II
Effects Of Use



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Under the Influence? Drugs and the American Work Force II Effects Of Use

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Under the Influence? Drugs and the American Work Force This page in the original is blank.

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Under the Influence? Drugs and the American Work Force 4 Impact of Alcohol and Other Drug Use: Laboratory Studies Despite substantial national efforts, drug abuse remains a serious public health problem for a sizable proportion of the population. Since data presented in Chapter 3 suggest that a sizable portion of the work force uses drugs, reducing use by the active work force would have an impact on drug use overall, reducing the pool of illicit drug users in the United States and moving us closer to the societal goal of eliminating drug abuse. The workplace is thus an obvious site for user-focused interventions. STRENGTHS AND LIMITATIONS OF LABORATORY STUDIES This societal perspective is seldom used to justify programs to reduce or eliminate drug use by the work force, and there may be constitutional problems with workplace drug-testing programs aimed predominantly at this goal. Interventions aimed at securing a drug-free workplace are justified instead largely on safety and productivity grounds. The data obtained in worker population studies, however, do not provide clear evidence of the deleterious effects of drugs other than alcohol on safety and other job performance indicators. This does not mean there are no deleterious effects; it may reflect the paucity of relevant data and the quality of the research done to date. The extent to which impaired worker performance due to drug use can affect safety and productivity in the workplace is not well understood, although

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Under the Influence? Drugs and the American Work Force a substantial amount of laboratory research has been carried out evaluating the effects of single doses of various abusable drugs on cognitive and psychomotor performance. The results of such research cannot be extrapolated directly to the workplace because the effects of drugs on workplace performance are a complex function of the interaction between the dynamic workplace environment and the multiplicity of other variables impinging on the worker. For example, the job performance of a worker who has slept little the night before, is anxious about a family member's problem, has not eaten breakfast, must work with a dangerous piece of equipment, and has continually changing job demands is likely to be affected differently by a prior night's use of marijuana or cocaine than a well-rested worker performing a routine task. The challenge of modeling such complex interactions and simplifying the issues so that they can be studied in the laboratory is obvious and may never fully be met. Yet laboratory research can provide a base from which to start understanding such problems. Even if it cannot capture the full richness of the occupational world, it can help us understand how the drugs people take interact with different kinds of ongoing behavior; this is knowledge we must have in order to design and implement effective intervention programs. A second goal of laboratory research on drug effects is to develop reliable measures of the acute impairment associated with drug use. To date, the most commonly used method for identifying drug use by the work force relies on urinalysis to detect the presence of drugs or their metabolites. Such testing does not address the issue of drug-induced impairment. Although there are data relating dose of alcohol to level of impairment, there are no data relating the level of other drugs (or their metabolites) obtained from urinalysis to levels of impairment. Laboratory-developed measures of impairment that lead to the development of a reliable and easily administered performance battery for the detection of workplace performance impairment could be an enormous improvement over the current technologies (discussed in Chapter 6). A myriad of laboratory performance studies have been carried out to test the effects, under controlled conditions, of such drugs as stimulants, marijuana, sedatives, benzodiazepines, and alcohol (see Table 4.1).1 However, 1    This discussion is based on a review, for the National Research Council, of approximately 250 papers by Foltin and Evans (1992). The studies included were published between 1970 and 1991 and involved healthy volunteers tested using laboratory tasks and given single doses of stimulant, sedative-hypnotic, alcohol, or marijuana. A shorter version of that review has recently been published by the Journal of Human Psychopharmacology (see Foltin and Evans, 1993). Review of the 250 papers yielded data on 305 tasks, only 118 of which were used in more than one experiment. For simplicity of discussion, tasks were grouped into general categories and only general behavioral effects are discussed.

