Solving the obesity crisis: knowledge, nudge or nanny?

Curated on Posted on by Stefaan Verhulst

BioMedCentral Blog: ” The 5th Annual Oxford London Lecture (17 March 2015) was delivered by Professor Susan Jebb from Oxford University. The presentation was titled: ‘Knowledge, nudge and nanny: Opportunities to improve the nation’s diet’. In this guest blog Dr Helen Walls, Research Fellow at the London School of Hygiene and Tropical Medicine, covers key themes from this presentation.

“Obesity and related non-communicable disease such as diabetes, heart disease and cancer poses a significant health, social and economic burden in countries worldwide, including the United Kingdom. Whilst the need for action is clear, the nutrition policy response is a highly controversial topic. Professor Jebb raised the question of how best to achieve dietary change: through ‘knowledge, nudge or nanny’?

Education regarding healthy nutrition is an important strategy, but insufficient. People are notoriously bad at putting their knowledge to work. The inclination to overemphasise the importance of knowledge, whilst ignoring the influence of environmental factors on human behaviours, is termed the ‘fundamental attribution error’. Education may also contribute to widening inequities.

Our choices are strongly shaped by the environments in which we live. So if ‘knowledge’ is not enough, what sort of interventions are appropriate? This raises questions regarding individual choice and the role of government. Here, Professor Jebb introduced the Nuffield Intervention Ladder.

 

Nuffield Intervention Ladder
Nuffield Intervention Ladder
Nuffield Council on Bioethics. Public health ethical issues. London: Nuffield Council on Bioethics. 2007.

The Nuffield Intervention Ladder or what I will refer to as ‘the ladder’ describes intervention types from least to most intrusive on personal choice. With addressing diets and obesity, Professor Jebb believes we need a range of policy types, across the range of rungs on the ladder.

Less intrusive measures on the ladder could include provision of information about healthy and unhealthy foods, and provision of nutritional information on products (which helps knowledge be put into action). More effective than labelling is the signposting of healthier choices.

Taking a few steps up the ladder brings in ‘nudge’, a concept from behavioural economics. A nudge is any aspect of the choice architecture that alters people’s behaviour in a predictable way without forbidding options or significantly changing economic incentives. Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not.

Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not.

The in-store environment has a huge influence over our choices, and many nudge options would fit here. For example, gondalar-end (end of aisle) promotions create a huge up-lift in sales. Removing unhealthy products from this position could make a considerable difference to the contents of supermarket baskets.

Nudge could be used to assist people make better nutritional choices, but it’s also unlikely to be enough. We celebrate the achievement we have made with tobacco control policies and smoking reduction. Here, we use a range of intervention types, including many legislative measures – the ‘nanny’ aspect of the title of this presentation….(More)”

New surveys reveal dynamism, challenges of open data-driven businesses in developing countries

Curated on Posted on by Stefaan Verhulst

Alla Morrison at World Bank Open Data blog: “Was there a class of entrepreneurs emerging to take advantage of the economic possibilities offered by open data, were investors keen to back such companies, were governments tuned to and responsive to the demands of such companies, and what were some of the key financing challenges and opportunities in emerging markets? As we began our work on the concept of an Open Fund, we partnered with Ennovent (India), MDIF (East Asia and Latin America) and Digital Data Divide (Africa) to conduct short market surveys to answer these questions, with a focus on trying to understand whether a financing gap truly existed in these markets. The studies were fairly quick (4-6 weeks) and reached only a small number of companies (193 in India, 70 in Latin America, 63 in South East Asia, and 41 in Africa – and not everybody responded) but the findings were fairly consistent.

