Behavioral Science in Diabetes - Diabetes Care - American Diabetes ...

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Behavioral Science in Diabetes Contributions and opportunities RUSSELL E. GLASGOW, PHD EDWIN B. FISHER, PHD BARBARA J. ANDERSON, PHD ANNETTE LAGRECA, PHD

DAVID MARRERO, PHD SUZANNE B. JOHNSON, PHD RICHARD R. RUBIN, PHD DANIEL J. COX, PHD

OBJECTIVE — To summarize the current status of behavioral research and practice in diabetes and to identify promising future directions. RESEARCH DESIGN AND METHODS — We review behavioral science contributions to diabetes in self-management and patient empowerment, interventions with children and adolescents, and special problems including blood glucose awareness training and complications such as depression. We also identify emerging areas in which behavioral science stands to make significant contributions, including quality of life, worksite and community programs, interventions using new information technologies, and translation research evaluating practical programs in representative settings. We then discuss the gap between the generally encouraging research on behavioral contributions to diabetes and the infrequent incorporation of such contributions in practice. Suggestions are made for how to close this gap, including ways to increase understanding of behavioral issues, opportunities for funding of key research and implementation questions, and how behavioral science principles can become more integrated into diabetes organizations and care. CONCLUSIONS — Changes are required on the part of behavioral scientists in how they organize and present their research and on the part of potential users of this knowledge, including other health professions, organizations, and funding agencies. Integrating behavioral science advances with other promising genetic, medical, nutritional, technology, health care, and policy opportunities promises not only to broaden our understanding of diabetes but also to improve patient care, quality of life, and public health for persons with diabetes. Diabetes Care 22:832–843, 1999

n the dualistic view of human nature that guides much of our thinking about health, many see the medical progress achieved with diabetes over the past decade as obviating the role of behavioral science. But in reality, improvements in medical

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care, such as intensive insulin regimens, require more patient counseling, education, and support than simpler regimens, such as “take one shot a day and watch the sweets.” Developments in biology, genetics, pharmacology, and medicine do not dimin-

From AMC Cancer Research Center (R.E.G.), Denver, Colorado; Washington University (E.B.F.), St. Louis, Missouri; Joslin Diabetes Center (B.J.A.), Boston, Massachusetts; University of Miami (A.L.), Miami, Florida; Indiana University School of Medicine (D.M.), Indianapolis, Indiana; University of Florida Health Sciences Center (S.B.J.), Gainesville, Florida; Johns Hopkins University School of Medicine (R.R.R.), Baltimore, Maryland; and University of Virginia (D.J.C.), Charlottesville, Virginia. Address correspondence and reprint requests to Russell E. Glasgow, PhD, AMC Cancer Research Center, 1600 Pierce St., Denver, CO 80214. E-mail: [email protected]. Received for publication 24 June 1998 and accepted in revised form 20 January 1999. Abbreviations: ADA, American Diabetes Association; BGAT, Blood Glucose Awareness Training; CAL, computer-assisted learning; CDC, Centers for Disease Control and Prevention; CVD, cardiovascular disease; DCCT, Diabetes Control and Complications Trial; DPT-1, Diabetes Prevention Program for Type 1 Diabetes; DQIP, Diabetes Quality Improvement Project; GHb, glycosylated hemoglobin; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIH, National Institutes of Health; SMBG, self-monitoring of blood glucose. A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

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ish but rather expand the importance of behavioral science. An excellent demonstration of the role of behavioral science in diabetes care lies in the Diabetes Control and Complications Trial (DCCT) (1). The DCCT tested the efficacy of a coordinated, comprehensive approach to intensive diabetes management and tactics for teaching and motivating patients to adhere to this approach (2,3). In this, it was extraordinarily successful. During the trial’s first year, adherence levels were 97% for visits completed according to protocol, 84–90% for selfmonitoring of blood glucose (SMBG), 99% for completion of capillary blood collections, and 96% for completion of end-ofyear assessments of main study variables (4). Over the 6.5 years of the trial, 97% of participants were retained (1). Individualization of the intensive regimen, ongoing staff support, and follow-up contact were central to the adherence the DCCT achieved (2,3). SMBG results, insulin management, and medical nutrition therapy were all pursued from a personalized, problem-solving approach (5). Throughout the trial, participants knew that a prestigious group of professionals was very interested in their care and available by phone 24 hours a day. In response to a survey regarding their experiences, participants in the intensive therapy condition reported 1.54 times the level of support from staff as those in conventional treatment (P , 0.001) (6). Thus, the DCCT’s chief finding, that “metabolic control matters” (2,5) rested on its attention to behavioral factors in helping participants adhere to complex and demanding treatment regimens. The DCCT is just one example of the many contributions behavioral science makes to diabetes care. It also illustrates a major point of concern. Although the DCCT effectively addressed behavioral issues, it did not adequately define or monitor the methods for doing so. Consequently, generalization and translation of its success is limited. As will be demonstrated, there are large gaps between the importance and potential of behavioral science in diabetes care and the attention and support it receives. Below, we review established behavioral science DIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999

