5

Description of Five Illustrative Mental Disorders

The diagnosis of mental disorders is made on the basis of signs and symptoms of aberrant thoughts, words, and behaviors. As yet there are no laboratory tests to diagnose these illnesses. Clinical research continues to refine our understanding of the symptomatology, natural course, co-morbidity, and treatment effectiveness for mental disorders. Continuing research on epidemiology provides needed data on incidence, prevalence, prodromal periods, and age of onset. In this chapter, the discussion of this knowledge is organized around five major mental disorders: conduct disorder, depressive disorders, alcohol abuse and dependence, schizophrenia, and Alzheimer's disease. In Chapter 6, the same disorders are examined for risk and protective factors that may eventually offer targets for intervention.

These five disorders were chosen as illustrations—for use in this chapter as well as in the rest of the report—because they are all serious disorders that have enormous emotional and financial costs associated with them. They demonstrate that specific disorders have their onset at varying stages in the life cycle, and that when they do occur, they often are disruptive to further stages of development. In addition, they represent the great diversity of mental illness and reflect a spectrum of causation, arising from clear genetic contributions in Alzheimer's disease to primarily psychosocial factors in conduct disorder. The choice of these five disorders is by no means meant to imply that these are the only disorders that should be targeted for preventive intervention research programs. Anxiety disorders, post-traumatic stress disorder, obsessive-compulsive disorder, and other adult and childhood mental



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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH 5 Description of Five Illustrative Mental Disorders The diagnosis of mental disorders is made on the basis of signs and symptoms of aberrant thoughts, words, and behaviors. As yet there are no laboratory tests to diagnose these illnesses. Clinical research continues to refine our understanding of the symptomatology, natural course, co-morbidity, and treatment effectiveness for mental disorders. Continuing research on epidemiology provides needed data on incidence, prevalence, prodromal periods, and age of onset. In this chapter, the discussion of this knowledge is organized around five major mental disorders: conduct disorder, depressive disorders, alcohol abuse and dependence, schizophrenia, and Alzheimer's disease. In Chapter 6, the same disorders are examined for risk and protective factors that may eventually offer targets for intervention. These five disorders were chosen as illustrations—for use in this chapter as well as in the rest of the report—because they are all serious disorders that have enormous emotional and financial costs associated with them. They demonstrate that specific disorders have their onset at varying stages in the life cycle, and that when they do occur, they often are disruptive to further stages of development. In addition, they represent the great diversity of mental illness and reflect a spectrum of causation, arising from clear genetic contributions in Alzheimer's disease to primarily psychosocial factors in conduct disorder. The choice of these five disorders is by no means meant to imply that these are the only disorders that should be targeted for preventive intervention research programs. Anxiety disorders, post-traumatic stress disorder, obsessive-compulsive disorder, and other adult and childhood mental

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH disorders may also be appropriate for the introduction of preventive research strategies. These five disorders are simply illustrative of the range of factors and approaches that must be considered in designing preventive intervention research programs. The brief descriptions presented here, each highlighting slightly different points, are examples of how the information that is available for a particular disorder should be reviewed. The disorders are presented here in developmental sequence to emphasize the importance of a life course perspective. DATA SOURCES, CONCEPTS, AND METHODOLOGIES USED IN THE DISORDER DESCRIPTIONS Epidemiologic Catchment Area Study The prevalence data for the five disorders are from several sources, including the National Institute of Mental Health's Epidemiologic Catchment Area (ECA) study, which has been discussed in more detail in other reports (various chapters of Robins and Regier, 1991, as cited below). Data on age of onset during the adult years are taken from the prospective one-year follow-up ECA study, designed, in part, to estimate the incidence of specific mental disorders (Eaton, Regier, Locke, and Taube, 1981). The onset data are not widely available elsewhere and so are highlighted here, along with their new application to delineation of prodromes, as well as explanations of the special utility of these concepts in preventive intervention research. The ECA study consisted of community surveys carried out by five university-based research teams in different locations in the United States. The data presented below are from four sites: Baltimore, Maryland (Johns Hopkins University); St. Louis, Missouri (Washington University); Durham, North Carolina (Duke University); and Los Angeles, California (University of California). At each of these sites, both the prevalence survey and the one-year follow-up were done. For the fifth site, New Haven, Connecticut (Yale University), the longitudinal aspects of the design, and the questionnaire used, were sufficiently different to make pooling of data problematic. The methods of the ECA study are described elsewhere (Eaton and Kessler, 1985). In brief, area probability samples of households were drawn, and household members 18 years of age or older were selected at random for interview. About 75 to 80 percent of those designated as respondents completed a 90-minute interview that included the Diagnostic Interview Schedule (DIS) (Robins, Helzer, Croughan, Williams, and Spitzer, 1981). At the one-year follow-up, a second interview was

