Army looks to outsmart soldiers’ bad habits


 at the Army Times: “You wouldn’t think that moving the salad bar to the front of the chow hall and moving the dessert bar back 10 feet would make the Army healthier. But at Fort Campbell, Kentucky, that bumped up salad sales about 24 percent and dessert sales down 10 percent, a nudge toward goals of soldiers eating, exercising and sleeping healthier.

That’s just an example of the kind of change Army Medical Command hopes to inspire and successes it hopes to share across installations through its first annual Health of the Force report.

“I’m pretty proud of what we’ve been able to accomplish with this inaugural report,” said Col. Deydre Teyhen during a recent roundtable at Defense Health Agency headquarters in Falls Church, Virginia.  “I think we can’t get to a better state of health unless we inform people of what’s working out there in the field.”

The Army hopes to reduce the figure of 17 percent of soldiers not medically deployable within 72 hours. …The overarching philosophy of these recent MEDCOM efforts is to improve overall health rather than play whack-a-mole with problems as they arise. Teyhen pointed out that the average soldier is a patient at a health care facility for about 100 minutes per year, and the trick is to influence soldier health choices over the other 525,500 minutes, extending influence outside of brick-and-mortar health facilities.It dovetails with the Army’s Performance Triad, the plan to improve readiness through sleep, nutrition and exercise….(More)”

Calling Dunbar’s Numbers


Pádraig MacCarron, Kimmo Kaski, and Robin Dunbar at arXiv: “The social brain hypothesis predicts that humans have an average of about 150 relationships at any given time. Within this 150, there are layers of friends of an ego, where the number of friends in a layer increases as the emotional closeness decreases. Here we analyse a mobile phone dataset, firstly, to ascertain whether layers of friends can be identified based on call frequency. We then apply different clustering algorithms to break the call frequency of egos into clusters and compare the number of alters in each cluster with the layer size predicted by the social brain hypothesis. In this dataset we find strong evidence for the existence of a layered structure. The clustering yields results that match well with previous studies for the innermost and outermost layers, but for layers in between we observe large variability….(More)”

NEW Platform for Sharing Research on Opening Governance: The Open Governance Research Exchange (OGRX)


Andrew Young: “Today,  The GovLab, in collaboration with founding partners mySociety and the World Bank’s Digital Engagement Evaluation Team are launching the Open Governance Research Exchange (OGRX), a new platform for sharing research and findings on innovations in governance.

From crowdsourcing to nudges to open data to participatory budgeting, more open and innovative ways to tackle society’s problems and make public institutions more effective are emerging. Yet little is known about what innovations actually work, when, why, for whom and under what conditions.

And anyone seeking existing research is confronted with sources that are widely dispersed across disciplines, often locked behind pay walls, and hard to search because of the absence of established taxonomies. As the demand to confront problems in new ways grows so too does the urgency for making learning about governance innovations more accessible.

As part of GovLab’s broader effort to move from “faith-based interventions” toward more “evidence-based interventions,” OGRX curates and makes accessible the most diverse and up-to-date collection of findings on innovating governance. At launch, the site features over 350 publications spanning a diversity of governance innovation areas, including but not limited to:

Visit ogrx.org to explore the latest research findings, submit your own work for inclusion on the platform, and share knowledge with others interested in using science and technology to improve the way we govern. (More)”

The Evolution of Wikipedia’s Norm Network


Bradi Heaberlin and Simon DeDeo at Future Internet: “Social norms have traditionally been difficult to quantify. In any particular society, their sheer number and complex interdependencies often limit a system-level analysis. One exception is that of the network of norms that sustain the online Wikipedia community. We study the fifteen-year evolution of this network using the interconnected set of pages that establish, describe, and interpret the community’s norms. Despite Wikipedia’s reputation for ad hocgovernance, we find that its normative evolution is highly conservative. The earliest users create norms that both dominate the network and persist over time. These core norms govern both content and interpersonal interactions using abstract principles such as neutrality, verifiability, and assume good faith. As the network grows, norm neighborhoods decouple topologically from each other, while increasing in semantic coherence. Taken together, these results suggest that the evolution of Wikipedia’s norm network is akin to bureaucratic systems that predate the information age….(More)”

