A Comparison of Tobacco-Related Risk Factors Between Adolescents With and Without Cancer

Abstract

Objective To compare adolescents with and without cancer on current smoking status, intentions to smoke, and tobacco-related risk factors. Methods Ninety adolescents undergoing treatment for cancer (median time since diagnosis was 2.4 months) and a comparison sample of 279 adolescents without cancer, ages 12 to 18 years, completed questionnaires that asked about their smoking habits, intentions to smoke, and tobacco-related psychosocial risk factors. Results Approximately 2% of adolescents with cancer and 22% of adolescents without cancer reported current smoking. Compared to nonsmoking adolescents without cancer, nonsmoking adolescents with cancer were one third less likely to report intentions to smoke. No significant interactions were detected between group (having cancer or not) and each of the tobacco-specific and psychosocial variables tested in two separate multivariable models. Intentions to smoke were best predicted by variables most proximal to smoking. Adolescents who smoked in the past and who had lower tobacco knowledge and greater perceived instrumental value were more likely to report intentions to smoke. Adolescents who were less optimistic were also more likely to intend to smoke. Conclusions Tobacco-related risk factors for intentions to smoke appeared to be similar among adolescents with and without cancer. Implications of these findings for tobacco control among adolescents with cancer are discussed.

Received September 3, 2003; revisions received March 26, 2004; accepted August 2, 2004

Adolescent smoking continues to be a significant national public health problem. Data from the 2000 National Youth Tobacco Survey found that 11% of middle school students and 28% of high school students in the United States were current cigarette smokers (Centers for Disease Control and Prevention [CDC], 2001). Despite the health risks associated with smoking, a diagnosis of cancer does not eliminate the smoking habits of adolescents. A number of studies of childhood cancer survivors have demonstrated that although patients treated for cancer smoke at rates below that of the general population, the rates reported are still unacceptably high. For example, in the largest childhood cancer survivor cohort studied to date, 17% of patients (18 years of age and older) reported being a current smoker, with low income and low education patients reporting smoking rates comparable to their counterparts in the general population (Emmons et al., 2002). Although there is limited data on the prevalence of smoking among adolescents undergoing active treatment for cancer, data from protocols being conducted at a large pediatric oncology center estimate that between 5% and 10% of these adolescents are smokers (Tyc et al., 2003).

Respiratory symptoms and infections, decreased lung function, lipid profiles that predispose to cardiovascular disease later in life, and compromised physical fitness are among the early consequences of youth smoking (U.S. Department of Health and Human Services [USDHHS], 1994; Woolf, 1997). Continued smoking into adulthood greatly increases the risk of developing chronic obstructive pulmonary disease, coronary heart disease, stroke, lung cancer, and other cancers. These tobacco-related health risks are magnified among young cancer patients since many of them are exposed to cardiopulmonary toxic chemotherapies and radiation treatments that are known to compromise their cardiac, vascular, and/or pulmonary functioning (Meisler, 1993). In addition, youngsters treated for cancer are already at risk for developing second cancers because of genetic and treatment-induced predispositions (Meisler, 1993; Robison & Mertens, 1993), which may be exacerbated by tobacco use.

Research has identified a profile of risk factors derived from major psychosocial models, including the social learning theory and health belief model, used to explain smoking onset and smoking progression in healthy adolescents (Chassin, Presson, & Sherman, 1990; Choi, Harris, Okuyemi, & Ahluwalia, 2003). This complexity of factors contributing to adolescent tobacco use is compounded by differences in age, gender, race, and socioeconomic status (SES; Robinson & Klesges, 1997; Wahlgren et al., 1997). Likewise, these factors may perform differentially in medically compromised adolescents, but correlates of smoking have never been studied in the adolescent treated for cancer.