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH conducted with about 80 percent of those interviewed at the first wave. The DIS portion of the interview consisted of specified questions directly pertinent to diagnostic criteria from the third edition of the Diagnostic and Statistical Manual (DSM-III) of the American Psychiatric Association. The revised DSM-III-R is the best classification system available at the current time (DSM-IV is in press) and is the basis for the definitions used throughout the rest of this report. However, operational definitions of specific mental disorders as given in DSM-III, when major diagnostic criteria changes were made, were used in the ECA study and are used for determining onset in the analyses below. Onset is defined here as the first diagnosis of the disorder. Diagnoses were made from the DIS symptom data by means of computer algorithms that simulated the application of DSM-III criteria (Boyd, Burke, Gruenberg, Holzer, Rae, George et al., 1984). Because the ECA results depended on both the diagnostic criteria chosen and the method of ascertainment, the mental disorders as classified therein are referred to here as “DIS/DSM-III disorders.” Conceptualization of Onset The absence of firm data on the validity of the DSM-III system for classifying mental disorders enjoins us to be careful about conceptualizing the process of disease onset. It is particularly difficult to establish the validity of a threshold for the presence versus the absence of disorder, because signs and symptoms of mental disorders are widespread in the population and do not always reflect the presence of a mental disorder. From the clinical standpoint, subtle differences in how behaviors are categorized may suggest quite varied thresholds for making diagnoses; from the epidemiological standpoint, subtle differences in threshold may produce widely varying prevalences. A disorder that has a complex causal chain, where no particular cause is regarded as sufficient, may be preventable up to the point of onset, when the individual meets full criteria for diagnosis. The concept of attributable risk (see Chapter 4) allows quantitative comparison of risk factors in the population, which helps in selecting risk factors for intervention programs. Risk factors having high attributable risk for a specific disorder, or especially risk factors having high attributable risk for multiple disorders, would be prime targets for preventive interventions. But each risk factor may operate differently, and may be differentially malleable, that is, modifiable, at different times in life. Also, each risk factor may have a sensitive period in which an important contribution to the disorder may occur only at a particular phase of

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH development, such as infancy, adolescence, or old age. Interventions should be planned before or during sensitive periods. Unfortunately, the sensitive periods of the risk factors are not well known, but they must occur before onset. The first incidence of a disorder is the first onset of the disorder in the lifetime of the individual. It is usually simply called incidence in referring to age of onset in a population. The numerator for the incidence rate is composed of those individuals who have had an onset for the first time in their lives, and the denominator includes only persons who start the period of study with no history of the disorder. The incidence rate is the best quantitative expression of the force of morbidity in the population at a given age. Onset of first episode is a key concept for prevention because it is assumed that the causal structure producing morbidity changes after that point; that is, the risk factors that initiate the onset of a disorder may not be the same as the risk factors that prolong or exacerbate the disorder once it has occurred. Incidence rate is distinct from attack rate (also sometimes referred to as incidence, especially by those studying acute diseases such as respiratory infections), which is the rate at which episodes of disorder develop in a population not currently in an episode. The denominator for the attack rate is different from that for first incidence in that it may include persons who have had an episode of disorder earlier in their lives, but who do not currently meet the criteria for disorder; that is, it includes remitted cases. For mental disorders and for many physical disorders, the force of morbidity may be expressed by the rate at which individuals cross a variety of thresholds, including onset, in the process of development of a disorder. These thresholds may be below the current diagnostic criteria or above them. The causal structure is not well understood for either initiation, prolongation, or exacerbation. Therefore the relative value of incidence versus attack rate is an empirical question that has not yet been resolved. The prodrome is the period prior to onset of a disorder, when some early signs or symptoms are nevertheless present. Given the widespread prevalence of individual signs and symptoms of mental disorders in the general population, it is likely that many individuals with early signs and symptoms of disorder will not go on to develop the full criteria for diagnosis, perhaps because there is a dynamic flux of risk and protective factors over time. In this situation the signs and symptoms are not prodromal, in the strict sense of the word. For a particular individual a prodrome can be known only in retrospect, after he or she has developed the disorder. If he or she never develops it, the early signs were not part of a prodrome. Signs and symptoms from a