Applying Behavioral Economics to Public Health Policy


Jennifer L. Matjasko, et al in the American Journal of Preventive Medicine: “From the beginning, health has been recognized as a fertile area for applying nudges. The subtitle of the bookNudge is Improving Decisions about Health, Wealth, and Happiness. In their discussion of health behaviors, Thaler and Sunstein propose new nudges in health, such as simplifying decision making in Medicare. In fact, section 1511 of the Affordable Care Act requires large employers to automatically enroll workers into health insurance; similar to the previous example on organ donation, this switched from an opt-in to an opt-out system in order to harness the power of defaults. We will provide examples in which concepts from behavioral economics were applied to public health policy and led to improvements in health attitudes and behaviors. A summary of these applications is provided in Table 1.

Nudges can be effective because people are influenced by stimuli that are visible and new; thus, at least in theory, small changes can lead to behavior modification. Several studies have found that simply prompting (nudging) individuals to make a plan increases the probability of the subject eventually engaging in the prompted health behavior, such as immunizations, healthy eating, and cancer screening. For example, one study found that e-mailing patients appointment times and locations for their next influenza vaccination increased vaccination rates by 36%. Another intervention was even simpler. Rather than assigning a date and time for the patient to be vaccinated, patients were simply mailed a card that asked the patient to write down the day or day and time they planned to get the influenza vaccine (they were also sent the day and time of the free influenza vaccine clinics). Relative to a control condition (people who only received the information about the day and time of the clinics), those prompted to write down the day and time they planned to get the influenza vaccine were 4.2 percentage points (12.7%) more likely to receive the vaccine at those clinics. Those prompted to write down the date but not the time were not significantly more likely to be vaccinated at the clinics. Decision heuristics, such as highlighting consensus, may also help. Highlighting descriptive norms among a group of trusted experts, or priming (e.g., that 90% of doctors agree that vaccines are safe) can significantly reduce public concern about (childhood) vaccines and promote intentions to vaccinate.

The significant influence of framing has been demonstrated in many public health domains, such as messaging about blood transfusion,  smoking cessation, sunscreen use, and mammography utilization. In particular, gains-framed messages (i.e., emphasizing the health gains of a behavior or treatment) were more likely to have a positive impact on the attitudes toward activities targeting prevention (e.g., blood safety, sunscreen use, smoking cessation). Loss-based messages may be more effective at encouraging screening behaviors, such as mammography screening. This points to the importance of testing messages for the uptake of preventive services among varying subgroups, many of which are now covered without cost-sharing as a result of the coverage of preventive services mandated in the Affordable Care Act.

Detailed Illustrative Examples (More)”

What works?


Dan Davies at TheLong & Short: “Evidence-based policy is very much in fashion at the moment in all departments of government. Of course it’s a good idea; the main argument for it is summarised admirably by the name. But people who expect big things from evidence-based approaches ought to be really quite worried right now.

Because the methodology used in a lot of evidence-based policy analysis is very similar to that used in experimental psychology. And at the moment, psychology is a subject with some very serious methodological problems.

It’s being called the ‘reproducibility crisis’ and in summary, the problem is that large-scale and careful attempts to replicate some of the best-established and most important results of the last few decades are not finding the effects they were meant to find. This is even happening for effects like ‘ego depletion’ (the idea that resisting temptation requires effort and makes it harder to exercise willpower), which are the subject of dozens or even hundreds of research papers.

There appear to be two related problems. First, there is a knot of issues relating to methodology and the interpretation of statistical tests, which means that there is a systematic tendency to find too many statistically significant results. And second, it turns out that a lot of psychology results are just ‘fragile’ – they describe much smaller sets of individuals than hoped, and are very dependent on particular situations, rather than reflecting broad truths about humanity.