Several investigators have found that social influences reliably predict cigarette use among adolescents (USDHHS, 1994). Parental smoking has been found to be important in molding youngsters’ attitudes toward cigarette use (Flay et al., 1994). Smoking among peers has been the strongest and most consistent predictor contributing to the onset and progression of adolescent smoking (Wang, Fitzhugh, Westerfield, & Eddy, 1995). Likewise, the instrumental value an adolescent associates with smoking—that is, perceptions of smoking as an effective way to impress their peers—has been found to affect the likelihood of regular cigarette use (Robinson, Klesges, Zbikowski, & Glaser, 1997; USDHHS, 1994). Smoking among parents and peers provides ready access to cigarettes, early models for smoking behavior, and social reinforcement for smoking (Tercyak, Peshkin, Walker, & Stein, 2002).

Less proximal psychosocial determinants of smoking—such as an adolescent’s propensity toward risk taking and rebelliousness, as well as perceived success and social support—have also been investigated. A number of studies have shown that rebellious adolescents are significantly more likely to engage in smoking (Burt, Dinh, Peterson, & Sarason, 2000; Pederson, Koval, McGrady, & Tyas, 1998; Tyas & Pederson, 1998). The odds of becoming a smoker are also higher for adolescents who feel unsuccessful and unsupported by their parents and friends (Pederson et al., 1998). Such adolescents may cope with this related stress and seek peer approval by smoking cigarettes (Mates & Allison, 1992; USDHHS, 1994).

Perceptions of health risk—also known as perceived vulnerability, health value, and optimism—are well-recognized components of current models proposed to explain adolescent health behaviors, including smoking (Weinstein, 1993). For example, adolescents with more optimistic views have been reported to be less likely to initiate smoking. Those low in optimism and perhaps less able to self-regulate one’s actions are at greatest risk for the escalation of smoking, once having started (Carvajal, Wiatrek, Evans, Knee, & Nash, 2000). Likewise, adolescents who progress to be regular smokers have been found to have lower perceptions of health risk, consistent with predictions of the health belief model (Choi et al., 2003; Weinstein, 1993). Adolescent smoking status may also be influenced by one’s perceived health value and personal health concerns (Bennett, Norman, Moore, Murphy, & Tudor-Smith, 1997; Pederson et al., 1998; Tyas & Pederson, 1998). Additionally, adequate knowledge about tobacco-related health risks has been found to a protective factor for adolescent smoking (Pederson et al., 1998).

As adolescents with cancer are strongly encouraged to abstain from smoking, it remains unclear how these well-established smoking risk factors operate in the context of a diagnosis and treatment for cancer. At present, it is unknown whether the psychosocial factors that contribute to smoking onset in adolescents deter or promote smoking among adolescents with cancer relative to their peers without cancer. For instance, is it possible that adolescents with cancer are less likely to be subject to smoking models and peer influences as a result of their illness? Additionally, do they perceive smoking as a mechanism to connect socially with peers from whom they have been detached because of their cancer experience? Because adolescents with cancer report heightened vulnerability to health risks as a result of their cancer experience (Mulhern et al., 1995), their greater health concerns and perceptions of health risk may in turn affect their smoking behaviors or future intentions to smoke. Likewise, adolescents with cancer spend more time with health care providers and may have greater opportunity to be counseled about the health risks associated with tobacco use that could affect their decision to smoke.

In light of these issues, the goals of this study were to determine the prevalence of current smoking and intentions to smoke among adolescents with cancer in comparison to adolescents without cancer. Self-reported intentions to smoke have consistently been used as a proximal outcome measure in adolescent smoking research because prospective studies have consistently demonstrated smoking intentions to be a strong predictor of future smoking behavior (Eckhardt, Woodruff, & Elder, 1994; Pierce, Choi, Gilpin, Farkas, & Merritt, 1996). We intended to explore tobacco-specific and less proximal psychosocial predictors of smoking intentions in adolescents with cancer as compared to their peers without cancer. This was the first study to compare adolescents treated for cancer to their peers without cancer on a number of tobacco-related risk factors.

