The impact of smoking cessation on drug abuse treatment outcome

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1 Addictive Behaviors 28 (2003) Short Communication The impact of smoking cessation on drug abuse treatment outcome Stephenie C. Lemon, Peter D. Friedmann*, Michael D. Stein Division of General Internal Medicine, Department of Medicine, Rhode Island Hospital, Providence, RI, USA Department of Community Health, Brown University School of Medicine, Providence, RI, USA Accepted 19 March 2002 Abstract Although cigarette smoking is endemic among illicit drug users, drug abuse treatment programs rarely encourage smoking cessation and often discourage it. The purpose of this study was to determine whether smoking cessation after entering drug abuse treatment influenced drug use 12 months after drug abuse treatment. We analyzed 2316 cigarette smokers in the Drug Abuse Treatment Outcome Study (DATOS), a national, longitudinal study of drug abuse treatment. Heckman probit selection models assessed the association of self-reported smoking cessation while in drug abuse treatment on self-reported drug abstinence in the year after treatment completion, while simultaneously accounting for possible nonparticipation bias. Controlling for multiple factors, smoking cessation was associated with greater abstinence from drug use after completion of drug abuse treatment ( P=.04). Despite drug abuse treatment programs hesitance to encourage smokers to quit, smoking cessation does not negatively impact drug use outcomes. D 2002 Elsevier Science Ltd. All rights reserved. Keywords: Drug abuse treatment; Smoking cessation 1. Introduction Cigarette smoking is endemic among illicit drug users with prevalence estimates of 75% among patients in drug abuse treatment programs (Burling, 1988; Stark & Campbell, 1993; Kalman, 1998). Smoking cessation, however, has not been a traditional focus of drug abuse * Corresponding author. Division of General Internal Medicine, Department of Medicine, Rhode Island Hospital, 593 Eddy Street, Providence, RI 02903, USA. Tel.: ; fax: address: Pfriedmann@Lifespan.org (P.D. Friedmann) /02/$ see front matter D 2002 Elsevier Science Ltd. All rights reserved. doi: /s (02)

2 1324 S.C. Lemon et al. / Addictive Behaviors 28 (2003) treatment (Battjes, 1988) often because addiction treatment providers feel that only one addictive behavior change can be conquered at a time, with illicit drug abuse being the most immediate need and others secondary (Goldsmith & Knapp, 1993). While cessation of drug use is the primary goal, clients in treatment programs may also aim to alter other unhealthy behaviors, including smoking (Clemmey, Brooner, Chutuape, Kidorf, & Stitzer, 1997; Frosch, Shoptaw, Jarvik, Rawson, & Ling, 1998). Although initial attempts to quit smoking while in drug treatment may be unsuccessful, limited research suggests that contemporaneous attempts to quit do not compromise the primary goal (Burling, Marshall, & Seidner, 1991; Campbell, Wander, Stark, & Holbertt, 1995; Hurt et al., 1994; Joseph, Nichol, Willenbring, Korn, & Lysaght, 1990; Shoptaw, Jarvik, Ling, & Rawson, 1996). However, the effect of smoking cessation on drug use outcomes has yet to be studied among heterogeneous drug abuse treatment clients across modalities. The purpose of this study was to determine whether smoking cessation during drug abuse treatment influenced drug use in the year after treatment in a diverse, national sample. 2. Methods 2.1. Study design and sample The methodology of the Drug Abuse Treatment Outcome Study (DATOS), a nationally representative longitudinal study of persons entering drug abuse treatment between 1991 and 1993, is described in detail elsewhere (Flynn, Craddock, Hubbard, Anderson, & Etheridge, 1997). DATOS enrolled 10,010 patients, with 8755 completing baseline interviews, 4786 selected for follow-up 12 months after treatment, and 2966 who completed follow-up interviews. Of the 10,010 patients initially enrolled in DATOS, 7823 (78%) reported cigarette smoking at the time of treatment entry; follow-up interviews were available for 2316 (30%) Measures Drug use abstinence The outcome of interest is long-term abstinence from drug use. At the 12-month follow-up, clients reported use of illicit drugs, including heroin, opiates/narcotics, sedatives/tranquilizers, cocaine, amphetamines/stimulants, marijuana/hash, hallucinogens, or any other type of drug. Clients who indicated no drug use during the follow-up period were compared to those who reported any Smoking cessation At the intake interview, clients reported the average quantity of cigarettes smoked each day as: less than a half pack per day, about a half pack per day, about a pack per day, more than one but less than two packs per day, or two or more packs per day. The 12-month follow-up interview included the same question. Persons who reported that they did not smoke at the

