The Role of Behavioral Medicine in Integrated Healthcare

  • Dawn K. WilsonEmail author
  • Allison M. Sweeney


This chapter reviews evidence from randomized controlled trials that demonstrate the importance of behavioral interventions for improving lifestyle behaviors and preventing and treating chronic diseases. Taking a lifespan approach, we review trials including participants ranging from children to elderly adults, and show that critical components of effective interventions include targeting self-regulation and self-efficacy through strategies such as self-monitoring, receiving feedback, developing action plans, and utilizing effective goal setting strategies. Although limited research exists on comparing the effectiveness of integrating behavioral health experts into the integrated care team, the effects of traditional randomized trials show the consistent effectiveness of implementing behavioral interventions with a high fidelity of delivery. Furthermore, there is a growing literature that supports the cost-effectiveness of behavioral interventions on reducing hospital utilization and medication usage. Thus, the field of behavioral medicine has the potential to play a fundamental role in reducing healthcare utilization and costs by improving lifestyle habits that have been related to the prevention of chronic diseases.


Healthcare Behavioral interventions Self-regulation Motivational interventions Life span 


The United States has the highest costs associated with healthcare expenditures per capita and has been shown to have poorer health outcomes compared to other industrialized countries (Woolf & Aron, 2013). Improving the quality of healthcare and population health has recently become a national public health priority (Stoto, 2013). Although medical treatments are often considered a critical component of healthcare, they explain a relatively small amount of variability in physical health outcomes. For example, when examining the factors that contribute to premature death, investigators have estimated that access to healthcare explains 10% of the variance in outcomes (Schroeder, 2007). Alternatively, behavioral patterns explain 40% of the variance, with the remaining variance being explained by environmental exposure (5%), social circumstances (15%), and genetic predispositions (30%). Furthermore, the Oxford Alliance for Health has suggested that most chronic diseases can be traced to a limited set of modifiable health behaviors, including tobacco smoking, alcohol consumption, physical activity, and diet (Suhrcke, Nugent, Stuckler, & Rocco, 2006). Such findings suggest that interventions focused on improving engagement in healthy lifestyle habits may be a highly effective approach for both treating and preventing the development of chronic illness. Thus, the field of behavioral medicine has the potential to play a fundamental role in reducing healthcare utilization and costs by improving lifestyle habits that have been related to the prevention of chronic diseases.

Effectiveness of Lifestyle and Self-Management Interventions

Converging evidence from randomized controlled trials suggests that improving self-regulation through behavior change techniques is an effective approach for promoting changes in health-related behaviors across the life span . For example, self-monitoring, which involves prompting people to keep a record of a specified behavior (e.g., in an electronic or written diary), is considered to be one of the most effective strategies for eliciting changes in diet and physical activity (Michie, Abraham, Whittington, McAteer, & Gupta, 2009). Other common strategies include prompting specific goal setting, including planning details such as the frequency, intensity, or duration of a behavior, as well as specifying when, where, and how the goal will be carried out (Gollwitzer, 1999). Furthermore, action planning, including prompting people to identify potential barriers to performing a behavior and planning ways to overcome them, is another frequently used strategy (Ayotte, Margrett, & Hicks-Patrick, 2010; Bandura, 2004). In this section, we review interventions in which various professionals, including teachers, primary care physicians, and community members, were trained to use behavior change strategies as a method for improving health-related behaviors among high-risk populations.

Children-Focused Randomized Controlled Interventions

The Child and Adolescent Trial for Cardiovascular Health (CATCH; Perry et al., 1997) was a multi-site intervention that examined the role of the elementary school environment, school-based health education, and home-based health education. Across four states, 96 elementary schools were randomly assigned to implement (1) a school-based program (including a school food service modification, PE intervention, and a behaviorally oriented health skills training), (2) a school-based program plus a home-based program, or (3) the usual health curriculum. School cafeteria lunches were modified to provide healthier meals with less fat and salt, and PE classes were modified to encourage more vigorous physical activity. The classroom education program was teacher-led and implemented across three academic school years. The primary goals of the intervention were to teach students to identify and choose healthy food, to engage in regular physical activity, and to avoid tobacco use. The program emphasized behavioral skill development around healthy eating and physical activity, including encouraging students to set behavior change goals and receiving feedback from teachers and support from peers. The home-based intervention was designed to complement the behavioral skills learned at school. Students were instructed to complete additional skill-building education activities with their parents and were encouraged to attend family fun nights, school-based evening events in which families could spend time together engaging in physical activity and eating healthy snacks. On average, 58% of the students attended the family fun nights, bringing two other family members with them. Overall, 69% of the students participated in the home curricula each year, but, on average, only 43% completed the entire home curricula. On average, 79% of the parents of students in family intervention schools participated in some of the home curricula.