Glasgow and Associates

contributions to diabetes care and emerging areas in which behavioral science stands to make contributions. We then discuss existing gaps between the demonstrated potential of behavioral science and the current level of integration into practice, ways to close these gaps, and future opportunities. Behavioral science contributions to diabetes care Assessment and determinants of selfmanagement. Diabetes treatment is predominantly behavioral (involving daily medication-taking, glucose testing, exercise, and dietary actions) and is at heart a self-management issue (7–9). Problems in following diabetes regimens have been well documented (10,11). Research has consistently found that while the various diabetes self-care behaviors are relatively independent of one another (11–14), dietary aspects of the regimen are experienced as the most difficult (3,15,16), followed by exercise. Most patients find medication taking to be the area in which they have the least difficulty (15,17), which may be because this is the regimen area emphasized most by physicians and most associated with “managing an illness” in the public’s perception (18–22). Nevertheless, while most patients may take their medication, they are far less adherent with timing or adjusting medication administration (5,11). There is a large gap between our knowledge about diabetes self-management and how to assess it and its application in clinical settings. For example, providers may assume too much about patient adherence from the patient’s glycosylated hemoglobin (GHb) assay; those with “good” GHb assay results are presumed to be “adherent” while those with “poor” GHb results are presumed to be “nonadherent” (23). This is unfortunate, because GHb results are, in fact, often a poor indicator of patient behavior (24). A high GHb value tells us something is wrong, but not what. If we wish to identify which of the many possible patient behaviors or other factors (e.g., illness, inadequate prescription, comorbid conditions) might be responsible, we must conduct a behavioral assessment. Adherence is one important contributor to good control, but is not the same as control and cannot be evaluated just by looking at laboratory values. Determinants of adherence. Self-management behaviors are not only multidiDIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999

mensional, they are also multiply determined (3,25). At a personal level, variables related to an individual’s confidence or ability to carry out self-management are important. These variables include self-efficacy or empowerment (26,27), behavioral intentions (28), and problem-solving or coping skills (29–32). Another important influence on adherence is patient-provider communication (12,33–37). Sometimes patients’ self-care is poor because they lack sufficient skill or understanding to carry out a provider recommendation. Miscommunication between patients and providers about important components of diabetes care has repeatedly been documented (11). Other variables shown to be related to adherence are diabetes-specific knowledge (24), beliefs and personal models of diabetes (18), emotional well-being (38), motivation (39), readiness or “stage of change” (40), and social and environmental factors such as family and other support resources (41–44) and barriers to self-management (17,20,45). Reliable and valid assessments of selfmanagement are now available (11,46,47) but seldom employed in clinical practice. There seems to be a double standard here. When the object of our assessment is the patient’s biological status, time-consuming, expensive, and invasive procedures are well accepted. When the object of our assessment is the patient’s behavior, procedures tend to be dismissed if they are not brief, inexpensive, and convenient. Certainly, we would prefer that all measures, whether of biology or behavior, be quick, inexpensive, and noninvasive. Indeed, there have been advances in this area (48–52). However, our first allegiance must be to reliable and valid assessment. There is no a priori reason why behavior should be easier and cheaper to measure than biology (53). Patient empowerment and interventions to enhance self-management. Since implementing diabetes management lies largely with the patient’s daily efforts (7,9,12), patient education programs have increased emphasis on the patient’s role and responsibility. Several patient activation interventions (8,26,54) have reported strong and wide-ranging effects including improvements in self-efficacy, self-management, metabolic control, patient satisfaction, and quality of life. Long-term (12-month) reductions in GHb similar to the 2% difference between the DCCT conventional and standard treatment groups have been achieved through self-manage-