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH diagnostic cluster that precede disorder, but do not predict the onset of disorder with certainty, are referred to here as precursor signs and symptoms. Signs and symptoms from a diagnostic cluster that do precede the development of a disorder in a particular individual are referred to as prodromal signs and symptoms. At the present state of our knowledge of the onset of mental disorders, there are few or no signs and symptoms that predict onset with certainty. Nevertheless, precursor signs and symptoms can be helpful in identifying groups at much higher risk for onset than the general population. Methods for Analyzing Onset An important problem in presenting data on age of onset is censoring (Lawless, 1982). In the context of age of onset, censoring occurs when the exact age of onset is known for only a portion of the sample; for the remainder, the age is known only to exceed some given age (right censoring) or to be below some given age (left censoring). Most presentations on age of onset arise from cross-sectional data and are fight censored (e.g., Christie, Burke, Regier, Rae, Boyd, and Locke, 1988). In field surveys, the cross-sectional method is used to determine the presence or absence of disorder over the history of an individual, through retrospective recall, and then to determine age of onset for those with a positive history. In such surveys the vast majority of individuals do not report a history of disorder, and some of the individuals without disorder will develop a disorder after the survey is completed. Therefore the right-censored data from such a survey are inevitably biased in the direction of earlier age of onset. The degree of bias is difficult to know without knowledge of the age of onset, but it can be sizable. For example, imagine ascertaining age of onset for a disorder that typically has a very late onset, such as Huntington's disease, through a cross-sectional survey of the general population. Most persons in the sample would be too young to have had onset; only a handful would have lived through the age of risk for the disorder. Therefore the age of onset would appear younger than it really is. The prospective aspect of the data presented below avoids the problem of right censoring. But because the target population in the ECA surveys was defined as adults 18 years of age or older, onset for earlier years cannot be displayed. Data on psychopathology for population-based samples of children are discussed later in this chapter. Age of onset is presented here in cumulative form because that form is, for reasons explained below, most relevant to prevention. However, cumulative presentation can obscure important relationships of the force

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH FIGURE 5.1 Annual incidence of DIS/DSM-III Alcohol Abuse/Dependence. of morbidity to the life course, which may have etiological significance. For example, Figure 5.1 presents data on the incidence of DIS/DSM-III alcohol abuse or dependence among males at four sites of the ECA study (Eaton, Kramer, Anthony, Dryman, Shapiro, and Locke, 1989). The figure shows an upturn in incidence in the later years of life. The upturn is due to only a few individual onsets in a total sample of over 10,000, but a similar pattern in the only other comparable study (Hagnell, Lanke, Rorsman, and Ojesjo, 1982) suggests it is not a statistical artifact. The upturn in late life may indicate causal factors such as a decline in physical functioning or the effects of retirement. In the cumulative form presented in Figure 5.2, however, the upturn in later life is obscured. Figure 5.1 illustrates other methodological issues. One issue is the considerable statistical volatility of the prospective data, which is based

