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Book Title: Treating and Preventing Adolescent Mental Health Disorders
> pp. [360]-[364]
UNDEFINED: AUTHORS
Treating and Preventing Adolescent Mental Health Disorders
Print ISBN 9780195173642, 2005
pp. [360]-[364]
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Larger amounts consumed than intended
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Unsuccessful attempts to stop
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Excessive time spent drinking
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Important activities given up
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Continued use despite awareness of negative effects of drinking
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While the number and type of symptoms needed to determine a diagnosis appear to be valid for adults (e.g., Schuckit et al., 2001), investigators have questioned the validity of the DSM-IV diagnostic criteria for identifying AUDs in adolescent populations (Winters, 2001). This skepticism is not surprising given that six of the seven research sites from the DSM-IV field trials did not contribute data on adolescents (Cottler et al., 1995). In addition, symptoms such as “risky sexual behaviors” are not explicitly assessed in the currently accepted list of symptoms used to determine a diagnosis of alcohol abuse or dependence. Pollack and Martin ( 1999) studied 372 adolescent regular drinkers. More than 10% of this sample reported symptoms of alcohol dependence but not enough to have a diagnosis, and they also did not have symptoms of alcohol abuse (termed “diagnostic orphans”). However, these individuals had drinking-related problems similar to those of adolescents who did meet diagnostic criteria for an AUD, and they had significantly more drinking-related problems than did adolescents with no symptoms of alcohol abuse or dependence. In the review by Chung and colleagues ( 2002), “diagnostic orphans” represented from 1.9% to 16.7% of adolescent community samples and from 7.5% to 33.7% of adolescent clinical samples. Clearly additional conceptual and empirical research is needed to adequately diagnose AUDs in adolescents. Finally, the two physiological symptoms (withdrawal and tolerance), that are part of the diagnostic DSM-IV criteria for determining if an individual has an AUD may have limited utility in diagnosing AUDs in adolescents (Martin, Kaczynski, Maisto, Bukstein, & Moss, 1995). Withdrawal symptoms are infrequently reported by adolescents (Chung et al., 2002), even in clinical samples, presumably because these symptoms
take years to develop. Tolerance, by contrast, seems to develop quickly in most adolescents, but does not readily distinguish problem from normative drinkers in the adolescent population.
Etiology: Risk and Protective Factors
The greater number of risk factors an adolescent has for developing an AUD, the more likely he or she is to abuse or to be dependent on alcohol (Jaffe & Simkin, 2002; Newcomb, 1997). However, sometimes there are protective factors that counteract risk factors. For example, a strong religious commitment, dedication to constructive activities such as sports, intense anti-alcohol beliefs, and high self-esteem all can serve to neutralize inherent risk factors for developing an AUD (Liepman, Calles, Kizilbash, Nazeer, & Sheikh, 2002). The relevance of some of the risk factors varies with the age, gender, and ethnicity of the adolescent. In addition, other factors have been identified that influence the risk for AUDs as well as other substance use disorders. Newcomb ( 1997) classified these risk factors into four generic domains: cultural/societal, interpersonal, psychobehavioral, and biogenetic. The first three factors are summarized here. Discussion of genetic factors is given at the end of this chapter.
Cultural and societal factors.
While many factors contribute to the availability and acceptability of alcohol in a community (cultural, economic, legal, etc.), probably the single, most influential factor that relates to alcohol consumption in adolescents is the attitude of the adult community in the particular geographic location (see review by Newcomb, 1997). For example, the purchase of alcohol by underage drinkers is prohibited in all 50 states. However, in some places, the laws are not regularly enforced by police officers, and the liquor stores and bars do not consistently require identification from minors (Windle, 1999). Underage drinking at family gatherings or special celebrations may be acceptable to parents and relatives in some communities. An in-depth examination of the relationship between community attitudes and alcohol availability (economic and le
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gal) is of paramount importance but beyond the scope of this book.
Interpersonal factors that relate to AUD risk are parental (referring to other than heredity), sibling, and peer influences. Despite waning parental influence with the passage of time, parents' level of nurturing, monitoring, communication, and their own alcohol use affects the amounts and patterns of alcohol drinking in their adolescents (see reviews by Gilvarry, 2000; Liepman et al., 2002; Schulenberg & Maggs, 2002; Windle, 1999). That is, although adolescents may reject many of their parents' ideas and behaviors, the majority do not seem to reject their parents' drinking behaviors. Higher levels of maternal and paternal alcohol consumption are related to higher levels of alcohol use among adolescents (e.g., Kilpatrick et al., 2000; Webb & Baer, 1995). However, parents can have a positive influence on their adolescents. Higher levels of emotional support and warmth (nurturance), higher levels of appropriate monitoring and limit setting, more time spent together, and higher levels of parent–adolescent communication have been associated with lower levels of adolescent alcohol-related problems (Windle, 1999). Siblings represent another familial influence. Older siblings typically serve as role models and there is a greater likelihood that younger siblings will drink alcohol before they are adults if their older siblings drink. This relationship is stronger if the older sibling is closer in age and the same gender (Windle, 1999). The commonly held notion that peers exert considerable influence on the initiation and maintenance of alcohol use is sustained empirically (Schulenberg & Maggs, 2002). But there is little support for overt peer pressure causing the initiation of alcohol use. Rather, most studies support a more complex, developmental interactional process in which an adolescent selects and unselects peer groups. The individual is influenced by the course of behaviors and attitudes of these groups and in turn influences them (Schulenberg & Maggs, 2002). However, overt peer pressure can play a role in relapse (Brown, 1993).
