuristics. In the social sciences, heuristics have been believed to be generally inferior to complex methods for inference, or even irrational.
Although this may be true in “small worlds” where everything is known for certain, we show that in the actual world in which we live, full of uncertainties and surprises, heuristics are indispensable and often more accurate than complex methods. Contrary to a deeply entrenched belief, complex problems do not necessitate complex computations. Less can be more. Simple heuristics exploit the information structure of the environment, and thus embody ecological rather than logical rationality.
Simon (1999) applauded this new program as a “revolution in cognitive science, striking a great blow for sanity in the approach to human rationality.” By providing a fresh look at how the mind works as well as the nature of rationality, the simple heuristics program has stimulated a large body of research, led to fascinating applications in diverse fields from law to medicine to business to sports, and instigated controversial debates in psychology, philosophy, and economics.
In a single volume, the present reader compiles key articles that have been published in journals across many disciplines. These articles present theory, real-world applications, and a sample of the large number of existing experimental studies that provide evidence for people’s adaptive use of heuristics.
“This volume makes a powerful case for the importance of fast and frugal heuristics in explaining a wide range of aspects of cognition. It brings together the latest developments in one of the most influential research programs in the decision sciences, and will provide a valuable stimulus for, and a challenge to, research across the field.”
– Nick Chater, Professor of Cognitive and Decision Sciences, University College London
TABLE OF CONTENTS
1. Homo heuristicus: Why Biased Minds Make Better Inferences.
Gerd Gigerenzer, and Henry Brighton
Part I: Theory
Opening the adaptive toolbox
2. Reasoning the Fast and Frugal Way: Models of Bounded Rationality.
Gerd Gigerenzer, and Daniel G. Goldstein
3. Models of Ecological Rationality: The Recognition Heuristic.
Daniel G. Goldstein and Gerd Gigerenzer
4. How Forgetting Aids Heuristic Inference.
Lael J. Schooler and R. Hertwig
5. Simple Heuristics and Rules of Thumb: Where Psychologists and Behavioral Biologists Might Meet.
John M.C. Hutchinson and Gerd Gigerenzer
6. Naive and Yet Enlightened: From Natural Frequencies to Fast and Frugal Decision Trees.
Laura Martignon, Oliver Vitouch, Masinori Takezawa, and Malcolm R. Forster
7. The Priority Heuristic: Making Choices without Trade-Offs.
Eduard Brandstätter, Gerd Gigerenzer, and Ralph Hertwig
8. One-Reason Decision making: Modeling Violations of Expected Utility Theory.
Konstantinos V. Katsikopoulos and Gerd Gigerenzer
9. The Similarity Heuristic.
Daniel Read and Yael Grushka-Cockayne
10. Hindsight Bias: A By-Product of Knowledge Updating?
Ulrich Hoffrage, Ralph Hertwig, and Gerd Gigerenzer
How are heuristics selected?
11. SSL: A Theory of How People Learn to Select Strategies.
Jörg Rieskamp and Philipp E. Otto
Part II: Tests
When do heuristics work?
12. Fast, Frugal, and Fit: Simple Heuristics for Paired Comparison.
Laura Martignon and Ulrich Hoffrage
13. Heuristic and Linear Models of Judgment: Matching Rules and Environments.
Robin M. Hogarth and Natalia Karelaia
14. Categorization with Limited Resources: A Family of Simple Heuristics.
Laura Martignon, Konstantinos V. Katsikopoulo, and Jan K. Woike
15. A Signal Detection Analysis of the Recognition Heuristic.
Timothy J. Pleskac
16. The Relative Success of Recognition-Based Iinference in Multichoice Decisions.
Rachel McCloy, C. Philip Beaman, and Philip T. Smith
When do people rely on one good reason?
17. The Quest for Take-the-Best.
18. Empirical Tests of a Fast and Frugal Heuristic: Not Everyone “Takes-the-Best.”
Ben R. Newell, Nicola J. Weston, and David R. Shanks
19. A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making.
F. Bryan Bergert and Robert M. Nosofsky
20. Sequential Processing of Cues in Memory-Based Multi-Attribute Decisions.
Arndt Bröder and Wolfgang Gaissmaier
21. Does Imitation Benefit Cue-OrderLlearning?
Rocio Garcia-Retamero, Masanori Takezawa, and Gerd Gigerenzer
22. The Aging Decision Maker: Cognitive Aging and the Adaptive Selection of Decision Strategies.
Rui Mata, Lael J. Schooler, and Jörg Rieskamp
When do people rely on name recognition?
