Health rests on our daily behavioral routines (Weisner, 2002
). Five habits lead to 70% of morbidity and mortality: how much and what we eat, exercise, smoking, and alcohol use (deVol & Bedrosian, 2007). These lifestyle behaviors are significantly and positively related to quality of health and mental health (Walsh, 2011
). Delivering care for the chronic illnesses resulting from these habits accounts for more than 75% of medical care costs (Centers for Disease Control & Prevention [CDC], 2009
). If we add sleeping, mating, drug use, and relationship habits, we account for another significant proportion of the burden of chronic and infectious diseases.
Concurrently, 27% of Americans experience mental health symptoms and disorders that significantly impact families’ daily routines, workplace productivity, and quality of life (Kessler & Wang, 2008
). Mental health symptoms result in at least $500 billion annually in lost workplace productivity (Birnbaum, et al., 2010
) and often lead to over-utilizing medical care (O’Donohue & Cucciare, 2005
). Containment of America’s health care costs rests not only in health care reform, but also in the daily routines and lifestyles of American families.
Psychologists’ primary technology for influencing Americans’ routines are EBIs, both for prevention and treatment (Kazak, Hoagwood, Weisz et al., 2010
). There are now hundreds of EBI programs that can reliably shape or reshape Americans’ habits (National Research Council & Institute of Medicine, 2009
) validated by at least a dozen different registries or organizations (e.g., National Registry of Evidence-based Prevention Programs [NREPP] and the CDC Diffusion of Effective Behavioral Interventions [DEBI]). Similarly, psychotherapeutic EBIs achieve significant and sustained improvements for children, families, and adults (Weisz & Kazdin, 2010
; Nathan & Gorman, 2007
). However, neither preventive nor therapeutic EBIs have been fully scaled nationally (Glasgow & Sanchez, 2011).
Implementation data are not available for the diffusion of the compendiums of EBIs for prevention. Principal investigators or parties with vested interests have typically only tracked the diffusion of their own EBIs. Two EBI programs are perhaps the best examples of diffusing EBIs for prevention. The Nurse-Family Partnership (NFP) is a home visiting program during the first two years of life that has demonstrated significant and substantial improvements in maternal and child outcomes over 15 years in multiple randomized controlled trials (e.g., Olds, Sadler, & Kitzman, 2007
). Improvements have been demonstrated in maternal reproductive health, criminal justice contact, and income, as well as children’s behavior problems, substance use, and criminal justice contact. Every day 22,000 low income mothers are reached by the NFP program. Yet, there are about 1.6 million low income women whose families would benefit from these services who do not receive them (Hill et al., 2009
). Similarly, Gil Botvin’s Life Skills Training (LST), a school-based drug abuse prevention program for adolescents, has repeatedly demonstrated significant positive impacts on alcohol, tobacco, and drug use, as well as violence and delinquency (Botvin, Griffin, & Nichols, 2006
). LST is adopted in 3,000 schools and serves approximately 1 million elementary and middle school children annually (“About the Botvin LifeSkills Training,” n.d.). However, there are over 90,000 public elementary and secondary schools in the U.S. needing drug abuse prevention (U.S. Department of Education, 2004-2005). These successfully diffused EBIs suggest a sizable gap exists between the potential and realized impact of preventive EBIs.
A similar gap exists for EBIs for treatment of mental health problems and disorders. Access to mental health care is highly limited; even though parity legislation exists, mental health and physical health disorders continue to be treated differentially (Wang, Lane, Olfson, Pincus, & Wells et al., 2005
). Only 24% of children and 35%–45% of adults with mental health needs have received any mental health services (Ringel & Sturm, 2001
; Leatherman & McCarthy, 2005
; Goldstein, Olfson, Martens, & Wolk, 2006
). When services are received, the service is likely not the most effective option (Zima et al., 2005
; Weisz et al., 2006
). The gap is even greater for African-Americans and Asian Americans, compared with white Americans (Harris et al., 2005
). Under-utilization of effective prevention and therapeutic services contributes significantly to excess morbidity and mortality (Strong, Mathers, Leeder, & Beaglehole, 2005
), as well as higher medical costs (DiMatteo, 2004
Thus, EBI science could be more useful. We are not realizing its potential. To put our progress in perspective, mobile phones and social networking have revolutionized families’ lives globally in under five years. Facebook went from 0 to 500 million members in 6 years; adults are spending an average of 5.5 hours social networking daily (http://blog.nielsen.com/nielsenwire/online_mobile/what-americans-do-online
). Private enterprise saturates our daily lives with messages and cues that change our behaviors. Brand loyalty to McDonald’s, for example, is established by the age of nine (Schlosser, 2001
). Our EBI science needs to shape families’ daily lives as much as McDonald’s or Facebook shapes Americans’ daily routines. Reconsidering how science can be broadly applied to servicing human behavior may help us achieve this goal.