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH FIGURE 5.2 Age of onset of DIS/DSM-III Alcohol Abuse and Dependence. Population estimates are from 125 new cases (with 20th and 50th percentiles marked). Source: NIMH Epidemiologic Catchment Area Study, Four Sites, 1978 to 1983. on the occurrence of a handful of new cases among many thousands of persons at risk for developing the disorder over the one-year follow-up. The volatility is best demonstrated by the thin black bars, which represent age-specific rates at each site. The open rectangle is the age-specific rate for all four sites collapsed, and it shows more stability due to pooling of data. The curve itself involves the maximal smoothing of the data, using only two degrees of freedom. The cumulative form of presentation obscures this statistical volatility. The cumulative distributions presented for the five disorders below are weighted statistically to represent a population with age, gender, and race characteristics identical to those of the U.S. population (as in Robins and Regier, 1991). The cumulative form of presentation, along with the statistical weighting, links the data to the concept of attributable risk. The cumulative form allows one to estimate the proportion of cases in the United States that would be prevented if a 100 percent effective preventive intervention were applied at or before a given age. The attributable risk proportion, which is the percentage effectiveness of the intervention in eliminating the risk factor, and the cumulative percentage drawn from the figures below, can be chain multiplied to estimate the effectiveness of a given intervention program and to compare various intervention strategies. Data on the cost of modifying risk factors could also be incorporated in such calculations in designing a preventive intervention research program.

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH A variety of malleable risk factors may be available for intervention for any given disorder. Intervention should start as early in life as possible, other things being equal. But in many situations, an intervention later in life may still be effective, even if some will already have the disorder. Combining the cumulative distributions with the attributable risk and with cost and outcome factors can aid policymakers in making decisions on priorities in the use of resources. Figure 5.2 ,Figure 5.3, Figure 5.4 through 5.5 present two cumulative distributions each. The distribution on the right focuses on the age at which the individual first meets full criteria for the given DIS/DSM-III diagnosis. For this distribution, onset must occur during the one-year prospective period of follow-up. The population being studied includes all those who had never met criteria for diagnosis at the beginning of the follow-up period. It includes those with no symptoms, as well as those with some symptoms of disorder, but not meeting full DSM-III criteria. The distribution on the left focuses on the age at which a prodromal sign or symptom related to that disorder first occurred, as reported by the individuals who had developed the disorder by the end of the follow-up period. Dotted lines mark the twentieth and fiftieth percentiles, and age values for these are recorded on the figure. The area between the two curves gives a rough outline of the prodromal period. In the text and figures below, data are presented regarding prevalence and prodromal periods in individuals who have experienced the onset of disorder.* During these prodromal periods, precursor signs and symptoms were present, and ideally these individuals could have been identified as being at high risk. The data were, however, subject to the problems of retrospective recall by individuals with a current mental disorder. ILLUSTRATIVE DISORDERS Conduct Disorder The essential feature of conduct disorder, according to DSM-III-R, is a persistent pattern of conduct in which the basic rights of others and major age-appropriate societal norms or rules are violated. This diagnosis is made among children and adolescents under age 18 when at least 3 of 13 possible criteria have been present for at least six months (see Table 5.1). The behavior pattern may be simultaneously present in *These data were prepared in 1992 by William Eaton and Mohamed Badawi, both from The Johns Hopkins University, explicitly for this report.