The results of the trial showed that compared to the control group, participants in the two intervention groups reported significantly greater dietary knowledge; greater perceived parental, friend, and social reinforcement for food choices; lower daily total energy intake; lower daily energy intake from fat; and more minutes of daily physical activity (Luepker et al., 1996). Although the intervention groups were more effective than the control group on several outcomes, few differences were observed between the school-based and school plus family-based intervention. Additionally, blood pressure, body mass index, heart rate, and cholesterol did not differ significantly between groups. Taken together, the CATCH trial demonstrated that providing children with behavioral skills training and an environment that supports a healthy lifestyle (e.g., healthy school lunch choices, PE class activities) is an effective approach for helping children to maintain a healthy diet and engage in regular physical activity.

School-based behavioral interventions have also been found to be an effective approach for changing health-related behaviors among middle school students. The Active by Choice Today (ACT) trial was a multi-site randomized trial that aimed to increase intrinsic motivation and improve behavioral skills for engaging in regular physical activity (Wilson et al., 2008). Twenty-four middle schools in South Carolina (matched by size, percentage of minority students, percentage of free or reduced lunch, and urban vs. rural) were randomly assigned to implement a motivational and behavioral skills intervention or a general health education program. Students in the intervention group participated in a 17-week after-school program which consisted of (1) a 10-min snack break, (2) 60 min of physical activity of the student’s choice, (3) a 20-min motivational and behavioral skills training session, and (4) 30 min of homework assistance.

The skills training sessions focused on a variety of behavioral skills designed to increase self-efficacy, behavioral competency, and social support for engaging in physical activity (from parents and peers); these skills included goal setting (completed in a group setting), communication skills, and providing and seeking support outside of the program. Additionally, students in the intervention group completed two video-taped sessions in which they described positive coping strategies for increasing physical activity outside of the program days with family and friends. The purpose of these sessions was to help students develop increased motivation and a positive self-concept for physical activity. Alternatively, students in the general health education program completed a 17-week after-school program in which they received information about nutrition, stress management, drug prevention, and dropout prevention.

To examine whether the behavioral skills training facilitated greater moderate to vigorous physical activity, all students were instructed to wear an accelerometer for 7 consecutive days prior to the intervention, mid-intervention, and 2 weeks post-intervention. At mid-intervention, students in the intervention group engaged in greater physical activity than students in the control group (Wilson et al., 2011). However, 2 weeks after the intervention was completed, there was no longer a significant difference in physical activity between the two groups. In post-intervention focus groups, students reported several environmental barriers that prevented them from engaging in physical activity outside of school including interfering demands at home, a lack of motivation without the support of teachers, and a lack of support or involvement from parents. These results suggest that providing students with behavioral skills training is effective at increasing school-based physical activity; however, additional support and training is needed to help students cope with barriers in the home environment that interfere with physical activity maintenance.

In addition to demonstrating changes in health-related behaviors, there is evidence that behavioral skill-oriented health sessions can lead to a reduction in the prevalence of obesity. In the Planet Health trial, ten middle schools were randomly assigned to implement the Planet Health educational program or the usual curriculum and PE classes (Gortmaker et al., 1999). The Planet Health program aimed to implement four behavioral changes: reducing television viewing to 2 h/day, increasing physical activity, decreasing consumption of high-fat foods, and increasing consumption of fruits and vegetables. Teachers were trained to implement an interdisciplinary curriculum approach so that the intervention materials were integrated into students’ major subject courses and PE over 2 academic years. More specifically, the curriculum was designed to provide students with the behavioral and cognitive skills to enable behavior change (e.g., problem-solving, self-monitoring), opportunities to practice skills to increase perceived competence in carrying out new behaviors, and behavior change support from multiple teachers.