Method

Participants

The current study included 90 adolescents who were currently being treated for cancer at a large pediatric oncology center (M = 15.1 years, SD = 1.8) and 279 junior high school and high school students without cancer in the same age range (M = 14.1 years, SD = 1.7). The demographic characteristics of the two samples in terms of age, gender, race, and SES levels are provided in Table I. Adolescents in our school sample were eligible for the study if they were in grades 7 to 12, spoke English, and were not enrolled in full-day special education programs. The school sample was recruited from students attending one large junior high school (n = 155, 55.6%) and two senior high schools (n = 124, 44.4%) located in the Memphis area. These schools were selected a priori in an effort to obtain a control group that was demographically similar to the group of adolescents with cancer. Eligibility criteria for adolescents with cancer required that they be 12 to 18 years of age at the time of enrollment, spoke English, had a primary diagnosis of malignancy, were in active treatment, and were at least 1 month from diagnosis. The median time from diagnosis for adolescents with cancer who participated in the study was 2.4 months (range = 1.0–7.7 months). At the time of the study, the majority of adolescents with cancer were outpatients (n = 74, 82.2%). Approximately 53% of patients were hospitalized in the preceding month with the median number of overnight stays being 5.5 days (range = 1–28 days). Almost 49% (n = 44, 48.9%) of the sample was being treated for leukemias/lymphomas, 30.0% (n = 27) for solid tumors, and 21.1% (n = 19) for brain tumors.

Procedures

All adolescents in the cancer sample who met our eligibility criteria were recruited during routine outpatient clinic visits. Adolescents were asked if they were willing to participate in an institutional review board–approved study that asked about their tobacco use and beliefs about tobacco use. Adolescents were told that their participation did not depend on their smoking status. Signed informed consent according to institutional guidelines was obtained and written assent was obtained from all adolescents. All participants were informed that their responses would remain confidential and would not be reported in their medical chart. Of the 94 eligible patients approached for the study, only four refused to participate due to lack of interest and lack of time. All assessments were conducted by master’s-level graduate students.

For the school sample, a consent and description of the approved study was sent home with 525 students. Only students who returned signed parental consent forms and provided assent—or were 18 years of age and provided consent—were permitted to participate in the study. Approximately 55% of students returned them with parental signatures. This return rate is within the range typically obtained for published studies of adolescent smoking (Koval, Pederson, Mills, McGrady, & Carvajal, 2000; Robinson & Klesges, 1997). Of these, five parents refused child participation. No adolescents refused to complete the survey. Five additional students reported experimenting with smokeless tobacco and were later excluded from the analyses. Students were told that they would be asked to complete a survey about smoking and that participation was voluntary. To ensure that their responses were confidential, an identification number was assigned to each student and was used on study forms, rather than names. For the high school students, two graduate assistants administered the research measures during the students’ study hall, health and wellness class, or home economics class. For the junior high school students, the research measures were administered by the school’s curriculum coordinator. Students were instructed to answer the questions honestly and ask for assistance as needed. To further ensure confidentiality, students were permitted to seal their packets in unmarked manila envelopes before returning them to the research assistants or the curriculum coordinator. Adolescents in the cancer and control cohorts were asked to complete the following measures.

Measures

Smoking Status

Current smoking status was measured by self-report regarding whether the adolescent had smoked a cigarette in the past 30 days, a commonly used measure of smoking status in recent national surveys of similarly aged adolescents (CDC, 2001). As there is no consensus in the published literature on the most acceptable definition of adolescent smoking (Kaufman et al., 2002), we selected one that was less stringent. We did so to most accurately capture smokers among our adolescents with cancer, who might not have the same opportunity to smoke as their peers, given the constraints of the hospital setting. If the adolescents were not currently smoking, they were asked if they had ever smoked in the past. Adolescents were also asked to indicate whether their parents had smoked in the last month and if any of their friends currently smoked.

Smoking Survey

As used in previous research, a questionnaire assessing a variety of factors thought to be related to smoking onset among healthy adolescents was included as a primary measure (Robinson & Klesges, 1997; Robinson et al., 1997). Measures that have been used in prior studies of young cancer patients were also included (Tyc, Hadley, & Crockett, 2001; Tyc et al., 2003).

Instrumental Value of Smoking.

The instrumental value of smoking was assessed by six 4-point Likert scales, scored from 0 to 3, with higher scores indicating greater instrumental value. Cronbach’s alphas for the control and cancer samples were .89 and .80, respectively. These items asked the adolescent to indicate, for example, the degree to which smoking would make them look “cool.”