Psychobehavioral influences.
Newcomb ( 1997) cites age of onset and comorbid psychopathol
ogy as primary psychobehavioral influences in alcohol use. An earlier age of first use of alcohol is frequently associated with increased alcohol-related problems then and later in life. But it is not clear whether excessive drinking in early adolescence is a marker of serious preexisting or coexisting psychopathological factors (e.g., fractured gene pool, flawed personality, poor parental modeling, nurturing, monitoring, etc.), or, alternatively, whether excessive alcohol drinking in adolescence introduces a “toxin” that negatively impacts a person who is still experiencing a critical period of growth toward adulthood. Recently, Ellickson, Tucker, and Klein ( 2003) published a 10-year prospective study in which students recruited from 30 Oregon and California schools were assessed at grades 7 and 12, and then later at age 23 ( N = 6,338, 4,265, and 3,369, respectively). Young drinkers in both middle school and high school, compared to nondrinkers, were more likely to report academic problems, delinquent behaviors, and other substance use. At age 23, compared to nondrinkers, those who had been adolescent drinkers were more likely to report employment problems, continued “other” substance abuse, and criminal and violent behaviors. These findings were supported by several retrospective reports as well. According to adults interviewed as part of the National Longitudinal Alcohol Epidemiological Survey, Grant and Dawson ( 1997) found that over 40% of adults who had reported using alcohol before age 14 had developed alcohol dependence later in their lives. This compared to a rate of less than 10% of alcohol-dependent adults who said they did not start drinking alcohol until after the age of 18. Also, DeWit, Adlaf, Offord, & Ogborne ( 2000) examined a larger health survey of adult reports. Of 5,856 drinkers, 501 had a DSM-IV diagnosis of lifetime alcohol abuse, and 473 had a DSM-IV diagnosis of lifetime alcohol dependence. Approximately 13.6% of the respondents who said they had their first drink between 11 and 14 years of age met diagnostic criteria for alcohol abuse 10 years later. This compares to only 2% of alcohol abusers who said they had had their first drink after the age of 18. These rates were parallel in adults diagnosable with alcohol de
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pendence. That is, 15.9% of the respondents who said they had their first drink between 11 and 12 years of age reported alcohol dependence 10 years later. In comparison, those who said they had their first drink after age 18 represented only 1% of the respondents.
Comorbid psychiatric disorders frequently co-occur with AUDs (Deas & Thomas, 2002; Gilvarry, 2000), but it is often difficult to distinguish etiological from consequential associations. For example, it is easy to imagine that a psychiatric disorder can result from continual, excessive alcohol consumption, especially in a physiological and psychological developmental period such as adolescence. In this example, the AUD would precede the comorbid disorder. Another scenario, however, is drinking alcohol to treat the symptoms of a psychiatric disorder; this is called “self-medication.” For example, an individual with a social phobia may desire the relaxing and disinhibitory effects of a few drinks prior to attending a social gathering. In this case, if an AUD is identified, it is likely that the comorbid disorder preceded the AUD. Finally, both AUD and a psychiatric disorder may have the same etiology (e.g., genetic, neurochemical). Naturally, an understanding of the etiology of both concomitant disorders can guide treatment decisions. Behavioral disorders, mood disorders, and anxiety disorders have been frequently associated with AUDs (Deas & Thomas, 2002; Gilvarry, 2000). Attention deficit-hyperactivity disorder (ADHD) has been associated with AUDs, but its independence from conduct disorder (CD) has not been well established (Gilvarry, 2000). In a 4-year longitudinal study of ADHD children and controls (6 to 15 years old), there was no difference in the prevalence of AUDs between youths with and without ADHD (Biederman et al., 1997). Conduct disorder proved to be a significant predictor of AUDs in the target and control groups. In another study, Moss and Lynch ( 2001) used structural modeling to illustrate an association between ADHD and AUD for adolescent males but not females, yet CD symptoms had the strongest association with AUD in adolescents. As implied above, there is strong empirical evidence relating CD and similar disorders (e.g., oppositional defiant disorders [ODD]) with