After 2 years, there was a significantly greater reduction in the prevalence of obesity among female students in the intervention group compared to the control group. Among male students, obesity declined in both the intervention and control group, with no significant difference shown between these groups. Both male and female students in the intervention demonstrated a significant reduction in television viewing time relative to the control group. Among female students only, there was a significant increase in fruit and vegetable consumption and a significant decrease in total energy intake relative to the control group. Reduced television watching mediated the effect of the intervention on the reduction in obesity among female students, such that each hour reduction in television viewing predicted a reduced odd of being obese. Female students appear to have been more responsive to the intervention, which suggests that the causal processes guiding weight loss may be different for male and female students. Although the findings did not generalize to all students, the Planet Health trial was the first randomized controlled field trial to provide evidence that a school-wide behavioral skills program can be successful at helping to reduce the prevalence of obesity.

Another approach to reducing obesity among adolescents is to provide parents with the behavioral skills and motivation to help their children change their health-related behaviors. Motivational interviewing (MI) is a patient-centered counseling style designed to decrease ambivalence and increase patients’ motivation for behavioral change (Miller & Rose, 2009). Rather than providing overt advice or educational information, MI aims to elicit the motivation to change from the patients themselves by using strategies such as reflective listening and shared decision-making. The early stages of MI counseling focus on building motivation, whereas the later stages can be adapted to incorporate behavioral skills training, including helping patients to identify goals, create an action plan, anticipate potential barriers, and engage in self-monitoring (Resnicow & McMaster, 2012). Previous studies have integrated MI with behavioral skills techniques (Wilson et al., 2015). There is ample evidence that MI is an effective strategy when coupled with behavioral skills training for helping overweight and obese adults lose weight (for a review, see Armstrong et al., 2011) and an effective strategy for helping parents to facilitate weight loss among their overweight or obese children (Spear et al., 2007).

In a recent randomized controlled trial, BMI2, Resnicow et al. (2015) provided MI and behavioral skills training to pediatricians and registered dieticians (RD). Pediatric offices were then randomly assigned to provide parents of overweight or obese adolescents with (1) usual care, (2) four MI sessions with a pediatrician (pediatrician only), or (3) four MI sessions with a pediatrician and six MI sessions with a dietician (pediatrician + RD). At a 2-year follow-up, patients in the integrated healthcare group (pediatrician + RD) demonstrated the lowest body mass index. The integrated healthcare group was significantly different from the usual care group, but there was no significant difference in BMI between the usual care and pediatrician only group. These findings provide one example of how a well-established counseling strategy, coupled with behavioral skills training, can be improved further by incorporating an integrated team of healthcare professionals.

Middle Age Adult-Focused Randomized Controlled Interventions

Primary care offices present a good opportunity to identify and intervene with patients who may be high risk for developing a chronic health problem (e.g., those who are physically inactive and/or overweight). For example, the Activity Counseling Trial (King et al., 1998) tested the effectiveness of primary care-based physical activity counseling across a 2-year period. Sedentary adults (Mage = 51 years) were randomly assigned to (1) a standard care group, (2) a staff-assistance group, or (3) a staff-counseling group. All participants were given the same recommendations for physical activity and written materials from their primary care provider. The staff-assisted group received additional behavioral skills training including meeting with a health counselor to form an individualized physical activity plan, self-monitoring physical activity with an accelerometer, receiving personalized feedback about overcoming barriers via mail, and structured counseling sessions during naturally occurring doctor visits. The staff-counseling intervention group received the same treatment as the staff-assistance group, plus additional resources including frequent phone-based behavioral skills counseling (e.g., to evaluate success at meeting their physical activity goals, develop solutions for dealing with barriers, and provide social support), in addition to in-person counseling sessions and behavior skills training classes.

After 2 years, there was no significant difference in self-reported physical activity; however, both intervention groups demonstrated significantly greater cardiorespiratory fitness than the standard care group, as measured by maximal oxygen uptake (Simons-Morton et al., 2001). Follow-up analyses revealed that several demographic, physiological, environmental, and psychosocial variables influenced the effectiveness of the intervention. Specifically, among patients in the assistance group, those with relatively low income and worse health at baseline were less likely to maintain their physical activity goal past the first year. Among participants in the counseling group, those who reported seeing other walkers/exercisers in their neighborhood and relatively high self-efficacy for overcoming barriers at baseline were significantly more likely to meet their physical activity goals at the 2-year time point. Taken together, these findings indicate that educational information alone is insufficient for improving adherence to physical activity goals . Behavioral counseling that incorporates self-monitoring and personalized feedback appears to be an effective approach, but it is important also to account for individual differences in responsivity.