Perceived Social Support/Success.

Eight 4-point items scored from 0 to 3 provided an overall measure of perceptions of social support and success. Cronbach’s alphas for the control and cancer samples were .67 and .72, respectively. Adolescents were asked, for example, how they were doing in school and how popular they believed themselves to be. Higher scores indicated greater perceived social support and success.

Rebelliousness.

This scale consisted of five 4-point items assessing rebelliousness and risk taking. Cronbach’s alphas were .81 and .85 for the control and cancer samples, respectively. These items were scored 0 to 3, with higher scores reflecting greater rebelliousness. An example of an item on this scale asked adolescents to respond to the following: “I enjoy doing things people say I shouldn’t do.”

Optimism.

Adolescents’ general life expectations and level of optimism were measured using the Youth Life Orientation Test (Ey et al., in press). The responses on the 12-item Total Optimism scale for each item ranged from 3 (true for me) to 0 (not true for me) with possible total scores ranging from 0 to 36. Higher scores reflected higher levels of optimism. Cronbach’s alphas of .84 and .83 were obtained for the control and cancer samples, respectively. An example of an item on this scale includes “When things are bad, I expect them to get better.”

Health Value.

Adolescents’ perceptions of the importance of their health were assessed by a single item that asked, “Compared to others your age, how important do you think it is to keep yourself healthy?” Scores ranged from 1 to 5, with higher scores indicating greater health value.

Perceived Vulnerability (PV) to General Health and Tobacco-Related Problems.

Because of the low internal reliability computed for the original eight-item PV scale used in prior studies (Tyc et al., 2001; Tyc et al., 2003), we selected two items to assess adolescents’ PV to general health problems as well as specific tobacco-related health problems. Perceptions of vulnerability to general health problems were assessed by degree of agreement with the statement “In general, I am in more danger of developing health problems than others my age.” Perceptions of vulnerability to tobacco-related problems were assessed by reported degree of agreement with the statement “My chances are high that I will have serious health problems if I smoke or use tobacco now or in the future.” Responses for these items ranged from 1 (strongly disagree) to 5 (strongly agree), with higher scores representing greater PV.

Knowledge.

The Knowledge scale consists of 25 true–false questions (maximum score = 25) related to the adverse consequences associated with tobacco use. Internal consistency was determined by the Kuder-Richardson statistic and was .53 and .72 for the control and cancer samples, respectively. This scale has been used in studies with young cancer survivors (Tyc et al., 2001; Tyc et al., 2003).

Intentions.

The Intentions scale consists of six items that measure intentions to use tobacco as rated on a 5‐point Likert scale ranging from very unlikely to very likely. Total scores range from 6 to 30, with higher scores reflecting greater intentions to use tobacco. The Intentions scale was dichotomized into no intentions to smoke (score = 6) and some intention to smoke (scores > 6) to better differentiate adolescents at low versus high risk for future smoking as suggested in the literature (Pierce et al., 1996). Susceptibility to smoking, or intentions to smoke, has been reported to significantly predict experimentation with smoking among healthy adolescents (Pierce et al., 1996). Cronbach’s alphas for the control and cancer samples were .90 and .73, respectively. Good internal reliability for this measure has been consistently demonstrated in studies with young cancer survivors (Tyc et al., 2001; Tyc et al., 2003).

Data Analysis

To make group (cancer vs. control) comparisons of background variables, Pearson’s chi-square and two-sample t tests (alpha = .05) were used for categorical and continuous data, respectively (see Table I). Next, univariate comparisons according to intentions to smoke (none vs. some) were conducted using two-sample t tests and chi-square tests. Given the demographic differences observed according to group in Table I, results were stratified according to group (see Table II). Hierarchical logistic regression methods were used to select variables for inclusion in models predicting intentions (none vs. some for nonsmokers) to smoke and to investigate interactions with group (see Tables III and IV). Two models were fit to investigate interactions with tobacco-specific variables and with general psychosocial variables; demographics and group (cancer or control) were tested in the first two steps for both models. In the first model, tobacco-specific variables (past smoking status, parent and peer smoking status, knowledge, instrumental value, and perceived vulnerability for tobacco-related illnesses) were assessed in Step 3 followed by Step 4, which added interactions between tobacco-specific variables with group. In the second model, general psychosocial variables (perceived social support and success, total optimism, rebelliousness, health value, and perceived vulnerability for general health) were assessed in Step 3 and interactions in Step 4. A generalized R² was reported for each step (Nagelkerke, 1991), as well as the χ² for each step’s contribution. The examination of interactions was considered exploratory given the number of variables investigated and the limited sample size of the group of adolescents with cancer. Additionally, point biserial correlations were conducted to investigate the association between the tobacco-specific and general psychosocial predictor variables and the intention group for adolescents with and without cancer (see Table II).