3 follow-up interview were considered to have quit smoking. Smoking cessation was measured as a binary (yes/no) variable Program level covariates The four treatment modalities were: long-term residential (LTR), short-term inpatient (STI), outpatient methadone maintenance (OMM), and outpatient drug-free (ODF). Other program characteristics included: reported client capacity, a marker for program size, the proportion of patients that had no legal source of income, that received public assistance, and that had public insurance Individual level covariates Sociodemographic characteristics included: gender, age at admission, race, and educational level. Health insurance status, criminal justice involvement, and employment status were also assessed. Substance use related variables included: severity of addiction at baseline, measured using a variable modeled after the Addiction Severity Index (ASI) drug use composite score (Friedmann et al., 2001; McLellan et al., 1992), which is weighted summary score ranging in severity from 0 (no problem) to 1(most severe), primary type of drug used, method of illicit drug administration, the number of prior treatment episodes, and problem alcohol use (defined as typically consuming five or more alcoholic beverages at least one time per week in the year prior to admission). Treatment retention, a binary variable, was defined as the minimal time threshold necessary to have therapeutic benefit, according to treatment modality: 90 days for LTR and ODF programs, 28 days for OMM programs, and 365 days for OMM programs (Condelli & Hubbard, 1994; Hubbard et al., 1982; Simpson, 1979). The Treatment Readiness scale (range: 1 3) measured motivation (Simpson & Joe, 1993). Psychiatric and medical severity measures were weighted summary scores ranging in severity from 0 (no problem) to 1(most severe) (McLellan et al., 1992) Statistical analyses S.C. Lemon et al. / Addictive Behaviors 28 (2003) Because DATOS follow-up sample had a low completion rate, selection bias might result if differences between smokers who did (n = 2316) and did not participate (n = 5507) in follow-up were correlated with abstinence from drugs. To address this concern, we used a two-part estimation procedure to adjust for bias that might result from differential follow-up (Heckman, 1979; Van de Van & Van Pragg, 1981). We generated a two-stage model that first performed probit regression in the entire sample of clients to estimate the likelihood of having completed a 12-month follow-up interview. Independent variables previously described, as well as a variable indicating the number of DATOS interviews completed (i.e., intake 1, intake 2, 1 month in treatment, and 3 months in treatment), were included. From this procedure, a selection bias parameter (l) that summarized information about the factors that influenced completion of follow-up (yes/no) and, consequently, observation of the dependent variable in a second-stage probit model were generated (Breen, 1996). l was included in the second-stage model, a main effects model to determine the factors associated with abstinence

4 1326 S.C. Lemon et al. / Addictive Behaviors 28 (2003) from drug use. Random effects terms, accounted for clustering of responses of individuals within programs, and robust standard errors were estimated. 3. Results 3.1. Study characteristics The distribution of program modality was 24% LTR, 15% STI, 27% OMM, and 34% ODF. Range of program capacity was clients (median = 119). Mean ( ± S.D.) proportion of clients with no legal income was 0.34 ± 0.14, of clients receiving public assistance was 0.23 ± 0.13, and of clients with public insurance was 0.37 ± Cigarette consumption before admission did not differ by whether or not the patient participated in the follow-up interview (Table 1). Table 1 Comparison of baseline characteristics of smokers in DATOS, stratified by whether 12-month follow-up interview was completed Follow-up sample (n = 2316), % nfollow-up (n = 5507), % Female Age mean (S.D.) 33.5 (7.6) 31.9 (7.2) Race White, non-hispanic African American Other race High school graduate Health insurance Private Public ne Any criminal justice involvement Any full-time work Severity of drug use mean (S.D.) 0.16 (0.13) 0.15 (0.12) Primary drug type Cocaine Heroin Other of prior drug treatments mean (S.D.) 2.2 (3.9) 1.9 (4.4) Heavy alcohol use Treatment retention Reported cigarette consumption < 1/2 pack/day /2 pack/day pack/day packs/day or more packs/day

5 3.2. Smoking cessation rates S.C. Lemon et al. / Addictive Behaviors 28 (2003) Approximately 35% of the total sample reported that they did not smoke at the follow-up interview. A linear relationship was observed between quantity of cigarettes smoked at baseline and smoking cessation ( P <.001). Smoking cessation was greatest among those who Table 2 First-stage of probit Heckman selection model, predicting participation in the 12-month follow-up interview (N = 7823) b (S.E.) P value Treatment modality LTR.26 (.20).20 STI.03 (.24).90 OMM.40 (.23).09 ODF Gender Male Female.09 (.05).08 Age units of 10 years.09 (.03).002 Race White, non-hispanic African American.03 (.08).70 Other race.28 (.10).005 Educational level < High school High school.05 (.04).29 Health insurance Private Public.07 (.12).58 ne.13 (.16).43 Criminal justice involvement Yes.09 (.05).08 Full-time employment Yes.004 (.04).92 Primary drug type Cocaine.09 (.08).24 Heroin.05 (.07).44 Other. of prior drug treatments.004 (.004).34 Problem alcohol use Yes.02 (.05).61 Treatment retention Yes.46 (.08) <.001. of completed interviews.35 (.04) <.001