ment training programs (14). Controlled studies have demonstrated lasting improvements in quality of life as well as glycemic control (29,55–57). These benefits can also be accomplished with minority and older type 2 patients (58,59). As noted above, dietary issues have been found to be the most difficult aspects of the diabetes regimen. Wing et al. (60) have conducted the most systematic research in this area, focusing on intensive, structured behavioral group and individual programs for weight loss. They found that long-term interventions (e.g., regular meetings over periods as long as 2 years) may be required to produce substantial weight loss. On the other hand, Glasgow and colleagues (61,62) found that a brief, low-cost computer-assisted dietary intervention conducted during regular outpatient office visits produced sustained changes at 12-month follow-up in fat intake and serum cholesterol levels (but not large weight losses). Other studies of medical nutrition therapy have also documented cost-effectiveness (63). Interventions with children and adolescents. The multiple factors affecting glycemic control noted earlier apply also in youth. Successful interventions address them, typically involve both the youngster and the family, and include 1) reeducation for diabetes care, 2) reinforcement for selfcare behaviors, 3) problem-solving and good communication between youngster and family, and 4) encouragement and social support. Children’s and families’ knowledge of disease symptoms and regimen requirements are important (64). Educational and skill training approaches appear to be especially important for children and families at the time of initial diagnosis of diabetes (65) or for adolescents who are assuming increased responsibility for their daily care (66). However, knowledge alone is not sufficient for successful self-management. Additional procedures, such as support, supervision, and reinforcement for proper self-care, are usually essential. Reinforcement for self-management has proven to be useful (67,68). For example, Wysocki et al. (69) found that instruction in SMBG was not an effective intervention strategy for adolescents unless paired with incentives. Combining an educational intervention with parental praise and reinforcement for glucose tests that indicated good metabolic control led to increases in the percentage of tests indicating good con833

Behavioral science in diabetes

trol, and these gains were maintained at 22week follow-up (70). Given the substantial role that families play in children’s diabetes management, it is surprising that few studies have directly targeted family support, communication, and problem-solving regarding daily regimen tasks. One exception is the work of Satin et al. (71), who evaluated a multifamily group intervention for adolescents and their family members that stressed communication skills, problem-solving, and family support for adolescents’ self care. Adolescents in the multifamily groups demonstrated improvements in both selfcare and metabolic control 6 months posttreatment compared with randomized control subjects. Given the complexities of diabetes, it is unrealistic to expect that any one intervention strategy will be a cure-all. Successful intervention programs often adopt a multistrategy approach. For example, a program for newly diagnosed youngsters and their parents included 1) patient and parent education, 2) patient and parent problem-solving (e.g., use of SMBG data for making adjustments), 3) increased medical supervision, and 4) parental reinforcement of youngsters’ self-care behaviors (65). Children randomized to this comprehensive intervention achieved significantly better metabolic control 1 and 2 years postdiagnosis than those receiving conventional control treatments. Active interventions are necessary to prevent or minimize the frequently observed deterioration in glycemic control that occurs during early adolescence (65,72). Anderson et al. (73) treated adolescents and parents in separate groups at regular clinic visits (every 3–4 months). Adolescent sessions focused on the use of SMBG for solving diabetes management problems. The adolescents also ate, exercised, and completed SMBG together. Clinic nurses contacted adolescents between clinic visits, providing increased medical supervision. Parent sessions focused on strategies for negotiating appropriate levels of parental involvement and adolescent responsibility for diet, exercise, and SMBG. Metabolic control deteriorated in 50% of the adolescents randomized to usual care but in only 23% of the intervention group. There are now sufficient findings regarding children and adolescents with diabetes to formulate guidelines for health care providers (66). One is that the “honeymoon” period, soon after the diagnosis of 834

type 1 diabetes, may be an optimal time for interventions to encourage future self-management (65,74). A second is that efforts to work with children and adolescents should involve parents, problem-solving, and reinforcement, and occur during the first few years after diagnosis. Serious selfmanagement problems typically emerge about 3.5 years after diagnosis or during early adolescence (13–15 years of age) (75). Once serious problems are established, they become exceedingly difficult to rectify (76). Special problems Depression. Depression is three times more common among individuals with diabetes than the general population, affecting at least 15% of patients with diabetes (77,78). Depression is a concern not only because of its mental health ramifications, but also because of its negative impact on self-management, glycemic control, and complications in both adults (79) and adolescents (38). Yet depression is often underdiagnosed in patients with diabetes (80). Depression in people with diabetes has been successfully treated (57% remission rate) with tricyclic antidepressants (nortriptyline) (81). Also, studies in the general population indicate that cognitive behavior therapy is at least as effective as pharmacotherapy (82). Consequently, Lustman et al. (83) randomized patients with depression and diabetes to the combination of cognitive behavior therapy and self-management training versus self-management training alone. After 10 weeks of therapy, remission of depression was 85% with cognitive behavior therapy versus 27% in the control subjects. At 6-month follow-up, these remission rates were 70% versus 33.3% (83). In addition, at 6-month follow-up, GHb levels were 9.5% for cognitive behavior therapy and 10.9% for control subjects (P = 0.03) (83). Detecting extreme blood glucose fluctuations. In a series of studies over the past decade, Cox and colleagues (84–86) have developed and evaluated a program called Blood Glucose Awareness Training (BGAT) to teach patients how to identify symptoms of both hypo- and hyperglycemia. BGAT includes education, skills training, and practice in 1) increased sensitivity to symptoms of hypo- and hyperglycemia so that they may serve as cues for appropriate action; 2) identification of external events such as insulin administration, exercise, or changes in diet that may