Results

Univariate Analyses of Demographic Variables

The demographic characteristics for the controls and adolescents treated for cancer are listed in Table I. Adolescents with cancer were significantly older than those not treated for cancer. Significant differences were also found for race and SES. Compared to the cancer cohort, the controls were characterized by a greater proportion of whites and a lower proportion of African Americans. Inspection of SES levels (Hollingshead, 1975) indicated that relative to the cancer cohort, a greater proportion of adolescents without cancer were from middle SES levels and fewer were from lower SES levels. There were no significant differences between adolescents with and without cancer on the basis of gender.

Univariate Analyses of Tobacco Outcomes

Significantly fewer adolescents with cancer reported current smoking (n = 2, 2%) than adolescents without cancer (n = 61, 22%), χ² (1) = 18.6, p < .001. The percentage of former smokers was similar between adolescents with cancer (n = 18, 20%) and those without cancer (n = 51, 18%). Given the limited number of current smokers in the cancer group, current smoking was not included as a tobacco outcome in subsequent analyses.

As shown in Table II, we tested for differences between adolescents who reported some intention to smoke versus those who reported no intention to smoke for demographic and psychosocial variables in the control and cancer groups, with the current smokers excluded. Of the combined sample of adolescents, 66% reported some intention to smoke. Adolescents without cancer (74%) were more likely to report intentions to smoke relative to adolescents with cancer (48%), c²(1) = 13.3, p < .01. Among adolescents with cancer, those who were enrolled in the study 3 or more months from diagnosis (50%) were not significantly more likely than those enrolled less than 3 months from diagnosis (47%) to report intentions to smoke, c²(1) = 0.1, ns. Likewise, outpatients (49%) were not significantly more likely than inpatients (40%) to intend to smoke in the future, c²(1) = 0.4, ns.

Among adolescents with and without cancer, those who reported intentions to smoke reported higher levels of perceived instrumental value of smoking compared to those who reported no intentions to smoke—with cancer, t(67) = 2.6, p < .05, without cancer, t(197) = 3.5, p < .001. Adolescents without cancer who intended to smoke had higher levels of rebellious/risk taking, t(201) = 2.1, p < .05, had perceived less social support/success, t(201) = 2.3, p < .05, were less optimistic, t(216) = 2.8, p < .05, and were less knowledgeable about tobacco-related health risks, t(129) = 2.5, p < .05, than those with no intentions to smoke. Among adolescents without cancer, those with greater perceived vulnerability to general health problems, c² (4) = 10.1, p < .05, were more likely to report some intention to smoke compared with those with lower perceived vulnerability. Adolescents without cancer who reported exposure to smoking peers were more likely to report intention to smoke than those not exposed to peer smoking, c² (2) = 7.9, p < .05.

To determine which variables were significantly associated (p < .05) with intention group, point biserial correlations were conducted for each of the cohorts. Among the control group, tobacco knowledge (r = −.15), perceived social support (r = −.16), and total optimism (r = −.19) were inversely associated with intentions to smoke. Instrumental value (r = .24) and rebelliousness (r = .14) were positively associated with smoking intentions. For adolescents in the cancer group, only instrumental value (r = .28) was significantly associated with intentions to smoke.