23. On the Psychology of the Recognition Heuristic: Retrieval Primacy as a Key Determinant of its Use.
Thorsten Pachur and Ralph Hertwig
24. The Recognition Heuristic in Memory-Based Inference: Is Recognition a Non-Compensatory Cue?
Thorsten Pachur, Arndt Bröder, and Julian N. Marewski
25. Why You Think Milan is Larger than Modena: Neural Correlates of the Recognition Heuristic.
Kirsten G. Volz, Lael J. Schooler, Ricarda I. Schubotz, Markus Raab, Gerd Gigerenzer, and D. Yves von Cramon
26. Fluency Heuristic: A Model of How the Mind Exploits a By-Product of Information Retrieval.
Ralph Hertwig, Stefan M. Herzog, Lael J. Schooler, and Torsten Reimer
27. The Use of Recognition in Group Decision Making.
Torsten Reimer and Konstantinos V. Katsikopoulos
Part III: Heuristics in the Wild
28. Psychological Models of Professional Decision Making.
Mandeep K. Dhami
29. Geographic Profiling: The Fast, Frugal, and Accurate Way.
Brent Snook, Paul J. Taylor, and Craig Bennel
30. Take-the-Best in Expert-Novice Decision Strategies for Residential Burglary.
Rocio Garcia-Retamero and Mandeep K. Dhami
31. Predicting Wimbledon Tennis Results 2005 by Mere Player Name Recognition.
Benjamin Scheibehenne and Arndt Bröder
32. Heuristics in Sports That Help Ws Win.
W.M. Bennis and Torsten Pachur
33. How Dogs Navigate to Catch Frisbees.
Dennis M. Shaffer, Scott M. Krauchunas, Marianna Eddy, and Michael K. McBeath
34. Optimal versus Naïve Diversification: How Inefficient is the 1/N Portfolio Strategy?
Victor DeMiguel, Lorenzo Garlappi, and Raman Uppal
35. Parental Investment: How an Equity Motive Can Produce Inequality.
Ralph Hertwig, Jennifer Nerissa Davis, and Frank J. Sulloway
36. Instant Customer Base analysis: Managerial Heuristics Often “Get It Right.”
Markus Wübben and Florian v. Wangenheim
37. Green Defaults: Information Presentation and Pro-Environmental Behavior.
Daniel Pichert and Konstantinois V. Katsikopoulos
38. “If …”: Satisficing Algorithms for Mapping Conditional Statements onto Social Domains.
Alejandro López-Rousseau and Timothy Ketelaar
39. Applying One-Reason Decision Making: The Prioritisation of Literature Searches
Michael D. Lee, Natasha Loughlin, and Ingrid B. Lundberg
40. Aggregate Age-at-Marriage Patterns from Individual Mate-Search Heuristics.
Peter M. Todd, Francesco C. Billari, and Jorge Simão
MORAL HAZARDS AND WOMEN’S LACROSSE
The New York Times just ran a piece called “A Case Against Helmets in Lacrosse“.
The hook of the article is that wearing helmets, which one would expect to make the game safer, could make the game more dangerous. Let’s review the quotes.
It’s hard to absolutely prove, but what we’ve seen is that behavior can change when athletes feel more protected, especially when it comes to the head and helmets,” said Dr. Margot Putukian, Princeton’s director of athletic medicine services and chairwoman of > the U.S. Lacrosse safety committee. “They tend to put their bodies and heads in danger that they wouldn’t without the protection. And they aren’t as protected as they might think.”
Then again, other sports have spent the last several years realizing that safety equipment can bring dangers of its own. Checking in professional hockey became considerably more vicious with the adoption of helmets in the 1970s and ’80s, and football players felt so protected by their helmets and face masks that head-to-head collisions became commonplace at every age level.
Three (re: protective eyewear in Women’sLacrosse):
[Someone] said that after the move to make eyewear mandatory for the 2005 season, “It’s subconscious, but you see harder checking, and rougher play.”