In addition to working individually with patients in primary care offices, there may also be opportunities to instill behavioral skills training at the community level. For example, the Positive Action for Today’s Health (PATH) trial was a randomized trial that tested whether increasing perceptions of safety and access for physical activity, and using social marketing to address motivators for walking, was effective at increasing neighborhood walking (Wilson et al., 2010, 2015). Across three low-income communities in South Carolina (matched by crime, ethnicity, physical activity, and income), communities were randomly assigned to implement an intervention combining a police-patrolled walking program with social marketing strategies for increasing physical activity, a police-patrolled walking program only, or a general health education program (control group). The intervention focused on African American adults (Mage = 51.0 years) residing in the targeted low-income communities who were capable of engaging in regular walking (i.e., no disabling medical conditions). In both intervention groups, participants had the opportunity to engage in scheduled neighborhood trail walks during weekday evenings and Saturday mornings. The scheduled walks were organized through local community centers, led by a walking leader trained in CPR and safety prevention, and were patrolled by a police officer. Alternatively, the general health education program included general health events highlighting chronic disease prevention.

Participants in the full intervention program also received social marketing materials aimed at addressing individual-, interpersonal-, and community-level barriers for neighborhood walking. This information was delivered through a 1-year calendar, with each month focusing on one of the following objectives: (1) beliefs about safety and access to local walking trails, (2) beliefs and attitudes toward increasing physical activity, (3) beliefs and attitudes about improving mental health and well-being, (4) building self-efficacy for engaging in regular walking, and (5) improving community connectedness. The calendar was designed to give participants the opportunity to practice several behavioral strategies, including goal setting, self-rewards, and progress tracking. The calendar was intended to increase self-efficacy, promote the five objectives of the program, and provide logistics about the scheduled community walks.

To test whether the intervention was effective at increasing physical activity, all participants were instructed to wear an accelerometer for 7 consecutive days. Accelerometer-assessed moderate to vigorous physical activity was measured pre-intervention, at the end of the 1-year intervention, 6 months after the end of the intervention, and 12 months after the end of the intervention. Additionally, attendance was recorded at each scheduled PATH walk to index the total number of monthly participants. Across the 24-month follow-up period, there was no significant difference in moderate to vigorous physical activity between the three groups. However, walking attendance in the full intervention group increased significantly from 40 walkers per month to 400 walkers by 9 months, with a sustained average of about 200 walkers per month after 18 and 24 months. This change in trail walking was not observed in the community that received only the police-patrolling support. Furthermore, a follow-up analysis showed an intervention effect of the full intervention program on accelerometry estimated moderate-to-vigorous PA among older adults in the PATH trial (Sweeney, Wilson, & Van Horn, 2017). Results from the PATH trial suggest that behavioral skills training delivered through social marketing campaigns can be effective for influencing neighborhood walking; these findings further highlight the importance of taking into account physical and social and environmental factors (e.g., perceptions of safety) when designing behavior change interventions.

Behavioral interventions have been shown to be effective for changing health-related behaviors, including physical activity and diet. Extending these findings, there is further evidence that changes in health-related behaviors can reduce or delay the onset of chronic disease. A seminal example highlighting the utility of lifestyle interventions for preventing chronic illness is the Diabetes Prevention Program (DPP; DPP Group, 1999, 2002). The DPP was a 27-center randomized controlled trial that compared the effectiveness of a lifestyle intervention relative to pharmacological therapy and a placebo control group for preventing the onset of type 2 diabetes, among high-risk individuals (Mage = 50.6). Participants in the lifestyle-intervention group set weight-loss and physical activity goals. They worked individually with a case manager who delivered a series of core-curriculum sessions, which consisted of a weigh-in, review of self-monitoring records, presentation of educational information, continuous identification of barriers to weight loss and physical activity, and the development of a weekly action plan for meeting the physical activity and weight-loss goals. These sessions were tailored based on the individual’s specific needs and his or her cultural background.

Across a 3-year follow-up period, diabetes incidence was lowest among the lifestyle-intervention group, with the lifestyle-intervention group showing a reduced risk of onset of 58% and the medication group showing a reduced risk of 31%, relative to the control group. In a follow-up study, to examine the long-term maintenance of these effects, participants from all three groups were recontacted and offered the opportunity to participate in a group-based lifestyle intervention (DPP Group, 2009). Ten years after the original assignment to the DPP , the cumulative incidence of diabetes remained lowest among individuals assigned originally to the lifestyle-intervention group.