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH TABLE 5.1 DSM-III-R Diagnostic Criteria for Conduct Disorder A disturbance of conduct lasting at least six months, during which at least three of the following have been present: has stolen without confrontation of a victim on more than one occasion (including forgery) has run away from home overnight at least twice while living in parental or parental surrogate home (or once without returning) often lies (other than to avoid physical or sexual abuse) has deliberately engaged in fire-setting is often truant from school (for older person, absent from work) has broken into someone else's house, building, or car has deliberately destroyed others' property (other than by fire-setting) has been physically cruel to animals has forced someone into sexual activity with him or her has used a weapon in more than one fight often initiates physical fights has stolen with confrontation of a victim (e.g., mugging, purse-snatching, extortion, armed robbery) has been physically cruel to people Note: The above items are listed in descending order of discriminating power based on data from a national field trial of the DSM-III-R criteria for Disruptive Behavior Disorders. If 18 or older, does not meet criteria for Antisocial Persona lity Disorder. Criteria for severity of Conduct Disorder: Mild: Few if any conduct problems in excess of those required to make the diagnosis, and conduct problems cause only minor harm to others. Moderate: Number of conduct problems and effect on others intermediate between “mild” and “severe.” Severe: Many conduct problems in excess of those required to make the diagnosis, or conduct problems cause considerable harm to others, e.g., serious physical injury to victims, extensive vandalism or theft, prolonged absence from home. SOURCE: American Psychiatric Association, 1987, p. 55. several settings—home, school, with peers, and in the community—but often it is not. Reports by parents and teachers on a particular child's behavior have shown remarkably little agreement (Loeber, Green, Lahey, and Stouthamer-Loeber, 1989; Offord, Boyle, and Racine, 1989b; Rutter, Tizard, and Whitmore, 1970). For many years, there has been considerable debate regarding the definition of conduct disorder. Robins (1991) has described the changes in both the ICD and the DSM classification systems and the differences between the systems. Indeed, there are those who question the validity of the disorder itself. For example, F. Earls (personal communication,

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH FIGURE 5.3 Age of onset of DIS/DSM-III Antisocial Personality Disorder. Population estimates are from 46 new cases (with 20th and 50th percentiles marked). Source: NIMH Epidemiologic Catchment Area Study, Four Sites, 1978 to 1983. 1992) has suggested that conduct disorder is not a condition, or even a series of conditions, but rather an emotional or behavioral symptom of disorder analogous to fever as a marker of infection. Robins (1991) has suggested, alternatively, that conduct disorder might better be viewed as the middle phase of a chronic mental disorder that typically begins early in life and continues into adulthood but which can abort at any time along the way. DSM recognizes the chronicity of the disorder but labels it differently at each stage. Taylor and colleagues found that children meeting the criteria for conduct disorder were quite heterogeneous in their symptoms (Taylor, Schachar, Thorley, and Wieselberg, 1986). This heterogeneity adds support to the increasingly held view that conduct disorder is really a cluster of disorders or subtypes. All of these variations in conceptualization, including definition and subtyping, affect apparent changes in prevalence, contribute to ethical dilemmas regarding labeling and deciding whom to treat, and complicate both treatment and prevention research. Conduct disorder is the most common disorder seen in child mental health clinics in North America. Six-month and one-year prevalence rates obtained from general and health care clinic populations in the United States, Canada, and New Zealand range from 1.5 to 11.9 percent, depending on the gender and age range of subjects, but generally boys are diagnosed as having conduct disorder more often than girls and the rate for girls and boys increases with age (Costello, 1989; Offord, Boyle,

