On an intuitive level, preventing mental, emotional, and behavioral (MEB) disorders among young people is one of the soundest investments a society could make. The benefits include higher productivity, lower treatment costs, less suffering and premature mortality, and more cohesive families—and, of course, happier, better adjusted, more successful young people. Given the evidence that feasible actions can be taken to achieve these benefits, the case for action is compelling. Emerging evidence that some of these interventions are also cost-effective makes the case even stronger.
In an analysis conducted for the committee, Eisenberg and Neighbors estimate that the annual costs of MEB disorders among young people totaled roughly $247 billion in 2007 (see Box 9-1). Demonstrating the effectiveness of interventions is necessary to establish a scientific basis for prevention approaches aimed at avoiding these costs. As outlined in this report, there is reason for optimism about the ability to successfully intervene in the lives of young people and prevent many negative outcomes. However, decisions about how to invest limited public resources must consider the cost of delivering the service and demonstrate that the benefits that can be expected from an intervention—both those that can be readily valued in dollars (e.g., increased productivity, decreased treatment costs) and those that cannot (e.g., alleviation of pain and suffering of both
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9
Benefits and Costs of Prevention1
O
n an intuitive level, preventing mental, emotional, and behav-
ioral (MEB) disorders among young people is one of the soundest
investments a society could make. The benefits include higher
productivity, lower treatment costs, less suffering and premature mortality,
and more cohesive families—and, of course, happier, better adjusted, more
successful young people. Given the evidence that feasible actions can be
taken to achieve these benefits, the case for action is compelling. Emerging
evidence that some of these interventions are also cost-effective makes the
case even stronger.
In an analysis conducted for the committee, Eisenberg and Neighbors
estimate that the annual costs of MEB disorders among young people
totaled roughly $247 billion in 2007 (see Box 9-1). Demonstrating the
effectiveness of interventions is necessary to establish a scientific basis
for prevention approaches aimed at avoiding these costs. As outlined in
this report, there is reason for optimism about the ability to successfully
intervene in the lives of young people and prevent many negative out-
comes. However, decisions about how to invest limited public resources
must consider the cost of delivering the service and demonstrate that the
benefits that can be expected from an intervention—both those that can be
readily valued in dollars (e.g., increased productivity, decreased treatment
costs) and those that cannot (e.g., alleviation of pain and suffering of both
1 This chapter is based in part on a paper written for the committee by Daniel Eisenberg and
Kamilah Neighbors in the Department of Health Management and Policy, School of Public
Health, University of Michigan.
24
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242 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
BOX 9-1
Methodology for Cost Estimates
1. Mental Health Service Costs
a. Multiply Ringel and Sturm’s 1998 estimate of $11.7 billion by (73.7 + 29.45)/73.7
to expand age group to include ages 18-24 (they only included ages 0-17).
b. Multiply by 2 to account for fact that their estimates do not account for full range
of settings, as suggested by Costello, Copeland, and colleagues (2007).
c. Inflate to 2007 dollars (multiply by 1.28), based on the Bureau of Labor Statis-
tics’ consumer price index (see http://www.bls.gov/cpi/).
d. Multiply by population growth between 1998 and 2007 for people under age
25 (1.07) = $45 billion.
2. Health, Productivity, and Crime Costs
a. Mental disorders: Multiply share of mental health and substance abuse–
related DALYs incurred by 0-24 age group (0.355), times National Institute of
Mental Health (2002) estimate ($102 billion for 1995—$185 billion less the
portion of total costs attributable to health care since counted in part 1), times
inflation adjustment from 1995 to 2007 dollars (1.37), times population growth
between 1995 and 2007 for people under 25 years old (1.07) = $54 billion.
b. Drug abuse: Multiply share of mental health and substance abuse–related
DALYs incurred by 0-24 age group (0.355), times Office of National Drug
Control Policy (2004) estimate ($165.1 billion for 2002—$180.9 billion less
the $15.8 billion in health care costs since counted in part 1), times inflation
adjustment from 2002 to 2007 dollars (1.15), times population growth between
2002 and 2007 for people under 25 years old (1.05) = $71 billion.
c. Alcohol abuse: Multiply share of mental health and substance abuse–related
DALYs incurred by 0-24 age group (0.355), times Harwood (2000) estimate
($158 billion for 1998—$185 billion less the portion of total costs attributable
to health care since counted in part 1), times inflation adjustment from 1998
to 2007 dollars (1.27), times population growth between 1998 and 2007 for
people under 25 years old (1.07) = $77 billion.
Total = $247 billion, which, divided by 104 million people ages 0-24, equals about
$2,380 per young person.
individuals and their families)—outweigh the costs that would be incurred
in a real-world environment. As one example of the complexity of measur-
ing costs, a serious mental disorder in a parent or a child has obvious and
measurable financial costs associated with treatment and lost productivity.
However, the disorder also often profoundly affects the overall function-
ing of the family in psychosocial ways that are devastatingly costly to the
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BENEFITS AND COSTS OF PREVENTION
family but not readily susceptible to quantification, much less valuation in
dollars and cents.
This chapter opens with a brief tutorial on cost-benefit and cost-
effectiveness analysis, as well as an explanation of what the terms
“cost-beneficial” and “cost-effective” mean. The chapter then synthe-
sizes existing knowledge on the benefits that could be achieved (namely,
avoided costs) if prevention were widely implemented on a national scale.
Next the available research on the benefits and costs of individual preven-
tion programs or types of intervention is summarized. The chapter then
discusses limitations of the available research and concludes by offering
recommendations for future research in these areas.
It is important at the outset to acknowledge the basic purpose and
limitations of economic analysis in the context of prevention and preven-
tion research. Economic analysis may be valuable at the beginning of
prevention research by quantifying the costs associated with the disorder
or problem being targeted for prevention, or at least those costs that lend
themselves to quantification. This provides a sense of the potential value
of prevention of the problem. Evaluating the cost-effectiveness of an
intervention at the end of the prevention research cycle helps determine
whether funding the intervention is a wise use of societal resources and
hence desirable for dissemination. However, economic analysis has limi-
tations as a decision-making aid. In particular, as mentioned above, even
the best analyses are challenged to capture all of the psychological and
emotional costs associated with MEB disorders in a manner that would
be deemed universally acceptable. As a consequence, estimates of the cost
of these disorders may misestimate the true social costs, possibly consider-
ably. Equally importantly, economic analysis addresses efficiency but not
equity. In some cases, a society or an organization may prefer investing
in a less cost-effective program if it is more likely to reach disadvantaged
populations. Also, particularly in the context of prevention, economic
analysis may rely on a number of unproven assumptions (see Current
Knowledge Regarding Intervention Benefit and Costs, below).