Multivariable Analyses

Multivariable modeling (Table III) shows the percent variation in intentions explained for each step as indicated by generalized R². Demographic variables accounted for only 3% of the variance of intentions, and since the block was not significant, it was not retained. Group (having cancer or not) explained 9% of the variance in intentions, and tobacco-specific and general psychosocial variables explained an additional 17% and 6%, respectively. Interactions between group and tobacco-specific variables and between group and general psychosocial variables did not significantly add to the variation explained by the model. The final models are provided in Table IV.

Because the demographic and interaction blocks were not significant, they were removed from the final models. The final multivariate model in Table IV that included tobacco-specific variables (Model 1) accounted for 26% of the variance in smoking intentions for current nonsmokers. After controlling for the other variables in the model, significant predictors of intentions to smoke in Model 1 were group (having cancer or not), past smoking status, tobacco knowledge, and perceived instrumental value of smoking. Results suggest that adolescents without cancer were over three times more likely to report intentions to smoke compared to adolescents with cancer. Greater perceived instrumental value and decreased knowledge were associated with an increased likelihood of intending to smoke in the future. Adolescents who were past smokers were over 2.5 times more likely to endorse future intentions to smoke.

The final multivariate model that addressed general psychosocial variables (Model 2) accounted for 15% of the variance in smoking intentions. Significant predictors of intentions to smoke in this model were group (having cancer or not) and optimism. Adolescents without cancer and those who were less optimistic were more likely to endorse future intentions to smoke.

Discussion

Study results indicated that the rate of ever smoking among adolescents with cancer was 22%, almost half the rate reported by adolescents without cancer. The data also revealed that only 2% of adolescents with cancer currently smoked cigarettes, compared to 22% of adolescents without cancer, as based on their self-reports. Although these low rates of current smoking among adolescents with cancer are promising, the rates obtained in the current study are somewhat lower than the 5% to 10% smoking rates reported in the literature (Tyc et al., 2003). Earlier estimates, however, were based on small heterogeneous samples with differing definitions of smoking status.

The low incidence of smoking observed in our study may reflect the adolescents’ active treatment status and their relative recency to diagnosis. Although the majority of patients were outpatients at the time of the study, some were hospitalized during the month preceding the study such that the low incidence of smoking may reflect the constraints of the hospital setting. What may also account for the observed low rates of smoking are treatment-related side effects and the smoking restrictions at the hospital and in the housing facilities where many of our patients reside during treatment. The fact that some adolescents with cancer were past smokers suggests that the low incidence of smoking could reflect a temporary decrease in smoking, secondary to illness and treatment-related factors. Future studies should more closely examine the change in smoking behaviors before and throughout the adolescent’s treatment course to better understand whether these adolescents temporarily decrease smoking and under what conditions they resume smoking. As it is well known that smoking onset is delayed among African American adolescents (Robinson & Klesges, 1997), the low smoking rates in our study could also be partially attributed to a higher proportion of African Americans in the cancer sample. Lastly, although efforts were made to ensure confidentiality, we cannot exclude the possibility that some adolescents with cancer may have underreported their intentions to smoke or misrepresented their smoking status, as the assessment for this sample was conducted by health care professionals in a medical setting.

Among current nonsmoking adolescents, adolescents with cancer were approximately one third as likely as adolescents without cancer to endorse some intention to smoke. Susceptibility to smoking, defined as the absence of a firm decision not to smoke, has been reported to significantly predict experimentation with smoking 4 years later in a nationally representative sample of 4,500 healthy adolescents (Pierce et al., 1996). This relation has yet to be studied longitudinally in young cancer patients. Nonetheless, greater efficacy in preventing smoking onset among adolescents with cancer may be achieved by targeting at-risk youngsters who clearly intend to smoke or those whose current intentions to smoke are less clearly established.

Previous research has not compared adolescents with and without cancer on tobacco-related risk factors. The results of the exploratory multivariable analyses suggest that intentions to smoke are best predicted by tobacco-specific variables—that is, those variables most proximal to smoking. In addition, variables predictive of future intentions to smoke appeared to be similar among adolescents with and without cancer. However, it should be noted that power was somewhat limited to detect interactions given the small sample size of our cancer cohort.