  • Open data is still a very nascent concept in emerging markets. and there’s only a small class of entrepreneurs/investors that is aware of the economic possibilities; there’s a lot of work to do in the ‘enabling environment’
    • In many regions the distinction between open data, big data, and private sector generated/scraped/collected data was blurry at best among entrepreneurs and investors (some of our findings consequently are better indicators of  data-driven rather than open data-driven businesses)
  • There’s a small but growing number of open data-driven companies in all the markets we surveyed and these companies target a wide range of consumers/users and are active in multiple sectors
    • A large percentage of identified companies operate in sectors with high social impact – health and wellness, environment, agriculture, transport. For instance, in India, after excluding business analytics companies, a third of data companies seeking financing are in healthcare and a fifth in food and agriculture, and some of them have the low-income population or the rural segment of India as an intended beneficiary segment. In Latin America, the number of companies in business services, research and analytics was closely followed by health, environment and agriculture. In Southeast Asia, business, consumer services, and transport came out in the lead.
    • We found the highest number of companies in Latin America and Asia with the following countries leading the way – Mexico, Chile, and Brazil, with Colombia and Argentina closely behind in Latin America; and India, Indonesia, Philippines, and Malaysia in Asia
  • An actionable pipeline of data-driven companies exists in Latin America and in Asia
    • We heard demand for different kinds of financing (equity, debt, working capital) but the majority of the need was for equity and quasi-equity in amounts ranging from $100,000 to $5 million USD, with averages of between $2 and $3 million USD depending on the region.
  • There’s a significant financing gap in all the markets
    • The investment sizes required, while they range up to several million dollars, are generally small. Analysis of more than 300 data companies in Latin America and Asia indicates a total estimated need for financing of more than $400 million
  • Venture capitals generally don’t recognize data as a separate sector and club data-driven companies with their standard information communication technology (ICT) investments
    • Interviews with founders suggest that moving beyond seed stage is particularly difficult for data-driven startups. While many companies are able to cobble together an initial seed round augmented by bootstrapping to get their idea off the ground, they face a great deal of difficulty when trying to raise a second, larger seed round or Series A investment.
    • From the perspective of startups, investors favor banal e-commerce (e.g., according toTech in Asia, out of the $645 million in technology investments made public across the region in 2013, 92% were related to fashion and online retail) or consumer service startups and ignore open data-focused startups even if they have a strong business model and solid key performance indicators. The space is ripe for a long-term investor with a generous risk appetite and multiple bottom line goals.
  • Poor data quality was the number one issue these companies reported.
    • Companies reported significant waste and inefficiency in accessing/scraping/cleaning data.

The analysis below borrows heavily from the work done by the partners. We should of course mention that the findings are provisional and should not be considered authoritative (please see the section on methodology for more details)….(More).”

White House Releases 150 Data Sets to Fight Climate Change

Curated on Posted on by Stefaan Verhulst

 at GovTech: “To support the president’s Climate Data Initiative, the White House revealed on Tuesday, April 7, a series of data projects and partnerships that includes more than 150 new open data sets, as well as commitments from Google, Microsoft and others to cultivate climate analysis.

The undertakings were released at a White House climate and health conference where John Holdren, director of the White House Office of Science and Technology Policy, pressed the need for greater data to compel decreases to greenhouse emissions.

“This is a science-based administration, a fact-based administration, and our climate policies have to be based on fact, have to be based on data, and we want to make those data available to everybody,” Holdren said.

The data initiative touches multiple agencies — including NASA, the Centers for Disease Control and Prevention, the National Institutes of Health and the Environmental Protection Agency — and is part of the White House proclamation of a new National Public Health Week, from April 6 to April 12, to spur national health solutions and awareness.

The 150-plus data sets are all connected to health, and are among the 560 climate-related data sets available on Data.gov, the U.S. government’s open data portal. Accompanying the release, the Department of Health and Human Services added a Health Care Facilities Toolkit on Toolkit.climate.gov, a site that delivers climate resilience techniques, strategies, case studies and tools for organizations attempting climate change initiatives.

Holdren was followed by White House Chief Data Scientist D.J. Patil, who moderated a tech industry panel with representatives from Google, Microsoft and GIS mapping software company Esri.

Google Earth Outreach Program Manager Allison Lieber confirmed that Google will continue to provide assistance with 10 million hours for high-performance computing for climate data projects — down from 50 million in 2014 — and the company will likewise provide climate data hosting on Google Earth….(More)”

Innovating for Impact in Public Policy

Curated on Posted on by Stefaan Verhulst

Post by Derek B. Miller and Lisa Rudnick: “Political systems across democratic countries are becoming more ideologically and politically divided over how to use increasingly limited resources. In the face of these pressures everyone wants results: they want them cheap and they want them now. This demand for better results is falling squarely on civil servants.