The cost-effectiveness of an intervention also often depends on the
perspective of the decision maker. In many cases, an intervention is cost-
effective from the perspective of society as a whole, but not from the
narrower perspective of a single organization considering whether to fund
the intervention. For example, consider the case of an investment in pre-
vention of MEB disorders by a health care provider. That provider incurs
the costs of the intervention and derives some of the benefits, in the form
of reduced future costs of care. However, major social benefits of the inter-
vention may be realized in other sectors of society, including the education
sector (e.g., when students are less disruptive in class) and the criminal
justice sector (e.g., when recipients of the intervention are less likely to get
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244 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
into trouble with the law). It is quite plausible that the health care orga-
nization may not perceive the intervention as worthwhile from its narrow
perspective, whereas from a social perspective the intervention is highly
cost-effective (see Chapter 11 for a discussion of implementation issues).
Addressing the disjunction between those who bear the costs of an interven-
tion and those who experience its benefits may require coordinated plan-
ning of interventions and, if possible, aligning of incentives across service
systems.
COST-BENEFIT AND COST-EFFECTIVENESS ANALYSIS
Cost-benefit analysis (CBA) and cost-effectiveness analysis (CEA) are
two methods of economic analysis used to assess whether an intervention is
desirable from an economic perspective; put simply, they evaluate whether
the benefits derived from the intervention are worth the cost invested in
the intervention. The principal distinction between the two techniques lies
in the measurement of desired outcomes. In CBA, all such outcomes are
valued in monetary units (dollars), permitting a direct comparison of the
benefits produced by the intervention with its costs. When benefits exceed
costs, the intervention is said to be cost-beneficial. When benefits fall short
of costs—and assuming that one is comfortable that all important posi-
tive outcomes have been captured in monetary terms—the conclusion is
that the intervention is not worth undertaking. CBA is the ideal form of
analysis given that it allows a comparison of desired outcomes (benefits)
and undesired outcomes (costs) in the same metric. This permits a precise
conclusion about the desirability of the intervention. Is the intervention
“worth it”?
CEA, in contrast, is used when one or more major desired outcomes
cannot be readily measured in monetary terms but a major outcome, mea-
sureable in another metric, is common to the interventions being compared.
A notable example in the health care literature pertains to interventions that
avoid preventable premature deaths (or preventable illness or disability).
Historically, the principal outcome in published studies was measured in
terms of life-years saved. Now, most commonly, outcomes are measured
as quality-adjusted life years (QALYs). Analysts typically employ CEA
when they think that the desired outcome does not lend itself readily to
monetization. Thus, breast or prostate cancer screening and treatment
avoid premature deaths, but as they do so primarily for people beyond
their working years, many analysts are uncomfortable attributing a dollar
value to the beneficiaries’ extra years. It is possible to do so, using a mea-
sure of willingness-to-pay (Gafni, 1997). Since the desired outcomes and
the undesired outcomes (costs) are measured in different metrics in CEA
(life years and dollars, respectively), the bottom line of a CEA is a ratio,
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245
BENEFITS AND COSTS OF PREVENTION
in this case cost per QALY. An intervention is deemed cost-effective if it
produces the desired outcome at a reasonable price, typically the lowest
cost to realize a QALY among competing interventions. Thus, if an analyst
is comparing three different interventions, all other things being equal, the
cost-effective intervention is the one for which the cost per QALY is the
least. (This simplification ignores additional concerns—the other things not
being equal—such as who benefits from the extra life years.) Often, analysts
will label cost-effective an intervention not compared directly with alterna-
tive investments. In such instances, typically they are comparing their find-
ings to a standard in the literature. As a rule of thumb, ratios in the range
of $50,000 to $100,000 or lower per life year lost are generally considered
cost-effective (Ubel, Hirth, et al., 2003).2
In theory, a well-designed CBA and CEA of the same intervention
should yield the identical conclusion about the desirability of the interven-
tion (Bleichodt and Quiggin, 1999). An intervention will be cost-effective—
that is, cost less per unit of benefit than alternative interventions—if its
benefits exceed its costs and do so with a net benefit that is greater than that
of the alternative interventions. In practice, however, because researchers
often focus on somewhat different outcomes depending on the method
being used,3 one cannot assume that CBA and CEA will yield identical con-
clusions about intervention desirability. Furthermore, all of these analyses
rest on assumptions related to the quantification and valuation of important
outcomes, assumptions that can drive the conclusions reached. Indeed, stan-
dard practice in CBA and CEA should include use of sensitivity analysis, a
family of methods to evaluate whether bottom-line conclusions are sensitive
to assumptions made in the analysis (Gold, Russell, et al., 1996).
The health care literature is dominated by CEAs; that is, one finds rela-
tively few CBAs (Hammitt, 2002). The principal reason is the inability, or
reluctance, of analysts or policy makers to place dollar values on important
health outcomes. As we describe below, however, the prevention field seems
to be an exception: the majority of studies to date have employed CBA.
ECONOMIC NEED FOR PREVENTION
Prevention, by definition, is undertaken to avoid harmful outcomes; the
potential benefits of prevention are therefore equivalent to the net harms,
or costs, of those outcomes. MEB disorders among young people account
2 Ubel, Hirth, and colleagues (2003) assert that the cost-effectiveness threshold should be
raised to $200,000 or more per QALY.
3 For example, researchers using CBA may ignore improvements in health-related quality of
life, because other benefits, such as reduced crime and increased employment, are easier to
quantify in dollar terms.
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246 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
Mental, Emotional, and Behavioral Disorders
Health of Individual Health of Others
• Mortality • Family
• Health-related quality • Victims of crimes
of life
• Peers
Economic Resources Informal Care
Juvenile Justice
Services
Productivity
Education
Health Care Child Welfare
FIGURE 9-1 Costs of mental, emotional, and behavioral disorders among young
people.