Interesting topic! Let’s get Dan and Peter’s take on it:
This is an example of moral hazard, which the Wikipedia (at least during the last five minutes) defines as a situation in which “a party insulated from risk behaves differently than it would behave if it were fully exposed to the risk.” The top 10 Google Scholar papers with “moral hazard” in the title have over 10,000 collective citations. You hear a lot about moral hazards, for example, that people began driving more recklessly when seat belts were invented, at cocktail parties, coffee breaks, dinners with visiting speakers, and other moments in which people say what they really think.
Is it possible that requiring lacrosse players to wear helmets will increase risk to players? I doubt it. My grounds for skepticism? TCTBT: too cute to be true.
TCTBT (also “too clever to be true”) arguments survive not because they are correct, or supported by the best evidence, but because they are elegant, counter-intuitive, and make a person sound smart at a cocktail party. They fly well in Op-Ed pieces, keynote speeches, and other places where one is unlikely to be asked for evidence.
The smart thing to do when you hear a TCTBT explanation is to doubt it. Since repeating a clever explanation is clearly its own reward, how is one to say that the person offering it is well-informed or just trying to be conversationally brilliant?
While I feel that moral hazard is overhyped, I must admit that I’ve gone spelunking with a helmet and without a helmet, and yes, a person does let his head bump against the cave walls more often with the helmet on than off. However, the net impact to your head is less with the helmet on. This is what I would expect to happen in lacrosse. More helmets will bump against helmets, which seems more ‘violent’, but the net noggin impact will be less. And despite popular belief, they have rules in lacrosse, so the temptation to run helmet first into people may not even have an advantage.
Interestingly, the article says, “checking in professional hockey became considerably more vicious with the adoption of helmets in the 1970s and ’80s”. Again, correlation, is not causation. And is ‘viciousness’ measured in injuries?
I say let Moral Hazards join Prisoner’s Dilemmas, Tragedies of the Commons, and other cleverly constructed scenarios that don’t arise in proportion to the vast numbers of articles written about them. Pay more attention to boring things like default effects that exert large and demonstrable influences on hundreds of decisions in daily life.
That said, I know nothing about lacrosse except that I watched Pete play it once, so without further ado, I’ll turn the typing over to him. If you have empirical evidence of moral hazards we should be concerned about, please post in the comments.
As someone with more than 30 years of (combined) lacrosse coaching and playing experience, my intuition leads me to believe that introducing helmets into the women’s game will increase the behaviors that put players at risk of injury. However, given that I regularly lecture on the fallibility of intuition, I also agree with Dan. I would like to see causal evidence before drawing a line in the sand. More important than just examining if helmets increase risky behavior, the analysis for deciding to institute helmets would need to balance the costs of the risky behavior against the benefits of the helmet. That is, the temporary bumps and bruises caused by more aggressive play may be worth incurring in order to reduce the risk of concussion. In that way, a thorough risk analysis would seem to be worth the price given the many thousands of women and girls who play the game.
The question of wearing a helmet creates a moral hazard in the game of lacrosse is complicated because the presence of the helmet would seem to influence more than just the offensive and defensive player’s behavior. The protection that a helmet provides could influence the way that the official monitors the game. Officials could more laxly (no pun intended) enforce the rules because they perceive the aggressive behavior as less risky, which in turn could further increase aggressiveness.
One last way to think about the helmet debate is to consider how much the debate is being colored by tradition (aka the status quo). And in this way, a useful question would be, if a new sport like lacrosse was created, would helmets be required given the emerging evidence about the risks of concussion?
TYPES OF DEFAULTS AND HOW TO SET THEM
Defaults are settings or choices that apply to individuals who do not take active steps to change them (Brown & Krishna, 2004). Collections of default settings, or “default configurations” determine the way products, services, or policies are initially encountered by consumers, while “reuse defaults” come into play with subsequent uses of a product. At the finest level, a single question can have “choice option default”, which on electronic forms can take the shape of a pre-checked box (Johnson, Bellman, and Lohse, 2002).
Defaults have been shown to have strong effects on real-world choices in domains including investment (Cronqvist & Thaler, 2004; Madrian & Shea, 2001), insurance (Johnson et al, 2003), organ donation (Johnson & Goldstein, 2004), marketing (Goldstein et al, 2008) and beyond.
