9
Infrastructure

Research that is conducted to elaborate the impact of interactions among social, behavioral, and genetic factors on human health places several demands on the research infrastructure. This infrastructure includes, in addition to laboratory space and equipment, the human infrastructure (e.g., education and training), data, and incentives and rewards. Some aspects of infrastructure are largely affected by the actions of the National Institutes of Health (NIH), while others are largely driven by university actions, although the two domains are inextricably related. For example, NIH supports training, but the universities actually provide the training; research tools are needed by university researchers, while NIH policies and practices may dictate what tools are funded. This chapter examines three aspects of infrastructure: education, data, and incentives and rewards. The discussion explores ways in which existing mechanisms can be focused to strengthen the infrastructure and examines potential new mechanisms that could be developed.

EDUCATION

The foundation of the research enterprise is the education of its researchers. Ideally, appropriate training would occur before launching a research career. The committee believes that the responsibility for education and training is shared among our universities (and high schools) and NIH and other funders of research training. For example, the National Science Foundation (NSF) calls for a more explicit involvement in precollege



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 181
9 Infrastructure Research that is conducted to elaborate the impact of interactions among social, behavioral, and genetic factors on human health places sev- eral demands on the research infrastructure. This infrastructure includes, in addition to laboratory space and equipment, the human infrastructure (e.g., education and training), data, and incentives and rewards. Some aspects of infrastructure are largely affected by the actions of the National Institutes of Health (NIH), while others are largely driven by university actions, although the two domains are inextricably related. For example, NIH sup- ports training, but the universities actually provide the training; research tools are needed by university researchers, while NIH policies and practices may dictate what tools are funded. This chapter examines three aspects of infrastructure: education, data, and incentives and rewards. The discussion explores ways in which existing mechanisms can be focused to strengthen the infrastructure and examines potential new mechanisms that could be developed. EDUCATION The foundation of the research enterprise is the education of its re- searchers. Ideally, appropriate training would occur before launching a research career. The committee believes that the responsibility for educa- tion and training is shared among our universities (and high schools) and NIH and other funders of research training. For example, the National Science Foundation (NSF) calls for a more explicit involvement in precollege 181

OCR for page 181
182 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT education. A partnership between NSF and NIH could help ensure the seamless development of a talent pool that could address biomedical re- search topics or other topics that require a fundamental grounding in math and science. However, since the advances in genomics have been recent—and the challenge of incorporating genetic research with behavior and social factors is even more recent—it is likely that there are many current researchers who have gaps in their scientific training. Therefore, by and large, the recom- mendations offered here are directed to NIH and aimed at the college level and beyond. NIH is the major source of funding for researchers in the biomedical and behavioral arenas and is poised to contribute to the training of a cadre of researchers who could address the issues described in this report. As the pace setter for the biomedical research enterprise, NIH is central to the infrastructure issues for this research, especially in the realm of education and training. NIH provided about $704 million in 2004 in support of research train- ing through the National Research Service Act (NRSA) (NIH, 2004b). It is generally agreed that postdoctoral training received in conjunction with research grants serves at least as many—and perhaps twice as many—as postdoctoral training through the NRSA (NRC, 2000). Since NIH is the dominant source of funding for the training of researchers in these fields, the NIH policies are fundamental to the ability of the United States to advance research on transdisciplinary issues such as those addressed in this report. The need for transdisciplinary research to address the study of gene- environment interactions was discussed earlier. As a beginning approach to fostering the development of transdisciplinary research on the impact of interactions among social, behavioral, and genetic factors on health, the committee believes that NIH should consider holding a conference for interested individuals. Such a conference would assist universities in shar- ing their best practices in interdisciplinary and transdisciplinary research and would foster the exchange of knowledge and practices. It will be challenging, but important, to ensure that participants in such a confer- ence share specific strategies that others could adopt or modify; the con- ference should not simply provide another forum devoted to encouraging the goal of collaboration. Also, since the challenge of educating across boundaries is not exclusive to health, it might be timely for the NSF or a private foundation (e.g., the Pew Charitable Trust) to bring together educators from many fields that have developed interdisciplinary and transdisciplinary programs specifi- cally in order to educate across boundaries and help students learn how to work in transdisciplinary teams. The Science Education Partnership Awards

OCR for page 181
183 INFRASTRUCTURE (NIH, 2005c) are an example of an excellent outreach effort to support science at the K-12 level. Although this program does not focus on transdisciplinary research, other programs, such as the Genome Science Education Program (SEPA, 2005), could emphasize the transdisciplinary aspects. Early Career Education At the initiation of careers, fellowship support is very important. There- fore, NIH could advertise individual pre- and postdoctoral awards specifi- cally for transdisciplinary research on the impact of interactions of social, behavioral, and genetic factors on health and provide easy links to the institutions and investigators who already are working in a transdisciplinary manner. This would not involve creating any new mechanisms, or even necessarily identifying additional funds. However, it would require NIH to make support in this area a priority and to take active steps to ensure that potential applicants are aware of NIH’s interests. As NIH identifies univer- sities that are conducting transdisciplinary research effectively, such univer- sities could be urged to advertise specific opportunities at their sites for postdoctoral work. Additionally, these universities could be funded to sup- port innovative outreach efforts in the topical areas of interest. In general, the committee believes that NIH could apply its existing training mecha- nisms specifically to the transdisciplinary topic addressed here. In other cases, modifications of existing mechanisms would make them more valu- able in this area. Although postdoctoral training is common in biology, it is less so in the social sciences. Therefore, it is important that opportunities at the post- doctoral level are available in order to expose social scientists to broad, transdisciplinary training. Also, since postdoctoral fellows may devote two or three years to their disciplinary training, NIH could consider extending training beyond three years for those who are reaching beyond their tradi- tional boundaries and would be likely to contribute as researchers in the areas of social, behavioral, and genetic factors and health. In general, there is concern that individuals must be well grounded in a discipline, but also able to work and communicate with other disciplines. A slight extension of the training period might serve this focus well, and there may be value in continuing to support mechanisms that support disciplinary training, while also providing the means to extend skills to those in complementary scien- tific areas (see Box 9-1). NIH initiated a T90 grant in 2004 to support transdisciplinary training (NIH, 2004a). Although these projects have been under way for only about one year, it would be useful to assess what has been learned from these early experiences and craft a T90 specifically for training in the impact of