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Under the Influence? Drugs and the American Work Force TABLE 4.1 Examples of Task and Performance Effects of Selected Drugs of Abuse Drug/Study Taska Results Stimulants     Lane and Williams (1985) (caffeine, 250 mg) arithmetic not significant Klorman et al. (1984) (methylphenidate, 20 mg) continuous performance not significant Hindmarch et al. (1990) (nicotine, 2 mg gum) complex reaction time not significant Heishman and Stitzer (1989) (amphetamines, 20 mg) circular lights not significant Marijuana     Jones and Stone (1970) (4.5, 9.0 mg) time estimation impaired Pihl and Sigal (1978) (8 mg) time estimation impaired Marks and MacAvoy (1989) (2.6, 5.2 mg) divided attention impaired Heishman et al. (1989) (12, 21 mg) divided attention not significant Hooker and Jones (1987) (12 mg) arithmetic not significant Barnett et al. (1985) (7, 14, 17.5 mg) tracking impaired Evans et al. (1976) (1.75 mg/70 kg) tracking impaired Alcohol     Strömberg et al. (1988) (1 g/kg) postural stability impaired Erwin et al. (1986) (0.8 g/kg) divided attention impaired Collins (1980) (3.25 ml) reaction time impaired Wilson et al. (1984) (BAC 100 mg) tapping impaired Taberner et al. (1983) (0.1-0.4 g/kg) cancellation impaired Peterson et al. (1990) (0.132-1.32 ml) reaction time impaired Linnoila et al. (1990) (0.8 g/kg) continuous performance not significant Foltin et al. (1993) (19.4-58.1 g) vigilance impaired Linnoila et al. (1990) (0.8 g/kg) complex reaction time not significant Peterson et al. (1990) (0.132-1.32 ml) tracking impaired

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Under the Influence? Drugs and the American Work Force Drug/Study Taska Results Folton et al. (1993) (19.4-58.1 g) list recall not significant Sedatives     Mattila et al. (1986) (Buspirone, 15 mg) divided attention not significant Preston et al. (1989) (Lorazepam, 1-4 mg) circular lights impaired Patat et al. (1987) (Diazepam, 10 mg) tapping not significant Mattila et al. (1986) (Diazepam, 10.5, 21 mg) cancellation impaired Curran and Lader (1987) (Lorazepam, 1.2 mg) arithmetic impaired Erwin et al. (1986) (Diazepam, 10 mg) continuous performance impaired Alford et al. (1991) (Clobazam, 10 mg) complex reaction time not significant Patat et al. (1991) (Triazolam, 0.25 mg) list recall impaired Alford et al. (1991) (Lorazepam, 1 mg) recognition memory impaired a Definition of tasks: Arithmetic: subjects required to perform simple mathematical tasks, most often ''in their heads" rather than using pencil and paper. Complex reaction time: subjects required to respond differentially to a change in stimulus conditions. Time estimation: subjects required to give time estimations. Divided attention: subjects required to perform two tasks simultaneously. Tracking: subjects required to track a moving stimulus with their dominant hand. Postural stability: a range of various tasks to provide measures of gross motor coordination. Circular lights: measures gross hand/eye coordination. Tapping: requires subjects to tap a key with one finger for a given number of taps or length of time. Cancellation: requires subjects to examine a field of information and mark as many target stimuli as possible in a fixed period of time. Reaction time: requires subjects to respond as rapidly as possible to a visual or auditory stimulus which has only one correct response. Continuous performance: requires subjects to attend to stimulus presentations and respond when certain patterns of stimuli occur. Vigilance: reaction time tasks under continuous attention conditions. List recall: requires subjects to recall previous learned tasks or information. Recognition memory: requires subjects to recall or list stimuli previously presented to them. SOURCE: Foltin and Evans (1992).