Both of these problems are likely to be shared by a lot of other areas. For example, the methodology of behavioural economics has a very big overlap with experimental psychology, and is likely to have many of the same reproducibility issues. So lots of ‘nudge’ schemes related to savings and pensions could be based on fragile results….(More)”

Innovation Prizes in Practice and Theory


Paper by Michael J. Burstein and Fiona Murray: “Innovation prizes in reality are significantly different from innovation prizes in theory. The former are familiar from popular accounts of historical prizes like the Longitude Prize: the government offers a set amount for a solution to a known problem, like £20,000 for a method of calculating longitude at sea. The latter are modeled as compensation to inventors in return for donating their inventions to the public domain. Neither the economic literature nor the policy literature that led to the 2010 America COMPETES Reauthorization Act — which made prizes a prominent tool of government innovation policy — provides a satisfying justification for the use of prizes, nor does either literature address their operation. In this article, we address both of these problems. We use a case study of one canonical, high profile innovation prize — the Progressive Insurance Automotive X Prize — to explain how prizes function as institutional means to achieve exogenously defined innovation policy goals in the face of significant uncertainty and information asymmetries. Focusing on the structure and function of actual innovation prizes as an empirical matter enables us to make three theoretical contributions to the current understanding of prizes. First, we offer a stronger normative justification for prizes grounded in their status as a key institutional arrangement for solving a specified innovation problem. Second, we develop a model of innovation prize governance and then situate that model in the administrative state, as a species of “new governance” or “experimental” regulation. Third, we derive from those analyses a novel framework for choosing among prizes, patents, and grants, one in which the ultimate choice depends on a trade off between the efficacy and scalability of the institutional solution….(More)”

Nudging voters


John Hasnas and Annette Hasnas at the Hill: “A perennial complaint about our democracy is that too large a portion of the electorate is poorly informed about important political issues. This is the problem of the ignorant voter. Especially this year, with its multiplicity of candidates, keeping track of the candidates’ various, and often shifting, policy positions can be extraordinarily difficult. As a result, many of those voting in the presidential primaries will cast their ballots with little idea of where the candidates stand on several important issues.

Isn’t there some way to nudge the voters into making more informed choices? Well, actually, yes, there is. But in making this claim, we use the word nudge advisedly.

Among contemporary policy analysts, “nudge” is a term of art. It refers to creating a context within which people make choices–a “choice architecture”–that makes it more likely that people will select one option rather than another. The typical example of a nudge is a school cafeteria in which fruits and vegetables are placed in front in easy to reach locations and less healthy fare is placed in less visible and harder to reach locations. No one is forced to select the fruit or vegetables, but the choice architecture makes it more likely that people will.
The key feature of a nudge is that it is not coercive. It is an effort to influence choice, not to impose it. People are always able to “opt out” of the nudge. Thus, to nudge is to design the context in which individuals make decisions so as to influence their choice without eliminating any options.

We think that nudging can be employed to help voters make more informed decisions in the voting booth.

Imagine the following scenario. A bipartisan good government group creates a list of the most significant contemporary policy issues. It then invites all candidates to state their positions on the issues. In the current campaign, candidates could be invited to state where they stand on gay marriage, immigration, intervention in Syria, climate change, tax reform, the minimum wage, gun control, income inequality, etc. This information would be collected and fed into the relevant election commission computer. When voters enter the voting booth, they would have the option of electronically recording their policy preferences on the same form that the candidates completed. The computer would display a ranking of the candidates on the basis of how closely their positions aligned with the voter’s. After receiving this information, voters would cast their ballots.

Our proposal is a nudge. It is completely non-coercive. No candidate would be required to complete the list of his or her policy positions, although refusing to do so might be viewed negatively by voters. No voter would be required to utilize the option. All would remain free to simply walk into the booth and cast their vote. Even those who utilize the option remain free to disregard its results and vote for whomever they please. The proposal simply alters the choice architecture of voting to build in access to a source of information about the candidates. Yet, it makes it more likely that citizens will cast more informed votes than they do at present….(More)”

Big data, meet behavioral science


 at Brookings: “America’s community colleges offer the promise of a more affordable pathway to a bachelor’s degree. Students can pay substantially less for the first two years of college, transfer to a four-year college or university, and still earn their diploma in the same amount of time. At least in theory. Most community college students—80 percent of them—enter with the intention to transfer, but only 20 percent actually do so within five years of entering college. This divide represents a classic case of what behavioralists call an intention-action gap.