OCR for page 181
184 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT BOX 9-1 Institute for Public Health Genetics, University of Washington, Seattle The Institute for Public Health Genetics (IPHG) at the University of Washington provides graduate education, opportunities for interdisciplinary research, and pol- icy workshops that integrate genomics with the public health sciences disciplines (epidemiology, biostatistics, environmental health sciences, and health services), and with pharmacogenetics, bioethics, social sciences, law, public policy and health economics. The mission of the Institute is to “provide broad, interdisciplinary training for future public health professionals, to facilitate research in public health genetics, and to serve as a resource for continuing professional education” (Bro- chure). Specifically, the IPHG offers an accredited masters of public health (M.P.H.), a doctorate (Ph.D.) in Public Health Genetics, and a transcripted gradu- ate certificate, all of which include this interdisciplinary training (IPHG, 2005). interactions among social, behavioral, and genetic factors on health. This program is fairly new, and while some may believe that it is premature to extend it without understanding the elements that lead to its success, the concept is clearly in alignment with the issues addressed by this committee. Therefore, the committee urges NIH to take every opportunity to learn from this cohort of projects and to extend them, while incorporating into new T90 projects the elements that have contributed to the program’s success. New programs require time to become organized and to enroll and educate trainees. Also, a lengthy period of time is required to observe the impact on the trainees’ careers and, subsequently, assess their impact on the field. Thus, the committee urges NIH to develop and use intermediate indicators for such programs in order to facilitate transdisciplinary training efforts, rather than wait the years that it might take to conduct a definitive assessment of impact. Intermediate indicators might include the level of interest in the program, success in recruiting top students, successful comple- tion of the training program, and continued interest in transdisciplinary research. Established Faculty Transdisciplinary research requires the development of “professionals that can interact synergistically” (IOM, 2003). Therefore, to develop a cadre of researchers who can participate in transdisciplinary research, fac- ulty members who are at a particular level of accomplishment in a particu-

OCR for page 181
185 INFRASTRUCTURE lar field must be presented with a realistic opportunity to extend their skills into new or changing fields. To assist established faculty in broadening their skills, NIH could revisit the senior fellowship (F33) concept to deter- mine whether it might be used as a mechanism to provide salary support for a defined release period (e.g., 30 percent to 50 percent). This support could be specifically used in structured education for disciplines involved in re- searching the impact of interactions among social, behavioral, and genetic factors on health. The award also would need to provide a modest institu- tional stipend. An advantage of this approach would be that researchers would be encouraged to seek out existing expertise in fields that they them- selves were lacking. NIH would not have to identify the fields or the indi- viduals, but, instead, would provide support if researchers in one field (e.g., social sciences) were to propose a structured study in another field (e.g., genetics). Although it is appealing to envision a new cohort of researchers who are trained from the earliest stages in transdisciplinary research, such a process requires time to develop. This kind of program could be part of a “toolbox” of approaches that would help to support the need for the continuous extension of abilities in these complex and changing fields. A more limited approach to extending skills could occur through the short course approach. In this way, NIH could assist researchers at all stages in broadening their skills by supporting a short course that focuses on studying the impact of interactions among social, behavioral, and ge- netic factors on health. Mechanisms exist (e.g., the T35) for this, but care is needed to ensure that such a course takes advantage of lessons learned from similar activities. It would be important for the short course to address the theoretical, statistical, and ethical aspects of this work and to ensure that participants are already strong in one (or more) of the arenas. In other words, such a short course should not be narrowly constructed in ways that would allow all of the students to be geneticists seeking to learn about social factors or, as another example, to be sociologists seeking to under- stand genetics. NIH has had experience in providing support in the past to areas of focus such as population behavior and Alzheimer’s disease (Bachrach and Abeles, 2004). The importance of bringing together investi- gators to collaborate on the study of the impact of social, behavioral, and genetic influences on health is no less compelling. It certainly can be argued that education that prepares researchers to work across fields needs to start early—perhaps at the undergraduate level. Universities have considerable latitude in how they construct courses and degree programs in order to allow, for example, social scientists to be exposed genetics and biologists to be exposed to cultural studies. Some universities offer degrees that explicitly encourage students to draw from more than one field. NIH has provided limited programs for under- graduates—typically those that encourage undergraduate programs to sup-