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Under the Influence? Drugs and the American Work Force even apart from the complex interaction effects mentioned above, these studies have numerous shortcomings as guides to understanding the effects of alcohol and other drug use by the work force. Although the doses studied are sometimes (but not always) the same as those being used by drug users in the work force, patterning of drug use comparable to that of many drug users (i.e., multiple doses, periodically repeated doses, etc.) has not been adequately addressed. Moreover, with few exceptions, no attempt has been made to model the specific task used to measure impairment after specific workplace performances, and multiple variations on similar tasks make generalization across studies difficult. To further complicate the picture, there has been little effort to model the subject population in laboratory studies after the work force population. The most frequently used research subject is a college student, paid to participate in a research project, or expected to participate in order to fulfill a course requirement. In addition, unlike the worker who is experienced in the task being performed, the subjects in most drug use studies are frequently performing the tasks on which impairment is measured for the first time or after only a brief period of training. Behavioral histories are seldom taken into account in laboratory research. Other common weaknesses of experimental design include inattention to doses used, time points for measurements, and contingencies in maintaining behavior. Despite these problems, however, a few generalizations can be drawn about the likely effects of different classes of drugs on performance. DRUGS AND THEIR EFFECTS Stimulant Drugs Stimulant drugs (e.g., caffeine, amphetamine, cocaine) increase general activity, lead to reports of positive subjective effects, and are often used clinically to reduce food intake (Fischman, 1987). Despite users' reports of substantial performance enhancement after stimulant use, this effect has not been systematically replicated in the laboratory (Johanson and Fischman, 1989). When improvement in performance has occurred, the margin of improvement has either been less than 10 percent, or stimulants prevented or reversed a decrement in performance due to fatigue or boredom. Of course in some situations like athletic competitions, a minor improvement in performance could have large positive effects for the performer (Laties and Weiss, 1981), and, when otherwise unavoidable fatigue or boredom are fought off, decrements in performance may be forestalled. In general, however, it is important to point out that significant performance enhancement is not apparent; much of what users report are the subjective effects of stimulants (e.g., increased levels of energy, friendliness), which lead to a

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Under the Influence? Drugs and the American Work Force belief that behavior is improved without any actual improvement (Fischman, 1987). Marijuana The use of marijuana and products containing δ9-tetrahydrocannabinol (THC) has a long history, and the literature on the effects of these substances on performance is voluminous. Concentrated efforts to delineate marijuana-related effects on behavior have yielded variable results, with the most consistent effects being decrements in time estimation and divided attention tasks (e.g., Jones and Stone, 1970; Marks and MacAvoy, 1989). Marijuana interfered with performance on a variety of other tasks on approximately 50 percent of the occasions it was studied (e.g., arithmetic, Chesher et al., 1977; tracking, Barnett et al., 1985), suggesting that experimental conditions play a substantial role in determining the effects of this substance. Although there is some evidence that marijuana can affect performance for several hours after it is used (e.g., Miller and Cornett, 1978), there are almost no data on what behaviors are impaired, for how long, and to what extent. There has been a general belief that smoking marijuana can lead to a cluster of signs and symptoms often referred to as an amotivational syndrome. If it does, repeated rather than occasional use of marijuana could have severe implications for behavior and productivity in the workplace. The motivational effects of marijuana have provided a focus for research over the past several decades, with variable results. In general, well-controlled epidemiological studies of marijuana use have failed to confirm the existence of such a syndrome (e.g., Comitas, 1976; Stefanis et al., 1977; Page, 1983), and laboratory research suggests that environmental conditions can influence the amotivational effects of marijuana, determining its presence or absence (Foltin et al., 1989, 1990). Alcohol and Sedatives The majority of studies evaluating acute effects of alcohol administration have found that single doses cause decrements in a variety of performance tasks, particularly tracking, visual vigilance, divided attention, postural stability, and cancellation tasks, with less robust effects on memory tasks. Since the problems that alcohol use poses for transportation safety are well recognized, it has received substantial attention from the transportation research community. As with other laboratory studies, the magnitude of impairment in transportation-related tasks has been shown to be dependent on the nature of the task, research subject characteristics (e.g., skill level, tolerance) and environmental factors (e.g., fatigue). Overlearned tasks

