Management of human resources associated with misuse of prescription drugs: analysis of a national survey.
Nonmedical use of prescription drugs is increasingly prevalent in
the United States, but limited research is available on prescription
drugs misuse in the workforce. We investigated whether absenteeism and
turnover are associated with having problems linked to prescription drug
misuse among employees. We also further explored the moderating effects
of employee drug policy and testing on the relation between having
problems linked to misuse of prescription pain relievers (PPRs) and
absenteeism and turnover. This is a crosssectional study (n=2,249) using
the 2007 U.S. national survey data ("National Survey on Drug Use
and Health"). The multivariate logistic analysis results
illustrate, after controlling confounding factors (gender, age, tobacco
use, and heroin use), absenteeism and turnover linked to having problems
of PPRs misuse. Our findings suggest the moderating effects of employee
drug policy on the association between absenteeism and turnover and
having problems linked to misuse of PPRs. Also, drug testing was found
to moderate the link between having negative outcomes of misuse of PPRs
and absenteeism. Having problems associated with misuse of PPRs is
linked to absenteeism and turnover. A drug policy program including drug
testing may play a significant role in reducing absenteeism and turnover
in relation to having problems linked to misuse of PPRs.
Key Words: employee, nonmedical use of prescription drugs, absenteeism, turnover, drug policy and testing
Human resource management (Health aspects)
Worker absenteeism (Health aspects)
Employee turnover (Health aspects)
Ross, Michael W.
|Publication:||Name: Journal of Health and Human Services Administration Publisher: Southern Public Administration Education Foundation, Inc. Audience: Academic Format: Magazine/Journal Subject: Government; Health Copyright: COPYRIGHT 2011 Southern Public Administration Education Foundation, Inc. ISSN: 1079-3739|
|Issue:||Date: Fall, 2011 Source Volume: 34 Source Issue: 2|
|Topic:||Event Code: 310 Science & research Canadian Subject Form: Absenteeism (Labour); Labour turnover|
|Product:||Product Code: 9918000 Business Personnel Management; 9918630 Absenteeism; 9918660 Unauthorized Leave|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
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.
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]
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:
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.
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.
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.
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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
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