OCR for page 181
186 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT port the growth of a diverse cohort of biomedical researchers. It has not played a significant role in guiding undergraduate education, and no com- pelling reason appears to indicate that the situation should be any different in this area. However, universities are capable of adjusting their course work to meet changing scientific needs—and this is clearly within their purview. The report Facilitating Interdisciplinary Research by the National Acad- emy of Sciences/National Academy of Engineering/Institute of Medicine (NAS/NAE/IOM) involved government, university, and industry members participating in a broad discussion of ways to foster interdisciplinary re- search, and offers many useful recommendations (NAS/NAE/IOM, 2004). (See Appendix B for the complete set of recommendations.) The challenges in supporting interdisciplinary research are not unique to the social, behav- ioral, and genetic aspects of health, and the lessons that can be learned from these other fields can be shared so that not all tools need to be developed de novo. There is, however, no clear single way for the transmission of this knowledge to take place. MECHANISMS OF SUPPORT NIH uses a variety of mechanisms to support research, each with its own advantages. The core mechanism for supporting research is the R01, the Research Project Grant or what is known as the “individual investigator award,” which reflects the value that is placed on the work of sole investi- gators. The challenge, however, is to reconcile the historic focus on the work of the individual with the needs of team science. This is the heart of the cultural challenge to research today. Should the R01 be changed to reflect teams? Or, should the R01 continue to play a pivotal role as the means to support an individual scientist’s work? There always will be value in the work of the individual scientist, and not all scientific questions require the mustering of a team. However, when the R01 is portrayed as the highest form of achievement—the gold standard—it then undermines the valuation of the team approach. How can the scientific community best value both the work of the individual and the work of the team? How can NIH best value the different types of approaches needed for answering different scientific questions? There is a benefit to clearly identifying the expectations for a given support mechanism and, therefore, it is most likely that success would come from creating a new mechanism that specifically supports team research. Given a new identifying number, such a mechanism might be used only when a team is needed and when the Principal Investigator (PI) is a team leader with some number of co-PIs who clearly are equal collaborators. Such a mechanism would differ from program projects in which the subprojects, although oriented around a common theme, are fairly independent.

OCR for page 181
187 INFRASTRUCTURE Furthermore, this new mechanism would be different from a Core Grant (P30) for a center that provides elements that are shared by other, individually funded projects. The new mechanism would not be a center mechanism, but rather would fund a specific research project that requires a team of people working together to conduct the research. It is important that this mechanism be given the same status as the R01 if the goal is to support and reward team science. It also is important that all the members of the team receive appropriate recognition, which would not eliminate the role of the PI or minimize the leadership that is required to bring a team together to ensure successful project functioning. Since, as described in the 2004 NAS report, it may take time to develop a team for transdisciplinary research, it may be helpful to construct a mechanism that allows one to two years for a developmental phase, followed by three to five years for the support of the research following administrative review. This would help to ensure that the team has established a well-functioning structure and has access to the data or populations that are needed. Such an approach is consistent with the NAS report (2004) suggestion that an allowance should be made “for the longer startup time required by some IDR programs.” Private foundations have used different mechanisms for supporting com- plex teams of investigators. The MacArthur Foundation has supported net- works devoted to specific topics. These awards typically are highly selective of the individuals involved, flexible in structure, and well funded (see Box 9-2). Another transdisciplinary effort was that conducted under the auspices of the Family Research Consortium III, described in Box 9-3 below. Whatever approaches NIH decides to take, the value of flexibility and sufficient funding should be incorporated into them. Just as the topic of social, behavioral, and genetic influences on health is broad, so too must be the approaches taken to support the diverse workforce that can address these topics. Therefore, the committee makes the following recommendation: Recommendation 8: Expand and Enhance Training for Transdisci- plinary Researchers. The NIH should use existing and modified training tools both to reach the next generation of researchers and to enhance the training of current researchers. Approaches include individual fellowships (F31, F32) and senior fellowships (F33), transdisciplinary institutional grants (T32, T90), and short courses. DATA Infrastructure also involves the tools that researchers use. In the area of social, behavioral, and genetic effects on health, there is a significant need for datasets that provide information across these disciplines and that would allow for the testing of interactions. Datasets used to study such interac-

OCR for page 181
188 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT BOX 9-2 The MacArthur Network Model The research networks that have been established by the John D. and Catherine T. MacAthur Foundation over the last two decades are successful ex- amples of interdisciplinary collaboration. As described by the foundation, these research networks function as “research institutions without walls” devoted to top- ics related primarily to human and community development. According to the de- scription provided by the foundation: “They are Foundation-initiated projects that bring together highly talented indi- viduals from a spectrum of disciplines, perspectives, and research methods. The networks explore basic theoretical issues and empirical questions that will increase the understanding of fundamental social issues and are likely to yield significant improvements in policy and practice” (www.macfound.org/site/c.lkLXJ8MQKrH/ b.948165/k.E3C/Domestic_Grantmaking__Research_Networks.htm). An example of a currently ongoing network is the Network on Socioeconomic Status and Health, established in 1997 and chaired by Nancy Adler of the Uni- versity of California, San Francisco (www.macses.ucsf.edu). The mission of the Network on Socioeconomic Status and Health is to enhance the understanding of the mechanisms by which socioeconomic factors affect the health of individu- als and their communities. The network’s research agenda is designed to inform both policy and practice, to stimulate additional research in diverse fields, to contribute data to discussions of economic and social policy, and to provide a basis for social and medical interventions that will foster better health among individuals and communities. To achieve their mission, the network’s investigators are drawn from a diverse range of fields including psychology, sociology, psychoimmunology, medicine, epidemiology, neuroscience, biostatistics, and economics. Their research is orga- nized around an integrated, transdisciplinary conceptual model of the environmen- tal and psychosocial pathways by which socioeconomic status (SES) alters the tions typically are large, difficult to collect, and costly. Therefore, it is important to support such datasets as a research tool to be shared among a wide audience of researchers. Three ways that NIH could foster the devel- opment of such datasets are described below. All three would have value, but each has different costs and benefits. Existing Datasets First, it is important that NIH undertake a systematic review of existing and ongoing datasets to determine their current usefulness for transdisci- plinary research that is aimed at assessing the interactions among social, behavioral, and genetic factors on health. Furthermore, this review should examine how the datasets could be made more useful with supplemental