In the performance of their jobs, everyone is being asked to do more with less. This demand comes independent of theme, scope, or size of the public institution. It is as true for those working in transportation as it is for those in education or public health or international peace and security; whether in local government or at UN agencies; or else in the NGOs, think tanks, and community-based organizations that partner with them. Even private industry feels the squeeze.

When we say “do more with less” we mean more impact, better results, and more effective outcomes than ever before with less money and time, fewer people, and (often) less political support.

In taking a cue from the private sector, the public sector is looking for solutions in “Innovation.”

Innovation is the act of making possible that which was previously impossible in order to solve a problem. Given that present performance is insufficient to meet demand, there is a turn to innovation (broadly defined) to maximize resources through new methods to achieve goals. In this way, innovation is being treated as a strategic imperative for successful governance.

From our vantage point — having worked on innovation and public policy for over a decade, mostly from within the UN — we see two driving forces for innovation that we believe are going to shape the future of public policy performance and, by extension, the character of democratic governance in the years to come. Managing the convergence of these two approaches to innovation is going to be one of the most important public policy agendas for the next several decades (for a detailed discussion of this topic, see Trying it on for Size: Design and International Public Policy).

The first is evidence-based policymaking. The goal of evidence-based policymaking is to build a base of evidence — often about past performance —  so that lessons can be learned, best practices distilled, and new courses of action recommended (or required) to guide future organizational behavior for more efficient or effective outcomes.

The second force is going to be design. The field of design evolved in the crucible of the arts and not in the Academy. It is therefore a late-comer to public policy…(More)”

Bloomberg Philanthropies Launches $100 Million Data for Health Program in Developing Countries

Curated on Posted on by Stefaan Verhulst

Press Release: “Bloomberg Philanthropies, in partnership with the Australian government, is launching Data for Health, a $100 million initiative that will enable 20 low- and middle-income countries to vastly improve public health data collection.  Each year the World Health Organization estimates that 65% of all deaths worldwide – 35 million each year – go unrecorded. Millions more deaths lack a documented cause. This gap in data creates major obstacles for understanding and addressing public health problems. The Data for Health initiative seeks to provide governments, aid organizations, and public health leaders with tools and systems to better collect data – and use it to prioritize health challenges, develop policies, deploy resources, and measure success. Over the next four years, Data for Health aims to help 1.2 billion people in 20 countries across Africa, Asia, and Latin America live healthier, longer lives….

“Australia’s partnership on Data for Health coincides with the launch of innovationXchange, a new initiative to embrace exploration, experimentation, and risk through a focus on innovation,” said the Hon Julie Bishop MP, Australia’s Minister for Foreign Affairs. “Greater innovation in development assistance will allow us to do a better job of tackling the world’s most daunting problems, such as a lack of credible health data.”

In addition to improving the recording of births and deaths, Data for Health will support new mechanisms for conducting public health surveys. These surveys will monitor major risk factors for early death, including non-communicable diseases (chronic diseases that are not transmitted from person to person such as cancer and diabetes). With information from these surveys, illness caused by day-to-day behaviors such as tobacco use and poor nutrition habits can be targeted, addressed and prevented. Data for Health will take advantage of the wide-spread use of mobile phone devices in developing countries to enhance the efficiency of traditional household surveys, which are typically time-consuming and expensive…(More)”

The Healing Power of Your Own Medical Data

Curated on Posted on by Stefaan Verhulst

in the New York Times: “Steven Keating’s doctors and medical experts view him as a citizen of the future.

A scan of his brain eight years ago revealed a slight abnormality — nothing to worry about, he was told, but worth monitoring. And monitor he did, reading and studying about brain structure, function and wayward cells, and obtaining a follow-up scan in 2010, which showed no trouble.

But he knew from his research that his abnormality was near the brain’s olfactory center. So when he started smelling whiffs of vinegar last summer, he suspected they might be “smell seizures.”

He pushed doctors to conduct an M.R.I., and three weeks later, surgeons in Boston removed a cancerous tumor the size of a tennis ball from his brain.

At every stage, Mr. Keating, a 26-year-old doctoral student at the Massachusetts Institute of Technology’s Media Lab, has pushed and prodded to get his medical information, collecting an estimated 70 gigabytes of his own patient data by now. His case points to what medical experts say could be gained if patients had full and easier access to their medical information. Better-informed patients, they say, are more likely to take better care of themselves, comply with prescription drug regimens and even detect early-warning signals of illness, as Mr. Keating did.

