Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Drug Alcohol Depend. Author manuscript; available in PMC 2012 April 1.
Published in final edited form as:
PMCID: PMC3062722

Measuring smoking knowledge, attitudes and services (S-KAS) among clients in addiction treatment



Addiction treatment programs are increasingly working to address prevalent and comorbid tobacco dependence in their service populations. However at present there are few published measurement tools, with known psychometric properties, that can be used to assess client-level constructs related to tobacco dependence in addiction treatment settings. Following on previous work that developed a staff-level survey instrument, this report describes the development and measurement characteristics of the Smoking Knowledge, Attitudes and Services (S-KAS) for use with clients in addiction treatment settings.


250 clients enrolled in residential drug abuse treatment programs were surveyed. Summary statistics were used to characterize both the participants and their responses, and exploratory factor analysis (EFA) was used to examine the underlying factor structure.


Examination of the rotated factor pattern indicated that the latent structure was formed by one Knowledge factor, one Attitude factor, and two “service” factors reflecting Program Services and Clinician Services related to tobacco dependence. Standardized Cronbach’s alpha coefficients for the four scales were, respectively, .57, .75, .82 and .82.


The proposed scales have reasonably good psychometric characteristics, although the knowledge scale leaves room for improvement, and will allow researchers to quantify client knowledge, attitudes and services regarding tobacco dependence treatment. Researchers, program administrators, and clinicians may find the S-KAS useful in changing organizational culture and clinical practices related to tobacco addiction, help in program evaluation studies, and in tracking and improving client motivation.

Keywords: Drug abuse treatment, addiction, smoking, tobacco dependence, clients, patients

1.0 Introduction

Currently over one billion persons smoke worldwide, and over 5 million deaths annually are attributed to tobacco (World Health Organization, 2010). In the United States (U.S.) tobacco control efforts have reduced smoking prevalence from 40% in 1964 to 20.6% currently (Centers for Disease Control and Prevention, 2009; Department of Health Education and Welfare, 1964). However, smoking remains prevalent among persons with alcohol and drug use disorders, and epidemiologic studies report smoking rates for these groups at 34% and 52%, respectively (Grant et al., 2004). Among persons in addiction treatment smoking prevalence ranges from 49–98% (Schroeder, 2009). This is true in the U.S., and in many countries where smoking rates have been reported for addiction treatment samples (Amit et al., 2003; Ellingstad et al., 1999; Gossop et al., 2007; Lawal et al., 1998; Nakamura et al., 2003). As one approach to elevated smoking rates, researchers in a number of countries have explored tobacco-related knowledge, attitudes and practices among clinicians (Ceraso et al., 2009; Walsh et al., 2005; Gokirmak et al., 2010).

In the context of high smoking rates in addiction treatment, three studies have concluded that tobacco dependence services are not provided in most U.S. addiction treatment programs (Friedmann et al., 2008; Fuller et al., 2007; Richter et al., 2004). Among program staff, tobacco-related knowledge and attitudes are barriers to providing tobacco services (Guydish et al. 2007). For example, smoking may be viewed by counselors as a low priority when compared to more immediate harms of other drug use, and staff may believe their patients are not interested in quitting (Hahn et al., 1999; Sees and Clark, 1993). Client attitudes may also affect tobacco services. Clients in one program were concerned that quitting smoking would create nicotine withdrawal symptoms and remove smoking as a coping strategy (Asher et al., 2003). Among clients entering a smoke-free rehabilitation facility, over half thought that smoking should not be addressed along with other addictions (Patten et al., 1999). Efforts to provide tobacco dependence interventions in addiction treatment must address staff and client attitudes about tobacco, while increasing access to tobacco-related services.

Several initiatives address tobacco dependence in addiction treatment. Veteran Affairs Medical Centers initiated practice guidelines for smoking cessation among all patients, including those in specialty addiction clinics (Sherman, 2008). New Jersey licensure standards encouraged all residential treatment programs to adopt smoke-free grounds (Williams et al., 2005), and New York recently required treatment programs to have smoke-free grounds and treat tobacco dependence for all clients on request (Tobacco-Free Services, 2008). Indiana initiated partnerships to support tobacco-free addiction treatment (Indiana Tobacco Prevention and Cessation, 2010), and other states have announced plans to adopt smoke-free grounds in their treatment systems (Oregon Department of Human Services, 2010; Utah Division of Substance Abuse and Mental Health, n.d.).