OCR for page 181
189 INFRASTRUCTURE performance of biological systems, thereby affecting disease risk, disease pro- gression, and ultimately, mortality. In its first phase, the network undertook a variety of studies focusing on the social, psychological, and biological processes involved in “social gradients” in health and disease. For example, the Network added new measures to waves of data collection in the Whitehall Study of British Civil Servants, a longitudinal study that has shown a persistent influence of SES on health well into old age. The group also has added new psychosocial measures to the 15-year follow-up wave of the CARDIA study, a multisite, longitudinal project funded by the National Heart, Lung, and Blood Institute, and has added the collection of biomarkers to characterize “allostatic load” in ancillary studies at the project’s Oakland and Chicago sites. The network also initiated a large study of work environment and health across 15 plants of a large industrial company. It is using data on administrative and physical status, supplemented with new surveys, to assess psychosocial and en- vironmental factors affecting allostatic indicators and health. Data collected from these and other studies will enable the group to test its integrative, transdisci- plinary model of the pathways by which SES alters biological systems and health (description taken from the Network’s website: www.macses.ucsf.edu). The success of the MacArthur Research Network model rests on several factors: first, it has facilitated the integration (or “consilience”) of knowledge, concepts, and methods across social and biological disciplines by carefully selecting a group of scholars who have demonstrated the willingness and capacity to overstep disciplin- ary boundaries in their previous research. Second, the network has been willing to invest in innovative, high-risk/high-reward projects initiated by the group’s members. These projects have ranged in size from small pilot projects to more ambitious un- dertakings (such as the collection of new data piggy-backed onto large-scale ongo- ing studies). Third, the network has been involved in mentoring a cadre of junior investigators who have attended the meetings of the Network over the years, and who have benefited from collaborating with the network investigators who have been funded by the network in carrying out exploratory research projects. data collection. In making this assessment, care should be given to identify datasets: • that are especially valuable for specific health outcomes, • in which there is sufficient social variation, and • in which the linkage to genetic factors can be plausibly explored with genetic measures that could be added to an existing project. It is possible that some datasets that already include biological and genetic measures could be augmented to include social and behavioral vari- ables. Not every dataset will ultimately be determined to be valuable for transdisciplinary research. However, to the extent that existing datasets can be augmented, there are efficiencies that should be exploited.

OCR for page 181
190 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT BOX 9-3 The Family Research Consortium III The Family Research Consortium (FRC) III was a multisite, 3-year postdoctoral training program that promoted interdisciplinary collaborative research and train- ing for the study of ethnic/racial diversity, family process, and child and adolescent mental health. Research partners and postdoctoral students came from a variety of disciplines. Trainees attended yearly Summer Institutes designed to bring to- gether members of the consortium as well as approximately 100 scholars from various universities worldwide. Students also attended a 6-week intensive summer training program during their first year, winter meetings focused on particular top- ics, and worked with one of the consortium faculty at his/her home institution. During their 3-year term, students were required to collaborate with at least two faculty members at different sites. The success of this effort led to funding for FRC IV which includes scholars from sociology, demography, developmental psycholo- gy, anthropology, economics, statistics, public health, and pediatrics. One example of a dataset that could be useful for the kind of trans- disciplinary research described in this report is the National Longitudinal Survey of Youth and Child Supplement. This dataset includes extensive information on social factors, developmental measures of children, data on family members (for a subset of participants), and a host of other measures. It does not, however, include biomarkers (Bureau of Labor Statistics et al., 2002). Therefore, NIH could explore the possibility of enhancing health measures and adding biomarkers. The large size, the representativeness of the sample, its longitudinal nature, and the wealth of existing data in this survey argue for a careful review of its potential regarding the impact of interactions on health. It could be valuable to collect biologic samples at any point in time during the course of a longitudinal study when the markers are stable over time, such as is the case with the HapMap. If the biologic measure is quite variable over time—and especially if the time sensitivity is associated with other behaviors of interest—then it would be necessary to collect the speci- mens at specific times. Similarly, social measures that are stable (e.g., paren- tal education) can be collected at virtually any point, but some measures are subject to considerable recall error, which makes the timing of their collec- tion important. The development of complex datasets must involve careful consider- ation of the stability of measures, the importance of different levels of stability, and the patience of research subjects to continue participation, among other factors.