6 1328 S.C. Lemon et al. / Addictive Behaviors 28 (2003) Table 3 Probit Heckman model, controlling for selection effects, predicting illicit drug use abstinence at 12-month followup (N = 2316) b (S.E.) P value Smoking cessation Yes.11 (.06).04 Treatment modality LTR.14 (.14).31 STI.17 (.11).11 OMM.66 (.13) <.001 ODF Gender Male Female.16 (.06).007 Age units of 10 years.10 (.005).03 Race White, non-hispanic African American.07 (.07).32 Other race.14 (.09).16 Educational level < High school High school.03 (.06).56 Health insurance Private Public.27 (.11).02 ne.16 (.09).10 Criminal justice involvement Yes.02 (.06).74 Full-time employment Yes.004 (.04).92 Drug severity composite.55 (.25).03 Primary drug type Cocaine.14 (.08).09 Heroin.07 (.10).52 Other Method of administration Smoking and injection.38 (.15).01 Smoking only.05 (.07).48 Injection only.22 (.08).01 Other method. of prior drug treatments.01 (.008).24 Heavy alcohol use Yes.12 (.07).08 Treatment retention Yes.19 (.12).12 (continued on next page)

7 S.C. Lemon et al. / Addictive Behaviors 28 (2003) Table 3 (continued) b (S.E.) P value Treatment readiness.16 (.10).12 Psychiatric severity composite.59 (.23).01 Medical severity composite.18 (.12).13 l.07 (.04).10 smoked less than a half-a-pack (50%) and decreased to less than 8% among those who reported smoking at least two packs per day at baseline Two-stage model Older age, treatment retention to threshold and number of completed interviews were the strongest correlates of participation in the 12-month follow-up interview (Table 2). In the second-stage model, greater likelihood of abstinence from drug use was observed among those who reportedly quit smoking, compared to those who did not ( P=.04) (Table 3). A moderate association for l ( P =.10) suggests the possibility of selection effects. Although small cell sizes restricted power, selection models stratified by the quantity of cigarettes smoked at baseline suggested that the effect of smoking cessation on abstinence from illicit drug use was greatest among those who smoked the most at baseline (approximately 1.5 packs/day, b=.30; approximately two or more packs per day, b=.44). 4. Discussion These results suggest that smoking cessation does not worsen drug use 12 months after completion of drug abuse treatment. Indeed, smoking cessation may be modestly associated with improved abstinence rates, a finding consistent with results from smaller studies (Burling et al., 1991; Campbell et al., 1995; Hurt et al., 1994; Joseph et al., 1990; Shoptaw et al., 1996). Our results further demonstrate that these associations hold true across a broad range of drug abuse program types and client populations. DATOS limitations are well-described (Flynn et al., 1997). The lack of a probability sample representative of American drug treatment programs limits generalizability. DATOS may, however, allow inference about clients who attend large urban programs. Although the two-stage model corrected for selection effects (Heckman, 1979), any violation of the functional form assumption used in identification may render the correction less than robust. We also acknowledge the limitation of self-report data and cannot exclude the possibility of social desirability bias among persons who indicated that they quit smoking and stopped using drugs. The high rate of smoking cessation observed in this study is likely the result of the ascertainment of smoking behavior as a point prevalence estimate. For example, a person who quit smoking on the day of the follow-up interview may have reported him/herself as a

