Management of human resources associated with misuse of prescription drugs: analysis of a national survey.

Lee, Doohee ; Ross, Michael W.

INTRODUCTION

Prescription drug abuse or misuse has been a strong public health concern in recent years (Compton & Volkow, 2006). In 2006, about 48 million Americans had misused prescription drugs in their lifetime (NIDA, 2006) and about 7 million Americans are current nonmedical users of prescription drugs (NIDA, 2008). The estimated number of emergency department visits for nonmedical use of opioid analgesics increased 111% during 2004-2008 (from 144,600 to 305,900 visits) (CDC, 2010). As recent literature continues to document prescription drug misuse problems among many Americans (CDC, 2010; Kroutil et al., 2006; Simoni-Wastila et al, 2004; Manchikanti, 2007;

Matzger & Weisner, 2007; McCabe et al, 2009; Fenton et al., 2010), it is necessary to further expand research of prescription drug abuse or misuse in the American workforce.

There are a host of recent studies largely focused on prescription drug problem among the general public (CDC, 2010; Kroutil et al., 2006; Simoni-Wastila et al, 2004; Manchikanti, 2007; Matzger & Weisner, 2007; McCabe et al, 2009; Fenton et al., 2010), but inadequate attention has been focused on employees' prescription drug use problems, although about 7% of the American labor force reported using prescription drugs nonmedically in the year prior to the survey (NIDA, 2008). A recent national estimate suggests (SAMHSA, 2007) that nearly 75% of illicit drug users aged 18 or older were employed either full-time or part-time. The same report indicates that approximately 17% of unemployed were current illicit drug users, while 8.2% of full-time employed and 11% of part-time employed were current illicit drug users. A considerable number of studies document alcohol and illicit drug use problems in the workforce (French et al., 1995; Matano et al., 2002; Roberts & Fallon, 2001; Frone, 2006a;

Frone, 2006b; Register & Williams, 1992; Webb et al, 1994; Lehman & Bennett, 2002), but very limited research on employee prescription drug misuse is available. French et al. (1995) report 17% of employees across 5 different workplaces misusing prescription drugs. Certain health care professionals are at a greater risk of abusing prescription drugs. Some problems linked to prescription drug abuse are reported among physicians (Sethi & Manchanda, 1980; Merlo & Gold, 2008). The 1999 research (Trinkoff et al., 1999) suggests that nurses with easy access to prescription drugs are more likely to abuse prescription drugs. Another study (McAuliffe et al., 1987) reports 46% of the pharmacy students using a controlled substance with a prescription. Surveying highly educated employees (n=504), Matano and colleagues (2002) revealed 42% of respondents reporting the use of moodaltering prescription drugs (analgesics, antidepressants, sedatives, or tranquillizers) and 11% using illicit drugs (cocaine, hallucinogens, heroin, or marijuana) in the past year.

Understanding employee absenteeism and job turnover linked to prescription drug misuse is important in the context of human resource management for at least two reasons. First, organizations are by and large concerned about the quality of human capital; in particular employees' risky behaviors because those risk behaviors diminish performance (Serxner et al., 2001) and increase injury or accidents in the workplace (Spicer et al., 2003). Prior research supports the association between work performance and alcohol and illicit drug use (French et al., 1995; Mangione et al., 1999; Bass et al., 1996; Normand et al., 1990). Surveying 1,200 employees at five different worksites, French et al. (1995) reveals the association between illicit drug uses including prescription drug misuse and reduced performance and absenteeism. A recent national survey report (SAMHSA, 2007) also suggests that drug using employees, compared to their non-drug-using counterparts, had higher job turnover, missed work more than 2 days because of illness and injury, and skipped work for more than 2 days in the past month. A recent Substance Abuse and Mental Health Services Administration (SAMHSA) report confirms prescription drug abusing employees missing more than 2.2 days of work monthly when compared to the 0.83 days monthly for the average person(US DHHS, 2008; Ruetsch, 2010). Second, in addition to workplace performance issue, employers may experience financial difficulty of providing excessive healthcare coverage to those drug using employees (Harwood et al., 1998). Substance abuse problems in the workforce cost American firms billions of dollars each year (SAMHSA, 2009) and evidence suggests associations between employees' substance misuse and costs (US DHHS, 1999). Rising health care spending makes many American firms less competitive in the global marketplace (US DHHS, 2004; Porter, 2004) and employees' risk behaviors negatively benefit competitive advantages of a firm in the current economic downturn market.