OCR for page 181
191 INFRASTRUCTURE The AddHealth survey currently includes measures of social, behav- ioral, and genetic characteristics (Udry, 2003). In the recently funded Wave IV data collection, biomarkers (e.g., glycosylated hemoglobin, C-reactive protein levels, blood pressue, lipids, etc.) will be collected, and DNA will also be collected from all 17,000+ participants. These new data, added to the rich longitudinal social environment data already available from adoles- cence on this sample that is now aged 25-31 will make the AddHealth dataset a valuable resource for transdisciplinary research in the coming years. Care should be taken to ensure that this uniquely valuable dataset is sustained and made available to researchers. The inclusion of parents and the oversampling of twins and siblings make this an especially valuable dataset. Of course, the focus on adolescents restricts the types of health questions that can be addressed, but each dataset has its own strengths and weaknesses. In this case, the strengths are exceptional, and a high priority should be placed on continuing the study and the excellent access that is available to it. With the increased use of existing datasets comes the challenges that are associated with data sharing, privacy, confidentiality, and the scope of informed consent. Chapter 10 examines these issues. However, it is worth a brief discussion here. The sharing of data is a powerful tool for ensuring that the benefits of large investments in complex datasets are realized and that such datasets are not unduly restricted to a small number of research- ers. Careful consideration must be given to the understanding that partici- pants have about who will have access to their information, under what circumstances, and perhaps for what purposes. However, it is difficult—if not impossible—to envision all of the specific ways in which the data could be used. Researchers and funding agencies should give careful attention to how participants are informed of the potential sharing of their information (i.e., data and/or biological samples), the protections in place to guard their privacy, and the uses to which these data might be put. Although there is movement toward greater sharing of data, the need still exists to be atten- tive to and involved in this fast-moving field. Another valuable NIH role could be the development of a guide that includes measures of key concepts in data collection about the impact of interactions among social, behavioral, and genetic factors on health. This is not a new idea, but it is one that has proved useful in other fields (NIH, 2005b) and is one that also could help introduce researchers in disparate fields to the methods used by their colleagues. It is not uncommon for researchers to realize the need for measures from another field and, there- fore, to add data elements that are either not state-of-the-art or not appro- priate for the specific circumstances. To the extent that such a guide in- cludes a discussion of the underlying concepts being measured or the

OCR for page 181
192 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT circumstances in which specific measures were or were not appropriate, it could be useful to researchers. In some cases, the measures are either static (e.g., the genome) or can be recalled (e.g., education), such that supplementation is feasible. However, these additions must be scientifically compelling and not simply feasible. A particularly challenging issue in data collection is the collection of biologi- cal specimens, as well as their storage, sharing, and characterization. Also, collecting DNA at one point in time does not provide the breadth of gene expression data over time that might be necessary in order to understand the interplay of genetic and environmental factors over time. Development of such a guide also could also include a review that would seek to identify broadly agreed-upon measures in different scientific sectors. These measures would aid researchers who are interested in adding biomarkers to a behavioral study, providing, for example, some specific guidance about preferable measures and the logistics of collecting biologi- cal samples. Similarly, guidance for geneticists about better or worse ways to collect social and behavioral data could have widespread value and could be a valuable contribution regardless of which approach is taken to data collection. Such a guide would facilitate discussion of the concepts underly- ing frequently used measures and specifically address them in the context of contributing to the understanding of the impact of interactions among social, behavioral, and genetic factors on health. Although such a review would be a significant undertaking, it could provide a useful guide to a wide array of researchers. New Datasets A second approach to strengthening the data infrastructure is to design specific studies of social, behavioral, and genetics factors that influence specific health outcomes. Health conditions or diseases could be identified for which there is a suspected or known genetic contribution, for which behavioral factors are likely to be involved, and for which hypotheses have been formed regarding the role of social factors. Given the relationship of some social factors, such as race, ethnicity, and social support, to a variety of health conditions (see Chapters 2 and 5), the number of most likely candidate studies could be narrowed. Such studies also could focus on topics for which the best methodological tools already exist or can be developed fairly easily. An advantage of this approach would be that the datasets would be specifically focused on a given condition. However, it is likely that a large sample size would be required, and this could make such studies costly and perhaps difficult to construct. Finally, it also is possible that true advancement in this field requires a major new cohort study. Some refer to this as a “last cohort” concept. The

OCR for page 181
193 INFRASTRUCTURE benefits of such a study lie in the ability to craft specific measures of relevant concepts and to ensure that the periods of data collection are appropriate for the scientific questions being asked. A study to assess the impact of interactions of social, behavioral, and genetic factors on health could require hundreds of thousands—perhaps even a million—subjects and would involve a large part of the scientific community. This number of subjects would be far larger than any other existing U.S. cohort, but the sheer size of such a cohort would make it a valuable tool for many different exploratory projects, even those that were not conceptualized at the outset. Although there would be benefit in having such statistical power, the cost and the time required for data collection might seem daunting. Because there is still the need to identify topics that are likely to benefit from understanding the interplay of social, behavioral, and genetic factors on health, it was not clear to the committee that a last cohort approach would be necessary, at this time, to advance transdisciplinary research linking these domains. Understanding the interplay of these factors and health likely will progress through the building up of each of these key areas and most likely will require substantial investment in understanding link- ages, developing measures, and carefully selecting subjects. This is not to say that a last cohort approach would not bring considerable insight and statistical power to many issues related to our understanding of health and disease, but it is not clear that this is an ideal strategy for understanding the interactions among the levels discussed here. Such a major investment in a research effort must build upon the basis of a skilled research workforce. It is not clear that strategies exist for optimal training in transdisciplinary skills, and it is not apparent that the necessary rewards and incentives are in place to support successful transdisciplinary research on a massive scale. Replication Another area in which NIH could be involved concerns the replication of research results. Scientific fields advance when findings are reproducible and when replication is a routine, expected stage of research. One role that NIH could play would be to ensure that the costs of replication are viewed as legitimate—either as a part of the original study, as an add-on to a study, or as a separate project. For example, supplements can be made available if there are findings that warrant replication and the costs cannot be absorbed within the basic costs of a research project. Projects that are essentially replications of other findings may need to be funded, yet they often lack the appeal (or innovativeness) of new projects. Without replication, however, fields can zig-zag from “finding” to “finding” without developing a critical mass of reproducible results. In a field such as the transdisciplinary study of health, the demands of replication may be greater than for other, more