In line with research suggesting that chronic illnesses cluster (Suhrcke et al., 2006), the lifestyle changes made by participants in the DPP appear to have also influenced their risk for developing cardiovascular disease (DPP Research Group, 2013). Specifically, over the 10-year follow-up period, all three groups showed a significant reduction in systolic blood pressure, diastolic blood pressure, and LDL cholesterol; however, the lifestyle-intervention group demonstrated the lowest use of lipid and blood pressure medication. These findings suggest that participants who made lifestyle changes, with less medication, achieved a similar long-term reduced risk of cardiovascular disease than participants in the medication and control groups. Since the DPP, several other randomized controlled trials have reported positive effects of lifestyle interventions as a strategy for preventing diabetes (Pan et al., 1997; Tuomilehto et al., 2001). There is converging evidence, then, that promoting healthy lifestyle habits is an effective strategy for reducing people’s risk for developing chronic illness.

Elderly Adult-Focused Randomized Controlled Interventions

In addition to preventing the onset of chronic illness, behavioral lifestyle changes may also improve health outcomes among patients already living with chronic illnesses. The Look AHEAD study (“Action for Health in Diabetes”; Look AHEAD Research Group, 2006) was the first randomized controlled trial to provide direct evidence for the longitudinal health benefits of lifestyle changes (i.e., weight loss) among patients with a chronic illness. The Look AHEAD study tested whether intentional weight loss among overweight or obese individuals with type 2 diabetes led to a reduction in cardiovascular morbidity and mortality (Mage = 59.0 years). Participants were randomly assigned to complete a diabetes support and education program (control group), or an intensive lifestyle-intervention program, designed to help patients lose at least 7% of their initial weight and to increase their physical to at least 175 min/week.

The lifestyle intervention drew upon the methods used in the DPP but was adapted for individuals already diagnosed with type 2 diabetes. Phase 1 of the program aimed to help patients achieve initial weight loss through weekly on-site sessions with a lifestyle counselor during the first 6 months and three sessions per month during months 7–12. Through a mixture of group and individual sessions, participants received educational information about behavioral weight control including topics such as the importance of self-monitoring and methods of physical activity. Participants were instructed to track their daily caloric intake and were provided with a portion-controlled meal plan. Additionally, they were instructed to gradually increase their weekly minutes of physical activity and were offered opportunities to participate in supervised activity classes. Among patients struggling to meet the dietary and physical activity recommendations, individualized support was offered to help patients identify problem behaviors, provide a list of solutions, and develop a written plan with specific goals and action plans.

During years 2–4, Phase 2 of the program aimed to help patients maintain their weight loss and consisted of bimonthly individual sessions in which a lifestyle counselor would reinforce strategies introduced in year 1 (e.g., reviewing self-monitoring records, problem-solving, goal setting). Participants had the opportunity to participate in a refresher group program and a reunion group program to reconnect with acquaintances from Phase 1. During Phase 3 of the program (year 5 and beyond), participants were encouraged to attend monthly, individual on-site sessions with a lifestyle counselor. The purpose of these sessions was to help review successes and challenges in maintaining weight and physical activity goals and to provide support for dietary and physical activity lapses and weight regain. Participants were followed for 13.5 years (median follow-up of 9.6 years; Look AHEAD Research Group, 2014a, 2014b).

The lifestyle-intervention group was effective at helping patients to lose weight. The largest change in body weight was observed in the first year, such that the intervention group had an average weight loss of 8.6%, whereas the control group has an average weight loss of 0.7% (Look AHEAD Research Group, 2007). By the end of the fifth year, patients in the intervention group had gradually regained about half of their lost weight and tended to remain at that weight for the rest of the trial (Look AHEAD Research Group, 20132014a). The control group displayed small decreases in weight across all years; however, at each time point, the intervention group displayed a greater change in weight loss than the control group. Importantly, patients in the intervention group reported greater practice of critical physical activity and weight control behaviors, including increasing self-reported physical activity, reducing caloric intake and fat intake, using meal replacements, and weighing themselves on a regular basis (Look AHEAD Research Group, 2014a). These results suggest that the successful weight loss of the intervention group may be attributable, in part, to the self-monitoring skills acquired during the individual and group sessions of the intervention.