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Under the Influence? Drugs and the American Work Force (e.g., coordination, balance) are relatively resistant to alcohol consumption (Burns, 1992), while divided attention, information processing, and attention processes are highly susceptible to alcohol-induced impairment (Streufert et al., 1992). Performance on these latter tasks are impaired at low blood alcohol levels, implying that relatively small amounts of alcohol can have detrimental consequences for both traffic safety as well as other workplace safety-sensitive positions. Although there is a relationship between blood alcohol level and decrements in performance, there is considerable variability in the alcohol level at which decrements occur. In addition, there is variability in the amount of alcohol required to reach a given blood alcohol level, even when body weight is controlled (O'Neil et al., 1983). This source of variability is largely related to variations in metabolic rate. Furthermore, although the data are not as clear for all the benzodiazepines, data with prototypic benzodiazepines (diazepam, lorazepam, and triazolam) suggest that, as with alcohol, these drugs produce decrements on a full range of performance tasks, from gross motor tasks such as postural stability (Evans et al., 1990) to complex tasks such as divided attention (Erwin et al., 1986). Residual Drug Effects Although residual effects can refer to any effects that occur a number of hours after major drug effects have dissipated, this has come to mean next-day effects or hangover effects. The issue here is whether substances used at home on one day affect job performance the next day. These effects can either be manifested as prolonged drug effects, similar to the initial drug effect, or can differ from the initial drug effect. This latter change in behavior is best characterized by what is commonly called hangover. Thus, alcohol consumed during the evening can produce intoxication, slurred speech, etc. Six or eight hours later, after some sleep and no further alcohol intake, a different set of symptoms (e.g., headache, irritability, inability to concentrate, etc.) might be apparent. Such hangover effects can be disruptive in the workplace, reducing productivity and perhaps interfering with safe and accurate performance and/or social interactions. In addition, it is possible that hangover or drug withdrawal effects are contributing factors in the maintenance of drug-seeking behavior. In addressing the issue of residual drug effects, we have to differentiate between chronic, regular, daily drug use and acute, or occasional, drug use. Repeated drug use can result in tolerance to some of the effects of the drug. When tolerance develops, it takes a larger dose of the drug to achieve the same effect. The development of tolerance does not by itself affect workplace performance, although it can moderate what would otherwise be the effects of drug-taking behavior or allow greater consumption of a drug than would otherwise occur. The aspect of chronic drug use that can affect

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Under the Influence? Drugs and the American Work Force workplace performance adversely is the development of dependence. Physical dependence is manifested as a syndrome of effects that appear upon abrupt cessation of a drug after chronic use and can be alleviated by intake of that drug. The most widely described drug dependence is probably for the opiates, as seen with chronic heroin use. Comparable dependence is seen with many if not all classes of psychotropic drugs. The data on the development of dependence to alcohol, sedatives, and opiates are clear. Repeated and regular intake of these substances has been shown to result in physical dependence, manifested by a replicable withdrawal syndrome that can be alleviated by the administration of the substance that the individual has been taking. The data for marijuana are less clear. A number of laboratory studies have been carried out in which research subjects were given marijuana cigarettes to smoke, or δ9-THC to consume, repeatedly for 10-30 days. In general, both tolerance to many of marijuana's effects and dependence are seen (Jones and Benowitz, 1976; Mendelson et al., 1976). Withdrawal is manifested as irritability, restlessness, decreased appetite, tremor, etc., and has been described (Jones, 1978) as a clinical picture similar to that seen after withdrawal of the sedative-hypnotics. It is possible that the maintenance of stable THC blood levels is important for the development of dependence, and that cessation of use could result in a withdrawal syndrome with workplace consequences. Residual effects of occasional marijuana use appear slight if they exist at all. Some researchers searching for hangover effects recount subjective reports of feeling "spacey" or "stoned" or "hung over'' the next day (Cousens and DiMascio, 1973). The few objective measures that purport to show decrements attributable to the consumption of marijuana a day earlier are suggestive at best (Yesavage et al., 1985; Leirer et al., 1991). Thus, we cannot at this time conclude that the occasional use of marijuana will have measurable next-day residual effects, nor can we conclude that some subtle effects are not present. Accuracy in identifying small amounts of cannabis metabolites in urine is excellent. This means that even occasional use of marijuana is often picked up in urine screens taken in relation to an accident or other workplace problems. We cannot, however, on the basis of the available data, assign particular behavioral consequences to the presence of these metabolites in the urine. Thus, when post-accident drug screening reveals that a responsible person tested positive for marijuana, it does not mean that marijuana use played a causal role in the incident. Alcohol hangover effects can apparently degrade performance. They have been reported to impair drivers' and pilots' performance (Laurell and Tornros, 1983; Yesavage and Leirer, 1986), although the extent of the impairment was in part related to both age and experience with the task. For example, performance of older pilots was more impaired than that of younger