raise the likelihood of hypo- or hyperglycemia; and 3) appropriate responses to internal and external cues so as to prevent hypo- and hyperglycemia. A long-term follow-up (mean 4.9 years) found that, compared with a relaxation control group, BGAT reduced the number of severe hypoglycemic episodes and automobile accidents (87). Emerging contributions of behavioral science Quality of life. Recognition of the importance of quality of life clarifies an important point of this article, that behavior and psychology are important dimensions of successful diabetes management, not just as they may facilitate desirable biological states but as outcomes in their own right (88). For example, many would judge as “not doing well” someone who had maintained near perfect metabolic control but complained that they were consequently depressed because they had let diabetes dominate their life (21). Several research teams have recently developed measures of diabetes-specific quality of life (89,90). Kaplan (91) pointed out that patient functioning and quality of life are themselves important health outcomes. Such factors have been demonstrated to be independent predictors of premature mortality and, in some cases, stronger predictors than biological measures (92). Future research is indicated to address the relative strengths and weaknesses of diabetes-specific quality of life instruments and how they relate to more general scales such as the SF-36 (93) or the Illness Intrusiveness Scale (94). An important issue will be the relative sensitivity of these various measures to detect change and intervention effects (95). The social context Health care behaviors of individuals and health care systems occur in a social context (25,96–98). The multiple levels of factors that influence both patients’ and health care providers’ actions to prevent and manage diabetes can be viewed as a pyramid of influences ranging from individual to group, community, and society (Fig. 1). To date, the majority of behavioral research on diabetes has focused on the top two levels of this pyramid: individual factors such as patient attitudes, knowledge and beliefs and family interactions. We are starting to see more work on patient-provider interactions and health care system factors (33). DIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999


Figure 1—Pyramid of psychosocial factors.

There has been far less work on the more distal influences of worksite, neighborhood, and community factors. Worksite factors. It is ironic that there has not been more research on worksite factors related to diabetes management, since most adults ,65 years old spend more of their waking hours at work than in any other setting. Behavioral research has identified unique strengths of the worksite as a setting for health promotion (99–101). These include 1) reaching persons who would not otherwise receive self-management education, 2) co-worker and supervisor support, and 3) the influence of worksite policies on employee behavior. However, worksite policies and practices can also make it more difficult for individuals to manage their diabetes. In particular, inflexible work schedules interfere with diabetes management (102). Cardiovascular disease (CVD) is implicated in the majority of increased health care costs and deaths associated with diabetes (103,104). This and the overlap between goals for diabetes management and CVD prevention suggest that worksite CVD risk reduction programs may be a resource for diabetes management. Such an approach also provides opportunities to normalize diabetes management and link it to activities that attract more resources than are often available for diabetes alone. Worksite health programs also create opportunities for liaison with other health organizations (20,105) and for integration with primary care (25,101,102). DIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999

Community interactions. A key area for future research is identifying the characteristics of medical practices and providers associated with delivery of quality care and the types of interventions that are most effective in different clinic settings (Fig. 1, level 3). Consideration of trends in population risk factors over recent decades, such as improved identification and management of hypertension and declines in prevalence of smoking, supports the role of community-based and policy approaches to health education (106,107). A number of reports indicate the value of community organization approaches to reaching underserved audiences. For example, Fisher et al. have shown that neighborhood residents can take meaningful roles in health promotion efforts and achieve improvements in smoking cessation and asthma management (108). Project DIRECT, sponsored by the Centers for Disease Control and Prevention’s (CDC’s) Division of Diabetes Translation, combines community-based activities with activities aimed toward health care providers (109). This initiative includes a social action approach to involving local citizens in directing program decisions (110,111), with training and support of the health care sector, and community organization around lifestyle issues. Initial results of a community-based approach to lifestyle modification among Native Americans are promising (112). Evaluation of culturally competent community-based interventions for other behavioral targets (e.g., fat, fruit,