Notwithstanding acknowledgement and the importance of substance abuse problem in the workforce, understanding nonmedical use of prescription drugs linked to employment factors has been largely unnoticed. The objective of this research is thereby (1) to explore the association of employment factors (absenteeism and turnover) with related problems of PPRs, (2) to investigate the moderating effects of employee drug policy/testing on the relation between having problems associated with misuse of PPRs and absenteeism/turnover.

METHODS

Data Source

The present study uses a 2007 National Survey on Drug Use and Health (NSDUH) (formerly known as National Household Survey on Drug Abuse) to examine employment factors associated with related outcomes of PPRs among the employed. NSDUH is a nationally representative annual survey conducted by SAMHSA, and it was designed to measure the prevalence and correlates of drug uses among members of the U.S. households aged 12 and older (SAMHSA, 2007). The survey was done using a combination of computer-assisted personal interviewing (CAPI) conducted by an interviewer and audio computer-assisted self-interviewing (ACASI). This survey takes about one hour to complete and employed a 50-State design with an independent, multistage area probability sample for each of the 50 States and the District of Columbia. Each participant received a monetary incentive of $30 in an effort to increase response rates. The study yielded a weighted screening response rate of 89.5 percent and a weighted interview response rate for the Computer Assisted Interview (CAI) of 73.9 percent. More detailed information about the NSDUH methods and study design is available elsewhere (SAMHSA, 2007).

For the purpose of the study, of the total surveyed samples (n= 55,435), only employed individuals who misused prescription pain relievers in the past year (n=2,249) were included in the analysis (Figure 1). Of the sample (n=2,249), 59.03% were male and 75.46% were non-Hispanic whites. About 34% were young adults (in the age range of 18-25), and nearly 40% were 35 years old or older.

[FIGURE 1 OMITTED]

Measure

Dependent variable. Having problems associated with misuse of prescription pain relievers (PPRs) was used as dependent variable. Specifically participants were asked, "During the past 12 months, did using prescription pain relievers cause you to have serious problems (neglecting children, missing work or school, doing a poor job at work or school, and losing a job or dropping out of school) either at home, work, or school." The response was categorical (yes=1, no=0). Misuse of PPRs refers to use of any form of prescription pain relievers that were not prescribed for themselves or that they took only for the experience or fee ling they caused.

Covariant variables. Every participant was asked about demographic characteristics including age (3 categories: 18-25, 26-35, >35), gender (male/female), race/ethnicity (Whites, Blacks, Asians, Hispanics), education (4 categories: <high school, H.S. graduate, some college, and college graduate). Current employment status was measured by asking respondents about their working status in the past week (full-time vs. part-time). The survey also collected the information about workplace variables that included the following items: (1) workplace drug policy ("At your workplace, is there a written policy about employee use of alcohol or drugs?") (yes or no); (2) workplace drug testing ("Does your workplace ever test its employees for drug use?") (yes or no); (3) workplace size ("How many people work for your employer out of this office?") (5 categories: <10, 10-24, 25-99, 100-499, and >500); (4) job turnover ("How many different employers, including yourself, have you had in the past 12 months?") (4 categories: 1, 2, 3, 4 or more jobs); and (5) work absent ("During the past 30 days, that is from up to and including today, how many whole days of work did you miss because you did not want to be there?) (Continuous response: 1-30 days). Individual risk behaviors (tobacco/alcohol/heroin use) were also measured (self-report uses in the past year) (yes or no).