SOURCE: Adapted from Eisenbergg9-1.eps
Fi and Neighbors (2007).
for considerable costs to the health care, child welfare, education, juvenile
justice, and criminal justice systems, as well as enormous additional costs
in terms of the suffering of individuals, families, and others affected (see
Figure 9-1). The most direct and probably most significant economic cost
is increased morbidity and decreased health-related quality of life of the
individual experiencing a MEB disorder.
The individual’s health problems, in turn, may lead to adverse conse-
quences for other members of society, such as family members, victims of
crime, and peers. Health problems typically also lead to additional costs,
in the form of reduced productivity and earnings (Kessler, Heeringa, et al.,
2008) and increased use of a range of social services. And, of course, MEB
disorders place enormous stress on young people themselves and interfere
with healthy development.
Morbidity and Quality of Life
MEB disorders among young people are associated with substantially
increased morbidity and reduced health-related quality of life. These health
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247
BENEFITS AND COSTS OF PREVENTION
problems are associated with psychological suffering (U.S. Public Health
Service, 1999a) as well as increased risks of physical illnesses (Vreeland,
2007). These health consequences represent an enormous burden during
childhood (Glied and Cuellar, 2003) and are also correlated with sig-
nificantly increased risks to health and reduced productivity in adulthood
(Kessler, Berglund, et al., 2005; Kessler, Ormel, et al., 2003).
A young person’s mental disorder or substance abuse may also lead to
negative health consequences for other members of society. For example,
mental disorders lead to lost productivity and functioning not only for the
children, but also for the parents and caregivers of the children (Tolan and
Dodge, 2005). Untreated mental illness may also have intergenerational
effects. Having a depressed mother, or having two parents with poor mental
health, is associated with mental, behavioral, and emotional problems in
children (Kahn, Brandt, and Whitaker, 2004; see also Chapter 7).
Substance abuse, and to a lesser extent other MEB disorders, are also
associated with more frequent risky behavior (such as driving under the
influence) (Harwood, 2000), which often have substantial health repercus-
sions for others. In addition, an individual’s health condition may affect his
or her peers; in particular, substance abuse (Gaviria and Raphael, 2001)
and suicidal behavior (Gould, Jamieson, and Romer, 2003) are thought to
spread among peers via a contagion effect.
To quantify the total health burdens posed by various illnesses and dis-
orders, researchers with the Global Burden of Disease project of the World
Health Organization (WHO) and the World Bank calculated disability-
adjusted life years (DALYs) lost due to each health condition. This measure
accounts for both morbidity (mainly measured by functional impairments)
and mortality. For the United States, depression and alcohol use and
abuse were among the top five sources of premature death and disability
(Michaud, McKenna, et al., 2006). According to the most recent estimates
by age group for the United States, in 1996 mental disorders and substance
abuse accounted for 30 percent of DALYs lost by people under age 25
(calculation by Eisenberg and Neighbors based on Supplementary Material,
Additional File 4 to Michaud, McKenna, et al., 2006).4 This represents by
far the highest burden of any disease category for this broad age range. By
more specific age intervals, the proportions were 3 percent for ages 0-4, 18
percent for ages 5-14, and 48 percent for ages 15-24. Given evidence that
people with mental disorders are at greater risk for both communicable
4 This percentage was calculated by including all conditions in the Global Burden of Disease
project’s neuropsychiatric category except epilepsy and multiple sclerosis, which are not typi-
cally considered mental disorders. Updated estimates for the United States, for the year 2005,
will be available within the next few years, according to Catherine Michaud, the first author
of the report used to generate the estimates here.
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248 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
and noncommunicable diseases and that their disorders contribute to both
intentional and unintentional injuries, the percentage may be even higher
(Prince, Patel, et al., 2007).
Economic Resource Costs
Health problems associated with MEB disorders decrease productivity
and significantly increase the utilization of services, thus reducing economic
resources available to society for other purposes.
Productivity5
During childhood and adolescence, when most people do not partici-
pate in the labor market, the direct impacts of mental disorders and sub-
stance use on economic productivity are small but real. Young people with
MEB disorders may diminish the productivity of others closely involved
in their lives, particularly family members. For example, the stress and
unpredictability of having a child with a serious MEB disorder can interfere
with parents’ work lives (Busch and Barry, 2007), or a disruptive child in
a classroom can interfere with other students’ learning. There may also
be significant costs to the work or educational productivity of siblings
(Fletcher and Wolfe, 2008).
The indirect and long-term consequences are also likely to be large.
These conditions interfere with young people’s ability to invest in their own
human capital via education. Many studies show that poor mental health
and substance use among young people are negatively related to participa-
tion and performance in school (Diego, Field, and Sanders, 2003; Glied and
Pine, 2002), as well as high school completion (Vander Stoep, Weiss, et al.,
2003), important determinants of productivity in adulthood. These factors
can increase risk for such behavioral problems as delinquent and antisocial
behavior (Yoshikawa, 1994). Also, to the extent that MEB disorders in
childhood carry over into adulthood, there will be further reductions in
economic productivity. A large number of studies, many of which focus on
depression, document that adults with mental illness and substance abuse
disorders are less likely to be employed, and those who are employed work
fewer hours and receive lower wages (see Ettner, Frank, and Kessler, 1997;
Kessler, Heeringa, et al., 2008). Similarly, as adults, employees with mental
5 When aggregating the costs of mental disorders and substance abuse, it is important to keep
in mind that productivity costs may already be reflected, at least to some extent, in measures of
health burden, such as DALYs. Thus, one might be double-counting by claiming, for example,
that a case of depression accounts for a certain number of DALYs in addition to productivity
costs. This caveat, however, does not take away from the fact that in general productivity costs
are large and important to consider in their own right.
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BENEFITS AND COSTS OF PREVENTION
health or substance abuse disorders can reduce the productivity of other
workers, particularly if the job affects the work of others (e.g., assembly
line work).