Although the intervention was successful at helping patients to achieve and maintain weight loss , there was no difference in cardiovascular deaths between the intervention and control groups (Look AHEAD Research Group, 2013). However, participants in the intervention group benefited in a number of other ways including improved metabolic control, blood pressure, and lipid profile (Look AHEAD Research Group, 2013). Participants in the intervention group reported a greater reduction in the use of glucose-lowering and antihypertensive medicine, were less likely to be diagnosed with metabolic syndrome, and displayed a greater rate of remission of type 2 diabetes (Look AHEAD Research Group, 2007, 2013). Furthermore, patients who completed the lifestyle intervention spent fewer days in the hospital and required less medication relative to patients in the control group, yielding savings of approximately $600 per year (Look AHEAD Research Group, 2014b). Thus, results from the Look AHEAD trial support the use of lifestyle interventions that emphasize self-monitoring as a cost-effective strategy for improving weight-related health outcomes among patients with chronic illness.

In addition to providing chronic illness patients with the information and skills to change their dietary and physical activity tendencies, behavioral interventions may be strengthened further by providing patients with information about how to self-manage their chronic conditions. Self-management education programs aim to provide patients with information about managing their symptoms and improving their quality of life. Such programs often incorporate a structured learning experience that aims to increase patients’ knowledge about (1) the medical management of their health condition; (2) changing or maintaining new behaviors, including adopting health lifestyle habits; and (3) coping with the emotional challenges of chronic illness (Corbin & Strauss, 1988; Lorig & Holman, 2003). Randomized controlled trials have provided ample evidence that self-management programs are effective for helping patients with a variety of chronic conditions, including asthma (Lorig, Gonzalez & Ritter, 1999), coronary heart disease (Clark, Dodge et al., 1997), and chronic pain (LeFort, Gray-Donald, Rowat, & Jeans, 1998).

One example of an effective self-management approach is the Chronic Disease Self-Management Program (CDSMP), a community-based self-management intervention (Lorig et al., 1999). Patients with at least one chronic illness (including heart disease, lung disease, stroke, arthritis) were randomly assigned to complete a 7-week educational program or to a control group (Mage = 62.2 years). The education program was led by trained lay leaders, many of whom had a chronic disease, and covered a range of topics including physical activity, the use of cognitive symptom management techniques, nutrition, fatigue and sleep management, dealing with negative emotions, communication with health professionals, and problem-solving. The sessions incorporated a variety of techniques designed to increase self-efficacy for managing one’s chronic illness, such as the use of weekly action plans and feedback.

At a 6-month follow-up, compared to the control group, patients who completed the CDSMP demonstrated a significantly greater change in minutes of physical activity, the practice of cognitive symptom management, and improved communication with their physicians. Additionally, the treatment group reported greater health, less disability, fewer limitations in their social activities, greater energy, less health distress, and fewer nights spent in the hospital. Additionally, participants who had originally participated in the control group were later offered the opportunity to complete the CDSMP. Six months after completing the program, similar to the original treatment group, these patients reported a significant increase in physical activity, a greater use of cognitive symptom management, less health distress, fewer limitations in their social activities, and fewer nights spent in the hospital. Furthermore, 2 years after completing the CDSMP, relative to their baseline status, patients continued to show reduced health distress, greater self-efficacy for managing their chronic illness, and fewer visits to their physician/ER (Lorig et al., 2001). The positive effects of the CDSMP have been replicated with diverse populations (Lorig, Ritter, & Gonzalez, 2003) and using Internet-based delivery (Lorig et al., 2008). Thus, the additional studies demonstrated the generalizability and translational aspects of the CDSMP approach to long-term lifestyle change.

Summary of Critical Components of Behavioral Interventions

The randomized controlled trials reviewed in this section represent a diverse range of approaches to promoting changes in health-related behaviors. Table 2.1 highlights some of the key features of these trials including information about the environment in which the study took place, primary goals, the type of behavioral strategies used, and main findings from the study. These interventions incorporated a range of behavioral skills training, with the majority of studies reporting that these strategies were aimed at increasing self-efficacy. Social cognitive theory proposes that self-efficacy, or an individual’s belief in his or her capacity to carry out behaviors needed to attain a desired outcome, plays a central role in how people approach goals (Bandura, 1986). Specifically, people high in self-efficacy tend to be more likely to believe that they can master challenging problems and recover quickly from setbacks, skills which may be especially important among people seeking to change health behaviors (Bandura, 2004).
Table 2.1

Summary of randomized control trials




Length of study

Primary goals

Behavioral training skills

Primary results for the intervention group

Child and Adolescent Trial for Cardiovascular Health (CATCH)

Children (Mage = 8.76 years)

Elementary school, classroom-based program

3 academic years

Teach students to identify and choose healthy food, engage in regular physical activity, and avoid tobacco-use