ANALYSES

Mean scores (s.d.) of all dependent and covariant variables were first generated and then the binary analysis of the sample by employment status was conducted. We also undertook the hierarchical logistic regression analysis to test how employment-related variables hold their significance in relation to related problems of PPRs misuse while controlling for other confounding variables. In Model 1, workplace variables such as employment status, workplace size and drug policy/testing were forced into the equation to test the bivariate association with having problems of PPRs misuse. In Model 2, absenteeism and turnover were added to the association with the dependent variable. Interaction terms were added to Model 3 to test the joint effect of two variables (drug policy/testing and absenteeism/turnover) on causing problems of PPRs misuse. Model 4 controlled for demographic variables (gender, age, race/ethnicity, and education) as well as personal risk behaviors (tobacco/alcohol/heroin uses in the past year) that were forced into the equation to test its association with having problems of PPRs misuse. Fstatistics were reported in the regression, instead of rsquared. The pseudo r-squared is not applicable to complex survey design data as we already correctly specified and distributed the sampling weights. STATA 10.1 (Stata Corporation, 2007) was used for all analyses. Correctly generating national estimates is critical when analyzing data with complex survey design and hence sampling weights were all applied using survey commands (svy) in STATA.

RESULTS

Mean scores and its standard deviations of all measured variables in the analysis are presented in Table 1.

Table 2 highlights sample characteristics by employment status. Full-time employees are more likely than their counterpart part-time employees to be older (3.11 vs. 2.51, p< .001), less educated (2.57 vs. 2.82, [beta]= .004), have a written drug policy (58% vs. 13%, p< .001) and drug testing (38% vs. 0.5%, p< .001) in their workplaces.

Table 3 displays the multivariate logistic regression analysis results. In the first two models, workplace drug policy was significant but did not remain significant in the last two models while controlling for personal confounding factors, suggesting that personal factors play a role affecting having problems associated with misuse of PPRs. Absenteeism ([beta] = .74, p= .004) and turnover ([beta] = 1.07, p= .04) remained significant while controlling for personal factors, suggesting that individuals having PPRs related problems are more likely to experience absenteeism and turnover. Workplace drug policy was found to interact with turnover ([beta] = .03, p= .006) and absenteeism ([beta] = -.71, p= .049) in relation to having negative impact of misuse of PPRs, suggesting the use of drug policy may increase absenteeism but reduce the job turnover rate. Drug testing was also found to be interacted with absenteeism ([beta] = - .39, p= .002), suggesting that drug testing may reduce absenteeism in relation to having problems of prescription drug misuse. Of personal confounding factors added to Model 4, only heroin use in the past year ([beta] =1.51, p= .025) was found to be associated with having problems caused by misuse of PPRs. This suggests that heroin using employees are more likely to face some problems linked to misuse of PPRs.

DISCUSSION

The current literature lacks evidence of the association between prescription drug misuse and employment factors in the American workforce. Our study offers an important contribution to the literature by revealing some problems associated with misuse of PPRs linked to absenteeism and turnover after controlling for personal factors, which is in line with prior research (French et al, 1995; SAMHSA, 2010) that substance abusing workers, compared with their non-substance abusing counterparts, are more likely to change jobs frequently and to be late to or absent from work. Prior research inadequately has examined the possible moderating roles of employee drug policy/testing in relation to having problems of misuse of PPRs. Our analysis adequately fills this research gap. Our finding that drug policy increases absenteeism in relation to having problems associated with misuse of PPRs is at odds with another finding that drug policy moderates the association between job turnover and facing problems related to misuse of PPRs. It is uncertain why the same policy variable produces dissimilar effects but no related research exists. One possible explanation would be that a comprehensive drug policy program including drug testing may motivate employees to be absent in order to avoid getting caught if they still have drugs in their system. So, employees may choose absenteeism over turnover after being exposed to drugs, which may lead to less employee turnover. Future study might want to take a further step to investigate this research question. Our study also found the moderating effect of employee drug testing on the link between absenteeism and having some problems associated with misuse of PPRs, suggesting that employees with PPRs-related problems are less likely to experience absenteeism if drug testing is in place. This finding may be comparable to prior studies that drug testing may benefit workplace performance in reducing absenteeism (Crouch et al., 1989). Employee perception of drug testing may play a likely role in increasing effectiveness of drug testing. If drug testing is negatively viewed by employees (e.g., perceive it as procedurally unfair), then as a result drug testing may negate employment performance increasing turnover and absenteeism (Konovsky and Cropanzano, 1991).