Utilization of Services
As one would expect, mental disorders and substance abuse are strongly
associated with increased utilization of mental health and substance abuse
services. Ringel and Sturm (2001) estimated the annual national costs
of mental health treatment for children under age 18, as of 1998, at
$11.68 billion, or $172 per child. They found that expenditures were $293
per child for ages 12-17, $163 per child for ages 6-11, and $35 per child
for ages 0-5. Adjusted to current dollars using the consumer price index,
the annual national costs in 2007 would be $14.8 billion. We are not aware
of analogous estimates for substance abuse treatment of young people,
although estimates are available for adults for alcohol abuse (Harwood,
2000) and drug abuse treatment (Office of National Drug Control Policy,
2004). In the past 15 to 20 years, the mix of mental health services for
young people has shifted from inpatient to outpatient settings (Ringel and
Sturm, 2001), as in the adult population (Wang, Demler, et al., 2006). Also,
as in the adult population, the relative treatment mix for children’s mental
health has shifted from specialty settings to primary care (Wang, Demler,
et al., 2006) and from therapy and counseling to medication (Glied and
Cuellar, 2003) (although this latter shift was interrupted in 2003 by the
Food and Drug Administration’s warnings about the use of antidepressant
medications for children) (Libby, Brent, et al., 2007). These changes are also
not fully reflected in the estimates cited.
Young people with MEB disorders have higher utilization of mental
health services across a range of social service systems, not just health care.
Costello, Copeland, and colleagues (2007) considered data from a range of
settings and demonstrated that mental health service costs in health care set-
tings represent only a modest fraction of the total costs incurred by children
with mental disorders for these services. Using a sample of adolescents ages
13-16 in western North Carolina, they estimated that mental health service
costs for adolescents with mental disorders equated to $894 per adolescent
in the local population, with more than one-quarter (27 percent) of the
total costs incurred in the school and juvenile justice systems.6 The overall
estimate is over three times that in the Ringel and Sturm (2001) study,
6 This number is based on converting the total costs per 100,000 population in Table 2 in
Costello, Copeland, and colleagues (2007) to total costs per person. The percentage attribut-
able to the school and the juvenile justice systems is based on dividing the sum of these costs
($10.9 million and $13.2 million, respectively) by the total costs ($89.4 million).
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250 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
which focused mainly on mental health service costs in health care settings.
The findings of Costello, Copeland, and colleagues (2007) are consistent
with other empirical studies showing that MEB disorders are associated
with increased use of services in nonmedical settings, such as foster care
(Harman, Childs, and Kelleher, 2000), special education (Bussing, Zima, et
al., 1998), and juvenile justice (Teplin, Abram, et al., 2002).
Youth with MEB disorders who become involved with the juvenile
justice system also often incur costs related to law enforcement and court
expenses, detention, placement and incarceration, and other forms of treat-
ment that are publicly provided (National Center on Addiction and Sub-
stance Abuse, 2004). In addition, violent crimes can result in victim costs,
such as medical care, treatment through public programs, and property
damages to victims. The costs associated with all juvenile (under age 18)
arrests in 2004 were estimated at about $14.4 billion (National Center
on Addiction and Substance Abuse, 2004), and the costs of medical care,
treatment through public programs, and property damages to victims of
juvenile violence were estimated at about $95 million (Miller, Sheppard,
et al., 2001). Although not all of these crimes were committed by young
people with MEB disorders, overall costs of these disorders would be
higher if the cost of relevant juvenile crimes were included with service use
estimates. In addition, these health problems lead to significantly increased
use of informal (unpaid) care by family members and others. For example,
family members with a child with mental health care needs are more likely
than family members whose children do not have these needs to reduce
their working hours or stop working to care for their child (Busch and
Barry, 2007).
Using data from the Fast Track project, Foster, Jones, and colleagues
(2005) estimated that each youth with conduct disorder incurs public costs
of more than $70,000 over a seven-year period, with costs incurred by the
juvenile justice, education, and general health care systems in addition to
the mental health system. Similarly, a study in the United Kingdom (Scott,
Knapp, et al., 2001) documented societal costs from childhood conduct
disorder that extended into adulthood. Children who had diagnosed con-
duct disorder at age 10 incurred public service costs by age 28 that were
10 times higher than those considered to have no problems and 3.5 times
higher than those with conduct problems but not diagnosed with conduct
disorder. This suggests that preventive interventions aimed at addressing
behavioral problems before they reach the threshold for a diagnosis could
yield significant savings.
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BENEFITS AND COSTS OF PREVENTION
Estimates of Total Costs
Comprehensive “cost of illness” studies quantify and aggregate, in
monetary terms, the various costs associated with particular illnesses or
disorders. Although there are many recent studies of this type in European
countries, the most recent estimates in the United States correspond to 1995
for mental disorders (National Institute of Mental Health, 2000), 2002 for
drug abuse (Office of National Drug Control Policy, 2004), and 1998 for
alcohol abuse (Harwood, 2000). Aggregating service costs and health and
productivity costs7 for individuals age 18 and older,8 the annual economic
costs of mental disorders were estimated at $185 billion in 1995 (National
Institute of Mental Health, 1999), the annual economic costs of drug
abuse in 2002 were estimated at $180.9 billion (Office of National Drug
Control Policy, 2004), and the annual economic costs of alcohol abused
in 1998 were estimated at $185 billion (Harwood, 2000). These reports
do not permit an estimate of costs specific to people from birth to age 24.
However, in an analysis for the committee, Eisenberg and Neighbors used
data in these reports to make a rough approximation, for the year 2007, by
making the following two assumptions: (1) the full cost of services for this
age group per person is twice as high as the mental health care costs per
person estimated by Ringel and Sturm (2001)9 and (2) the population share
of health, productivity, and crime-related costs for people ages 0-24 is 35.5
percent (a calculation based on Supplementary Material, Additional File 4
to Michaud, McKenna, et al., 2006). Under these assumptions, Eisenberg
and Neighbors estimated that the total annual economic costs are roughly
$247 billion as of 2007 (in 2007 dollars),10 or about $2,380 per person
under age 25. This per-person total includes about $500 in health service
costs and $1,900 in health, productivity, and crime-related costs.
Several caveats pertain to this estimate. Perhaps most notably, one
would not be able to prevent all of these costs, no matter how much one
7 The authors measured health and productivity costs by estimating the lost or diminished
income due to morbidity and mortality. This is typically called a human capital approach to
valuing health. Estimates from the human capital approach tend to be lower than estimates
from willingness-to-pay approaches and are typically considered lower bound estimates (Hirth,
Chernew, et al., 2000). Note that they also accounted for costs to other members of society,
such as informal care and crime.