They have a wide appeal among marketers and policy makers in that they guide choice while at the same time preserving freedom to choose. They are often regarded as the prototypical instruments of libertarian paternalism (Sunstein & Thaler, 2003).
Through default-setting policies, choice architects exhibit influence over resulting choices. The palette of policies includes simple defaults (choosing one default for all audiences), random defaults (assigning a configuration at random, for instance, as an experiment), forced choice (withholding the product or service by default, and releasing it only after an active choice is made), and sensory defaults (those that change according to what can be inferred about the user, for example, web sites that change language based on the visitor’s IP address).
Products and services that are re-used can also avail themselves of persistent or reverting defaults (which, respectively, remember or forget the last changes made to the default configuration) and predictive defaults (which intelligently alter reuse defaults based on observation of the user).
Those setting defaults should be aware of the ethical risks involved (Smith, Goldstein & Johnson, 2010). The ethical acceptability of using a default to guide choice has much to do with the reason why the default has an effect in the first place. When consumers are aware that defaults may be recommendations in some cases and manipulation attempts in other cases (Brown & Krishna), they exhibit a level of “marketplace metacognition” that suggests they retain autonomy and freedom of choice. However, if defaults are effective because consumers are not aware that they have choices, or because the transaction costs of changing from the default are too high, defaults impinge upon consumer autonomy. An often prudent policy, though not a cure-all, is to set the default to the alternative most people prefer when making an active choice, without time pressure, in the absence of any default. Running an experiment on a sample of the greater population can determine these preferences, and can be done in little time and at a low cost in the age of Internet experimentation (Gosling & Johnson, 2010).
Brown, Christina L. and Aradhna Krishna (2004), “The Skeptical Shopper: A Metacognitive Account for the Effects of Default Options on Choice,” Journal of Consumer Research, 31 (3), 529-539.
Cronqvist, Henrik and Richard H. Thaler (2004), “Design Choices in Privatized Social Security Systems: Learning from the Swedish Experience,” American Economic Review, 94 (2), 424-428.
Goldstein, Daniel G., Eric J. Johnson, Andreas Herrman, and Mark Heitmann (2008), “Nudge Your Customers Toward Better Choices,” Harvard Business Review, December, 99-105.
Gosling, Samuel D. and John A. Johnson (2010), Advanced methods for conducting online behavioral research. Washington, DC: American Psychological Association.
Johnson, Eric J., Steven Bellman, and Gerald L. Lohse (2002), “Defaults, Framing, and Privacy: Why Opting In Is Not Equal To Opting Out,” Marketing Letters, 13 (1), 5–15.
Johnson, Eric J. and Daniel G. Goldstein (2003), “Do Defaults Save Lives?” Science, 302, 1338-1339.
Johnson, Eric J., John Hershey, Jacqueline Meszaros, and Howard Kunreuther (1993), “Framing, Probability Distortions, and Insurance Decisions,” Journal of Risk and Uncertainty, 7, 35-53.
Madrian, Brigitte C. and Dennis F. Shea, D. F. (2001), “The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior,” Quarterly Journal of Economics, 116 (4), 1149-1187.
Thaler, Richard, Daniel Kahneman and Jack L. Knetsch (1992), “The Endowment Effect, Loss Aversion and Status Quo Bias,” in Richard Thaler, The Winner’s Curse, Princeton: Princeton University Press, 63-78.
Samuelson, William and Richard Zeckhauser (1988), “Status Quo Bias in Decision Making,” Journal of Risk and Uncertainty, 1 (1), 7-59.
Smith, N. Craig, Daniel G. Goldstein, and Eric J. Johnson (2010). Choice without Awareness: Ethical and Policy Implications of Defaults. Working paper.
Sunstein, Cass R. and Richard H. Thaler (2003), “Libertarian Paternalism Is Not an Oxymoron,” The University of Chicago Law Review, 70 (4), 1159-1202.
DSN OF THE WEEK
Attari, S. Z., DeKay, M. L., Davidson, C. I., & Bruine de Bruin, W. (in press). Public perceptions of energy consumption and savings. Proceedings of the National Academy of Sciences of the United States of America.