As such strategies are implemented, treatment programs may measure how those strategies affect client knowledge or attitudes related to tobacco, or whether such policies increase tobacco services. A number of studies have used client surveys for this purpose (Bernstein and Stoduto, 1999; Perine and Schare, 1999; Trudeau et al., 1995), with findings reported for individual survey items. For example, Joseph et al. (2004) used a client survey as one in a number of policy outcome measures, and reported on whether patients were counseled to quit smoking at their last clinic visit. To evaluate the New Jersey policy, Williams et al. (2005) reported on whether clients thought the policy was helpful.

Multi-item scales offer an alternative to individual items, giving comparability across studies, more stable estimates of underlying constructs, and known psychometric properties (Allen and Yen, 1979). The Barriers to Quitting Smoking in Substance Abuse Treatment (BQS-SAT) assesses whether respondents think that quitting smoking would lead to nicotine withdrawal symptoms or urges to use other drugs (Asher et al., 2003). The Nicotine and Other Substance Interaction Expectancies Questionnaire (NOSIE; Rohsenow et al., 2005) measures expectancies concerning the effects of smoking on addiction recovery. These measures are tailored to addiction treatment samples, but do not measure knowledge of the hazards of smoking, or tobacco services clients may receive while in treatment.

Delucchi et al. (2009) reported on a staff survey with scales assessing smoking-related knowledge, attitudes and practices (S-KAP). This paper reports on a similar survey of smoking-related knowledge, attitudes and services (S-KAS) among clients. The S-KAS may be useful to addiction treatment programs, or county, state or regional treatment systems, who want to assess whether their tobacco strategies are associated with changes in client knowledge or attitudes, or with tobacco services clients receive. The S-KAS is not a measure of client smoking cessation outcomes. It is designed to measure conditions that support clients in quitting smoking: knowledge of the hazards of smoking, attitudes about treating smoking in the program where they are enrolled, and tobacco-related services they receive.

2.0 Methods

Data were collected in the course of another NIDA funded study testing an organizational intervention to improve tobacco dependence treatment in residential programs (Ziedonis et al., 2007). Cross-sectional client samples were interviewed pre-intervention. Data collection began in all sites at the same time but the intervention was implemented sequentially, enabling a second pre-intervention sample in two sites, giving five samples (n=50 per sample) and 250 interviews.

Clients in residential treatment for at least 14 days were eligible. This ensured some time in program during which clients may have received tobacco-related services. Smokers and non-smokers were eligible. While smokers are more likely to receive tobacco dependence services, the knowledge and attitudes of both smokers and non-smokers can reflect the organizational climate of the program, and may change in response to policy interventions, staff training, or client groups concerning tobacco.

The survey contained 40 items. Knowledge items were selected from the CDC Adult Tobacco Survey (Centers for Disease Control and Prevention, n.d.) and the California Adult Tobacco Survey (California Department of Health Services, 2004). Items concerning attitudes toward treating tobacco dependence and tobacco-related services that clients received were drawn from prior research (Borrelli et al., 2001; Glynn and Manley, 1989; Goldstein et al., 1998; Joseph et al., 1990; Velasquez et al., 2000).

In each agency a research liaison posted sign up sheets and screened those signing for inclusion criteria. Most clients were interested because participation involved a $20.00 incentive. As the sign up procedure did not yield the desired sample size (n=50), the program liaison invited any eligibles who had not expressed interest to participate. Finally, the liaison monitored new admissions and, when they met time-in-treatment criteria, recruited them.

For interested clients, the liaison arranged a phone appointment with the research interviewer. At the time of the appointment, the interviewer called the program liaison, who indicated the client’s clinic identification number and left the room. The interviewer completed verbal informed consent and conducted the interview. No participants declined at this stage. After the interview the client brought the liaison back to the phone, the interviewer verified completion, and the liaison provided the incentive to the client. As the census of each program was lower than the recruitment target, these procedures continued in each clinic for approximately 10 weeks, until 50 clients had been interviewed. Study procedures were approved by the Institutional Review Board of the University of California, San Francisco.