This analysis comes with limitations. Some individuals (active military personnel, persons living in institutional group quarters such as prisons and residential drug use treatment centers, homeless persons not living in a shelter on the survey date) were excluded from the survey and thus caution is necessary when generalizing our findings to those who did not participate in the study. Our study design is cross-sectional. We cannot determine the direction of causality between misuse of PPRs and other variables assessed. Misuse of PPRs on the job (or off the job) is an important research variable that may directly influence employees' work performance, but our study did not explore on-the-job prescription drug abuse or misuse. The survey did not collect this information. Future study might look into the extent to which on-the-job prescription drug misuse affects workplace performance. Our study excluded other types of prescription drugs including tranquilizers, stimulants, and sedatives. Thus, it is inappropriate to interpret our findings for other types of prescription drug misuse. Other relevant research questions that are unexplored in our study include: (1) where employees obtain prescription drugs; (2) how they misuse prescription drugs (e.g., abusing on the job or off the job); (3) how and the extent to which misuse of prescription drugs affects other workers or colleagues in the same organization and therefore negatively affects competitive advantages of the firm; and (4) different organizational and cultural factors that may be related to misuse of prescription drugs.

Notwithstanding the aforementioned study limitations, our findings are valuable in advancing the labor literature in the context of misuse of prescription drugs. In summary, our findings suggest the association between having problems associated with misuse of PPRs and absenteeism and turnover in the American workforce. This may pose a potential threat to many employers who are pressured to make their workplaces secure and industrious. As portrayed in our study, drug policy plays a moderating role for absenteeism and turnover in relation to having problems linked to misuse of PPRs. Employers and practitioners must recognize this prescription drug misuse problem among their employees and consider introducing and developing best practices of workplace prescription drug misuse prevention/treatment programs that should be available for every employee. There is a general view that employees' misuse of alcohol and illicit drugs lessens work performance and increase injury and illness, but no such observation currently exists on employees' prescription drug abuse or misuse.

Although there is a concern of privacy invasiveness (Tepper & Braun, 1995; White, 2003), workplace drug testing has been considered as a common practice to lessen addictive behaviors among employees. We found the moderating effects of drug testing on the association between absenteeism and having some problems linked to misuse of PPRs. This finding offers an important practice implication that employers may consider drug testing as another alternative in an effort to control prescription drug misuse in the workforce. Along with the Employee Assistance Programs (EAPs), drug testing has long been utilized in the U.S. employment setting since the U.S. government delivered two major regulations, the Drug-Free Workplace Act of 1988 and the Federal Workplace Drug Testing Programs, to combat alcohol and illicit drug misuse in the workforce. In 1997, about 49% of employees reported drug testing in their workplaces (US DHHS, 1999). The literature provides evidence that drug testing is effective and reduces alcohol and drug use problems in the workforce (Bush & Autry, 2002; Carpenter, 2007; Marini, 1991). In a recent national study, Carpenter (2007) found that workplace drug testing significantly reduced marijuana use. Another evidence of successful workplace drug prevention efforts comes from the Federal Drug-free