Modeling by cartoon characters, food preparation, monitoring, goal setting, perceived support

Greater dietary knowledge; Greater perceived support for food choices; Lower daily total energy intake; Lower daily energy intake from fat; More minutes of daily physical activity

Active by Choice Today (ACT)

Children (Mage = 11.34 years)

Middle school, after-school program

17 weeks

Increase intrinsic motivation and improve behavioral skills, so as to increase physical activity

Goal-setting, developing communication skills, providing and seeking support outside of the program, developing a positive self-concept

Greater physical activity mid-way through the intervention; Participants encountered environmental barriers outside of the program that prevented physical activity maintenance

Planet Health

Children (Mage = 11.70 years)

Middle school, classroom-based program

2 academic years

Reduce television viewing to 2 h/day, increase physical activity, decrease consumption of high-fat foods, and increase consumption of fruits and vegetables

Goal-setting, self-monitoring, perceived support

Reduction in television viewing time; Reduction in the prevalence of obesity (female students only); Increase in fruit and vegetable consumption and a decrease in total energy intake (female students only)


Parents and children (Mage adults = 5.1 years)

Primary care office

2 years

Increase intrinsic motivation and teach behavioral skills to parents, so as to decrease BMI among adolescents

Goal-setting, action planning, problem-solving, self-monitoring

The group who received the intervention from both a physician and a dietician had the lowest BMI

Activity Counseling Trial

Adults (Mage = 51.0 years)

Primary care office

2 years

Increase and maintain physical activity and cardiorespiratory fitness among sedentary adults

Planning, self-monitoring with an accelerometer, goal-setting, problem-solving solutions for barriers

No significant difference in self-reported physical activity; Greater cardio-respiratory fitness (as measured by maximal oxygen uptake)

Positive Action for Today’s Health (PATH)

Adults (Mage = 51.0 years)


2 years

Increase perceptions of safety and access for physical activity, so as to increase physical activity

Goal-setting, self-rewards, self-monitoring

No significant difference in accelerometer-assessed physical activity; Significant increase in number of walkers on neighborhood trails

Diabetes Prevention Program (DPP)

Adults (Mage = 50.6 years)

Clinical centers

3 years; also completed 10 year follow-up

Prevent or delay the onset of type 2 diabetes through changes in physical activity and diet

Self-monitoring, planning, goal-setting, problem-solving solutions for barriers

Lower incidence of diabetes

Look AHEAD study (Action for Health in Diabetes)

Adults (Mage = 59 years)

Clinical centers

Three phases across 5 years; followed for 13.5 years

Test whether intentional weight loss leads to a reduction in cardiovascular morbidity and mortality

Self-monitoring, planning, problem-solving for barriers

Significant reduction in weight loss, but no significant difference in cardiovascular deaths; Significant improvement in metabolic control, blood pressure, and lipid profile; Less likely to be diagnosed with metabolic syndrome and displayed a greater rate of remission of type 2 diabetes

Chronic Disease Self-Management Program (CDSMP)

Adults (Mage = 62.2 years)


2 years

Health behaviors, health status, and health service utilization

Generating weekly action plans, modeling behaviors, problem-solving, goal-setting

Greater change in minutes of physical activity, the practice of cognitive symptom management, and improved communication with physicians; Greater health, less disability, fewer limitations in their social activities, greater energy, less health distress, and fewer nights spent in the hospital.

Although it is evident that many of the trials included in this section focused on similar types of behavioral skills, including goal setting, action planning, self-monitoring, and problem-solving, there is likely considerable variability in how these skills were defined and implemented (Abraham & Michie, 2008). For example, goals can vary on a number of dimensions, including specificity, time span, and feasibility. Similarly, self-monitoring strategies may range from the use of objective tools such as an accelerometer to keeping behavioral logs to greater conscious awareness of one’s actions. Variability in these constructs may be critical for understanding when and why behavioral skills training is likely to be most effective for changing health behaviors (for a similar critique, see Sheeran, Klein, & Rothman, 2016). Relatedly, although behavioral skills training is presumed to increase self-efficacy, trials rarely report manipulation checks to confirm whether behavioral skills training engendered higher levels of self-efficacy among the intervention (relative to the control) group. Future research may consider incorporating more explicit definitions describing how behavioral skills are being defined and implemented and provide evidence that these skills are having positive effects on people’s level of self-efficacy. For an example of explicit definitions and taxonomy of behavioral change techniques, see Abraham and Michie (2008).