OCR for page 181
194 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT discrete, fields because studies are more difficult to mount and more expen- sive to replicate. A number of data issues and concerns need to be addressed in order to facilitate research that is aimed at explicating the impact on health of interactions among social, behavioral, and genetic factors. Therefore, the committee makes the following recommendation: Recommendation 9: Enhance Existing and Develop New Datasets. The NIH should support datasets that can be used by investigators to address complex levels of social, behavioral, and genetic vari- ables and their interactive pathways (i.e., physiological). This should include the enhancement of existing datasets that already provide many, but not all, of the needed measures (e.g., the Na- tional Longitudinal Survey of Youth, ADDHealth) and the en- couragement of their use. Furthermore, NIH should develop new datasets that address specific topics that have high potential for showing genetic contribution, social variability, and behavioral contributions—topics such as obesity, diabetes, and smoking. INCENTIVES AND REWARDS—NIH AND ACADEME According to the 2004 NAS/NAE/IOM report on interdisciplinary re- search, several key conditions are required for the conduct of effective interdisciplinary research. The committee believes that these same condi- tions are necessary for success in transdisciplinary research—a primary recommendation of this current report. The conditions identified by the 2004 report include “sustained and intense communication, talented lead- ership, appropriate reward and incentive mechanisms (including career and financial rewards), adequate time, seed funding for initial exploration, and willingness to support risky research.” Although such aspects of university functioning are not within the NIH’s purview, they may affect its ability to find scientists who can conduct the kind of transdisciplinary research that is envisioned here. The 2004 report is thorough and detailed, and the commit- tee believes that its recommendations are crucial to the successful imple- mentation of interdisciplinary and transdisciplinary research. The purpose of discussing certain key points of the 2004 report in the following section of this report is to emphasize their relevance and importance to the topic under consideration—assessing the interactions among social, behavioral, and genetic factors on health. Researchers generally work in a university environment (only about 10 percent of NIH research funds are expended at independent research insti- tutes, and an additional 10 percent of the NIH budget is expended in the NIH intramural program [IOM, 1998]). Furthermore, universities are the sites for virtually all professional training. Therefore, it is useful to consider

OCR for page 181
195 INFRASTRUCTURE how the structures and reward systems of universities may influence the incentives and rewards that are available for working in the area of trans- disciplinary research. One example is the hiring, promotion, and tenure (P/T) process, a key aspect of success in the university research setting. It is widely acknowl- edged that the P/T process rewards individual initiative and products of research, such as grant proposals, research projects, and publications. Al- though being a PI on a research project or a senior, lead, or sole author on a paper is a clear sign of scholarly achievement, there may be other indica- tors as well. Participation in team projects for transdisciplinary research may be discouraged for those who have not yet achieved tenure, but there would be value in providing junior faculty ways to become engaged in transdisciplinary research from the early stages of their careers. The criteria for promotion and tenure will, of course, affect the hiring process, because presumably an institution seeks to hire people it believes will thrive and grow in that instituition’s environment. Because the review process for P/T shares some attributes with the NIH peer review process, there may be some common observations about how these processes can support transdisciplinary research. One would be the importance of having someone participate in the P/T review who is experi- enced in transdisciplinary research, who understands the challenges and metrics for success, and who is able to evaluate contributions made by individuals to team projects. Because the P/T process is so critical to the career pathway of academic researchers it might be valuable for leading university associations (e.g., the American Association of Universities, the National Association of State Universities and Land Grant Colleges, and the American Association of Medical Colleges) to jointly develop models that would ensure that work in such important and critical fields is ad- equately rewarded before faculty reach the senior—or tenured—level. One of the suggestions made in the 2004 NAS/NAE/IOM report is that academic institutions should “increase recognition of co-principal investi- gators’ research activities during promotion and tenure decisions.” As NIH explores new approaches to acknowledging multiple investigators on team projects, the next step would be for universities to use that information in ways that would ensure that the impact of the incentives and rewards are felt at the campus level. Interestingly, in the guidance for the new clinical (Clinical and Translational Science Award) awards, NIH specifically calls on universities to put forward PIs with broad institutional authority, in- cluding authority over promotion: . . . that the program director have authority, perhaps shared with other high-level institutional officials, over requisite space, resources, faculty appointments, protected time, and promotion (NIH, 2005a).

OCR for page 181
196 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT This is a sign that NIH acknowledges the need for institutions to align their policies with the goals of supporting transdisciplinary research, even though these are policies and procedures that are under the control of the university, not NIH. Universities also should consider the incentives that come with sharing funding with researchers, departments, and colleges. The NAS/NAE/IOM report (2004) suggests that academic institutions “experiment with admin- istrative structures that lower administrative and funding walls between departments and other kinds of academic units.” Furthermore, the report recommends that “institutions should develop equitable and flexible bud- getary and cost-sharing policies that support IDR.” Among examples pro- vided is the suggestion that institutions “credit a percentage of all projects’ indirect costs to support the infrastructure of research activities that cross departmental and school boundaries.” There is wide variability in how recovered indirect costs are shared within universities, in part because universities face an array of demands and constraints on their use of such funds. In many institutions, some portion of the indirect cost recovery may be returned to investigators, departments, colleges, or other components to be used for research pur- poses. Even small amounts of such funding can either advance or retard the development of transdisciplinary teams. If, for example, the only recovery made is to the PI, then there is a clear disadvantage to being a participant on a team project. On the other hand, if the recovery is divided according to the involvement of individuals in the project, then there is a greater incen- tive to engage in teamwork. Such sharing could also minimize individual departments having to work to keep faculty participating only on projects within the department and could help encourage faculty members to engage in opportunities to work across organizational boundaries. Another example comes from the experiences of nontraditional struc- tures within universities, such as transdisciplinary research centers or insti- tutes. If all of the faculty members involved in a project reside within such an institute, there may not be any issue regarding how incentives flow. But, if individuals have home departments or colleges, as well as center or institute affiliations, there can be problems of attributing “credit” and providing rewards. The amount of incentive funds could be increased to ensure that some share went to such centers or institutes, or the overall amount of funding could be held steady, with the proportions adjusted to allow for incentives to accrue to such centers. Universities should examine their practices to ensure that, to the extent funds are distributed as incen- tives, they do not disadvantage the structures that may be key to conduct- ing transdisciplinary research. Simply put, universities cannot embrace the concept of transdisciplinary research without reviewing their policies and