and fiber intake; retinopathy screening) and for other underserved populations is needed. Health promotion programs in the worksite and community can complement those provided through clinical settings or aimed at individuals. Such interventions also permit study of the interaction between health policies (such as no smoking regulations, food labeling practices) and self-management interventions. The CDC’s state-based Diabetes Control Programs are now in all 50 states. Because they are concerned with translating the results of research into lasting changes in health plans and care, they provide a natural laboratory and opportunity for studies of interactions among different program channels and levels. The few studies of diabetes management in larger social units such as worksites and communities show promising results. Deserving of particular attention are studies that cut across multiple levels of influence (25,97,101,113,114). At each level of the pyramid shown in Fig. 1, there are numerous psychosocial and behavioral factors that act to support, and others that interfere with, successful diabetes management (Table 1). Unfortunately, as important as they are (114,115), studies of interventions that cut across multiple levels, especially controlled studies, are expensive. To date, there has not been funding for a largescale, multicenter collaborative study to address such organizational and behavioral issues in diabetes. The role of technology in behavioral aspects of diabetes The increasing availability of powerful computer technologies is rapidly expanding the role of behavioral science in diabetes in three domains: education, patient-provider communication, and provider support. One of the most prolific expansions is in the application of computer-assisted learning (CAL) to diabetes education. Historically, diabetes education has relied on didactic, verbal, and written modes of information transfer, often following a “one-size-fits-all” format (116). The effectiveness of these methods is modest (117–119) and reduced by problems with scheduling, the availability of appropriately trained staff, and the need to tailor education content to meet diverse learning needs. Indeed, because of such factors, many diabetic patients have never attended a diabetes class or program (120). CAL programs are increasingly being used to 835

Behavioral science in diabetes Table 1—Factors supporting and interfering with chronic disease comanagement at each level of influence Influence level

Supportive factors

Inhibitory factors

Personal

Empowerment; high self-efficacy. Good problem-solving skills.

Lack of knowledge; low self-efficacy.

Family/significant other

Social support.

Miscarried helping. Poor role models.

Health care provider/system

Integrated systems approaches. Collaborative goal-setting. Follow-up support. Personalized attention.

Lack of reimbursement or insurance coverage. Inconsistency among different team members.

Worksite/school/organization

Worksite health promotion programs. Coworker and supervisor support. Policies (e.g., no smoking) that support healthy behaviors.

Inflexible work schedules. Lack of healthy food choices or exercise facilities. No accommodation to diabetes needs.

Neighborhood/community

Awareness and use of nutrition and physical activity resources. Support groups. Strong library and volunteer programs.

Lack of nutrition education or self-management. Lack of safe convenient exercise locations.

Regulatory policy and incentive

Taxes and subsidies on tobacco and food products. Labeling information on food. Insurance coverage for self-management.

Media that do not consider diabetes serious. Lack of support for education and self-management supplies.

address these problems, allowing the user to select areas of particular interest and control the pace of learning. In addition, many programs include self-evaluation modules that review areas needing additional study (121,122). Arcade-style games are increasingly available that teach principles of diabetes management to a traditionally difficult population to educate—children and adolescents (121,123). Another trend is the use of sophisticated computer-based simulations to enable exploration of therapeutic options without the risks associated with real-life trial and error. The management of error is a key component of the learning process. Identifying the error, getting patients to discover it for themselves, and questioning how they would correct it are essential steps (119,124,125). The development of glucose assessment devices with memory capacity has led programs to aid in the collection, storage, and presentation of SMBG data. These programs have significantly influenced patientprovider communication (122,126–128). Patient utilization of SMBG can now be easily verified. This increases the ability of providers to identify and discuss issues 836

affecting self-management. SMBG data can also be displayed to illustrate a particular clinical problem the patient is experiencing. This reinforces collaborative problem-solving during the clinic encounter, allows the patient to review the discussion at home, and encourages comparison with subsequent data to evaluate progress. An important reason for using computer-assisted SMBG programs is that patients report preferring this type of feedback and feel that it represents a better-quality interaction with their physician (129,130). Another recent application of computer-assisted technologies has been to extend contact and support between diabetic patients and health care professionals. In their simplest form, patients are provided with a telephone-based hotline they can call to gain assistance in self-management decisions, by either discussion with a health care professional or voice mail exchange (131,132). More sophisticated applications of this concept enable users to transmit SMBG data from home to their provider, who can then review the data and contact patients to discuss regimen adjustments (130,132) or provide proactive and personalized automated voice mail

messages (133). These approaches offer several advantages. They enable patients to maintain contact with their providers at times that are most advantageous without having to make physical contact. In addition, slowly developing clinical trends can be identified and corrected before they become serious. Patients have reported feeling that such a telecommunication system offered them better protection and an enhanced sense of security (130,134,135). Interactive telecommunication systems are being used with increasing frequency in diabetes care. Prototypes have been evaluated that enable diabetes users to obtain psychological and social support using a touch-screen computer counseling session format (62,136) and via internet-based selfmanagement support programs (137). Future systems will integrate response algorithms with increasingly sophisticated voice recognition programs that enable the user to engage in dialog and receive responses specific to their situation. Translation and reach applications Behavioral science is essential to the translation and dissemination of innovations in diabetes care. If we accept that diabetes is a DIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999


Figure 2—Algebraic model of dissemination of innovations in care.