“Today he is a big exception, but he is also a glimpse of what people will want: more and more information,” said Dr. David W. Bates, chief innovation officer at Brigham and Women’s Hospital.

Some of the most advanced medical centers are starting to make medical information more available to patients. Brigham and Women’s, where Mr. Keating had his surgery, is part of the Partners HealthCare Group, which now has 500,000 patients with web access to some of the information in their health records including conditions, medications and test results.

Other medical groups are beginning to allow patients online access to the notes taken by physicians about them, in an initiative called OpenNotes. In a yearlong evaluation project at medical groups in three states, more than two-thirds of the patients reported having a better understanding of their health and medical conditions, adopting healthier habits and taking their medications as prescribed more regularly.

The medical groups with OpenNotes programs include Beth Israel Deaconess Medical Center in Boston, Geisinger Health System in Pennsylvania, Harborview Medical Center in Seattle, the Mayo Clinic, the Cleveland Clinic and the Veterans Affairs department. By now, nearly five million patients in America have been given online access to their notes.

As an articulate young scientist who had studied his condition, Mr. Keating had a big advantage over most patients in obtaining his data. He knew what information to request, spoke the language of medicine and did not need help. The information he collected includes the video of his 10-hour surgery, dozens of medical images, genetic sequencing data and 300 pages of clinical documents. Much of it is on his website, and he has made his medical data available for research….

Opening data to patients raises questions. Will worried patients inundate physicians with time-consuming questions? Will sharing patient data add to legal risks? One detail in the yearlong study of OpenNotes underlines doctors’ concerns; 105 primary physicians completed the study, but 143 declined to participate.

Still, the experience of the doctors in the evaluation seemed reassuring. Only 3 percent said they spent more time answering patient questions outside of visits. Yet knowing that patients could read the notes, one-fifth of the physicians said they changed the way they wrote about certain conditions, like substance abuse and obesity.

Evidence of the benefit to individuals from sharing information rests mainly on a few studies so far. For example, 55 percent of the members of the epilepsy community on PatientsLikeMe, a patient network, reported that sharing information and experiences with others helped them learn about seizures, and 27 percent said it helped them be more adherent to their medications.

Mr. Keating has no doubts. “Data can heal,” he said. “There is a huge healing power to patients understanding and seeing the effects of treatments and medications.”

Health information, by its very nature, is personal. So even when names and other identifiers are stripped off, sharing personal health data more freely with patients, health care providers and researchers raises thorny privacy issues.

Mr. Keating says he is a strong believer in privacy, but he personally believes that the benefits outweigh the risks — and whether to share data or not should be an individual’s choice and an individual responsibility.

Not everyone, surely, would be as comfortable as Mr. Keating is sharing all his medical information. But he says he believes that people will increasingly want access to their medical data and will share it, especially younger people reared on social networks and smartphones.

“This is what the next generation, which lives on data, is going to want,” Mr. Keating said….(More)”

Sensor Law

Curated on Posted on by Stefaan Verhulst

Paper by Sandra Braman: “For over two decades, information policy-making for human society has been increasingly supplemented, supplanted, and/or superceded by machinic decision-making; over three decades since legal decision-making has been explicitly put in place to serve machinic rather than social systems; and over four decades since designers of the Internet took the position that they were serving non-human (machinic, or daemon) users in addition to humans. As the “Internet of Things” becomes more and more of a reality, these developments increasingly shape the nature of governance itself. This paper’s discussion of contemporary trends in these diverse modes of human-computer interaction at the system level — interactions between social systems and technological systems — introduces the changing nature of the law as a sociotechnical problem in itself. In such an environment, technological innovations are often also legal innovations, and legal developments require socio-technical analysis as well as social, legal, political, and cultural approaches.