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH Fleming, Blum, and Grant, 1989a; Velez, Johnson, and Cohen, 1989; Bird, Canino, Rubio-Stipec, Gould, Ribera, Sesman et al., 1988; Anderson, Williams, McGee, and Silva, 1987; Offord, Boyle, Szatmari, Rae Grant, Links, Cadman et al., 1987). The costs to society of having such a high prevalence are not known, but obviously they are high, for they include the costs of damage to other people's property, the costs of educational, legal, and social service interventions, and the costs of loss of potential and eventual productivity of these individuals. Conduct disorder is not easily treated. Although many treatments are being applied and some, including problem-solving skills training, parent management training, and functional family therapy, have achieved positive short-term outcomes (Kazdin, 1993), the long-term success of these interventions is not known. Symptoms of conduct disorder may arise from many different pathways. Loeber and colleagues (Loeber, Wung, Keenan, Giroux, Stouthamer-Loeber, Van Kammen, and Maughan, 1993) have postulated three routes: (1) an aggressive-versatile route with early onset, with symptoms that are already severe in preschool; (2) a nonaggressive, antisocial pathway with onset in late childhood to early adolescence, with conduct problems but no hyperactivity or aggression; and (3) an exclusive substance abuse pathway with onset in middle to late adolescence. There is a marked difference between the early-onset form of conduct disorder in a temperamentally difficult child who has accompanying attention deficit disorder and learning difficulties, and the late-onset form appearing in an adolescent who has previously functioned well but who in response to environmental stress suddenly changes patterns of behavior. Robins's (1980) work has suggested that late-onset conduct disorder is typically predated by early experimentation with sex, drugs, and alcohol. Adolescents who are most likely to be chronically antisocial are those who show early-onset, pervasive disorder, and co-occurrence of early hyperactivity (White, Moffitt, Earls, Robins, and Silva, 1990). Within the DSM classification system, a majority of children with conduct disorder also have other concomitant psychiatric diagnoses. Conduct disorder often occurs in tandem with attention deficit disorder. Forty percent of children with attention deficit disorder go on to develop symptoms of conduct disorder (Offord, Boyle, Racine, Fleming, Cadman, Blum et al., 1992). The salient difference between those who remain attention deficit disordered but do not develop conduct disorder may lie in the level of family functioning. Families who provide a supportive, consistent environment with clearly defined limits presumably allow these children to develop enough social skills that they can

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH mental disorders overlap to a large degree (Regier, Farmer, Rae, Locke, Keith, Judd, and Goodwin, 1990; Boyd et al., 1984). The study of epidemiological data on age of onset for co-morbid disorders (to determine which of two disorders came first) has begun only recently (e.g., Merikangas, Eaton, Angst, Kraemer, Canino, Rubio-Stipec et al., 1993). The relative risks for symptoms of one disorder, or for the disorder itself, in predicting first onset of a second disorder, are probably not as high as for the precursor signs and symptoms that specifically belong within the diagnostic cluster of the second disorder; but these relative risks may be higher than other risk factors, and sufficiently high to warrant use in screening in some situations. For example, the relative risk for first onset of major depressive disorder for those with a panic attack is 3.4, as estimated in a time-dependent proportional hazards model (Andrade, Chilcoat, and Eaton, 1993). The prevalence of panic attack is about 10 percent (Eaton, Dryman, and Weissman, 1991). Applying the formula for attributable risk yields an estimate of 19 percent. The distinction between indicated preventive interventions and treatment interventions can be further clarified as the precursor symptoms of coexisting disorders become more understood. Transition to Adulthood The transition to adulthood is poorly understood, in spite of the fact that it is probably the age period when most adult disorders have their peak rates of incidence. There are prevalence surveys of mental disorders in adults, such as the ECA study, and in children, such as those reviewed in Table 5.8. The ECA study is the only one in the United States that estimates incidence of specific disorders in adults, and there is only one study estimating incidence rates for a DSM-III disorder in a population under age 18 (Lewinsohn et al., 1993). There are no studies that estimate incidence of specific disorders during the age period of the transition to adulthood, that is, from about age 15 to about age 25. Studies under way using synthetic cohort designs (in which the effects of aging can be studied by using a cross-sectional design that includes a range of ages but requires strong assumptions about the effects of birth cohort and historical period [Beltes, Cornelius, and Nesselroade, 1979]) have the capacity to yield estimates of incidence, and to study the effects of risk factors that are relatively close to the time of the beginning of the study. But synthetic cohort designs will not be able to study the effects of combinations of these risk factors and ones that occur later. Because these combinations may be very important in the transition to adult