3.0 Results

Four eligible clients declined participation. An unknown number were lost because they left the program after becoming eligible but before the phone interview. Mean age was 35.3 (SD= 10.0), 55.5% were women, and frequently reported drugs were opioids (29.6%), alcohol (29.2%), and crack/cocaine (24.4%). Most (70.8%) were White, 19.6% were African American, and 85.2% smoked.

Exploratory factor analysis with Varimax rotation was used to examine the underlying factor structure. Items were dropped if endorsed by fewer than 5% of respondents (1 item) or uncorrelated with any scale totals (4 items), and 7 tobacco medication items were collapsed to one. Response codes for 28 remaining items included dichotomous and Likert formats. To achieve a common format, Likert items were coded from 1 (strongly disagree) to 5 (strongly agree) and dichotomous items were coded 1 (no) and 5 (yes).

There were four eigenvalues greater than 1.0 with the last one at 1.18, supporting a four factor solution (Table 1). One factor concerned knowledge about the effects of smoking (Factor 4) and one concerned attitudes toward treating smoking in the current program (Factor 3). Two scales concerned tobacco services that clients received from their clinician (Clinician Services, Factor 1) or services available in the program (Program Services, Factor 2). Service factors remained distinct when forcing a 3 factor solution, suggesting separate constructs. One item (“I am aware of community resources to help people quit smoking”) loaded on Factor 1 (Program Service) and Factor 4 (Knowledge). This item was placed in the Knowledge scale, where it increased the number of items. Two items loaded primarily on Factor 2 (Clinician Service) and also loaded on other factors (see Table 1), and were retained in the Clinician Service scale.

Table 1
Means, Standard Deviations and Rotated Factor Pattern for 29 Client Survey Items.

Alpha coefficients for the Knowledge, Attitude, Clinician Service and Program Service scales were, respectively, 0.57, 0.75,0.82 and 0.82. Means ranged from 2.23 (SD=0.89) for Clinician Service to 3.89 (SD=0.60) for Knowledge. Inter-scale correlations ranged from 0.15 to 0.37, indicating independence, except for the two service scales which correlated 0.59. All inter-scale correlations were statistically significant. Items are shown in Table 2.

Table 2
Survey Items and Response Codes in Knowledge, Attitudes, Clinician Service and Program Service Scales.

As a preliminary assessment of predictive validity, S-KAS scale scores were correlated with number of times quit smoking in the past year, whether any medications (yes/no) were used in those quit attempts, Fagerström test for nicotine dependence (FTND) scores (Heatherton et al., 1991), and smoking status (yes/no). Number of quits was associated with the Attitude scale (r = 0.18, p< .01). Prior use of tobacco medications was associated with Knowledge (r= 0.21, p < .01), Program Service (r= .55, p< .001), and Clinician Service (r= 0.27, p < .001). FTND scores were not correlated with S-KAS scales. For all participants, including both smokers and non-smokers, current smoking was negatively associated with Attitudes (r= −0.22, p < .001).

4.0 Discussion

For nearly 30 years, papers have observed the high rate of smoking among persons with other addictions (e.g., Bobo and Gilchrist, 1983; Friend and Pagano, 2005; Kalman, 1998; Little, 2000) and the need for addiction treatment to address smoking (Hoffman and Slade, 1993; Kozlowski et al., 1986; Schroeder and Morris, 2009). As addiction settings increasingly address tobacco (Baca and Yahne, 2009), there is a need for measurement tools to assess whether policy, training or other initiatives affect client tobacco knowledge, attitudes and services. The S-KAS scales have reasonably good psychometric properties, and also offer a client analogue to the staff measure (Delucchi et al., 2009). Staff and client surveys could be used independently, or used in tandem to reflect similar constructs among staff and clients in the same program. Using this approach Chisolm et al. (2010) found that staff underestimated client interest in quitting smoking.