major public health problem (98,138,139), it is important to consider several behavioral, systems, and public health issues in translating and evaluating innovations. As depicted in Fig. 2, the long-term public health impact of an intervention is a function of its rates of reach, efficacy, adoption, implementation, and institutionalization (114,140). To illustrate these issues, consider the example of genetic markers. It may be possible to reliably identify genetic markers for at least some types of diabetes in the near future. However, the public health impact of such discoveries will depend on a variety of largely behavioral and socioenvironmental factors. If insurance does not cover the costs of this testing and/or counseling, if the public is not informed (or is misinformed) about the benefits and costs of such testing and counseling, if recommendations for testing and counseling are not appropriately tailored to the readiness of different patients, or if there are large social, cultural, religious, or economic barriers to receiving these services, the reach of the services will be small and they may not be delivered to those who most need them. The efficacy of an assessment procedure or screening test includes such issues as the sensitivity and specificity of a test result and the social and psychological implications and costs of false positives and false negatives. Efficacy refers to the outcomes of an intervention—both positive and negative—when delivered under optimal conditions. If the genetic tests are very expensive, are beyond the competence of most medical settings, or raise difficult ethical issues, the tests will be less likely to be adopted in many settings. The implementation characteristics of a procedure refer to how skillfully and consistently it is administered in practice. Even if a laboratory or genetic test is highly accurate, the counselDIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999

ing or the ways the information is communicated to the parties who need to make major decisions based on test results are not necessarily so reliable or consistent. Finally, even if implemented well initially, a program may not continue to be routinely administered or institutionalized. This analysis of dissemination is not limited to scientific breakthroughs such as in genetics. Instead of genetic testing for diabetes, substitute “physicians following recommended guidelines” or “widespread adoption of intensive therapy or staged diabetes management.” In all of these cases, psychosocial factors strongly influence levels of reach, efficacy, adoption, implementation, and institutionalization. Each of these steps in dissemination entail behaviors—of patients, providers, or organizations—that significantly affect the success of a program. Behavioral research addresses how to enhance reach, efficacy, adoption, implementation, and institutionalization (2,141,142). The gaps There are large gaps between the current evidence and potential of behavioral science to contribute to diabetes care and the current application of behavioral science principles and research. This section reviews these gaps, along with progress toward closing them and additional strategies for their reduction. Gap 1: Recognition of behavioral science relevance. Many reimbursement and practice policies still reflect a view of biology as the predominant determinant of disease and its only solution, despite the demonstrated contributions of behavioral science in diabetes care and health care in general (140,143,144). Coverage for behavioral and educational interventions, such as self-management training, is often denied by health insurance or health care systems.

Gap 2: Funding for behavioral science research. Only 7% of the 1994–1996 National Institutes of Health (NIH) budget supported behavioral research, although, in terms of risk factors and conditions that lead to disease, behavior accounts for 50% of U.S. mortality (145). Type 2 diabetes is a prime example of underfunding of behavioral science. Type 2 diabetes is responsible for 90–95% of all cases of diabetes and the vast majority of the mortality and health care costs attributable to diabetes. Lifestyle patterns, especially excess calorie and saturated fat intake and sedentary lifestyle, are central causes of type 2 diabetes (146,147). They also play a critical role in management, along with other preventive behaviors such as foot care, blood glucose testing, and smoking cessation. Yet, of the $657.1 million National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 1996 budget for research awards, contracts, and training (NIH Awards by NIH Component and Funding Mechanism, Fiscal Years 1986–1996, at nih.gov/grants/award/ trends96/pdfdocs/TBL18.PDF), only $25.6 million, less than 4%, went to behavioral science research (Office of Behavioral and Social Science Research estimate of NIDDK dollars allocated to behavioral research). Toward the close of 1997, following a congressionally mandated increased authorization, the NIDDK announced seven funding initiatives. None addressed behavioral science in diabetes care in any substantial manner, and the recent Working Group Report on diabetes opportunities gives little attention to behavioral or psychosocial issues. This is unfortunate, since it places obvious limitations on both acquisition of basic science knowledge and applications of behavioral science in clinical care. Support for behavioral science from the American Diabetes Association (ADA) also remains modest and incongruent with the 837