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH hood, this is a stark gap in our epidemiological knowledge relevant to the prevention of mental disorders. FINDINGS AND LEADS A disorder may be preventable up to the point of onset of first episode. Although onset can rarely be accurately pinpointed, the time at which an individual meets full criteria for diagnosis can be used as an approximation. As more becomes known about precursors and prodromes, the age of onset will become more accurately known. Epidemiological research on children and adults should gather and retain data on a wide range of signs and symptoms, as well as disorders, to help ensure that maturational changes and changes in the diagnostic classification system do not interfere with the study of the development of psychopathology over time. Prospective epidemiological studies that estimate incidence of specific risk factors and disorders in childhood, adolescence, and during the transition to adulthood, from age 15 to 25, are greatly needed for prevention research. Such studies could help clarify the mechanisms linking risk factors to the first occurrence of disorders. For a particular disorder, a review of what is known about prodrome, age of onset, diagnostic criteria, course, co-morbidity, incidence and prevalence, effectiveness of treatment, and costs to society can help the investigator determine if the knowledge base is sufficient to consider designing a preventive intervention. For example, the incidence of a disorder will help determine the necessary size of the sample so that statistical analyses are meaningful (Muñoz and Ying, 1993); the demographics of a disorder will help determine who is at highest risk and what population groups should be targeted; and if a specific treatment is known to be effective, it could be considered for use before onset. Such a review could in turn help policymakers set priorities for preventive intervention programs. Many mental disorders, including conduct disorder, depressive disorders, alcohol abuse and dependence, schizophrenia, and Alzheimer's disease, are thought to be a cluster of several different illnesses or to have subtypes. Identification of these groups and clearer delineation of their etiologies may clarify which individuals may be most amenable to preventive interventions. Risk factors that have a role in the etiology of a mental disorder may be differentially malleable at different phases of the life course. More research regarding the sensitive periods of risk factors, that is, when they contribute most to etiology, could lead to more strategic

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REDUCING RISKS FOR Mental Disorders: FRONTIERS FOR PREVENTIVE INTERVENTION RESEARCH timing of preventive interventions, that is, before or during those sensitive periods. From a clinical perspective, the prodromal periods for some of the illustrative mental disorders may seem unusually lengthy. Because the prodromal data presented here were subject to retrospective recall by individuals who currently had a disorder, the time of the first sign or symptom may not be accurate. Also, the signs and symptoms may not have been sufficiently specific to differentiate them from a range of normal behavior. The only way of determining true prodromal periods is through prospective studies with cutoff points for carefully defined signs and symptoms. However, if through such studies prodromal periods are indeed found to be quite lengthy, the timing of preventive interventions may be adjusted accordingly. Prospective epidemiological studies could identify precursor signs and symptoms that are below the criterion level for the diagnosis of a mental disorder, as well as the age of the first occurrence of these precursor symptoms. Thus it may be possible to identify individuals at heightened risk for developing the full-blown disorder, who would then become candidates for indicated preventive interventions. For example, populations could be screened for precursors, such as a two-week period of sad mood. Research advances in understanding of the cause of Alzheimer's disease (AD) have been substantial. Genetic evidence suggests that AD may be a collection of specific diseases with a single common pathway. If this pathway can be clarified and a marker found to identify individuals at high risk for developing AD, an intervention may eventually be found that could inhibit a crucial step, such as amyloid formation, and prevent emergence of the disease or at least delay its onset. REFERENCES Alleback, P.; Wistedt, B.( 1986) Mortality in schizophrenia. Archives of General Psychiatry; 43: 650–653. American Psychiatric Association.( 1987) Diagnostic and Statistical Manual of Mental Disorders (Third Edition —Revised). Washington, DC: American Psychiatric Association. Anderson, J. C.; Williams, S.; McGee, R.; Silva, P. A.( 1987) DSM-III Disorders in Preadolescent Children. Archives of General Psychiatry; 44: 69–76. Andrade, L.; Chilcoat, H.; Eaton, W. W.( 1993) Comorbidity of panic and depression: Age of onset. Unpublished manuscript. Barraclough, B.; Bunch, J.; Nelson, B.; Sainsbury, P.( 1974) A hundred cases of suicide: Clinical observations. British Journal of Psychiatry; 125: 355–373. Battelle Memorial Institute.( 1984) The Economics of Dementia. Contract report prepared for the Office of Technology Assessment. Washington, DC: U.S. Congress.

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