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Under the Influence? Drugs and the American Work Force pilots, but the older pilots were more aware of their impairment for up to 4 hours after reaching peak blood alcohol levels. There are no data on the residual effects of occasional stimulant use except for fatigue related to secondary sleep deprivation. When stimulants are used repeatedly in binges, a "crash," marked by irritability, hypersomnolence, and some depression can occur (Fischman, 1987). This constellation of next-day effects, however, has not been linked to specific performance changes, and it may be that the effects do not differ from decrements measured after sleep deprivation in the absence of drug use. METHODOLOGICAL ISSUES Where laboratory conditions are different from the conditions that characterize actual drug use, drug users, and job performance, there is a question of how far one can generalize from laboratory results to predict the actual implications of drug use that are of interest (Berkowitz and Donnerstein, 1982; Dipboye and Flanahan, 1979; Locke, 1986; Sears, 1986; Sackett and Larson, 1991). This is the external validity problem. Not all differences between the laboratory and the outside world pose serious threats to external validity. This depends on whether there is reason to believe the differences are consequential for the generalizations one would like to make. Unfortunately, in assessing the research done to date on the performance implications of drug use, many of the differences between the currently available laboratory studies and drug use outside the laboratory appear large and potentially important. Often, however, these differences, or at least the size of these differences, are not inherent in the laboratory methodology. Thus identifying important differences not only highlights the limitations of extant research, but it also suggests ways in which future studies can be improved. The failure to examine combinations of drugs constitutes a major gap in the research on drugs' effects on performance. It is becoming increasingly rare to find a single-drug-class abuser (or even drug user). Polydrug use is generally the norm, and this is particularly the case for alcohol. Many substances, such as marijuana, nicotine, and sedatives, are frequently taken in combination with alcohol, and the effects of these combinations are generally unknown. It has recently been reported that the combined intake of cocaine and alcohol results in formation of a metabolite, cocaethylene, which has a half-life of more than 2 hours, and is considerably more toxic than either drug alone (Hearn et al., 1992; Perez-Reyes and Jeffcoat, 1992). Although not yet studied, it is possible that this active metabolite could result in behavioral changes long after measurable cocaine or alcohol levels are present in the body. Other combinations of drugs may have effects that