8 Although the reports are not specific about the age groups included, one can infer that they
apply to those age 18 and over based on the data sources used.
9 This is a conservative assumption in two respects. First, it is lower than the adjustment
factor of 3-4 estimated by Costello, Copeland, and colleagues (2007). Second, treatment costs
are rising over time; for example, Mark, Coffey, and colleagues (2005) found that mental
health and substance abuse treatment costs for the full population increased from $60 billion
in 1991 to $104 billion in 2001.
10 Note also that the estimate of total costs accounted for population growth.
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252 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
invested in prevention. Not all MEB disorders are preventable, given cur-
rent knowledge, and some may never be preventable. On one hand, from
this perspective, the estimate of $247 billion overstates the potential value
of prevention. On the other hand, this estimate includes only costs avoided
from preventing disorders that would meet full clinical criteria and does not
include costs that would be avoided from reducing problem behaviors and
symptoms in the range in which symptoms are not severe enough to meet
diagnostic criteria. These costs are generally not included in cost-of-illness
studies, but they may be very large. From this perspective, the estimate
of $247 billion understates the aggregate costs of MEB disorders among
young people. As well, the estimate does not fully capture the quality of life
of the children and their families.
Quantifying the costs of MEB disorders among young people is useful
as a way to approximate the potential value of prevention and to compare
the burden of these disorders11 among young people with other disease
burdens, but very few studies have addressed this topic. In general, as Hu
(2006) describes, methodologies in cost-of-illness studies vary and often
depend on several assumptions that require further study. In the context
of MEB disorders among young people, one important next step for this
research literature is to conduct a comprehensive cost-of-illness study for
the United States that builds on previous studies, such as Harwood, Ameen,
and colleagues (2000) and Ringel and Sturm (2001), and the estimates cre-
ated for this report by Eisenberg and Neighbors (2007) and accounts for
the substantial use of services outside medical settings shown by Costello,
Copeland, and colleagues (2007). After the initial work is completed to
refine the methodology and identify data sources, periodic updates will be
much easier to produce. In addition, further research is needed to improve
the ability to project lifetime consequences of mental disorders in child-
hood. In particular, researchers face the challenge of disentangling con-
founding factors from true causal relationships in observed relationships
between mental disorders in childhood and later outcomes.
Miller (in Biglan, Brennan, et al., 2004) provides a much higher esti-
mate of $435.4 billion in 1998 ($557.3 in 2007 dollars) for the costs of
problem behaviors among youth, defined as underage drinking, heroin or
cocaine abuse, high-risk sex, youth violence, youth smoking, high school
dropout, and youth suicide acts. More than half was attributable to suffer-
ing and quality of life, with the balance consisting of work losses, medical
spending, and other resource costs. Averaged across all youth, this would
be an average cost of $12,300 per youth ages 12-20 ($15,744 in 2007
dollars).
11 Thediscussion that follows refers specifically to emotional and behavioral disorders rather
than problems, as it is referring to costs associated with actual disorders.
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COST-EFFECTIVENESS OF PREVENTIVE INTERVENTIONS
Although the potential benefits from preventing MEB disorders are
clearly large, and there is a substantial and growing body of evidence
documenting the positive outcomes of prevention interventions, relatively
few evaluations have been conducted to assess the cost-effectiveness of the
interventions. The evaluations that are available tend to be those associ-
ated with the interventions with the longest follow-up and include some
of the most successful programs. Similarly, cost-effectiveness evaluations
tend to be limited to such areas as early childhood development, youth
development, and prevention of violence, depression, and substance abuse,
in which there has been more research overall. In addition, most of the
favorable cost-effectiveness results apply to interventions for higher risk
populations, although a small number of universal prevention programs
have also been shown to be cost-effective.
Aos, Lieb, and colleagues (2004) reviewed the economic analyses of a
large number of relevant interventions. The authors conducted a compre-
hensive and detailed review and analysis for the Washington State govern-
ment of prevention and early intervention programs designed to (1) reduce
crime; (2) lower substance abuse; (3) improve educational outcomes, such
as test scores and graduation rates; (4) decrease teen pregnancy; (5) reduce
teen suicide attempts; (6) lower child abuse or neglect; and (7) reduce
domestic violence. In addition to the discussion below based in part on
their analysis, we refer the reader to this study as a resource for additional
empirical results as well as a detailed discussion of methodological issues.
Early Childhood Interventions
Perhaps the most heavily researched preventive programs are early
childhood interventions for children from birth to age 5. Some of these
programs are primarily home-based, whereas others are primarily cen-
ter-based. In a meta-analysis of over 25 studies of home visitation pro-
grams (by nurses or other trained professionals), Aos, Lieb, and colleagues
(2004) concluded that the average benefits per child were about $11,000
and costs were about $5,000.12 The benefit-cost ratio has been shown to
be higher for certain programs; for example, in an economic evaluation
of the Nurse-Family Partnership Program, Karoly, Kilburn, and Cannon
12 All dollar values in this section are in 2002 or 2003 dollars. In addition to average effects
for this group of programs, Aos, Lieb, and colleagues also estimated the benefits of the Nurse-
Family Partnership at $26,298 and the costs at $9,118 and the benefits of the HIPPY (Home
Instruction Program for Preschool Youngsters) at $3,313 and the costs at $1,837. They esti-
mated that benefits exceeded costs for the Comprehensive Child Development Program and
the Infant Health and Development Program.
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254 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
(2005) found that the program cost about $7,000 per child and produced
total benefits of about $41,000 per child for the higher risk sample and
about $9,000 per child for the lower risk sample.13 In general, some of the
main benefits of home visitation programs, converted into dollar estimates
of their value, have been reduced child abuse, improved achievement test
scores, and decreased likelihood of arrest later in life. The benefits from
reduced child abuse are generally estimated on the basis of reductions
in medical, child welfare, and other public service costs and crime costs,
based on epidemiological evidence showing correlations between child
abuse and these costs later in life. Improved achievement test scores are
usually valued on the basis of how earnings relate to education. Finally,
arrests are valued in terms of both the costs to the criminal justice systems
and victims (particularly health costs for crimes involving injuries) and
lost productivity while incarcerated (see also the technical appendix to
Aos, Lieb, et al., 2004).
