Previous Columns From the Director

In 1982, Megatrends author John Naisbitt wrote, “The most exciting breakthroughs of the 21st century will not occur because of technology but because of an expanding concept of what it means to be human.” Now, almost three decades later, we are at a moment in time when technology actually has the potential to expand our concept of what it means to be human —that is, to better understand the complex interplay of the many factors critical to physical and mental health and well-being.

In the biomedical sciences, technical advances in genomics ⁽¹⁾ and neuroscience ⁽²⁾ and the emerging tools of nanotechnology ⁽³⁾ are transforming how we conduct science and understand our world. Similarly, the explosion of new technologies and networking capabilities ⁽⁴⁾ are producing data and tools that can revolutionize the behavioral and social sciences. Researchers are still in the earliest stages of tapping into the vast potential of an array of tools to contribute to human knowledge, including—

• personal mobile and network communications;
• transactional data capture;
• cyberinfrastructure for storing, integrating, and sharing data; and
• software development for modeling and simulation.

By capturing, combining, and analyzing data in new ways, we can begin to measure and understand phenomena that to date have been immeasurable in any reliable sense. This opens the door to new kinds of science. It expands our ability to sort through dynamically complex biological, behavioral, and social factors and begin to understand their relative influences on health.

New technologies already have begun to reshape behavioral and social science methods and knowledge. In recent decades, tools for measuring reaction times have been used to assess unconsciously held associations and prejudices ⁽⁵⁾. Geospatial positioning technologies have permitted researchers to locate individuals in physical space and to study how their environments influence their behaviors ⁽⁶⁾. New blood spot collection and assay tools have permitted the collection of biological measures outside the laboratory, making it possible for representative population surveys to explore the interface between biology, behavior, and environment ⁽⁷⁾. Portable hand-held or wearable devices have been used to study behavior as it unfolds, minimizing recall bias and maximizing validity of self-reported measures ⁽⁸⁾ and providing direct measures of physical activity ⁽⁹⁾.

Emerging technologies promise to exponentially expand this innovation. One of the most active new approaches to data collection involves the use of portable devices and the Web. Cell phones are not only diffusing rapidly around the globe; they are simultaneously evolving into complex, multipurpose personal communication devices, capable of transmitting text and photos as well as transactional and location information. The beauty of these technologies is their ability to collect information from people where they live, work, and play. The scientific literature is growing with reports of research in which mobile phones were used to collect information on behavior, for example, alcohol use in adults ⁽¹⁰⁾ or craving for cocaine in homeless populations ⁽¹¹⁾. Newly developed mobile phone applications assist users in tracking weight management, monitoring blood pressure, and adhering to medications ⁽¹²⁾).

Information on naturally occurring transactions, including health and administrative records, has been used in research for some time ^{(13, 14)}. But as our use of technology to capture the daily transactions of our lives gathers momentum, we create deep pools of data that could potentially be used for research ⁽¹⁵⁾. Not only electronic health records, but also records of credit card and grocery store purchases, cell phone usage and the clickstreams from on-line activities, are captured in real time. These data, accessed with appropriate permissions and protections, can provide unique information about the patterning of human behavior in space and time.

Then there is cyberspace. Online groups such as Facebook and MySpace produce a wealth of information that can be used to study social networks, social interactions, collaboration, and the sharing of information on the Internet ⁽¹⁵⁾. Online virtual worlds provided through games such as Second Life and World of Warcraft provide environments where people can work and interact in a somewhat realistic manner. The social, behavioral, and economic dynamics of these virtual worlds can be studied for their own sake, or treated as models of human and social behavior in the “real” world ⁽¹⁶⁾.

As the data pour in, we need methods for making sense of the billions of gigabytes that can be collected. The term cyberinfrastructure, first coined by the National Science Foundation, describes evolving research environments that support the acquisition, storage, management, integration, mining, visualization, and computing of data over the Internet. Cyberinfrastructure allows knowledge communities to “collaborate and communicate across disciplines, distances and cultures” ⁽⁴⁾ and to create “virtual organizations that transcend geographic and institutional boundaries” ⁽⁴⁾. Even more important, as these environments mature, they are likely to have a catalytic effect on research that seeks to integrate data and knowledge on the environmental, individual, and biological factors affecting health and behavior, and to use that knowledge to improve health. A key challenge will be interoperability – the ability to make diverse kinds of data work with each other.