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Under the Influence? Drugs and the American Work Force is positively correlated with household income. This might occur because higher income leads to increased discretionary consumption of alcohol. Marijuana Use and Productivity Heavy or long-term marijuana use is negatively related to both household income and wages for men but appears to be positively related to wages and household income for women. Harwood et al. (1984), considering a population that aggregates men and women, find that daily marijuana use for a period of at least a month at some point in the past is negatively related to household income. Register and Williams (1992), considering men only, report that in the 1984 National Longitudinal Survey of Youth (NLSY), marijuana use for longer than 8 years is negatively related to current wages. Kaestner (1991), who also examines the 1984 NLSY, finds that heavy lifetime or past-30-day marijuana use is insignificantly negatively related to wages for men and significantly positively related for women. Current or moderate lifetime marijuana use is either essentially uncorrelated with wages or income or is modestly positively correlated. Harwood et al. (1984) report that all measures of current marijuana use or lifetime marijuana use other than having smoked marijuana daily for at least a month display insignificant correlations with household income, with some point estimates positive and some negative. Rice et al. (1990) state that results based on use of particular drugs are ill defined and therefore do not report any details. Register and Williams (1992) find that, averaged over the whole sample, marijuana users and slightly lower wages than nonusers. Controlling for a range of observed characteristics, however, reveals a positive and significant correlation between marijuana use and current wages. Kaestner (1991) reports negative, insignificant correlations for men and positive, generally significant correlations for women with all measures of marijuana use. Cocaine and Other Drug Use and Productivity The relation between any level of cocaine or other nonmarijuana drug use and wage rates or income is either insignificant or positive. Harwood et al. (1984) state that they could find no significant results relating illicit drug use to household income for any illicit drug other than marijuana. Again, Rice et al. (1990) state that results based on the use of particular illicit drugs were ill defined and therefore do not report any details. Gill and Michaels (1992), using 1980 and 1984 NLSY data, find that a wage differential that favors illicit drug users over nonusers increases when the comparison is made between hard drug users (cocaine, heroin, etc.) and all other illicit drugs. Register and Williams (1992) document a higher average

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Under the Influence? Drugs and the American Work Force wage for cocaine users than nonusers, and they show that cocaine use is positively although insignificantly correlated with wages after accounting for observable characteristics. Kaestner (1991) finds that virtually all measures of cocaine use are positively correlated with wage rates, and these correlations are substantially larger and more significant for women than men. Demographic Differential Effects In studies for which comparisons are available, the relation between alcohol and other drug use and productivity is usually more negative (less positive) for men than for women. Rice et al. (1990) show that alcohol abuse is more negatively correlated with household income for men than women up through age 34, after which the relation reverses, and that illicit drug abuse is negatively correlated with household income for men of all ages but positively correlated for women of all ages. Kaestner (1991) documents a negative and usually insignificant correlation between various measures of marijuana use and wages for young men and a positive and usually significant correlation for young women. He documents a positive but small and usually insignificant correlation between various measures of cocaine use and wages for men and a positive, larger, and usually significant correlation for women. Variations in Results Across Outcome Measures The comparisons that employ household income as a measure of productivity suggest, on average, associations that are more negative between alcohol and other drug use than comparisons based on wages. However, no study uses data on both measures of productivity, so it is difficult to isolate the effects of using a particular productivity measure. In comparing studies with one measure or the other, one also faces differences in data sets, drug variables, control variables, sample periods, and population characteristics (e.g., only young people in the wage regressions whereas all ages in household income regressions). Nevertheless, when similar alcohol and other drug variables are employed, household and individual measures of productivity display similar correlations with alcohol and other drug use. In large part, earlier studies appear to have obtained substantially more negative relations than more recent studies because they emphasized those results that used measures of heavy use or abuse. Even in the early studies, most measures of use for alcohol and other drugs show small negative to small positive correlations with productivity. The failure of alcohol and other drug use to display the ''expected" negative correlation with productivity does not appear to result mainly from