In summary, greater standardization of implementation of behavioral interventions is needed to advance the effectiveness of health promotion interventions in integrated healthcare settings. Critical factors include addressing self-monitoring, receiving feedback, action plans, problem-solving, and goal setting. Engaging significant others such as family members, parents, teachers, and healthcare providers in the process may increase the likelihood of successful implementation and improvements in youth health-related outcomes.

Multidisciplinary Approaches to Healthcare and Cost-Effectiveness

While behavioral skills training interventions have been effectively delivered by clinical and health psychologists, interventions that have been offered by physicians have been shown to produce relatively small effects. For example, a meta-analysis of 17 randomized controlled trials found that brief advice from a physician (compared to no advice) was associated with a small but significant increased probability of quitting smoking (relative risk (RR) 1.66, 95%; CI = 1.42–1.94 (Stead, Bergson, & Lancaster, 2008). Similarly, a recent meta-analysis found that relative to control settings, behavioral lifestyle interventions implemented in primary care settings were effective for reducing body mass index among adolescents, but the overall effect size was small in magnitude (d = 0.26; Mitchell, Amaro, & Steele, 2016). In general, while physician-based interventions have shown small effects on improving health behaviors, more research is needed to compare the integration of behavioral interventions in healthcare settings with behavioral health experts and to evaluate the cost-effectiveness of effectively implementing behavioral interventions in the healthcare setting.

An increasing number of trials are providing cost-effectiveness analyses that further support the benefits of integrating behavioral interventions into part of the integrated care treatment plan. The DPP trial conducted cumulative undiscounted per capita direct medical costs analyses of the interventions over 10 years (DPP Research Group, 2012). The cumulative combined total direct medical costs of care were least for lifestyle outside of the DPP trial ($26,810 lifestyle vs. $27,384 pharmacological therapy vs. $29,007 placebo). The cumulative quality-adjusted life years were greatest for lifestyle (6.89) than pharmacological therapy (6.79) or placebo (6.74). When costs and outcomes were discounted at 3% and adjusted for survival, lifestyle cost $12,878 per quality-adjusted life years and pharmacological therapy had slightly lower costs and nearly the same quality-adjusted life years as placebo. These results suggest that from a payer perspective, lifestyle and pharmacological therapy interventions provided marginally more cost savings compared to placebo.

 The Look AHEAD Research Group (2014b) assessed the relative impact of the intensive lifestyle intervention on use and costs of healthcare in the Look AHEAD trial. Overweight and obese adults were randomized to the intensive lifestyle intervention or a diabetes support and education comparison program. The intensive lifestyle intervention resulted in reductions in annual hospitalizations, hospital days, and number of medications and resulted in a cost savings for hospitalization and medication producing a relative per-person 10-year cost savings of $5280. However, these cost savings were not demonstrated for those with a history of cardiovascular disease. Lorig et al. (2001) have also estimated that the savings accrued by fewer visits to the hospital and emergency rooms across a 2-year period is at least three times greater than the cost of providing the CDSMP.

Taken together, the results from these cost-effectiveness studies suggest that providing patients with self-management and behavioral lifestyle programs not only improves their ability to manage and cope with their chronic illnesses, but it is also a cost-effective approach that can ultimately lead to reductions in national healthcare costs. As evidenced by a recent special issue, there is an increased need for developing standardized approaches to cost-effective analyses for the evaluation of behavioral interventions (Wilson, Christensen, Jacobson, & Kaplan, 2018). 

Summary and Conclusions

In this chapter we reviewed the evidence from randomized controlled trials that demonstrate the importance of integrating behavioral interventions for improving lifestyle behaviors (e.g., physical activity, healthy diet, weight management) for preventing and treating a variety of chronic diseases. Critical components of effective interventions included targeting self-regulation and self-efficacy through strategies such as self-monitoring, developing action plans, and utilizing effective goal setting strategies across the life span. While limited research exists on comparing the effectiveness of integrating behavioral health experts into the integrated care team, the effects of traditional randomized trials show the consistent effectiveness of implementing behavioral interventions with a high fidelity of delivery. Furthermore, there is a growing literature that supports the cost-effectiveness of behavioral interventions on reducing hospital utilization and medication usage. Overall, cost savings are potentially substantial and have important implications for reducing national healthcare costs.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PsychologyBarnwell College, University of South CarolinaColumbiaUSA

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