Why would so many students who enter community colleges intending to transfer fail to actually do so? Put yourself in the shoes of a 20-something community college student. You’ve worked hard for the past couple years, earning credits and paying a lot less in tuition than you would have if you had enrolled immediately in a four-year college or university. But now you want to transfer, so that you can complete your bachelor’s degree. How do you figure out where to go? Ideally you’d probably like to find a college that would take most of your credits, where you’re likely to graduate from, and where the degree is going to count for something in the labor market. A college advisor could probably help you figure this out,but at many community colleges there are at least 1,000 other students assigned to your advisor, so you might have a hard time getting a quality meeting.  Some states have articulation agreements between two- and four-year institutions that guarantee admission for students who complete certain course sequences and perform at a high enough level. But these agreements are often dense and inaccessible.

The combination of big data and behavioral insights has the potential to help students navigate these complex decisions and successfully follow through on their intentions. Big data analytic techniques allow us to identify concrete transfer pathways where students are positioned to succeed; behavioral insights ensure we communicate these options in a way that maximizes students’ engagement and responsiveness…..A growing body of innovative research has demonstrated that, by applying behavioral science insights to the way we communicate with students and families about the opportunities and resources available to them, we can help people navigate these complex decisions and experience better outcomes as a result. A combination of simplified information, reminders, and access to assistance have improved achievement and attainment up and down the education pipeline, nudging parents to practice early-literacy activities with their kids or check in with their high schoolers about missed assignments, andencouraging students to renew their financial aid for college….

These types of big data techniques are already being used in some education sectors. For instance, a growing number of colleges use predictive analytics to identify struggling students who need additional assistance, so faculty and administrators can intervene before the student drops out. But frequently there is insufficient attention, once the results of these predictive analyses are in hand, about how to communicate the information in a way that is likely to lead to behavior change among students or educators. And much of the predictive analytics work has been on the side of plugging leaks in the pipeline (e.g. preventing drop-outs from higher education), rather than on the side of proactively sending students and families personalized information about educational and career pathways where they are likely to flourish…(More)”

How Google Optimized Healthy Office Snacks


Zoe ChanceRavi DharMichelle Hatzis and Michiel Bakker at Harvard Business Review: “Employers need simple, low-cost ways of helping employees make healthy choices. The effects of poor health and obesity cost U.S. companies $225 billion every year, according to the Centers for Disease Control, and this number is quickly rising. Although some employer-sponsored wellness programs have yielded high returns — Johnson & Johnson reported a 170% return on wellness spending in the 2000s — the employee wellness industry as a whole has struggled to prove its value.

 

Wellness initiatives often fail because they rely on outdated methods of engagement, placing too much emphasis on providing information. Extensive evidence from behavioral economics has shown that information rarely succeeds in changing behavior or building new habits for fitness and food choices. Telling people why and how to improve their health fails to elicit behavior changes because behavior often diverges from intentions. This is particularly true for food choices because our self-control is taxed by any type of depletion, including hunger. And the necessity of making food decisions many times a day means we can’t devote much processing power to each choice, so our eating behaviors tend to be habit- and instinct-driven. With a clearer understanding of the influences on choice — context and impulsivity, for instance — companies can design environments that reinforce employees’ healthy choices, limit potential lapses, and save on health care costs.

Jointly, the Google Food Team and the Yale Center for Customer Insights have been studying how behavioral economics can improve employee health choices. We’ve run multiple field experiments to understand how small “tweaks” can nudge behavior toward desirable outcomes and yield outsized benefits. To guide these interventions, we distilled scattered findings from behavioral science into a simple framework, the four Ps of behavior change:

  • Process
  • Persuasion
  • Possibilities
  • Person

The framework helped us structure a portfolio of strategies for making healthy choices easier and more enticing and making unhealthy choices harder and less tempting. Below, we present a brief example of each point of intervention….(More)”