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Under the Influence? Drugs and the American Work Force an effect of alcohol and other drug use on productivity via the labor supply. Register and Williams (1992), using the NLSY data, find that marijuana use is associated with a decreased probability of being employed but that cocaine use has no significant relation to the probability of employment. Zarkin et al. (1992), using the 1990 National Household Survey on Drug Abuse, examine the prevalence of illicit drug use by work status and the relation between illicit drug use and measures of labor supply: weeks worked during the past year, number of sick days taken during the past month, and number of days of work skipped for nonmedical reasons during the past month. Their prevalence estimates indicate that the working population has a slightly higher rate of alcohol and other drug use than the total household population. Their regression results indicate that illicit drug use is associated with fewer weeks worked, whereas alcohol use is associated with more weeks worked. Illicit drug use is not related to the number of sick days taken, but past-month illicit drug use is related to an increased number of work days skipped. Kaestner (1992) finds a negative relation between illicit drug use and labor supply in cross-sectional estimates but little significant relation in longitudinal estimates. INTERPRETING THE EMPIRICAL RESULTS Despite the substantial differences in results across studies, careful reading suggests some consistencies in the empirical results. Heavy or problem use of marijuana or alcohol is generally associated with lower productivity (with the possible exception of women in the case of marijuana) and low to moderate use of any illicit drug or alcohol is either positively associated with productivity or simply not significantly related. Despite the consistency of the empirical evidence, however, interpretation of this evidence must proceed cautiously. The key problem of interpretation may be called the heterogeneity effect. Put simply, individuals differ along several dimensions, some observable and some not. Observable characteristics include sociodemographics such as education, age, race, and gender. These variables are likely to influence job compensation and are usually included in wage equations. However, several unobservable characteristics may be equally or even more likely to influence wages. These unmeasured variables include motivation, aggression, intelligence, ambition, discipline, and the like. If characteristics such as these influence wages, and if alcohol or other drug use is correlated with one or more of these variables, then the estimated relation between such use and wages will tend to pick up these latent effects. Thus, an estimated negative relation between use and wages or income may simply indicate that less ambitious people are likely to both use alcohol or other drugs and have low wages; the inference that such use causes low wages would not be justified. Similarly, an estimated positive

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Under the Influence? Drugs and the American Work Force relation could indicate that creative or gregarious individuals are likely to both use alcohol or other drugs and have high wages without suggesting any causal effect. Another problematic aspect of some of these studies and others (Mills and Noyes, 1984; Newcomb and Bentler, 1986, 1988; Kandel 1984; White et al., 1988) that have examined the association between alcohol and other drug use and income level is that most results are based on cross-sectional data largely among youthful samples. Potential problems associated with cross-sectional designs and the use of restricted age range samples is illustrated by the results of recent analyses of longitudinal data. In analyzing income and alcohol and other drug use data, Newcomb and Bentler (1988) found that greater polydrug use by teenagers was associated with increased income 4 years later. They explained this finding by noting that adolescent polydrug users were more likely than those who used few or no drugs to begin working right out of high school and not attend college. Those who used few or no drugs as teenagers were more likely to go to college and delay entry into the work force. Therefore, adolescent heavy alcohol or other drug users may be expected to earn higher incomes than less heavy users as young adults, since they will have been in the work force for 4 years while those less involved in drugs continued their education. In a follow-up of this same sample, Newcomb and Bentler (1992) found that 4 years later the relationship between income and teenage polydrug involvement had reversed. Both adolescent alcohol and other drug use and increased use of alcohol and other drugs into adulthood was associated with reduced income by the time people reached their mid-to-late twenties. The researchers explain this reversal by assuming that the greater education of the low alcohol and other drug users eventually resulted in higher income (an elevated earning potential ceiling) than that enjoyed by those who were involved with alcohol and other drugs as teenagers and maintained or continued such involvement. The latter had a short-term income benefit but suffered over the long run from a low ceiling to their earning potential. Clearly, more prospective data must be analyzed to characterize more adequately and precisely the dynamic relationship between alcohol and other drug use and income. Reliance on cross-sectional data is inappropriate and possibly gravely misleading. Furthermore, a much wider age range must be studied than the primarily young groups represented in these studies. In addition to these general problems, there are some more technical but nonetheless fundamental problems with most cost-of-drug use research. Wage rates as a measure of productivity are biased because they are observed only for employed individuals and do not reflect the productivity costs that would be incurred by individuals out of the labor force. While researchers today commonly recognize and attempt to address this problem (Gill and Michaels, 1992; Register and Williams, 1992; Kaestner, 1991),