AUDs (Clark, Vanyukov, & Cornelius, 2002). Clark, Bukstein, and Cornelius ( 2002) provide convincing evidence that childhood antisocial behaviors precede and predict adolescent AUDs. They argue that the association between the behavior disorders and AUDs is best understood as manifestations of common underlying causes. These include poor behavioral regulation (possibly related to prefrontal cortex abnormalities), common genetic pathways (for instance, genetic variations influencing the dopamine system), and similar environmental factors (for instance, low levels of parental monitoring). Early identification and intervention efforts for these individuals with childhood antisocial behaviors may ameliorate later AUDs. In adults, a person with alcohol dependence is nearly four times more likely to have major depression than a person without alcohol dependence (Petrakis, Gonzalez, Rosenheck, & Krystal, 2002). Gilvarry ( 2000) reported that up to one third of adolescents in addiction treatment facilities are diagnosed with mood disorders, especially major depression and dysthymia. Deas-Nesmith, Campbell, and Brady ( 1998) reported that 73% of inpatient adolescents who used substances met diagnostic criteria for depression. Furthermore, in 80% of those cases, the depressive symptoms predated the substance use, suggesting that the mood disorder for these adolescents was an important risk factor for developing a subsequent AUD. In the Biederman et al. ( 1997) study, bipolar disorder predicted substance use disorders, independent of ADHD. Although not all studies have found that mood disorders predate substance use disorders (e.g., Rohde, Lewinsohn, & Seeley, 1996), these observations suggest that mood disorders may be a risk factor for developing an AUD in some adolescents. Anxiety disorders, especially social phobia and posttraumatic stress disorder (PTSD), may also be risk factors for AUDs. Rohde and colleagues (1996) reported that alcohol use among female high school students was associated with anxiety disorders that preceded the alcohol problems. Deas-Nesmith, Brady, and Campbell ( 1998) found that 60% of adolescents seeking treatment for addiction met diagnostic criteria for a social anxiety disorder. Furthermore, the
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anxiety symptoms generally predated substance dependence by about 2 years. Posttraumatic stress disorder has also been implicated as a risk factor for AUDs. Kilpatrick and colleagues ( 2000) explored PTSD as a risk factor for substance use problems in adolescents. These investigators found that physical or sexual abuse, assault, or the witnessing of violence (e.g., murder, sexual assault) increased the risk of abuse of several illicit drugs, including alcohol. In another study, Clark et al. ( 1997) found that adolescents with an AUD were more likely to have a history of physical and sexual abuse compared to an adolescent control group. Furthermore, the association of PTSD and alcohol dependence was stronger in females than in males.
Special Case of College Drinking
Thus far, this chapter has focused on alcohol drinking and disorders observed in adolescent youth, with most of this population attending middle school and high school. However, there are significant numbers of adolescents in the age group who have just graduated from high school and may be attending college (average college age ranges from approximately 18 to 24 years). It should be noted that drinking on college campuses has its own culture, with easy access to alcohol. This clearly distinguishes it from our traditional view of adolescent drinking patterns, prevalence, and disorder development. In addition, access to alcohol on most college campuses, from both attitudinal and economic perspectives, is unparalleled in any other large, established adult community, and has been associated with a high frequency of serious and sometimes life-threatening drinking-related negative behaviors. While it is not within the scope of this chapter to detail the phenomenology of college campus drinking, we briefly mention the nature of the problem here and the need for further research. Basically, the prevalence of drinking and heavy drinking among college students is higher than that of their peers who do not attend college (U.S. Department of Health and Human Services [DHHS], 2002). This difference is due to many factors, including specific ones such as the influence of sororities and fraternities, greater
amounts of unstructured time, easy access to those who can obtain alcohol legally, differential economic issues (parents or scholarships typically provide some financial support), and special advertising of alcoholic beverages targeted to the college population. College surveys reveal that approximately 40% of college students report heavy drinking in the 2 weeks prior to the survey. Consumption is heavier among males, highest among Caucasian students, and highest among the Northeast and North Central regions of the country (DHHS, 2002). Hingson, Heeren, Zakocs, Kopstein, and Wechsler ( 2002) recently reported on the serious consequences of college drinking in the United States. On an annual basis, alcohol consumption is associated with 1,400 deaths, 500,000 unintentional injuries, 600,000 assaults, and 70,000 sexual assaults of college students. Approximately 2.1 million college students drive while intoxicated each year, 400,000 report having unprotected sex while drinking, and over 150,000 develop health-related problems due to their drinking (Hingson et al., 2002). In an effort to address the serious problems of college drinking, the NIAAA ( 2003) recently released a program announcement “to provide a rapid funding mechanism for timely research on interventions to prevent or reduce alcohol-related problems among college students” (see http://grants1.nih.gov/grants/guide/pa-files/PAR-03-133.html
).
