“Politics is the art of the possible.” Bismarck (1)
Epidemiology—the study of the distribution and determinants of health and illness in human populations—plays a crucial role in characterizing the burden of suffering associated with any health problem, including child psychiatric disorders (2). Good-quality epidemiological information is essential for developing sound public policies to improve children’s mental health (3). In general, the intended outcomes of children’s mental health policies are optimal development and well-being for all children, a reduction in the impairments associated with mental disorders, and the effective and efficient use of public funds toward these ends (4–6). Good quality epidemiological information can assist policy-makers in achieving each of these outcomes. In particular, the following kinds of information are important for policy-making: data on prevalence to estimate needs, data on causal risk and protective factors to inform the design of effective prevention and treatment programs, and data on patterns of service use to monitor outcomes (4).
Several challenges complicate policy-making in children’s mental health. Development is an overarching issue that must always be considered in planning any programs or services for children (7). Moreover, because children develop in close interaction with their environment, their needs cannot be considered separately from conditions at home, at school, and in the community (8). Children’s mental health policies must therefore take both development and broader perspectives on the determinants of health into account (9,10). In addition, children’s services are typically provided by a diverse array of sectors, including health, education, social services, and (sometimes) child protection and justice services. This situation requires significant coordination among the multiple sectors involved (5,6). These challenges make it even more crucial for policy-makers in children’s mental health to have access to good-quality epidemiological information to guide planning.
Public policy-making is inherently complex, occurring in a crucible of competing ideas, interests, and institutional structures, where scientific information such as that derived from epidemiology is only one of many influences (11). Children’s mental health must compete with other health care needs, as well as with a myriad of other issues facing legislative and administrative policy-makers, issues such as education, the environment, fiscal restraint, and even road repair. The “art of the possible” for policy-makers concerned with children’s mental health often involves making trade-offs in dynamic, contentious, and nonrational environments.
This review examines how child psychiatric epidemiology can be more useful to policy-makers who craft the art of the possible in the complex context of children’s mental health. First, we summarize recent child psychiatric epidemiological research that pertains to Canadian public policy- making. While not all research should have eventual practical applications, the need for sound public policy poses an increasing challenge to the scientific community with respect to the relevance of research topics, methods, and findings. Consequently, we also discuss the state of the science and the issues that need to be resolved to make the research more useful to policy-makers. Finally, we comment on implications for policy-making.
Review of the Research
While previous studies have covered a wide range of populations and problems, they have not always focused on issues directly pertinent to Canadian children. For this reason, we undertook a review of the recent child psychiatric epidemiological research with a specific focus on relevance for Canadian public policy-making.
We wanted to focus on studies that were large-scale, rigorously designed, and reasonably comprehensive in terms of ages and disorders assessed. Further, we wanted to focus on studies conducted in populations that were comparable with Canadian children. Consequently, the following criteria were used to select studies for more detailed review: studies had to assess representative community samples of at least 1000 children from Canada, the US, Great Britain, Australia, or New Zealand. In addition, studies had to include both children and adolescents and both boys and girls. They had to employ standardized assessment protocols for evaluating clinically important symptoms based on the DSM (III, or later editions, or equivalent) (15). To further ensure that only clinically important disorders were included, studies had to specifically assess impairment. They also had to incorporate reports from multiple informants, such as children, parents, and teachers. Studies had to report overall prevalence rates and rates for 2 or more disorders. Finally, they had to examine associated factors, patterns of service use, or both.
A total of 1263 relevant publications were initially identified using Medline. Most large-scale studies were described in several different publications. As a result, publications were grouped according to study and then assessed by the first and third authors. We identified 15 unique studies as being likely to meet criteria (13 from Medline and 2 from the hand search). Of these 15 studies, 6 met criteria for inclusion in our review. Final decisions about which studies to include were reached by consensus among the first, second, and third authors.
Summary of Findings
Table 1 summarizes study characteristics, methodology, and overall prevalence rates for all 6 studies. Table 2 provides disorder-specific prevalence rates. Table 3 summarizes associated factors. Table 4 presents patterns of service use.
Some key findings emerged with respect to the prevalence of children’s mental disorders, associated factors, and patterns of service use. Table 1 shows that the overall community prevalence rates for clinically important mental disorders (based on assessment of both symptoms and impairment) ranged from 10% to 20%. This table also reveals the considerable heterogeneity among studies regarding sample size, age of children, basic methodology, and time frame.
Table 2 shows that the estimated overall prevalence rate for all disorders was 14%, which translates into approximately 1.1 million Canadian children who may be affected. Table 2 also outlines estimated disorder-specific prevalence rates compiled from all 6 studies. Anxiety, attention, conduct, and depressive disorders were the most common.
Two studies also reported overall comorbidity rates and found that 47% to 68% of children with mental disorders had 2 or more disorders (18,27). In addition, OCHS found that children with mental disorders also experienced more chronic physical health and school problems (18).
All studies except MECA reported on factors that were significantly associated
with increased prevalence of mental disorders in children, as shown in
Table 3. With respect to sex, boys are at greater risk for mental disorders.
Age, however, is also a factor: risks for boys are greater when they are
younger, while risks for girls are greater when they are older. There were
many disorder-specific rate variations; nevertheless, these data suggest
that interactions may exist between age and sex, affecting prevalence of
mental disorders. Significant differences in prevalence rates were not
found between urban and rural populations in 3 of the 4 studies that measured
this variable. However, low family income was associated with significantly
higher rates of mental disorder in all 3 studies that measured this variable.
Only 2 studies looked at ethnic groups, and no differences were found.
Although association does not imply causation, determining associated factors
is an important first step in identifying causal risk and protective factors
(2). These reports on factors associated with increased prevalence of mental
disorders provideb useful leads for further prospective research to establish
which factors may be causal and thus worth targeting in children’s mental
health prevention and treatment programs.
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