In a national online survey, 505 participants reported their perceptions of energy consumption and savings for a variety of household, transportation, and recycling activities. When asked for the most effective strategy they could implement to conserve energy, most participants mentioned curtailment (e.g., turning off lights, driving less) rather than effciency improvements (e.g., installing more effcient light bulbs and appliances), in contrast to experts’ recommendations. For a sample of 15 activities, participants underestimated energy use and savings by a factor of 2.8 on average, with small overestimates for low-energy activities and large underestimates for high-energy activities. Additional estimation and ranking tasks also yielded relatively flat functions for perceived energy use and savings. Across several tasks, participants with higher numeracy scores and stronger proenvironmental attitudes hadmore accurate perceptions. The serious defciencies highlighted by these results suggest that well-designed efforts to improve the public’s understanding of energy use and savings could pay large dividends.
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Peter McGraw, who is a big (in the sense of “notable” and in the sense of “six foot five inches tall” ) Decision Making researcher has launched a new
There’s a nice profile of the man here: What makes us laugh? Professor Peter McGraw thinks he’s found the answer to one of humanity’s greatest questions
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Here is a cool paper documenting an amusing sort of less-is-more effect in which professionals do worse than laypeople in a crime-solving task. In addition, learning valid information decreases people’s accuracy. That said, logisitic regression beats ‘em all, which doesn’t fit the less-is-more theme, but then again, logistic regression is less than human.
Bennell, C; Bloomfield, S; Snook, B; Taylor, P; Barnes, C. (2010). Linkage analysis in cases of serial burglary: comparing the performance of university students, police professionals, and a logistic regression model. Psychology, Crime and Law 16 (6), 507-524.
University students, police professionals, and a logistic regression model were provided with information on 38 pairs of burglaries, 20% of which were committed by the same offender, in order to examine their ability to accurately identify linked serial burglaries. For each offense pair, the information included: (1) the offense locations as points on a map, (2) the distance (in km) between the two offenses, (3) entry methods, (4) target characteristics, and (5) property stolen. Half of the participants received training informing them that the likelihood of two offenses being committed by the same offender increases as the distance between the offenses decreases. Results showed that students outperformed police professionals, that training increased decision accuracy, and that the logistic regression model achieved the highest rate of success. Potential explanations for these results are presented, focusing primarily on the participants’ use of offense information, and their implications are discussed.
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Finally, Isaac Dinner and I are working on a thought piece that applies our research on defaults to the question of energy conservation. It’s called:
We may add something about “reducing carbon emissions” to the title. We welcome feedback in the next week.
ASSOCIATION FOR CONSUMER RESEARCH CONFERENCE, OCT 7-10, 2010
What: The Association for Consumer Research Annual North American Conference [Website]
Where: Jacksonville, FL
Hotel: The Hyatt Regency [Map] [Booking]
When: OCT 7-10, 2010
Registration: Available now online
Early-bird deadline: Sept 1. Second price hike at Sept 25th.
ACR 2010 Jacksonville is open for registration!
Decision Science News notices that this year, the conference uses “green defaults”. Innovative! Check it out:
- You will have the option to opt out of the complete program given at the conference. You can build your own program on the ACR website by going to www.acrweb.org/acr and signing in. Once there, choose the “program” option, and you will see the new tool which you can utilize. Print your customized program and bring it with you!
- The default meal is vegetarian. You will have the option to opt out of the vegetarian meal.
Build-your-own-program is neat. We usually look at about half of the program, and end up needing about 20% of it at the conference. They have some other nudges as well:
- You will have the option of buying carbon offsets for your flight.
- You can choose the electronic version of the proceedings instead of a hardcover copy and receive a $20 discount.
The discount for the e-proceedings seems like a classic incentive. Decision Science News just registered and found that they used no default (forced choice) for this question. They could have made the default the green one and said “hardcover available for an extra $20″. In any case, we are glad to see research put to use.
SMARTPHONE UPLOADED PHOTOS AND VIDEOS REVEAL YOUR LOCATION BY DEFAULT
It wouldn’t be 2010 if people didn’t love going out, taking pictures with their iPhones and Blackberries and posting them online. It is not only a great way let your friends know what you are up to, it is a great way to unknowingly reveal your location and even home address to complete strangers.