Tobacco Use in Adolescence
Adolescent tobacco use is widely recognized as a major public health problem (Windle & Windler, 1999). According to recent data, 64% of adolescents reported ever having smoked cigarettes, 28% reported having smoked on at least 1 day in the past month, and 14% reported having smoked on at least 20 of the last 30 days (CDC, 2002b). Among high school seniors who indicated that they currently smoked, 29% reported symptoms that met the DSM-III-R criteria for nicotine dependence (Stanton, 1995). Moreover, over one half of adolescents indicated that they experience withdrawal symptoms following a quit attempt and 70% regret ever having started smoking (CDC, 1998; Colby, Tiffany, Shiffman,
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& Niaura, 2000a). Thus, early patterns of tobacco use among adolescents may develop into lifelong nicotine addiction.
Nicotine and Nicotine Dependence
Nicotine, a potent alkaloid in tobacco leaves, is what sustains tobacco smoking, which efficiently delivers nicotine to the brain (Benowitz, 1990). Nicotine, steam distilled from burning tobacco plant material in a cigarette, is inhaled into the lungs on small tar droplets and absorbed rapidly into arterial blood, reaching the brain within 20 sec after each puff. Nicotine has similarities to the neurotransmitter acetylcholine, binding to a complex family of nicotine cholinergic receptors distributed throughout the brain and elsewhere in the body. During cigarette smoking, with each puff, nicotine levels in brain tissues briefly rise and then decline rapidly, more because of the rapid distribution into tissues than of being broken down by metabolism. Each puff acts like an individual dose of drug. Blood and brain nicotine levels peak immediately after each cigarette, but gradually nicotine accumulates during 6 to 10 hr of repeated smoking because of nicotine's 2-hr half-life. During sleep, nicotine levels fall, but upon awakening, when the first cigarette of the day is smoked, levels begin to rise. Thus, someone smoking 10 cigarettes a day exposes their brain to nicotine 24 hr a day but along with rewarding perturbations in brain levels of nicotine after each of the 100 puffs. Each cigarette in effect delivers about 10 separate doses of nicotine to the brain. With marijuana or cocaine smoking, a similar pattern of drug delivery is involved. Adolescent smokers quickly learn to regulate, on a puff-by-puff basis, their smoked nicotine dose by maintaining a brain concentration of the drug that just avoids nicotine toxicity but satisfies the increasing need for nicotine as dependence develops. Tobacco smoking is initially aversive for almost everyone. It is unlikely that a young person would begin tobacco or other drug smoking without the support and teach-ing from peers, the observations of admired or envied adult smokers, and the reinforcement associated with the tobacco industry's multibil
lion-dollar advertising that promotes the rewards of cigarette smoking. Nicotine delivered by cigarettes offers a beginning smoker individualized and personal control of psychoactive drug dose unobtainable by any other drug delivery system. Rapid onset of nicotine toxicity, particularly the early symptoms of nausea, weakness, and sweating, gives rapid feedback that the absorbed dose is higher than optimal, exceeding the acquired tolerance level. After repeated exposure to smoking, the difficulty in concentrating and other symptoms of nicotine withdrawal that develop when brain levels are falling offer another set of cues that it is time for a cigarette to be smoked. If nicotine toxicity is avoided, adult tobacco smokers report enhanced concentration and improved mood. Attention to task performance improves, as does reaction time and problem solving. Adult smokers report enhanced pleasure and reduced anger, tension, depression, and stress after a cigarette. Whether performance and enhanced mood after smoking are due to relief of abstinence symptoms rather than intrinsic effects of nicotine remains unclear. However, enhanced performance of nonsmokers after nicotine suggests some direct nicotine enhancement. Reports from adolescent tobacco users parallel those of adults, which suggests that nicotine has these same pharmacologic effects in an adolescent smoker (Corrigall, Zack, Eissenberg, Belsito, & Scher, 2001). Nicotine, by its effects on nicotinic cholinergic receptors in the brain, enhances or modulates release of many neurotransmitters—dopamine, norepinephrine, acetylcholine, serotonin, vasopressin, β-endorphin, glutamate, GABA, and others (Tobacco Advisory Group Royal College of Physicians, 2000). Thus changes in brain neurochemistry after nicotine exposure are profound. Neurotransmitter release is assumed to mediate nicotine's positive effects on arousal, relaxation, cognitive enhancement, relief of stress, and depression. The mesolimbic dopamine system is important in mediating the pleasurable and other rewards of nicotine, as with other drugs of abuse, and is important for understanding the withdrawal phenomena as well. When brain nicotine levels decrease, diminished neurotransmitter release contributes to a
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doi:10.1093/9780195173642.003.0018
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