predominant role of behavior in diabetes. Progress has been made—the ADA has established a council on behavioral medicine and psychology, and behavioral scientists are now represented on most committees, including research and grant review committees. Still, only one of the numerous mentor-based training grants awarded by the ADA over the past several years and four of its 82 most recent research grants have been awarded on topics having any significant behavioral science component. Given the ADA’s 1995 statement of its vision “to make an everyday difference in the quality of life for all people with diabetes,” it is disappointing that so little funding and priority has historically been devoted to psychosocial, behavioral, and quality of life issues. It is hoped that systematic investigations of the issues at the interface of medicine, genetics, nutrition, and behavioral science, which impact the everyday quality of life of persons with diabetes (and are being considered by the recently appointed ADA Outcomes Research Task Force), will become a priority for both ADA and NIH. Gap 3: Attention to behavioral science factors in clinical research. Although behavioral issues were clearly central to the DCCT, the DCCT did not systematically characterize or measure self-management activities and strategies to promote adherence or behavioral and psychosocial processes or outcomes (with the exception of a quality of life scale developed for the DCCT). Thus, it provided little systematic information about how adherence to similar intensive regimens could be promoted. So, too, behavioral science has had a limited role in the design and implementation of the Diabetes Prevention Program for Type 1 Diabetes (DPT-1). This is unfortunate, since the psychological impact of screening programs to identify persons at risk for type 1 diabetes has been previously documented (148,149). Progress is reflected in the role of behavioral science in the current Diabetes Prevention Program for Type 2 Diabetes. One of the interventions tested in this program entails lifestyle approaches to preventing diabetes through diet and exercise. Behavioral scientists have taken leadership roles in intervention design as well as in planning recruitment and adherence strategies and assessing psychosocial factors likely to mediate program impact and quality of life outcomes. Ancillary studies supported by both the NIDDK and the NIH 838

Office of Behavioral and Social Science Research are addressing cultural perspectives of African Americans, risk perceptions, and social support. Although still limited in terms of the overall focus and cost of the trial, this trend should continue in other large-scale collaborative trials. Closing the gaps Understanding utility of behavioral science. The usefulness of behavioral science must be better appreciated by other professions and organizations. This should be enhanced by books such as Practical Psychology for Diabetes Clinicians by Anderson and Rubin (150), Bradley’s compendium of behavioral and psychosocial measures for diabetes (151), and literature reviews (3,25,30,57,152–154). Steps for behavioral scientists. To increase support for their research and their roles in multidisciplinary organizations, behavioral scientists will need to make changes also. They must become more active within ADA and other health organizations as well as state diabetes control programs, many of which would welcome behavioral expertise. They will need to publish more in medical and health journals (rather than solely in behavioral science journals). Behavioral science research also needs to be framed in terms more relevant to other health care professions. There is increasing opportunity for interdisciplinary work with physicians, nurses, and dietitians and for collaborations with others, such as geneticists, pharmacists, primary care practitioners, economists, and policy researchers. The current climate of costcontainment and health care reform poses demanding evaluation criteria for evaluation of all care approaches. Most behavioral scientists have been trained in traditions emphasizing empiricism, careful operationalization of concepts, and critical appraisal of results. But the emphases on cost containment and evidence-based medicine prompt new evaluation criteria such as effectiveness in routine implementation and cost benefit/efficiency. These issues need to be addressed in behavioral science research contributions (98,115). Research methods and evaluation. Support for behavioral science in diabetes care would benefit from further well-controlled evaluations of behavioral science interventions. The current emphases on cost containment and managed care suggest additional evaluation criteria that, if met,

would also enhance support for behavioral science research (115,155). They include 1) practicality and feasibility within the context of typical health care settings and without requiring substantial additional amounts of time or costs on the part of either patients or professionals; 2) reach and applicability to a wide variety of persons with diabetes, including those who may not be highly motivated or do not have access to many resources; 3) impact on quality of life and functioning (91,156); and 4) cost-effectiveness (156–158). Broader social targets. To date, most behavioral diabetes research has focused on individual patients and their families. Many key issues for future research have to do with the practices and policies of organizations, groups, medical settings, communities, and cultural subgroups (143,159) or what Biglan et al. (160) refer to as “larger social units.” Stated differently, if behavioral innovations are to be sustainable, increased attention will need to be directed to “social ecology” issues (3,25,96,161) regarding the fit between these practices and the context in which they are being introduced. The next decade of behavioral research will involve extending the questions, methodologies, and approaches that have proven promising with individuals and families to the larger levels illustrated in Fig. 1 and Table 1. Incorporation of behavioral factors in diabetes guidelines. A current opportunity to advance both diabetes care and behavioral science’s role would be to include validated evidence-based behavioral measures in the measurement set of the Diabetes Quality Improvement Project (DQIP). This interorganizational effort involving Health Care Financing Administration, National Committee on Quality Assurance, Foundation on Accountability, and the ADA is developing a set of evidence-based and practical measures of quality diabetes care. These measures will eventually be included in the Health Employer Data Information Set criteria for managed care practices. The ADA has recently developed its own set of care measures for its Provider Recognition Program (162). The ADA criteria, 11 in all, include five behavioral or patient-centered items in the criteria for provider recognition (self-management education, medical nutrition therapy, SMBG, tobacco status identification and counseling, and patient satisfaction). The current version of the DQIP reporting criDIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999