Here’s how it goes down:
Annoyingly, the addition of geographic information to your photos is usually tough to switch off without completely switching off the otherwise useful GPS on your phone. It’s a case of dumb defaults where smart defaults are in order.
ICanStalkU.com, which went live in May, is designed to raise awareness of the privacy risks of geo-tagged images. The software behind the site looks for location data in images shared on Twitter. It then runs that data through Geonames, an online service that finds place names associated with latitude and longitude coordinates. The result is a stream of messages that identify the current location of Twitter users.
By tracking images posted on Twitter by a single user it is also possible to plot that user’s movements on a map, say Ben Jackson and Larry Pesce, security consultants based in Boston and Providence, Rhode Island, respectively, and the creators of the site. Jackson says he will unveil this mapping tool next week at the Hackers on Planet Earth conference in New York.
That slightly paranoid feeling one gets when posting content to the Web is now justified. It’s a bit of victory for the intuitive decision maker in all of us that resisting sharing private information when social networks were new, but has since been ignored.
A better way to set defaults: Nudge Your Customers Toward Better Choices
One bit of relief is that Facebook strips EXIF data from photos that get uploaded.
Tweet and location data faked. Maximum likelihood location of such a tweet is estimated to be 41.789841,-87.588823
CHOICE ARCHITECTURE ON WHEELS
Decision Science News was in a cab in Houston some years ago. The driver said that he did not like it when people paid by credit card, claiming that if the card turned out not to be good, it was his loss. DSN never really understood this. Perhaps in Houston they used the old-fashioned schoonk-schoonk credit card readers that don’t approve the card first? One would have thought the drivers would appreciate having less cash on hand, giving people less reason to rob them.
New York City cabs now have credit card readers and touch-screen computers in the back. They present the passenger with preconfigured tip options, which start at 15%. The passenger can enter his or her own tip, but this requires more typing. What does this do to the amount people tip? The data are in. It turns out that the cabbies get bigger tips when cards are used.
Why? Good question. Perhaps when people tip by cash they tend to round against the driver’s favor. Or perhaps the menu of choice options causes people to see the merits of tipping at least 15%. Or perhaps when the least-effort option is to tip 15% or more, people will go down the path of least resistance. Similar, but not totally similar to default effects, a specialty of the house here at Decision Science News.
P.S. DSN likes to use its PayPass. One simply holds his or her keychain (or special credit card) up to a PayPass reader in the back of the cab et voila, payment magically occurs. It is the ultimate in payment decoupling, you literally do not have to touch anything in order to pay. We see a future PhD thesis topic in this somewhere. Would not having to touch anything make you more likely to pay? Would you pay more?
GET $7,500,000 TO INVESTIGATE NUDGES IN MEDICINE
People who have suffered heart attacks can improve their chances by taking aspirin and other medicines. There is a great deal of research on this, yet, we still don’t see 100% of hospitals prescribing these drugs, and the rate of prescription varies from region to region. In general, the US government has noticed “surprisingly modest behavioral response of health care providers and health care systems to information concerning treatments or procedures judged to be superior”.
How can we get the health practitioners to make decisions in line with evidence?
The goods new for you, decision-science-researching reader, is that the National Institutes of Health (NIH) and Agency for Healthcare Research and Quality (AHRQ) are looking to give away $15 million dollars to fund two projects on the effectiveness of nudges on health care practices. The executive summary and parts of the background section make for some interesting reading. Sorry about all the abbrevs.