Limitations to this study include the process of scale development and sample size. The S-KAS was not derived using scale development procedures, which select items with the goal of forming scales and then do so through iterative analysis and modification. Instead, the S-KAS was developed using items found in similar research, and factor analysis was used to discover an underlying structure. Because of this approach, response codes varied across items, and responses were recoded for analysis. The sample size is modest for factor analysis, which benefits from large and diverse samples. Nevertheless, the items coalesced into scales with face validity and internal consistency, and offer a starting point for further scale development and a measure for evaluating tobacco-related policy and training interventions. The psychometric properties of the scales may be improved by refining responses to a common format, and by the addition of more discriminative items designed to increase or improve reliability and validity.

Approximately 4 million persons in the U.S. received addiction treatment in 2008 (Substance Abuse and Mental Health Services Administration, 2009), and most of those were smokers (Schroeder and Morris, 2009). As addiction treatment systems work to address tobacco dependence, they will need improved measurement tools to evaluate their efforts. S-KAS scales offer robust and stable measures of underlying constructs, compared to single item measures, and may be useful to administrators, clinicians and researchers interested in improving tobacco dependence treatment in addiction programs.


Role of funding source

Funding for this work was supported by the National Institute on Drug Abuse (R01 DA020705), by the California–Arizona research node of the NIDA Clinical Trials Network (U10 DA015815), and by the NIDA San Francisco Treatment Research Center (P50 DA009253); the NIDA had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.


Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.