Like cyberinfrastructure, systems modeling technologies allow us to better capture the complexity of the real word. New advances made possible by increases in computational power allow scientists to build increasingly sophisticated computer representations of complex systems. For example, models may combine assumptions about the behavior of discrete “agents” who interact over time, responding to each others’ actions and to community-level factors which may, in turn, change in response to the collective actions of the agents. Models can be run over time and be repeated with changes in the assumptions to obtain a distribution of possible outcomes. This knowledge can then be used to form hypotheses for new research. These technologies already are being used to understand how residential environments or neighborhoods may affect health ⁽¹⁷⁾, and to shed light on the projected outcomes of various interventions, for example, how a hypothetical population might be affected by upstream prevention of disease onset versus downstream prevention of disease complications ⁽¹⁸⁾.

The power of these tools cannot be overstated. Just as the Human Genome Project produced hundreds of megabytes of biological information, the collection of data on human behaviors, societies, and economies is likely to produce its own tsunami of data. It will take many years of advanced computing and informatics – and the informed use of innovations in grid computing, visualization techniques, and other novel analytic methods – to achieve a complete understanding of the patterns detected and what they mean for health.

Organizing and interpreting the data will require team science. In the words of Ben Shneiderman, “Science 2.0 will require a shift in priorities to promote integrative thinking that combines computer science know-how with social science sensitivity” ⁽¹⁹⁾. New developments in cyberinfrastructure can facilitate this integration is powerful ways. Grid computing greatly increases the potential for scientific collaboration that transcends disciplinary boundaries. But, we have to be willing and ready to take advantage of this potential. We need to embrace the changes in vision and approach the new tools require of practitioners in the behavioral and social sciences ⁽²⁰⁾.

We need to study how these tools will color our observations of social and behavioral phenomena. One key issue is the “digital divide” – if 56% of the world’s population has cell phones by 2012, as predicted by one source ⁽²¹⁾, this means that 44% will still remain unconnected. How can we use these new technologies in research and intervention without turning a blind eye to who we are missing? Methodological research to adapt our use of new technologies in the behavioral and social sciences is an important priority.

We also need to consider the profound ethical issues surrounding much of this research. The collection of individual, real-time experiential data will be possible only if we do so according to the highest ethical standards, respecting the rights and privacy of citizens and being ever watchful that the collection and dissemination of such data promote the public good and garner public trust.

The revolution in “bits and bytes” has the power to catalyze research on human behavior and improve health. At OBSSR we are exploring the best investment strategies for applying these new technologies, facilitating methodological studies to address emerging challenges, and promoting developments in theory and methods that will enable the behavioral and social sciences to use these tools effectively. If we invest well, we will help the theories and knowledge of the behavioral and social sciences flourish within a dramatically new landscape of scientific discovery.

Much has been written about the obesity epidemic in the United States and its rapid march into other industrialized societies. Obesity is one of the most pressing public health threats facing us today. One-third of children and two-thirds of adults in the United States are overweight or obese. ⁽¹⁾

Obese adults are at increased risk for a number of chronic conditions, including type 2 diabetes, hypertension, heart disease, stroke, arthritis, liver and gallbladder disease, sleep apnea, and some types of cancer. Stigmatization of overweight individuals has been documented and includes discrimination in hiring. ⁽²⁾ Childhood obesity can lead to many of the same chronic conditions found in obese adults, as well as orthopedic problems and asthma. Obese children also are more likely to be teased and to suffer from low self-esteem and depression. These children also have a greater risk of becoming obese adults.

This epidemic also creates economic burdens. According to some estimates, rising obesity rates and the medical consequences account for as much as one-quarter of the increase in health care spending in the United States between 1987 and 2001. ⁽³⁾ One estimate projects that obesity will account for 16 percent of health care expenditures by 2030. ⁽⁴⁾ Lost productivity costs are even greater. ⁽⁵⁾

Nobody chooses to be obese, so why is it so hard to prevent, and once it has occurred, why is it so hard to reverse? If only the answer were as simple as telling people to balance their energy intake and energy expenditure. Unfortunately, the complexities of human biology and behavior—and their interface with the environment—limit the efficacy of linear or single-solution interventions.