This NIH Funding Opportunity Announcement (FOA), supported by funds provided to the NIH and AHRQ under the American Recovery & Reinvestment Act of 2009 (“Recovery Act” or “ARRA”), Public Law 111-5, invites applications proposing clinical trials using the principles of behavioral economics to enhance the uptake of the results of comparative effectiveness research (CER) among health care providers in their practice. For this FOA, applicants must propose controlled trials that randomize units (whether individuals or clusters such as practices, hospitals, or larger units) to conditions, resulting in a randomized clinical trial (RCT) or cluster randomized trial (CRT). Research to foster the uptake of CER is seen to be necessary given the surprisingly modest behavioral response of health care providers and health care systems to information concerning treatments or procedures judged to be superior in CER trials. An additional possible benefit is that some behavioral economic interventions to promote the uptake of CER (e.g., those that rely on manipulating a provider’s default options) could be more cost effective than conventional approaches including some pay for performance schemes (P4P). For the purposes of this FOA, the definition of comparative effectiveness research will adhere to that adopted by the Federal Coordinating Council given at http://www.hhs.gov/recovery/programs/cer/cerannualrpt.pdf. Behavioral economics refers to the interdisciplinary efforts involving cognitive and social psychologists, decision scientists, and other social scientists together with economists to model economic decision-making and consequent actions. The approach is inclusive, since at its heart it tries to take into account what is known about how people actually make decisions rather than relying on the assumption that economic agents are fundamentally rational in the sense of expected utility theory (see, e.g., Kahneman and Tversky’s (1979) work on Prospect Theory and Kahneman’s (2003) Nobel lecture). It is hoped that this line of research will lead to significantly greater consideration of CER by health care providers and therefore enhance the quality of the nation’s health.
From the Background section:
Comparative effectiveness research (CER) holds significant promise to improve health care quality and potentially lower costs. It appears that knowledge of which procedures and treatments are comparatively effective may not be sufficient to change critical provider practices and crucial patient behaviors. For example, although the prescription of aspirin, beta blockers, and ACE inhibitors/ARBs after acute myocardial infarction (AMI) has been shown to be extremely effective in clinical trials, strongly endorsed by professional societies such as the American College of Cardiology, and used as a quality indicator by government organizations including the Centers for Medicare and Medicaid Services (CMS), rates of prescription for these drugs in hospitals following AMI show substantial regional and institutional variation and are still below 100% according to the 2008 AHRQ National Healthcare Quality Report (NHRQ). Even when comparatively effective treatments are prescribed, adherence to treatment can be disappointingly low. For example, approximately 50 percent of all AMI patients stop taking prescribed statins within two years of their event as late as the beginning of this decade (Jackevicius et al., 2002). Among asthmatics, only 32% took their preventive asthma medicine daily. Similar adherence problems exist among diabetics, resulting in poor health outcomes. Fewer than 60% of all adults age 40 and over with diagnosed diabetes have their blood sugar, cholesterol, or blood pressure under optimal control. Only 40.1% receive all three recommended services for diabetes, including an HbA1c measurement, a dilated eye examination, and a foot examination. (2008 AHRQ National Healthcare Quality Report)
It is generally presumed that both providers and patients respond to incentives and disincentives to change their behaviors, but to date, efforts to incentivize the uptake of CER have had only modest success. This funding opportunity seeks applications that will investigate whether the principles of behavioral economics could enhance the uptake of the results CER among health care providers and thus improve the health of patient populations. …
In the context of this FOA, behavioral economics refers to the interdisciplinary efforts involving cognitive and social psychologists, decision scientists, and other social scientists together with economists to model economic decision-making and consequent actions. The approach is inclusive, since at its heart it tries to take into account what is known about how people actually make decisions rather than relying on the assumption that economic agents are fundamentally rational in the sense of expected utility. As a field, behavioral economics seeks to understand how human social, cognitive, and emotional factors affect economic decisions. It considers the values assigned to all aspects of a choice, including, but not limited to monetary factors. In addition, behavioral economics acknowledges the important role that a specific context (or frame) may have on decisions, and takes into account people’s apparently irrational preferences (e.g., losses count more than gains, an object that is owned is more valuable than the same object that is not owned). For a recent review of behavioral economics from an economic perspective, Dellavigna (2009) is useful; from a psychological standpoint, Kahneman and Tversky (2000) and Kahneman (2003) provide useful data and historical context. There is growing evidence that such approaches may hold more promise than approaches based on either conventional theories of behavior change or neoclassical economics. The application of approaches from behavioral economics to the healthcare field could be valuable in the development of incentives or disincentives to motivate sustainable changes in provider and patient behavior.