Workplace Program (FDWP) (Bush & Autry, 2002) that includes the following components: (1) written policy describing the employer's expectations about drug use and consequences of policy violations; (2) an employee assistance program (EAP) to provide confidential problem assessment, counseling, referral to treatment, and follow-up support after treatment; (3) supervisor training to orient supervisors to the employer's drug abuse policy, to define the supervisor's responsibility to refer employees when job performance deficits are noted, and to recognize and respond to employees with problems; (4) employee education to describe the signs and symptoms of drug abuse and its effects on performance and to explain the program; and (5) drug testing on a controlled and carefully monitored basis. Several sources, based on the best practice case analysis in business, report that the FDWP does work and is effective (Wickizer et al., 2004; ONDCP, 2010; US DOL, 2010). In particular, Wickizer et al. (2004), who examined workers' compensation claims data from the Washington State Department of Labor and Industries, observed that the drug-free workplace prevention intervention tool (similar to the FDWP concept) successfully reduced employees' injury rates. Unfortunately, however, most of the aforementioned studies and programs in relation to drug policy/testing did not consider the extent to which employees may suffer from misusing prescription drugs. More research effort is hence needed to advance our understanding about efficiency and effectiveness of drug policy/screening linked to misuse of prescription drugs in the workforce and in the workplace. Importantly, more organized efforts in practice including, among others, management commitment to recognizing and monitoring seriousness of prescription drug misuse or abuse, establishing a fair workplace drug policy/testing for misuse of prescription drugs in a timely fashion, openly discussing prevention and treatment alternatives, offering appropriate prevention/treatment benefits to drug using employees, should be planned and implemented in an effort to effectively respond to prescription drug problems among employees.

REFERENCES

Bass, A.R., Bharucha-Reid, R., Delaplane-Harris, K., Schork, M.A., Kaufmann, R., McCann, D., Foxman, B., Fraser, W., Cook, S. (1996). Employee drug use, demographic characteristics, work reactions, and absenteeism. Journal of Occupational Health Psychology, 1, 92-99.

Burton, W.N., Conti, D.J., Chen, C.Y., Schultz, A.B., Edington, DW. (1999). The role of health risk factors and disease on worker productivity. Journal of Occupational and Environment Medicine, 41(10), 863-77.

Bush, D.M., Autry, J.H. (2002). Substance abuse in the workplace: epidemiology, effects, and industry response. Occupational Medicine, 17, 13-25.

Carpenter, C. (2007). Workplace Drug Testing and Worker Drug Use. Health Services Research, 42, 795-810.

CDC (2010). Center for Disease Control and Prevention. Emergency department visits involiving nonmedical use of selected prescription drugs - United States, 2004-2008. Morbidity and Mortality Weekly Report, 28, 59(23), 705-9.

Compton, W.M., Volkow, N.D. (2006). Major increases in opioid analgesic abuse in the U.S.: concerns and strategies. Drug and Alcohol Dependence, 81, 1037.

Crouch, D. J., Webb, D. Q, Buller, P. E, & Rollins, D. E. (1989). A critical evaluation of the Utah Power and Light Company's substance abuse program: Absenteeism, accidents, and costs. In S. W Gust & J. M. Walsh (Eds.), Drugs in the workplace: Research and evaluation

data (Research

Monograph 91, pp. 169-193). Washington, DC: National Institute on Drug Abuse.

Fenton, M.C., Keyes, K.M., Martins, S.S., Hasin, D.S. (2010). The role of a prescription in anxiety medication use, abuse, and dependence. American Journal of Psychiatry, August 4 (Epub ahead of Print).

French, M.T., Zarkin, G.A., Hartwell, T.D., Bray, J.W. (1995). Prevalence and consequences of smoking, alcohol use, and illicit drug use at five worksites Prevalence and consequences of smoking, alcohol use, and illicit drug use at five worksites. Public Health Report, 110, 593-599.

Frone, M.R. (2006a). Prevalence and distribution of alcohol use and impairment in the workplace: a U.S. national survey. Journal of Studies on Alcohol and Drugs, 67, 147-56.

Frone, M.R. (2006b). Prevalence and distribution of illicit drug use in the workforce and in the workplace: findings and implications from a U.S. National Survey. Journal of Applied Psychology, 91, 856869.

Harwood, H., Fountain, D., Livermore, G. (1998). The economic costs of alcohol and drug abuse in the U.S. 1992. Rockville, MD: National Institute on Drug Abuse and National Institute on Alcohol Abuse and Alcoholism.

http://csat.samhsa.gov/IDBSE/employee/TheCostofSubstanceAbuse-wpb7.pdf. Konovsky, M.A. Cropanzano, R. (1991). Perceived fairness of employee drug testing as a predictor of employee attitudes and job performance. Journal of Applied Psychology. 76(5): 698-707.