8 1330 S.C. Lemon et al. / Addictive Behaviors 28 (2003) nonsmoker, then resumed smoking thereafter. DATOS did not include biological confirmation of self-reported cessation, but the limited stigma associated with cigarette smoking in addiction treatment programs makes biased report of less concern. While this analysis could not assess whether individual patients received smoking cessation services in drug abuse treatment, such services were rarely available in drug abuse treatment programs in the early 1990s. While on average smoking cessation was not detrimental to abstinence from drug use, it may be that the effects of smoking cessation differ from person to person. As always, treatment recommendations should be individualized. Despite these limitations, these findings suggest that concurrent smoking cessation during treatment for illicit drug abuse causes no harm and possibly has a beneficial effect. Our increasing understanding of the common neurochemical mechanisms of addiction, including nicotine addiction, raise questions about the clinical myth that nicotine dependence should be treated only after stabilization of the primary drug dependence. The addition of smoking cessation programs to core drug abuse treatment services would provide patients with much needed assistance in quitting smoking (Richter & Ahluwalia, 2000). Such services could increase drug abuse treatment patients awareness and education with respect to the harms of smoking. Future work should determine the most effective techniques for smoking cessation in this setting and develop programs to meet individual needs. s Battjes, R. J. (1988). Smoking as an issue in alcohol and drug abuse treatment. Addictive Behaviors, 13, Breen, R. (1996). Regression models. Censored, sample selected or truncated data. Sage Publications, Quantitative Applications in the Social Sciences, Lewis-Beck MS. Burling, T. (1988). Tobacco smoking: A comparison between alcohol and drug abuse inpatients. Addictive Behaviors, 13, Burling, T. A., Marshall, G. D., & Seidner, A. L. (1991). Smoking cessation for substance abuse inpatients. Journal of Substance Abuse, 3, Campbell, B. K., Wander, N., Stark, M. J., & Holbertt, T. (1995). Treating cigarette smoking in drug-abusing clients. Journal of Substance Abuse Treatment, 12, Clemmey, P., Brooner, R., Chutuape, M. A., Kidorf, M., & Stitzer, M. (1997). Smoking habits and attitudes in a methadone maintenance treatment population. Drug and Alcohol Dependence, 44, Condelli, W. S., & Hubbard, R. L. (1994). Relationship between time spent in treatment and client outcomes from therapeutic communities. Journal of Substance Abuse Treatment, 11, Flynn, P. M., Craddock, G. S., Hubbard, R. L., Anderson, J., & Etheridge, R. M. (1997). Methodological overview and research design for the Drug Abuse Treatment Outcomes Study (DATOS). Psychology of Addictive Behaviors, 11, Friedmann, P. D., Lemon, S., Stein, M. D., Etheridge, R. M., & D Aunno, T. A. (2001). Linkage to medical services in the Drug Abuse Treatment Outcome Study (DATOS). Medical Care, 39, Frosch, D. L., Shoptaw, S., Jarvik, M. E., Rawson, R. A., & Ling, W. (1998). Interest in smoking cessation among methadone maintained outpatients. Journal of Addiction Disorders, 17, Goldsmith, R. J., & Knapp, J. (1993). Towards a broader view of recovery. Journal of Substance Abuse Treatment, 10, Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47, Hubbard, R. L., Marsen, M. E., Rachal, J. V., Harwood, H. J., Cavanaugh, E. R., & Ginzburg, H. M. (1982). Drug abuse treatment: a national study of effectiveness. Chapel Hill: University of rth Carolina.

9 S.C. Lemon et al. / Addictive Behaviors 28 (2003) Hurt, R. D., Eberman, K. M., Croghan, I. T., Offord, K. P., Davis Jr., L. J., Morse, R. M., Palmen, M. A., & Bruce, B. K. (1994). Nicotine dependence treatment during inpatient treatment for other addictions: A prospective intervention trial. Alcoholism: Clinical and Experimental Research, 18, Joseph, A. M., Nichol, K. L., Willenbring, M. L., Korn, J. E., & Lysaght, L. S. (1990). Beneficial effects of treatment of nicotine dependence during an inpatient substance abuse treatment program. Journal of the American Medical Association, 263, Kalman, D. (1998). Smoking cessation treatment for substance misusers in early recovery: A review of the literature and recommendations for practice. Substance Use and Misuse, 33, McLellan, A. T., Kushner, H., Metzger, D., Peters, R., Smith, I., Grissom, G., Pettinati, H., & Argeriou, M. (1992). The fifth edition of the Addiction Severity Index. Journal of Substance Abuse Treatment, 9, Richter, K. P., & Ahluwalia, J. S. (2000). A case for addressing cigarette use in methadone and other opioid treatment programs. Journal of Addiction Disorders, 19, Shoptaw, S., Jarvik, M. E., Ling, W., & Rawson, R. A. (1996). Contingency management for tobacco smoking in drug-abusing clients. Addictive Behaviors, 21, Simpson, D. D. (1979). The relation of time spent in drug abuse treatment to posttreatment outcomes. American Journal of Psychiatry, 136, Simpson, D. D., & Joe, G. W. (1993). Motivation as a predictor of early dropout from drug abuse treatment. Psychotherapy, 30, Stark, M. J., & Campbell, B. K. (1993). Drug use and cigarette smoking in applicants for drug abuse treatment. Journal of Substance Abuse, 5, Van de Van, W. P. M. M., & Van Pragg, B. M. S. (1981). The demand for deductibles in private health insurance: A probit model with sample selection. Journal of Econometrics, 17,

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