OCR for page 181
197 INFRASTRUCTURE procedures in order to ensure that they facilitate such work rather than penalize it. Support for transdisciplinary research also will require incentives from NIH. Although the most powerful incentive is the financial support that is provided for such work, there are other types of incentives as well. One incentive is the credit that accrues to those who participate in such projects. The recent NIH announcement of plans to recognize multiple PIs represents a significant advancement in providing external recognition for members of research teams. This is a very important and valuable step in the enhance- ment of team science, and it is a step that clearly is needed for trans- disciplinary research. However, it is important that in seeking to appropri- ately recognize those who are conducting team research, systems not minimize the value of the leadership that such teams require. The develop- ment of complex proposals and the leadership for projects has been histori- cally recognized in the role of PI. That role still is important, even in settings in which there may be several collaborators who are critically important to the project. If NIH were also to recognize such collaborators, it would be easier for institutions to see how those roles are being played, not just on their own campus but on others as well. In reflecting on the P/T discussion, it was noted that it is obvious that those on an investigator’s campus know what their roles have been on research projects. However, it may be challenging in P/T review to under- stand how those roles are experienced by other researchers at a similar career stage. Team members need to be recognized for support received from NIH (e.g., through Computer Retrieval of Information on Scientific Projects). The use of such data is the responsibility of the university, but NIH (and other funders) could help by making the appropriate data easily available. The federal laboratories and industry have organizational structures that differ from those in universities in that they tend to be more problem focused than discipline focused. This structure may foster research that brings together different skills through a team approach to address a prob- lem, efforts that could provide insights for universities and, possibly, avoid unwarranted advocacy for particular disciplines, independent of their con- tribution to identified problems. In fact, the 2004 NAS report recommends that “universities may benefit by incorporating many IDR [interdisciplinary research] strategies used by industrial and national laboratories, which have long experience in supporting IDR.” Interestingly, some industries report that they prefer to hire trainees early in their careers before they have become too focused on independent activity and the anticipation of indi- vidual rewards. Industry frequently needs individuals who can work well in teams, a skill that is not necessarily fostered through a lengthy commitment to an academic career.

OCR for page 181
198 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT However, the larger obligations of universities to provide a broad intel- lectual environment and grounding for the next generation of scholars would not make a totally problem-oriented focus plausible as a general approach to institutional structure. The many calls for transdisciplinary research approaches to contemporary problems may mean that it is timely for universities to consider how to approach a balance of needs. Some of the deliberation in this area should involve considering how best to educate the next generation to contribute to the academy, as well as to industry and government. PEER REVIEW Scientific peer review of applications is a key step in supporting any area of research. It is not uncommon to hear investigators lament that transdisciplinary projects have difficulty in peer review. This reality, or even this impression, undermines the willingness of researchers to take on these important and difficult scientific areas. Transdisciplinary research is a challenge for the review of applications. The involvement of multiple disci- plines means that review groups need to reflect that diversity. There is great value in having more than one person representing a field on a review group, and a significant number should represent transdisciplinary research experiences and skills. The need to have multiple people in multiple fields, not to mention the need to include those who are skilled in systems approaches to analysis and disease endpoints, could rapidly escalate the number of reviewers needed overall. It is probably not enough to simply place people from different disciplines on a review group. Rather, it is important to take specific steps to ensure that reviewers will be able to appreciate the transdisciplinary nature or goals of a proposal. For example, selecting reviewers who actu- ally do transdisciplinary research would be one important step. If the project members are expected to function as team, then real-life experience with successful team science would be essential. This is far different from recruit- ing reviewers who have knowledge of the specific elements of work that the team will address, but no experience in working in teams. Another strategy for the NIH could be to focus review criteria to spe- cifically address transdisciplinary aspects (so that truly transdisciplinary projects were clearly valued). Establishing a specific mechanism for such team science could assist in focusing review groups on the requirements for such research. Also, review group members might spend time in advance of the specific review of proposals learning about one another’s disciplines, discussing the meaning of transdisciplinary inquiry, or even presenting a summary of the contributions of a field other than their own. Expanding the skill set of reviewers (and presumably program and review staff at the