Kroutil, L.A., Van Brunt, D.L., Herman-Stahl, M.A., Heller, D.C., Bray, R.M., Penne, M.A. (2006). Nonmedical use of prescription stimulants in the United States. Drug and Alcohol Dependence, 15, 135-43.

Lehman, W.E., Bennett, J.B. (2002). Job risk and employee substance use: the influence of personal background and work environment factors. American Journal of Drug and Alcohol Abuse, 28, 263-86.

Manchikanti, L. (2007). National drug control policy and prescription drug abuse: facts and fallacies. Pain Physician, 10, 399-424.

Mangione, T.W., Howland, J., Amick, B., Cote, J., Lee, M., Bell, N., Levine, S. (1999). Employee drinking practices and work performance. Journal of Studies on Alcohol and Drugs, 60, 261-270.

Marini, G.A. (1991). Comprehensive drug-abuse program can prove effective in the workplace. Occupational Health & Safety, 60, 58-9.

Matano, R.A., Wanat, S.F., Westrup, D., Koopman, C., Whitsell, S.D. (2002). Prevalence of alcohol and drug use in a highly educated workforce. Journal of Behavioral Health Services & Research, 29, 30-44.

Matzger, H., Weisner, C. (2007). Nonmedical use of prescription drugs among a longitudinal sample of dependent and problem drinkers. Drug and Alcohol Dependence, 86, 222-9.

McAuliffe ,W.E., Santangelo, S., Gingras, J, et al. (1987). Use and abuse of controlled substances by pharmacists and pharmacy students. American Journal of Hospital Pharmacy, 44, 311-317.

McCabe, S.E., Boyd, C.J., Teter, C.J. (2009). Subtypes of nonmedical prescription drug misuse. Drug and Alcohol Dependence, 102(1-3), 63-70.

Merlo, L.J., Gold, M.S. (2008). Prescription opioid abuse and dependence among physicians: hypotheses and treatment. Harvard Review of Psychiatry, 16(3), 181-94.

NIDA (2006). National Institute on Drug Abuse. NIDA Research Report Series: Prescription Drugs Abuse and Addiction. Retrieved June 20, 2010, from: http://www.drugabuse.gov/ResearchReports/Prescri ption/Prescription.html.

NIDA (2008). National Institute on Drug Abuse. Topics in Brief: Prescription Drug Abuse. March 2008. Retrieved April 25, 2010, from: http://www.drugabuse.gov/pdf/tib/prescription.pdf.

Normand, J., Salyards, S.D., Mahoney, J.J. (1990). An evaluation of pre-employment drug testing. Applied Psychology, 75, 629-39.

ONDCP (2010). Office of National Drug Control Policy. Drug-Free Workplace Programs: Successes and Future Challenges. Retrieved May 2, 2010, from: http://www.whitehousedrugpolicy.gov/prevent/workplace/success.html#go3.

Porter, E (2004). Rising Cost of Health Benefits Cited as Factor in Slump of Jobs. New York Times. Retrieved June 14, 2010, from http://www.nytimes.com/2004/08/19/business/19car e.html

Register, C.A, Williams, D.R. (1992). Labor market effects of marijuana and cocaine use among young men. Industrial and Labor Relations Review, 45, 435448.

Roberts, S., Fallon, L.F. Jr. (2001). Administrative issues related to addiction in the workplace. Occupational Medicine, 16, 509-15.

Ruetsch, C. (2010). Empirical view of opioid dependence. Journal of Managed Care Pharmacy, 16(1 Suppl B), S9-13.

SAMHSA (2007). Substance Abuse and Mental Health Services Administration. Worker Substance Use and Workplace Policies and Programs. Office of Applied Studies, Rockville, MD. Retrieved July 2, 2010, from

http://www.oas.samhsa.gov/work2k7/work.pdf. SAMHSA (2009). Substance Abuse and Mental Health

Services Administration. Center for Substance Abuse Treatment. Retrieved October 25, 2009, from:

SAMHSA (2010). Why You Should Care About Having A Drug-Free Workplace. Retrieved July 5, 2010, from:

http://www.workplace.samhsa.gov/wpworkit/pdfZwhy you should care about having a drug free workplace_fs.pdf

Serxner, S.A., Gold, D.B., Bultman, K.K. (2001). The impact of behavioral health risks on worker absenteeism. Journal of Occupational and Environmental Medicine, 43(4), 347-54.