Several different center-based early interventions also appear to have
benefits that exceed their costs (see Targeting Early Childhood Devel-
opment in Preschool in Chapter 6 for further discussion of these pro-
grams). In a meta-analysis of over 50 studies of early childhood education
programs for low-income 3- and 4-year-olds, Aos, Lieb, and colleagues
(2004) found that, on average, benefits per child were $17,000 and costs
were $7,000. In an economic analysis of the Abecedarian Early Childhood
project, an intensive, multiyear intervention for children from birth to age
5, Barnett and Masse (2006) found that per-child benefits were $158,000
and costs were $63,000; the primary benefits were related to cognitive
abilities and education, which were valued in terms of estimated impact
on future earnings. The intervention was also associated with a reduction
in smoking, which was valued in terms of estimated reduction in pre-
mature mortality (with a year of life then valued at $150,000, based on
willingness-to-pay estimates in the literature). The Perry Preschool proj-
ect, which included 1-2 years of intensive preschool, home visiting, and
group meetings of parents, had estimated per-child benefits of $240,000
and costs of $15,000 (Belfield, Nores, et al., 2006); the primary benefits,
some of which were observed well into adulthood, were reduced crime,
positive academic outcomes, and reduced smoking. The Chicago Child-
Parent Centers, a center-based preschool education for disadvantaged
children, had estimated benefits per child of $75,000 and costs of $7,400
(Temple and Reynolds, 2007); the primary benefits were improved aca-
demic outcomes and reduced crime.
Temple and Reynolds (2007) compared the benefit-to-cost ratios of
13 Although
the estimates provided by Aos, Lieb, and colleagues (2004) and Karoly, Kilburn,
and Cannon (2005) differ, the difference between benefits and costs is substantial for both.
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the Perry Preschool project, the Carolina Abecedarian project, and the
Chicago Child-Parent Centers to other types of interventions designed to
benefit children’s development. They concluded that preschool education
has a more favorable benefit-to-cost ratio than the Special Supplemental
Nutrition Program for Women, Infants, and Children, the Nurse-Family
Partnership, a class-size reduction initiative for grades K-3, and the Job
Corps. There has been debate, however, regarding the benefits and costs of
pre-K programs, including Head Start (Cook and Wong, 2007), the most
heavily funded and widespread early childhood education program. Ludwig
and Phillips (2007) attempt to resolve the debate by pointing out that Head
Start costs about $9,000 per child, and would need to produce academic
achievement gains only on the order of .1 to .2 standard deviations to con-
fer equivalent benefits. They argue that the evaluation literature on Head
Start strongly favors a benefit of this size or more, and that the program
should be viewed as cost-beneficial. Heckman (1999, 2007) argues that
investments in early childhood development, particularly for disadvantaged
children, have greater payoff in terms of the development of skills needed
for future success than do investments in any other period of life. A sys-
tematic review of economic analyses of programs targeting mental health
outcomes or accepted risk factors for mental illness by Zeichmeister, Kilian,
and colleagues (2008) concluded that, among the few available studies, the
most favorable results were for early childhood education programs.
Youth Development Interventions
Although comprehensive interventions in early childhood have prob-
ably received more attention from scholars and policy makers, many com-
prehensive interventions for older (school-age) children and adolescents
also appear to be cost-effective. Aos, Lieb, and colleagues (2004) found that
five of the six youth development programs reviewed,14 whose aims include
improving parent–child relationships and reducing problem behaviors, such
as substance use and violence, are cost-beneficial, with benefit-cost ratios
ranging from 3 to 28. These authors also found that several programs for
juvenile offenders, with a range of goals mostly pertaining to improved
behavior, are highly cost-effective, yielding net benefits per child well over
$10,000 in many cases.
14 The programs determined to have benefits that exceed costs include the Seattle Social
Development project, Guiding Good Choices, the Strengthening Families Program for Parents
and Youth 10-14, the Child Development project, and the Good Behavior Game. CASASTART
was determined to have costs exceeding benefits.
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Interventions Targeted at Specific Mental, Emotional,
and Behavioral Disorders or Substance Use
There are currently few economic analyses of interventions that target
the prevention of specific MEB disorders or substance use among young
people, although there are a large number of studies that document effi-
cacy, effectiveness, or both (see Chapters 6 and 7). The interventions in
these economic analyses address depression, violence and conduct disorder,
and substance use. Lynch, Hornbrook, and colleagues (2005) performed a
cost-effectiveness analysis of a highly successful group cognitive-behavioral
therapy intervention to prevent depression among adolescent children of
depressed parents (see Box 7-4). They found that the intervention is very
likely to be cost-effective, with an incremental cost of $610 per child and
a cost-effectiveness ratio of $9,275 per QALY15 (95 percent CI, –$12,148
to $45,641). Foster, Jones, and Conduct Problems Research Group (2006)
found that the Fast Track intervention, designed to reduce violence and
conduct disorders among at-risk children, was about 70 percent likely to
be cost-effective in preventing conduct disorder for the higher risk group,
but it had less than a 0.01 probability of being cost-effective for the lower
risk group, which represented the majority of the sample. Aos, Lieb, and
colleagues (2004) found that 10 of the 12 substance use prevention pro-
grams (including two programs that focus on smoking prevention) they
analyzed were highly cost-effective, with benefit–cost ratios ranging from
3 to over 100.16 The estimated benefits per child were generally small (less
than $1,000 in most cases), but the costs were even smaller (less than $200
in all but one program).
Current Knowledge Regarding Intervention Benefits and Costs
Overall, knowledge about the benefits and costs of specific interven-
tions aimed at preventing MEB disorders is promising but still limited. Rela-
tive to the number of efficacious or effective interventions (see Chapters 6
and 7), few investigators have conducted cost-effectiveness or cost-benefit
analyses. There is also considerable uncertainty about many of the estimates
in the available literature. For interventions that exhibit dramatically dif-
15 QALYs, like DALYs, are measures of health that account for both morbidity and mortality.
As mentioned earlier, ratios under $50,000 per life year lost are generally considered cost-
effective; this is regardless of whether life years are adjusted for quality of life (Ubel, Hirth,
et al., 2003).