Obesity is the product of multiple interacting factors, ranging from genes to behaviors to the physical and social environments. Although individual behaviors – specifically food intake and physical activity – play a central role in the obesity epidemic, the epidemic cannot be fought through targeting individuals alone. Because individuals vary in their genetic predispositions and learned habits, behavioral interventions may not work equally well for all. And the very best behavioral interventions may not work for long in the context of our obesogenic environment, with its abundance of low cost, energy-dense food and sedentary lifestyles. As our experience with combating tobacco use has shown, policies or interventions aimed solely at individuals and at increasing the number or type of small-scale interventions will not be sufficient. “If humans have built-in biological propensities at odds with their environment, top-down approaches may be needed to achieve population obesity prevention goals”. ⁽⁶⁾

The reality is that obesity is not just a personal health problem; it is also a systems problem. This means that researchers must seek ways of altering behaviors that are intertwined with broader social, cultural, physical, economic, and political environments. Behavioral and social scientists have a long history of studying how these environments are shaped by individual and social action, and how individual behavior is influenced by features of the environment such as cultural norms, economic incentives, and the physical layout of communities. In recent years, researchers have studied the effects of fast food outlets ⁽⁷⁾, access to recreation facilities ⁽⁸⁾, school policies ⁽⁹⁾, family feeding practices ⁽¹⁰⁾, and social networks on behaviors related to obesity. ⁽¹¹⁾ Behavioral scientists have also studied how genetics, the brain, and environments interact to shape individuals’ eating and physical activity preferences and habits. ⁽⁶⁾

One of the biggest public health challenges is how to get a sense of the “big picture” of all the factors that influence obesity rates. Although we are developing a piecemeal understanding of the various contextual factors involved in obesity, we do not yet understand how these multiple levels of risk interact with one another and with biology. One approach is the use of systems science methodologies or principles, which provide a way to address complex problems, while taking into account the “big picture” and context of such problems. These methods enable investigators to examine the dynamic interrelationships of variables at multiple levels of analysis (e.g., from cells to society) simultaneously, while also studying the impact on the behavior of the system as a whole over time. Systems science methodologies can help us understand why programs and interventions fail to have their intended effects, and why, in some cases, they can even make the problem worse.

Where should we focus our research, so that we can better invest our public health dollars?

We need to continue to build the knowledge base needed to inform the development of systems science research on obesity. This includes more basic research on how families and communities influence diet and physical activity, particularly in children; understanding how cultural norms relevant to these behaviors are acquired and changed; and better identifying the causal paths linking built environments to individual behaviors. We need to integrate our expanding knowledge through the development of systems science models and evaluate and refine these models in the light of new data and insights.

We need to translate these research-informed models into practice by using them to guide multi-level prevention approaches that reach into health care, school, workplace, and community settings. We must invest in research on upstream policy interventions and their downstream effects. For example, can nutrition assistance programs, nutrition and menu labeling, altered advertising, taxes on junk food, increased physical activity in the workplace and schools, and reformed transportation policies start to turn the tide? What is the potential for other broad-scale approaches, such as social and commercial marketing, for changing our cultural views of obesity and obesity-related behaviors? We must also evaluate the potential for innovative individual behavioral approaches for weight control or maintenance in the context of diverse environments.

Finally, we need to recognize that the initiation and maintenance of behavior change can be extremely difficult, and even those interventions that succeed in controlled clinical trials do not always transfer well into the uncontrolled environment in which we live. Not only do we need to build supportive environments, we also need to develop better delivery channels and systems in place to disseminate effective interventions to the public, policymakers, and other decision makers to ensure that they are implemented, adopted, and maintained.

The National Institutes of Health’s Office of Behavioral and Social Sciences Research is working to make this research agenda a reality. We have co-funded conferences exploring psychological, neurological, and social factors affecting eating behaviors; social science contributions to understanding family dietary practices, and multi-level approaches to combating childhood obesity. We have partnered with several NIH institutes on funding opportunity announcements for methodological, basic, and translational research on obesity. We have established a partnership with the Centers for Disease Control and Prevention, the Robert Wood Johnson Foundation, and other NIH partners to facilitate the translation of obesity science into effective prevention strategies.

OBSSR promotes an interdisciplinary perspective to improve our understanding of the forces that determine optimal health promotion and prevention, reduce disease burden, and improve chronic disease management. Tackling the obesity epidemic requires that we use scientific evidence from a wide range of disciplines in order to identify the broad range of factors that influence obesity. Building a shared understanding of the various pieces that make up the obesity puzzle is a critical step towards developing effective solutions.

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