Examples of areas in which sensors are already receiving legal attention are rife. A non-comprehensive listing includes privacy concerns beginning but not ending with those raised by sensors embedded in phones and geolocation devices, which are the most widely discussed and those of which the public is most aware. Sensor issues arise in environmental law, health law, marine law, intellectual property law, and as they are raised by new technologies in use for national security purposes that include those confidence- and security-building measures intended for peacekeeping. They are raised by liability issues for objects that range from cars to ovens. And sensor issues are at the core of concerns about “telemetric policing,” as that is coming into use not only in North America and Europe, but in societies such as that of Brazil as well.

Sensors are involved in every stage of legal processes, from identification of persons of interest to determination of judgments and consequences of judgments. Their use significantly alters the historically-developed distinction among types of decision-making meant to come into use at different stages of the process, raising new questions about when, and how, human decision-making needs to dominate and when, and how, technological innovation might need to be shaped by the needs of social rather than human systems.

This paper will focus on the legal dimensions of sensors used in ubiquitous embedded computing….(More)”

Open Research, Open Data, Open Humans

Curated on Posted on by Stefaan Verhulst

Ernesto Ramirez at Quantified Self: ….“Open Humans aims to break down data silos in human health and research. We believe data has a huge potential to live and grow beyond the boundaries a single study or program. Our online portal allows members to aggregate data from the research they participate in. By connecting individuals willing to share existing research data about themselves with researchers who are interested in using that data, data can be re-used and built upon.” — OpenHumans.org

On March 24, 2015 the Open Humans Network officially opened their virtual doors and began allowing individuals to sign up and engage in a new model of participatory research. We spoke with Co-founder & Principal Investigator of the Public Data Sharing study, Madeleine Ball, Ph.D. about Open Humans, what it means for research, and what we can look foward to from this exciting initiative. The following is an edited transcript of that conversation….

What excites me about Open Humans is the potential we have to transform future research studies — from how they treat data to how they think about data sharing. We’re building our system so that participants are central to the data process. A good example of this when researchers use our member’s data they must also agree to return any new data that results from their research back to the original participant. This decentralization of data is a key component of our design. No single person, researchers, or study has all the data…(More)

Most text message health interventions were effective

Curated on Posted on by Stefaan Verhulst

Aditi Pai at MobiHealthNews: “A majority of published text message interventions between 2009 and 2014 that addressed diabetes self-management, weight loss, physical activity, smoking cessation, and medication adherence were effective, according to a systematic review of reviews published in The Annual Review of Public Health.

The review looked at 15 studies that reviewed 228 text message intervention studies addressing health promotion, disease prevention, and chronic disease self management. Study sizes ranged from 10 to 5,800 participants.

When the researchers assessed the reviews by effectiveness, they reported five of the 15 reviews — focused on a wide range of disease prevention and health promotion topics — found text messaging interventions had “statistically significant positive effects on health outcomes and/or behaviors”. These reviews looked at studies that focused on smoking cessation, physical activity, weight loss, and chronic disease self-management.

Three of the 15 reviews focused on physical activity, diet, and weight loss. One of these reviews reported that six out of 13 studies found a statistically significant clinical outcome. A meta-analysis of these studies found that participants in the study had seven times greater weight loss on average than non-SMS control participants. 

Another review focused on physical activity, diet, and weight loss found that 11 of the 14 reviewed studies reported a decrease in weight. While five of 10 studies reported a reduction in body mass index, three of six studies reported a statistically significant increase in physical activity, and two of three studies found a reduction in blood pressure….(More)”

Methods to Protect and Secure “Big Data” May Be Unknowingly Corrupting Research

Curated on Posted on by Stefaan Verhulst

New paper by John M. Abowd and Ian M. Schmutte: “…As the government and private companies increase the amount of data made available for public use (e.g. Census data, employment surveys, medical data), efforts to protect privacy and confidentiality (through statistical disclosure limitation or SDL) can often cause misleading and compromising effects on economic research and analysis, particularly in cases where data properties are unclear for the end-user.

Data swapping is a particularly insidious method of SDL and is frequently used by important data aggregators like the Census Bureau, the National Center for Health Statistics and others, which interferes with the results of empirical analysis in ways that few economists and other social scientists are aware of.

To encourage more transparency, the authors call for both government statistical agencies as well as the private sector (Amazon, Google, Microsoft, Netfix, Yahoo!, etc.) to release more information about parameters used in SDL methods, and insist that journals and editors publishing such research require documentation of the author’s entire methodological process….(More)

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