Sethi, B.B., Manchanda, R. (1980). Drug abuse among resident doctors. Acta Psychiatrica Scandinavica, 62(5), 447-55.

Simoni-Wastila, L., Ritter, G., Strickler, G. (2004). Gender and other factors associated with the nonmedical use of abusable prescription drugs. Substance Use and Misuse, 39, 1-23.

Spicer, R.S., Miller, T.R., Smith, G.S. (2003). Worker substance use, workplace problems and the risk of occupational injury: a matched case-control study. Journal of Studies on Alcohol and Drugs, 64(4), 570-8.

Stata Corporation. 2007. Stata Statistical Software: Release 10. College Station, TX: StataCorp LP.

Tepper, B.J., Braun, C.K. (1995). Does the experience of organizational justice mitigate the invasion of privacy engendered by random drug testing? An empirical investigation. Basic Applied Social Psychiatry, 16, 211-225.

Trinkoff, A.M., Storr, C.L., Wall, M.P. (1999). Prescription-Type Drug Misuse and Workplace access Among Nurses. Journal of Addictive Diseases, 18(1), 9-17.

US DHHS (1999). Department of Health and Human Services. SAMHSA. Worker Drug Use and Workplace Policies and Programs: Results from the 1994 and 1997 national Household Survey on Drug Abuse. Rockville, MD: U.S. DHHS, 1999. Substance Abuse and Mental Health Services Administration (SAMHSA).

US DHHS (2010). Department of Health and Human Services (DHHS). Effects of Health Care Spending on the U.S. Economy. Retrieved Feb. 25, 2010, from:

http://aspe.hhs.gov/health/costgrowth/report.pdf. US DHHS (2008). Substance Abuse and Mental Health Services Administration. Center for Substance Abuse Treatment. Office of Applied Studies. Results from the 2007 national survey on drug use and health: national findings. NSDUH Series JH 34, DHHS publication no. SMA 08-4343. Retrieved March 24, 2010, from:

http://oas.samhsa.gov/nsduh/2k7nsduh/2k7Results.c fm#TOC.

US DOL (2010). Department of Labor. Working partners for an alcohol- and drug- free workplace: Drug-Free Workplace Promising Practices. Retrieved June 29, 2010, from:

http://www.dol.gov/asp/programs/drugs/workingpar tners/dfworkpl ace/promising_practices.asp.

Webb, G.R. Redman, S., Hennrikus, D.J., Kelman, G.R., Gibberd, R.W., Sanson-Fisher, R.W. (1994). The relationships between high-risk and problem drinking and the occurrence of work injuries and related absences. Journal of Studies on Alcohol and Drugs, 55, 434-46.

White, T. (2003). Drug testing at work: issues and perspectives. Substance Use and Misuse, 38, 1891902. Wickizer, T.M., Kopjar, B., Franklin, G., Joesch, J. (2004).

Do drug-free workplace programs prevent occupational injuries? Evidence from Washington State. Health Services Research, 39, 91-110.

DOOHEE LEE

Marshall University

MICHAEL W. ROSS

The University of Texas School of Public Health

Table 1
Descriptive Statistics of the Sample

Variable                     Observation   Mean    S.D.