16 The programs determined to have benefits that exceed costs include the Adolescent Tran-
sitions Program, Project Northland, Family Matters, Life Skills Training, Project STAR, the
Minnesota Smoking Prevention Program, the Other Social Influence/Skills Building Substance
Prevention Program, Project Toward No Tobacco Use, All Stars, and Project Alert. DARE and
STARS for Families were ineffective, making the costs exceed the benefits by definition.
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BENEFITS AND COSTS OF PREVENTION
ferent levels of benefits compared with costs, this uncertainty may be moot,
but in other cases, it is important to consider carefully.
Perhaps the most important source of uncertainty pertains to longer
term outcomes. In many economic evaluations, longer term outcomes of
participants in an intervention are not observed and instead must be pro-
jected on the basis of other data. Many long-term benefits of early preven-
tion programs cannot be measured until middle childhood and adolescence
(e.g., juvenile crime). Longitudinal data used to make projections, such as
correlations between the incidence of MEB disorders in childhood and in
adulthood, do not necessarily represent accurate causal estimates, as Foster,
Dodge, and Jones (2003) note. Another important source of uncertainty is a
lack of statistical power. As Mrazek and Hall (1997) observe, many studies
in this literature have modest sample sizes and are not sufficiently powered
to look at key measures of effectiveness; typically, adequately powered
estimates of cost-effectiveness require even larger samples than estimates
of effectiveness per se (Ramsey, McIntosh, and Sullivan, 2001). A third,
related source of uncertainty results from the outcomes measured: that is,
whether interventions that appear to be cost-effective in reducing risk fac-
tors closely connected to MEB disorders, but do not measure disorders as
an outcome, can actually prevent the incidence of these disorders.
Another source of uncertainty includes potential differences between
cost-efficacy and cost-effectiveness. Evaluations of interventions conducted
in research settings (efficacy studies) may get different results if conducted
in real-world settings (effectiveness studies), raising potential questions
about whether the cost-effectiveness (or more accurately, cost-efficacy)
would be realized if the intervention were implemented in a nonresearch
environment (see Foster, Dodge, and Jones, 2003, for a brief discussion of
this). Similarly, the costs of interventions implemented in real-world settings
may differ from the costs in a research setting.
In addition, as discussed in more detail in Chapter 11, a major challenge
in prevention research, particularly when dealing with whole communities,
is that preventive interventions are likely to have differential impact on
individuals in different contexts because (a) participants have different risk
and protective factors that cause different responses to the intervention; (b)
the level of participation in interventions varies; and (c) interventions are
routinely delivered with varying levels of fidelity and adoption. These factors
can reduce overall impact compared to that seen in efficacy trials; thus some
analyses of behavioral or economic outcomes in community implementation
studies may not find significant effects.
There are challenges in measuring the cost of the time of children
and other people involved in interventions. Those challenges can lead to
poor estimates of costs, creating either an over- or underestimate. Often,
however, analysts omit such time costs, introducing a clear bias toward
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258 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
underestimating total costs. For example, some studies do not consider the
opportunity cost incurred by teachers delivering an intervention who might
otherwise be engaged in productive teaching activities (Aos, Lieb, et al.,
2004). Finally, and importantly, other intangibles, most notably the suffer-
ing of children and their families, are likely to be costly but extremely dif-
ficult to quantify and assign a monetary value. The difficulty in measuring
and valuing these costs restricts the potential of CBA and CEA to accurately
evaluate the relative merits of preventive interventions for MEB disorders,
which may lead to a substantial underestimation of the benefits of success-
ful interventions. Research needs to be devoted to improving measurement
methods that will permit assessment of the economic value associated with
suffering related to these disorders.
Another important caveat is that the quality of the underlying evidence
used to project costs and benefits varies. Aos, Lieb, and colleagues (2004)
account for this in their meta-analysis by assigning different weights to
studies based on indicators of quality, but such a solution has unavoidable
limitations, as the authors acknowledge. Many evaluations do not meet
some of the important guidelines for quality of evidence, as stated by such
organizations as the Food and Drug Administration (1998) and the Society
for Prevention Research (Flay, Biglan, et al., 2005). For example, evaluators
have not always published a specific plan of analysis before collecting data,
which leaves open the possibility of selectively reporting positive results
among many outcomes and analytical approaches.
A final caveat for this literature is the reminder that, while some studies
employ CEA, most of the studies in the prevention field have employed CBA.
In practice, CEA and CBA results are not strictly comparable. However, in
this literature, because most of the studies yield strong conclusions (posi-
tive in most cases), it is unlikely that the basic findings would be sensitive
to the choice of method. As this literature evolves and more interventions
with borderline cost-effectiveness are evaluated, examining the sensitivity
of conclusions to alternative assumptions will be important.
CONCLUSIONS AND RECOMMENDATIONS
The potential value of prevention of MEB disorders among young
people is enormous. MEB disorders among young people result in sig-
nificant costs to multiple service sectors. Such disorders threaten children’s
future productivity and wellness and disrupt the lives of those around
them.
Conclusion: The economic, social, and personal costs of MEB disorders
among young people are extraordinarily high.
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To date, there is some evidence that the benefits of some specific inter-
ventions outweigh the costs. However, the scientific literature on the cost-
effectiveness of prevention is still young, and it faces a number of conceptual
and practical obstacles.
Conclusion: The current body of research on costs, cost-effectiveness,
and cost-benefits of preventive mental, emotional, and behavioral inter-
ventions is very limited.
Much of the strongest evidence to date is for interventions that improve
protective factors or reduce risk factors demonstrated through research to
be closely related to MEB disorders (see Chapter 4). For example, multiple
economic evaluations of early childhood development programs have dem-
onstrated benefits that exceed costs.
It is also notable that among the limited number of interventions shown
to be cost-effective, many were either targeted to higher risk children (e.g.,
the early childhood programs such as the Perry Preschool project) or were
cost-effective only for a higher risk subgroup within the analysis (e.g., the
Fast Track study). Aside from a small number of substance use prevention
programs (see review by Aos, Lieb, et al., 2004), few universal interventions
have been demonstrated to be cost-effective for preventing MEB disorders.