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Under the Influence? Drugs and the American Work Force the methods used, so-called Heckman corrections (Heckman, 1976, 1979), do not seem adequate to the task. Not only are they sensitive to model misspecification, but at best they can only estimate how alcohol and other drug use would have affected the wages of the unemployed if they were employed. What matters, however, is the extent to which alcohol and other drug use leads individuals to become unemployed. But even these criticisms are less important than the fact that Kaestner (1991) demonstrates that the corrections appear to make no difference to the results in any event. Some of the studies that use wages as the productivity measure attempt to control for the fact that the relationship between wages and alcohol and other drug use is potentially bidirectional; each may affect the other (e.g., Kaestner, 1991). Such similarity, if it exists, will inflate the estimated correlation between alcohol and other drug use and wages. Correcting for the simultaneity problem requires the availability of "instrumental" variables that affect alcohol and other drug use and not wages. Spousal income is commonly treated as such a variable, but Gill and Michaels (1992) demonstrate that the spouses of alcohol and other drug users typically have low income. If, holding other demographic characteristics constant, users of alcohol and other drugs tend to marry people with low incomes, then simultaneous equation estimation techniques will incorrectly adjust for the effect of income on alcohol and other drug use and could lead to overestimates of the negative relation between such use and wages. Simultaneous equations estimates may thus be worse than the estimates that make no correction for simultaneity bias. In sum, there are serious difficulties with estimating the causal relations between alcohol and other drug use and productivity and with attempts to estimate the costs of use in general. Current estimates can be taken only as ballpark figures. They are probably correct in suggesting that there are great costs, even if the most concretely measured costs are those incurred in the attempt to control alcohol and other drug use because of the assumed magnitude of nonenforcement costs. Work to refine cost-of-drug-use measures should proceed, but even if substantial progress is made, we should not confuse measures of the cost of drug use with the expected net benefits of policies aimed at limiting those costs. The committee's conclusions and recommendations that follow are based on a critical review of the literature on the impact of alcohol and other drug use on employees' work-related behavior as well as studies that have explored the relationship between use and productivity/cost estimates. They are intended to highlight the need to expand scientific knowledge of how alcohol and other drug use affects work-related behavior and to improve the quality of research aimed toward this end.

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Under the Influence? Drugs and the American Work Force CONCLUSIONS AND RECOMMENDATIONS Field studies have consistently linked alcohol and other drug use to higher rates of absenteeism; they also provide evidence of an association between alcohol and perhaps other drug use and increased rates of accidents, particularly in the transportation industry. Less consistent evidence exists linking alcohol and other drug use to other negative work behaviors, although the current research base is insufficient to support firm conclusions. When associations between alcohol and other drug use and counterproductive workplace behavior are found, relationships are most often of moderate or low strength even when they are statistically significant. The empirical relationships found between alcohol and other drug use and job performance are complex and need not imply causation. Relationships may exist for some job performance outcomes like absenteeism but not for others. Alcohol and other drug use may be just one among many characteristics of a more deviant lifestyle, and associations between use and degraded job performance may be due not to drug-related impairment but to general deviance or other factors. Recommendation: To intervene more effectively in improving job performance, we must develop a better research base from which to assess how alcohol and other drug use and other factors act alone and in combination to degrade job performance. • Widely cited cost estimates of the effects of alcohol and other drug use on U.S. productivity are based on questionable assumptions and weak measures. Moreover, these cost-of-drug-use studies do not provide estimates of potential savings associated with implementing particular public policies toward alcohol and other drugs. Recommendation: Further research is needed to develop refined, defensible estimates of how much alcohol and other drug use costs specific organizations and society at large. Business decision makers and policy makers should be cautious in making decisions on the basis of evidence currently available. REFERENCES Alleyne, B.C., P. Stuart, and R. Copes 1991 Alcohol and other drug use in occupational fatalities. Journal of Occupational Medicine 33:496-500. Berger, M.C., and J.P. Leigh 1988 The effect of alcohol use on wages. Applied Economics 20:1343-1351.

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