Short communicationMeasuring smoking knowledge, attitudes and services (S-KAS) among clients in addiction treatment
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 to 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.
Section snippets
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
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
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
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.
Contributors
Joseph Guydish planned and led the study and prepared the first draft of this report. Barbara Tajima and Doug Ziedonis contributed to the development and assembly of the survey measurement, and Barbara Tajima oversaw all data collection. Kevin Delucchi planned and Mable Chan executed the analyses, and consulted to inform interpretation. All authors participated in revision of the final paper.
Conflict of interest
No conflict declared.
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