Future research is needed to determine whether selective and indicated
prevention programs are inherently more likely to be cost-effective in the
context of MEB disorders, or if this finding is an artifact of the programs
that happen to have been subjected to economic evaluations thus far.
Conclusion: Of those few intervention evaluations that have included
some economic analysis, most have presented cost-benefit findings and
demonstrate that intervention benefits exceed costs, often by substan-
tial amounts.
However, few studies measure effects on diagnosable MEB disorders
as an outcome, and most do not conduct sufficient longitudinal follow-up
to fully capture potential long-term benefits. Also, considerable uncertainty
remains about some of these estimates. Economic analyses are important
for quantifying the potential value of prevention and assessing the actual
value of existing interventions.
Many scholars in the prevention field have called for more regular eco-
nomic analyses (Flay, Biglan, et al., 2005; Spoth, Greenberg, and Turrisi,
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260 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
2008; Zeichmeister, Kilian, et al., 2008).17 Many preventive interventions
have been shown to be highly effective but have not yet been evaluated
for cost-effectiveness in real-world settings. Guidelines on how to conduct
high-quality cost-effectiveness studies are needed to help shape the develop-
ment of this area of research as it continues to evolve.
Recommendation 9-1: The National Institutes of Health, in consulta-
tion with government agencies, private-sector organizations, and key
researchers should develop outcome measures and guidelines for eco-
nomic analyses of prevention and promotion interventions. The guide-
lines should be widely disseminated to relevant government agencies
and foundations and to prevention researchers.
For interventions involving young people, long-term outcomes are
often pivotal for determining cost-effectiveness, as significant benefits are
likely to accrue into adulthood, yet current knowledge is remarkably weak
in most contexts. Long-term follow-up data should be collected whenever
possible. As electronic data systems become more integrated and acces-
sible, one promising avenue is through administrative databases, which do
not necessarily depend on expensive efforts to track down and interview
participants.18 CEAs should also make clear the various sources of uncer-
tainty. If the cost-effectiveness results are dramatically positive or nega-
tive, wide intervals may not raise questions about the overall conclusion
that an intervention is cost-effective, but publishing such information will
make the assessment more transparent. Special attention should be given
to addressing the fact that costs from an intervention in one sector may be
evident in other sectors. While this has been done for early childhood, less
attention has been focused on this issue in other developmental stages, such
as adolescence.
Economic analyses should also be comprehensive in their accounting of
relevant costs and benefits. The work by Costello, Copeland, and colleagues
(2007), for example, illustrates the importance of measuring costs across a
range of service venues. Again, integration of electronic data systems may
be a valuable tool for capturing these costs. To capture the benefit of reduc-
tions in specific MEB disorders, interventions should measure diagnostic
outcomes whenever possible.
17 This is an issue not only for prevention but also for treatment of mental disorders in chil-
dren. A comprehensive review of economic evaluations of child and adolescent mental health
interventions (most of which are treatment, not prevention) found only 14 had been published
to date, although the authors speculated that two or three times that many would be in print
within five years (Romeo, Byford, and Knapp, 2005).
18 Of course, researchers would need to overcome hurdles related to informed consent and
privacy restrictions.
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Evaluations should begin to address the fact that multiple interventions
over the span of childhood may have important dynamic complementarities
(Heckman, 2007). For example, participation in an early childhood inter-
vention such as Head Start may enhance a child’s ability to benefit from a
later intervention to prevent substance use. Although it would be difficult to
randomize children to different sequences of interventions over a long time
span, empirical research to address these complementarities to the extent
possible would be very informative.
Similarly, understanding the causal links between aspects of poverty
(e.g., food insecurity, disadvantaged neighborhoods, low-quality schools)
and mental health should be improved. These links may reveal some of the
most important mechanisms by which to prevent MEB disorders in cost-
effective ways, but it is very difficult to establish incontrovertible causal
relationships due to the many likely confounders in observational data.19
While there have been calls for increased economic analyses, the num-
ber of projects that include calculation of costs and cost-effectiveness will
increase only if guidelines on how to conduct these types of analyses are
widely available and the additional costs recognized.
Recommendation 9-2: Funders of intervention research should incorpo-
rate guidelines and measures related to economic analysis in their pro-
gram announcements and provide supplemental funding for projects
that include economic analyses. Once available, supplemental funding
should also be provided for projects with protocols that incorporate
recommended outcome measures.
Although one might argue that grant awards should be increased
rather than providing supplemental funding to those that conduct eco-
nomic analyses, there is a precedent for providing supplemental funding in
other areas. For example, the National Institutes of Health (NIH) provides
research supplements for projects involving underrepresented minori -
ties and individuals to improve the diversity of the research workforce.
Although these supplements are modest, NIH has reported that they are
an effective means of encouraging institutions to recruit from currently
underrepresented groups.
Evaluations of the costs and cost-effectiveness of prevention inter-
ventions will increase only if researchers include them in their protocols.
Studies designed to determine the effectiveness of interventions in a real-
world setting should be clear not only on what the intervention costs, so
that a community can judge the feasibility of funding the project, but also
19 For
discussions of links between poverty and mental health among children, see, for ex-
ample, Ripple and Zigler (2003) and the Center on the Developing Child (2007).
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262 PREVENTING MENTAL, EMOTIONAL, AND BEHAVIORAL DISORDERS
the cost-effectiveness, or expected benefits, so that the community can
determine the potential value of their investment.
Recommendation 9-3: Researchers should include analysis of the costs
and cost-effectiveness (and whenever possible cost-benefit) of inter-
ventions in evaluations of effectiveness studies (in contrast to efficacy
trials).
Finally, cost-benefit and cost-effectiveness studies of mental health pro-
motion interventions—scarce in the literature to date—would be very useful
in permitting a meaningful comparison of the relative desirability of preven-
tion and promotion approaches.
In concluding this discussion, it is important to note that the significant
societal benefits of preventing mental, emotional, and behavioral problems
among young people may warrant intervention even when there is no spe-
cific cost-effectiveness data available, particularly if there is evidence that
an effective intervention is available. Waiting for future cost-effectiveness
analyses to become available, which might take years to develop, would put
many young people at unnecessary risk.