It should be noted that the use of conventional economic incentives to affect provider behavior, including the uptake of CER, has been the subject of considerable research. Perhaps most germane to the topic of this FOA is the literature on “pay for performance”, also known as P4P. The logic of P4P is clear: rather than paying physicians or other health care providers (just) for the specific, billable, services they provide (which naturally incentivizes the ordering of more tests and procedures), they should be paid based on patient outcomes or on their achievement of other objective milestones that should be directly related to patient outcomes. In a classical economic context, it would be a puzzle if physicians and other treatment providers did not align their practice with the procedures or guidelines for practice that are incentivized. Strikingly, however, the evidence for the effectiveness of P4P schemes are often quite modest (reviewed by, e.g., Petersen et al., 2006). Although there are explanations in part for some of these incentive failures (e.g., the principal-agent problem), it seems clear that the incentive system could be improved. Further, many behavioral economists would argue that key improvements could be made not only in the design and delivery of incentives but also in the construction of the decision environment for the health care provider.
To date, implementation of behavioral economic approaches to change decision-making and behavior has focused primarily on economic topics such as behavioral finance (but see, e.g., Volpp et al., 2009 for a recent trial involving smoking cessation). The underlying ideas would seem to have much broader applicability. Behavioral economic interventions are generally of two basic types: one can restructure the choice environment, or manipulate the individual’s perceived incentives. One notable example of the former was Choi, Laibson, and Madrian’s (2004) intervention to increase retirement savings participation. By changing the default action to “contribute” they relied on behavioral inertia to maintain that level of participation. This is an example of altering behavior by manipulating the “choice architecture” that confronts individuals in daily life (see also Thaler and Sunstein, 2008). By structuring choice architectures to subvert individuals’ entrenched biases to stick with the status quo and discount future benefits, a well-developed system of so-called asymmetric paternalism (Loewenstein, Brennan, and Volpp, 2007) could provide interesting opportunities to induce change in provider behavior with respect to selecting a comparatively effective treatment while preserving a clinician’s freedom to choose an alternative treatment when the CER-recommended treatment is counter-indicated. One relevant example of the use of a default option approach that has been successfully implemented (albeit not in the context of CER per se) can be seen in places where statute or policy allows generic equivalents to be substituted for brand name drugs by pharmacists unless a physician specifically notes (or checks off a box denoting that) the prescription is to be “dispensed as written” (DAW). Here, the “transaction cost” of over-riding the default is almost zero, but the effect on generic dispensing rates can be quite large. In particular, generic drug utilization rates varied from 37 percent to 83 percent among Medicare Part D plans (Levinson, 2007), and it would appear that some of this variation is attributable to systemic factors that could be manipulated.
In addition to these more passive, environmental manipulations, behavioral economists have explored the manipulation of incentives to alter behavior. There has been particular interest in the use of deposit contracts, lotteries, and other monetary contingencies to effect health-related behavior change (e.g., Volpp et al. 2008). (Also note that some self-imposed commitment devices can be at least modestly effective at nearly zero external cost, e.g., Ariely and Wertenbroch, 2002). The effect of these devices is generally to allow individuals to overcome their own behavioral inertia, or to make continued compliance with recommended courses of action more attractive. Some of these techniques are similar in spirit to P4P, but the design of the incentives can be very different, and reflects what is known by psychologists about people’s preferences, and how those preferences can be manipulated. Like P4P, however, there can be concerns about the efficiency of providing incentives to reward behavior that would occur in any event, and questions concerning the overall cost effectiveness of monetary incentives. Trials supported by this funding opportunity will, of course, have the option to directly compare rates of uptake in incentivized and non-incentivized conditions, potentially leading to estimates of the marginal cost of the incentive.
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DRIVEN TO DISTRACTION
The headline E-mails ‘hurt IQ more than pot’ caught our attention here at DSN. Reading the article, we see that the study is not about intelligence as a trait being affected by internet interruptions. It simply uses an IQ test as a measure, we suppose, of being able to think clearly.
In any case, it is a worthwhile topic, and one that will only get more important as time goes on. Do the distractions of working in a networked world prevent us from reasoning well and making good decisions? Stanford prof Jeffrey Pfeffer argues this in his comment Stop Working for Technology – Make It Work For You.
This ties back into our favorite topics of defaults and information design. Most people don’t change the default settings when they install software. If one person has a default browser homepage that puts out constant interruptions (e.g., news flashes, email inbox, portfolio updates, etc), and another person has one that promotes getting work done (e.g., a featureless search engine box), who will get more work done? Who will feel better about what they have accomplished at the end of the week? Decision Science News is working on this topic and has some studies in the can.