  • Allen MJ, Yen WM. Introduction to Measurement Theory. Belmont: Wadsworth, Inc.; 1979.
  • Amit Z, Weiss S, Smith BR, Markevitch S. The affinity for sweet substances and cigarette smoking in chronic alcoholism. Isr. J. Psychiatry Relat. Sci. 2003;40:96–102. [PubMed]
  • Asher MK, Martin RA, Rosenhow DJ, MacKinnon SV, Traficante R, Monti Monti. Perceived barriers to quitting smoking among alcohol dependent patients in treatment. J. Subst. Abuse Treat. 2003;24:169–174. [PubMed]
  • Baca CT, Yahne CE. Smoking cessation during substance abuse treatment: what you need to know. J. Subst. Abuse Treat. 2009;36:205–219. [PubMed]
  • Bernstein SM, Stoduto G. Adding a choice-based program for tobacco smoking to an abstinence-based addiction treatment program. J. Subst. Abuse Treat. 1999;17:167–173. [PubMed]
  • Bobo JK, Gilchrist LD. Urging the alcoholic client to quit smoking cigarettes. Addict. Behav. 1983;8:297–305. [PubMed]
  • Borrelli B, Hecht JP, Papandonatos GD, Emmons KM, Tatewosian LR, Abrams DB. Smoking-cessation counseling in the home: attitudes, beliefs, and behaviors of home healthcare nurses. Am. J. Prev. Med. 2001;21:272–277. [PubMed]
  • California Department of Health Services. California Adult Tobacco Survey. 2005 Questionnaire. Sacramento: Survey Research Group, Author; 2004.
  • Centers for Disease Control and Prevention, n.d. Question Inventory on Tobacco. Adult Tobacco Survey (ATS) [accessed on 05/05/2008].
  • Centers for Disease Control and Prevention. Cigarette smoking among adults and trends in smoking cessation - United States, 2008. MMWR Morb. Mortal. Wkly. Rep. 2009. pp. 1227–1232. [PubMed]
  • Ceraso M, McElroy JA, Kuang X, Vila PM, Du X, Lu L, Ren H, Qian N, Jorenby DE, Fiore MC. Smoking, barriers to quitting, and smoking-related knowledge, attitudes, and patient practices among male physicians in China. Prev. Chronic Dis. 2009;6:A06. [PMC free article] [PubMed]
  • Chisolm MS, Brigham EP, Lookatch SJ, Tuten M, Strain EC, Jones HE. Cigarette smoking knowledge, attitudes and practices of patients and staff at a perinatal substance abuse treatment center. J. Subst. Abuse Treat. 2010;39:298–305. [PMC free article] [PubMed]
  • Delucchi K, Tajima B, Guydish J. Development of the Smoking Knowledge, Attitudes and Practices (S-KAP) instrument. J. Drug Issues. 2009;39:347–364. [PMC free article] [PubMed]
  • Department of Health Education and Welfare. Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service. Washington, DC: US Government Printing Office; 1964.
  • Ellingstad TP, Sobell LC, Sobell MB, Cleland PA, Agrawal S. Alcohol abusers who want to quit smoking: implications for clinical treatment. Drug Alcohol Depend. 1999;54:259–265. [PubMed]
  • Friedmann PD, Jiang L, Richter KP. Cigarette smoking cessation services in outpatient substance abuse treatment programs in the United States. J. Subst. Abuse Treat. 2008;34:165–172. [PMC free article] [PubMed]
  • Friend KB, Pagano ME. Changes in cigarette consumption and drinking outcomes: findings from Project MATCH. J. Subst. Abuse Treat. 2005;29:221–229. [PMC free article] [PubMed]
  • Fuller BE, Guydish J, Tsoh J, Reid MS, Resnick M, Zammarelli L, Ziedonis DM, Sears C, McCarty D. Attitudes toward the integration of smoking cessation treatment into drug abuse clinics. J. Subst. Abuse Treat. 2007;32:53–60. [PMC free article] [PubMed]
  • Glynn T, Manley M. How to Help Your Patients Quit Smoking: A National Cancer Institute Manual for Physicians. Bethesda: Smoking, Tobacco and Cancer Program, Division of Cancer Prevention and Control, National Cancer Institute; 1989.
  • Gokirmak M, Ozturk O, Bircan A, Akkaya A. The attitude toward tobacco dependence and barriers to discussing smoking cessation: a survey among Turkish general practitioners. Int. J. Public Health. 2010;55:177–183. [PubMed]
  • Goldsmith RJ, Knapp J. Towards a broader view of recovery. J. Subst. Abuse Treat. 1993;10:107–111. [PubMed]
  • Goldstein MG, DePue JD, Monroe AD. A population-based survey of physician smoking cessation counseling practices. Prev. Med. 1998;27:720–729. [PubMed]
  • Gossop M, Neto D, Radovanovic M, Batra A, Toteva S, Musalek M, Skutle A, Goos C. Physical health problems among patients seeking treatment for alcohol use disorders: a study in six European cities. Addict. Biol. 2007;12:192–196. [PubMed]
  • Grant BF, Hasin DS, Chou SP, Stinson FS, Dawson DA. Nicotine dependence and psychiatric disorders in the United States: results from the national epidemiologic survey onalcohol and related conditions. Arch. Gen. Psychiatry. 2004;61:1107–1115. [PubMed]
  • Guydish J, Passalacqua E, Tajima B, Manser ST. Staff smoking and other barriers to nicotine dependence intervention in addiction treatment settings: a review. J. Psychoactive Drugs. 2007;39:423–433. [PMC free article] [PubMed]
  • Hahn EJ, Warnick TA, Plemmons S. Smoking cessation in drug treatment programs. J. Addict. Dis. 1999;18:89–101. [PubMed]
  • Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br. J. Addict. 1991;86:1119–1127. [PubMed]
  • Hoffman AL, Slade J. Following the pioneers. Addressing tobacco in chemical dependency treatment. J. Subst. Abuse Treat. 1993;10:153–160. [PubMed]
  • Indiana Tobacco Prevention and Cessation. Policy change in behavioral health care and addiction treatment facilities. 2010. [accessed on 09/10/2010].
  • Joseph AM, Arikian NJ, An LC, Nugent SM, Sloan RJ, Pieper CF. Results of a randomized controlled trial of intervention to implement smoking guidelines in Veterans Affairs medical centers: increased use of medications without cessation benefit. Med. Care. 2004;42:1100–1110. [PubMed]
  • Joseph AM, Nichol KL, Willenbring ML, Korn JE, Lysaght LS. Beneficial effects of treatment of nicotine dependence during an inpatient substance abuse treatment program. JAMA. 1990;263:3043–3046. [PubMed]
  • Kalman D. Smoking cessation treatment for substance misusers in early recovery: a review of the literature and recommendations for practice. Subst. Use Misuse. 1998;33:2021–2047. [PubMed]
  • Kozlowski LT, Jelinek LC, Pope MA. Cigarette smoking among alcohol abusers: a continuing and neglected problem. Can. J. Public Health. 1986;77:205–207. [PubMed]
  • Lawal RA, Adelekan ML, Ohaeri JU, Orija OB. Rehabilitation of heroin and cocaine abusers managed in a Nigerian psychiatric hospital. East Afr. Med. J. 1998;75:107–112. [PubMed]
  • Little HJ. Behavioral mechanisms underlying the link between smoking and drinking. Alcohol Res. Health. 2000;24:215–224. [PubMed]
  • Nakamura Y, Ishikawa A, Sekiguchi S, Kuroda M, Imazeki H, Higuchi S. Spirits and gastrectomy increase risk for chronic pancreatitis in Japanese male alcoholics. Pancreas. 2003;26:e27–e31. [PubMed]
  • Oregon Department of Human Services. Tobacco Freedom, August 17, 2010. Prepared by Richard L. Harris, Assistant Director. Salem: Addictions and Mental Health Division; 2010.
  • Patten CA, Martin JE, Hofstetter CR, Brown SA, Kim N, Williams C. Smoking cessation following treatment in a smoke-free Navy Alcohol Rehabilitation program. J. Subst. Abuse Treat. 1999;16:61–69. [PubMed]
  • Perine JL, Schare ML. Effect of counselor and client education in nicotine addiction on smoking in substance abusers. Addict. Behav. 1999;24:443–447. [PubMed]
  • Richter KP, Choi WS, McCool RM, Harris KJ, Ahluwalia JS. Smoking cessation services in U.S. methadone maintenance facilities. Psychiatr. Serv. 2004;55:1258–1264. [PubMed]
  • Rohsenow DJ, Colby SM, Martin RA, Monti PM. Nicotine and Other Substance Interaction Expectancies Questionnaire: relationship of expectancies to substance use. Addict. Behav. 2005;30:629–641. [PubMed]
  • Schroeder SA. A 51-year-old woman with bipolar disorder who wants to quit smoking. JAMA. 2009;301:522–531. [PubMed]
  • Schroeder SA, Morris CD. Confronting a neglected epidemic: tobacco cessation for persons with mental illness and substance abuse problems. Annu. Rev. Public Health. 2009;31:297–314. [PubMed]
  • Sees KL, Clark HW. When to begin smoking cessation in substance abusers. J. Subst. Abuse Treat. 1993;10:189–195. [PubMed]
  • Sherman SE. A framework for tobacco control: lessons learnt from Veterans Health Administration. BMJ. 2008;336:1016–1019. [PMC free article] [PubMed]
  • Substance Abuse and Mental Health Services Administration. Results from the 2008 National Survey on Drug Use and Health: National Findings. NSDUH Series H-36, HHS Publication No. SMA 09-4434. Rockville: Office of Applied Studies; 2009.
  • Tobacco-Free Services. Title 14 NYCRR Part 856. 2008. [accessed on 07/24/2008].
  • Trudeau DL, Isenhart C, Silversmith D. Efficacy of smoking cessation strategies in a treatment program. J. Addict. Dis. 1995;14:109–116. [PubMed]
  • Utah Division of Substance Abuse and Mental Health, n.d. Recovery Plus Tobacco Project. [accessed on 09/10/2010].
  • Velasquez MM, Hecht J, Quinn VP, Emmons KM, DiClemente CC, Dolan-Mullen P. Application of motivational interviewing to prenatal smoking cessation: training and implementation issues. Tob. Control. 2000;9:36–40. [PMC free article] [PubMed]
  • Walsh RA, Bowman JA, Tzelepis F, Lecathelinais C. Smoking cessation interventions in Australian drug treatment agencies: a national survey of attitudes and practices. Drug Alcohol Rev. 2005;24:235–244. [PubMed]
  • Williams JM, Foulds J, Dwyer M, Order-Connors B, Springer M, Gadde P, Ziedonis DM. The integration of tobacco dependence treatment and tobacco-free standards into residential addictions treatment in New Jersey. J. Subst. Abuse Treat. 2005;28:331–340. [PubMed]
  • World Health Organization. Tobacco Key Facts. 2010. [accessed on 09/10/10].
  • Ziedonis D, Zammarelli L, Seward G, Oliver K, Guydish J, Hobart M. Addressing tobacco through organizational change: a case study of an addiction treatment organization. J. Psychoactive Drugs. 2007;39:451–459. [PMC free article] [PubMed]