Having problems related to      2,249      .04      .20
prescription drug misuse
(last year)
Employment status               2,249      1.21     .40
Drug policy                     2,249      1.26     .44
Organization size               2,249      2.54    2.93
Drug testing                    2,249      1.54   18.64
Absenteeism (last month)        2,249      .40      .49
Turnover (last month)           2,249      1.59    1.75
Gender                          2,249      1.40     .87
Age                             2,249      2.98     .49
Race/ethnicity                  2,249      2.02    2.09
Education                       2,249      2.61    1.06
Tobacco use (last year)         2,249      .69      .45
Alcohol use (last year)         2,249      .90      .29
Heroin use (last year)          2,249      .02      .14

Variable                     Minimum   Maximum

Having problems related to      0         1
prescription drug misuse
(last year)
Employment status               1         2
Drug policy                     1         2
Organization size               1         5
Drug testing                    1         2
Absenteeism (last month)        0        30
Turnover (last month)           1         4
Gender                          1         2
Age                             1         4
Race/ethnicity                  1         7
Education                       1         5
Tobacco use (last year)         0         1
Alcohol use (last year)         0         1
Heroin use (last year)          0         1

Table 2
Sample Characteristics by Employment Status (mean or %)

Variable                      Full-time     Part-time      p
                              (n=1,533)      (n=716)

Having problems related to    .04 (.19)     .05 (.27)    .383
prescription drug misuse
(Mean, SD)
Drug policy                      58            13        <.001
Organization size (Mean,     2.53 (1.24)   2.55 (6.48)   .908
SD)
Drug testing                     38            .05       <.001
Absenteeism (last month)      41 (1.75)    .32 (1.19)    .254
(Mean, SD)                                               .489
Turnover (last month)        1.55 (.79)    1.75 (1.08)
(Mean, SD)                                               .015
Gender
Male                             47            12
Female                           30            11
Age (Mean, SD)               3.11 (.82)    2.51 (1.21)   <.001
Race/ethnicity                                           .749
White                            58            17
Black                            5.3           1.6
Native Am/Ak                     .5            .2
Native Hi/Other Pac Isl          .1            .01
Asian                            1.6           .7
Mixed                            1.5           .4
Hispanic                         10            2.2
Education (Mean, SD)         2.57 (.96)    2.82 (1.5)    .004
Tobacco use (last year)          52            17        .091
Alcohol use (last year)          70            20        .137
Heroin use (last year)           .14          .006       .407

Table 3
A Hierarchical Logistic Regression Analysis of Related
Problems of PPRs Misuse

                                Model 1        Model 2

                               B (s.e.)        B (s.e.)

Employment status            .32 (.31)       .30 (.30)
Workplace drug policy        -.03 (.01) **   -.03 (.01) *
Workplace size               -.15 (.11)      -.13 (.11)
Workplace drug testing       .001 (.01)      -.001 (.01)

Absenteeism (last 30 days)                   .05 (.11)
Job turnover (last year)                     .14 (.17)

Absenteeism x Workplace
drug policy

Job turnover x Workplace
drug policy

Job turnover x Workplace
drug testing

Absenteeism x Workplace
drug testing

Gender
Age
Race/ethnicity
Education
Tobacco use (last year)
Alcohol use (last year)
Heroin use (last year)

N                            2,249           2,249
F                            2.78            1.86
Prob.> F                     .035            .105

                                Model 3          Model 4

                               B (s.e.)         B (s.e.)

Employment status            .42 (.31)        .48 (.33)
Workplace drug policy        .59 (.33)        .68 (.04)
Workplace size               -.24 (.13)       -.23 (.08)
Workplace drug testing       .02 (.02)        .02 (.22)

Absenteeism (last 30 days)   .76 (.22) ***    .74 (.05) ***
Job turnover (last year)     .97 (.48) *      1.07 (.21) *

Absenteeism x Workplace      .03 (.01) ***    .03 (.02) ***
drug policy

Job turnover x Workplace     -.63 (.33)       -.71 (.009) *
drug policy

Job turnover x Workplace     -.01 (.01)       -.01 (.01)
drug testing

Absenteeism x Workplace      -.40 (.11) ***   -.39 (.21) ***
drug testing

Gender                                        .12 (.04)
Age                                           .20 (.40)
Race/ethnicity                                .09 (.19)
Education                                     -.08 (.08)
Tobacco use (last year)                       .72 (.16)
Alcohol use (last year)                       -.40 (.355)
Heroin use (last year)                        1.51 (.79) *

N                            2,249            2,249
F                            2.27             2.64
Prob.> F                     .027             .005

* p< .05, ** p< .01, *** p< .001