Interestingly, viewing smoking as a means to impress one’s peers (perceived instrumental value) was positively associated with intentions to smoke. This finding is consistent with a body of research that demonstrates a positive relationship between this tobacco-specific variable and experimentation with smoking as well as regular cigarette consumption (Robinson et al., 1997; USDHHS, 1994). When examining general psychosocial variables that are more distal to smoking, being less optimistic was also associated with intentions to smoke. Although this variable has been less extensively studied in the literature, it may also play a role in smoking initiation.

Despite the fact that adolescents with cancer are often removed from their peer social networks for extended periods due to treatment, peer influences appear to similarly affect tobacco outcomes for these adolescents as for those without cancer, as suggested by our multivariable model. Despite frequent isolation from their peers during cancer treatment, adolescents with cancer may not view smoking as a vehicle to reconnect with peers and/or seek peer approval, as the relation between peer smoking and smoking intentions does not appear to be stronger for adolescents with cancer. It should be noted, however, that our question about peer smoking was a general one, without any specification of the frequency of smoking among peers. Adolescents who observe their peers smoking at low levels (i.e., experimenters) or who infrequently have the opportunity to observe them (because of social restrictions due to their disease in the case of adolescents with cancer) may be less likely to define them as smokers.

Several additional limitations should be noted when interpreting the results of the current study. First, the smoking outcomes used relied on adolescent self-report and were not confirmed by a biological marker of smoking behavior. Second, the samples recruited were relatively small, and the control sample comprised a limited number of schools from a single geographic area. Obtained differences in race, SES, and age between the cancer and control groups in our study were likely due to sampling variability, despite our attempts to a priori select a demographically similar control sample. Therefore, our findings must be interpreted within the context of our control sample and should not be generalized beyond the parameters of the study. Third, despite our careful attention to the literature and the available measures for the risk factors being assessed, some of the outcomes used were brief single-item measures with limited psychometric data that may not have been optimal for measuring the outcomes in our two adolescent groups. Further methodological refinement may therefore help to elucidate the relationship between smoking behaviors and various risk factors.

The low rates of reported smoking among adolescents with cancer should not be interpreted to mean that smoking is not a problem in this vulnerable population. Rather, the implications of these findings for tobacco control among adolescents with cancer are quite significant. The treatment for cancer may provide an excellent opportunity for health care providers to encourage maintenance of smoking cessation for those smokers who may temporarily decrease their smoking secondary to illness and treatment and to counsel nonsmoking patients to continue to abstain from tobacco use, particularly those who intend to smoke in the future. Thus, cancer treatment may serve an inhibitory function as well as a motivational one on adolescent smoking behaviors, which should be capitalized on by health care providers.

Although tobacco risk counseling and health promotion programs have typically been reserved for survivors who have completed cancer treatment, and for whom reported smoking rates are typically higher than those reposted in the current study (Tyc et al., 2003), earlier provision of tobacco counseling—such as when patients are undergoing cancer therapy—may better serve to disrupt or delay the trajectory of tobacco use in this population. Counseling patients about their health risks is important in light of the current findings that youngsters with less knowledge about tobacco-related health risks are more likely to intend to smoke. Clinical practice guidelines suggest that at every health care visit, all adolescents should be asked about tobacco use, advised to stop or continue to abstain from smoking, assessed for their willingness to stop smoking, assisted with smoking cessation, and provided with a follow-up (Fiore et al., 2000). As supported by our findings, assessing adolescents’ knowledge about tobacco-related health risks and asking questions about their views regarding the value of smoking and their past smoking history may be particularly important in reducing their risk for smoking in the future. In the absence of other evidence, the results of this study suggest that smoking prevention programs built on traditional tobacco-specific and general psychosocial risk factors for healthy adolescents may be similarly applicable to the young patient treated for cancer. However, revisions to the content and delivery, as well as reliance on the supportive and motivational aspects of the treatment setting, may be necessary to enhance the impact of more traditional approaches implemented with young cancer patients.

References

Author notes

¹Division of Behavioral Medicine and ²Department of Biostatistics, St. Jude Children’s Research Hospital, ³Department of Pediatrics, College of Medicine, University of Tennessee, Memphis, ⁴University of Memphis, Tennessee