teria is almost identical to the ADA set for biologic and laboratory measures but does not include any patient-centered or behavioral measure. (Tobacco status is a criterion for all patients, and some other behavioral measures are included in a “test set” that may be added later.) Unfortunately, this suggests to both providers and patients that self-management and psychosocial aspects of care are not important. This omission overlooks currently available behavioral, quality of life, and patient satisfaction measures of quality of care that are as reliable and valid (48,151,156) as many of the biologic measures currently included, and usually much less invasive or costly to collect. Funding. A key step in closing the gaps is increased funding for behavioral research. This is not simply a cry for “more funding for our special interests.” Nor is it to imply that funding for critically important issues such as the human genome project should be transferred to behavioral research. Rather, our assertion reflects the key conceptual perspective that biology and behavior are complementary in their roles in health. Most geneticists project that geneenvironment interactions will explain most diseases—not genetics alone. Unless we devote systematic attention to behavioral and environmental issues, as well as genetic markers, pharmacology, etc., we will miss critically important opportunities. Our research investments will pay much greater dividends if they include a meaningful study of behavioral and psychosocial issues along with biologic issues. Recognition of behavior as an outcome. An important conceptual shift is the acceptance of behavioral measures as appropriate outcomes in diabetes research. Their importance is not limited to predicting or leading to subsequent biological or clinical endpoints. The judgment that someone with diabetes is “doing well” is multifactorial and configural. It reflects not only metabolic control, clinical status, and presence or absence of complications but also everyday behavioral functioning, congruence between personal preferences and management practices, emotional status, and quality of life. The assertion that behavioral outcomes are of value in their own right should not be misconstrued as an argument that change in a behavioral outcome is per force significant for clinical outcomes or cost-effective. We are not asserting that behavioral outcomes always justify policy decisions regarding the treatments that bring them about, but that they DIABETES CARE, VOLUME 22, NUMBER 5, MAY 1999

are of interest and worth evaluating in their own right. Training and other positive steps. Complementary to direct funding of behavioral science research in diabetes, there is a need for increased funding for training of behavioral science researchers in diabetes. This training would attract more talented researchers to the field and could emphasize the conceptual and methodologic approaches that behavioral scientists need to adopt to make their research more pertinent to the needs of the diabetes community. Signs of progress An expanded view of diabetes that includes behavioral, societal, quality of life, and health policy issues is starting to be reflected in the programs and advisory groups of the CDC’s Division of Diabetes Translation. In addition to Project DIRECT, described above, behavioral scientists in all 50 states now have the opportunity to become involved with their state’s CDCfunded Diabetes Control Program (159). The Division of Diabetes Translation is also developing a behavioral science section. The NIDDK’s support of behavioral science through the Diabetes Prevention Programs, the Demonstration and Education components of Diabetes Research and Training Centers, and current (but too few) investigator-initiated grants is another area of progress to be expanded. The ADA has recently constituted a Task Force on Outcomes Research. Finally, the NIH Office of Behavioral and Social Science Research is stimulating support for behavioral science research and interinstitute programs in which NIDDK is also participating. Summary and conclusions As noted at the start of this article, thinking about behavior, biology, and health has tended to reflect a dualism in which behavior and biology are viewed from an either-or perspective and, usually, from the perspective that biological advances will obviate behavior. In sharp contrast, we assert that biology and behavior are complementary in their roles in health, disease, and illness. Behavioral science has contributed substantially and shows promise of even more impressive contributions to the prevention and care of diabetes. These include conceptualization and measurement of self-management and patient empowerment, assessments and interventions for children and adolescents with diabetes, recognition and treatment of depression and other

comorbidities, improvement and understanding of patient-provider relationships, and promising results from the application of practical behavioral interventions (such as blood glucose awareness training) and interactive computer technologies. The most compelling evidence of the complementarity of behavioral science and biology is the observation that clinical advances, such as intensive therapy, islet transplantation, or genetic testing and “engineering,” raise rather than eliminate behavioral and psychological questions and needs. By integrating behavioral science concepts, interventions, measures and analyses into research programs, the field of diabetes care as a whole will benefit. Future opportunities for behavioral science are enormous. As more efficacious interventions are identified (be they medical, technological, genetic, pharmacologic, or organizational), the potential importance of behavioral science increases. There are two reasons for this. First, specification of the medical dimensions of problems and their treatment 1) puts in bold relief the centrality of behavioral processes and treatments and 2) raises issues of the effects of both medical and behavioral interventions on quality of life (163). Second, the issues of adoption, reach and level of participation, quality of implementation, and institutionalization are inherently behavioral. As we develop more efficacious treatments, behavioral issues become increasingly important in determining how, to whom, and under what conditions and settings these treatments are optimally delivered (25,115,164). Acknowledgments — Preparation of this manuscript was supported by NIH Grants DK 35524 and DK 20579 and by grant 030103 from the Robert Wood Johnson Foundation.

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