OCR for page 181
199 INFRASTRUCTURE same time) would lead to the development of more reviewers who are aware of the conceptual and technical issues involved in a particular type of research. In any emerging field there is the risk of a dearth of qualified reviewers or an over-reliance on a few reviewers. NIH could take modest steps that would help to improve the quality of review and that would be helpful to its own program and review staff as well. Although the tools might vary, the goal is to ensure that transdisciplinary work is fairly reviewed and truly valued. It is not sufficient to place individual scientists with expertise in the elements of a complex, integrative project on review groups unless there are already members with experience working in a transdisciplinary setting or with a special initiative within the review group to build that perspective prior to conducting the review. The gravitational pull to individual perspec- tives must be actively countered. If NIH establishes a goal of supporting projects that are addressing transdisciplinary issues or bringing transdisciplinary teams to bear on a project, then funding decisions need to reflect that goal. The value of adher- ing to peer review assessments is obviously quite strong, but it is not incom- patible with also making programmatic decisions in support of some de- fined areas. If a field or approach is truly cutting edge, it may present a challenge to peer review, but if it is to be advanced, then NIH should consider making modest use of such programmatic decisions. It is not clear that this necessarily requires specific solicitations for such research (al- though Requests for Applications and Program Announcements have a role), but may simply involve placing high programmatic relevance on such projects when funding decisions are made. In many respects the tools needed to advance this field are not novel, but they need to be systematically applied toward the goal of fostering a type of research that has inherent scientific challenges and that faces spe- cific institutional hurdles. In other words, it is the determination to use the available tools more than the need to rely on the development of new administrative tools that will allow this field to grow. Therefore, the com- mittee makes the following recommendation: Recommendation 10: Create Incentives to Foster Transdisciplinary Research. The NIH and universities should explore ways to create incentives for the kinds of team science needed to support trans- disciplinary research. Areas to address include (1) hiring, promo- tion, and tenure policies that acknowledge the contributions of collaborators on transdisciplinary teams; (2) peer review that in- cludes reviewers who have experience with inter- or transdisciplin- ary research and are educated about the complexity and challenges involved in such research; (3) mechanisms for peer review of

OCR for page 181
200 GENES, BEHAVIOR, AND THE SOCIAL ENVIRONMENT research grants that ensure the appropriate evaluation of trans- disciplinary research projects; and (4) credit for collaborators in teams, such as NIH acknowledgement of co-investigators and uni- versity sharing of incentive funds. CONCLUSION The infrastructure needed to support research on the impact of interac- tions among social, behavioral, and genetic aspects on health will require transdisciplinary teams of researchers. This infrastructure may be construed as a matrix of training, tools, and incentives that are applied by universities and by funders, most specifically NIH. As discussed in this chapter, steps could be taken in each of these arenas, some easy and some difficult. However, it is unlikely that there are simple responses to this complex challenge. If the university community and funding agencies would come together to share experiences, many strategies that already exist to address aspects of this challenge could be communicated and recorded. If a full range of approaches was applied rigorously to the current problem, consid- erable progress could undoubtedly be made. However, this may require new funding mechanisms from NIH, and it may challenge universities to address fundamental practices such as the P/T process. The infrastructure needed may take the form of new ways to train and educate researchers as well as ways to fund that training. The incentives to conduct research are influenced by both university and funding agency policies and practices and need to reflect the value of team science. Finally, there are tools that are needed to conduct research, not just the concrete tools of equipment and facilities, but the data that are key to this complex area of research. REFERENCES Bachrach CA, Abeles, RP. 2004. Social science and health research: Growth at the National Institutes of Health. American Journal of Public Health 94(1):22-28. Bureau of Labor Statistics, U.S. Department of Labor, National Institute for Child Health and Human Development. 2002. Children of the National Longitudinal Survey of Youth (NLSY79), 1979-2002. [Computer File]. Columbus, OH: Center for Human Resource Research, Ohio State University. IOM (Institute of Medicine). 1998. Scientific Opportunities and Public Needs: Improving Priority Setting and Public Input at the National Institutes of Health. Washington, DC: National Academy Press. IOM. 2003. Who Will Keep the Public Healthy? Educating Health Professionals for the 21st Century. Washington, DC: The National Academies Press. IPHG (University of Washington Institute for Public Health Genetics). 2005. Institute for Public Health Genetics. [Online]. Available: depts.washington.edu/phgen/about/about_ intro.shtml [accessed March 30, 2006].

OCR for page 181
201 INFRASTRUCTURE NAS/NAE/IOM (National Academy of Sciences/National Academy of Engineering/Institute of Medicine). 2004. Facilitating Interdisciplinary Research. Washington, DC: The Na- tional Academies Press. NIH (National Institutes of Health). 2004a. Training for a New Interdisciplinary Research Workforce. (NIH Award No. RFA-RM-04-015). Bethesda, MD: NIH. NIH. 2004b. NIH Awards (Competing and Non-Competing) by Fiscal Year and Funding Mechanism Fiscal Years 1994-2004. [Online]. Available: grants2.nih.gov/grants/award/ trends/fund9404.htm. [accessed February 15, 2006]. NIH. 2005a. Institutional Clinical and Translational Science. (NIH Award No. RFA-RM-06- 002). Bethesda, MD: NIH. NIH. 2005b. Methodology and Measurement in the Behavioral and Social Sciences. (NIH PA No. PA-05-090). Bethesda, MD: NIH. NIH. 2005c. NCRR Science Education Partnership Award (SEPA). (NIH PA No. PAR-05- 068). Bethesda, MD: NIH. NRC (National Research Council). 2000. Addressing the Nation’s Changing Needs for Bio- medical and Behavioral Scientists. Washington, DC: National Academy Press. SEPA (Science Education Partnership Award). 2005. Genome Science Education Program. [Online]. Available: www.ncrrsepa.org/program/year/2001/Genome.htm [accessed March 30, 2006]. Udry J. 2003. The National Longitudinal Study of Adolescent Health (Add Health), Waves I & II, 1994-1996; Wave III, 2001-2002. [Machine-Readable Data File and Documenta- tion]. Chapel Hill, NC: Carolina Population Center, University of North Carolina at Chapel Hill.