Linking measures of adult nicotine dependence to a common latent continuum and a comparison with adolescent patterns

Drug and Alcohol Dependence 120 (2012) 88–98

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Drug and Alcohol Dependence journal homepage: www.elsevier.com/locate/drugalcdep

Linking measures of adult nicotine dependence to a common latent continuum and a comparison with adolescent patterns David R. Strong a,b,∗, Yael Chatav Schonbrun a,b, Christine Schaffran c, Pamela C. Griesler c, Denise Kandel c,d a

Butler Hospital, United States Warren Alpert Medical School of Brown University, United States c New York State Psychiatric Institute, United States d Columbia University, United States b

a r t i c l e

i n f o

Article history: Received 2 August 2010 Received in revised form 20 May 2011 Accepted 3 July 2011 Available online 19 August 2011 Keywords: Nicotine dependence Item response theory Adolescent smoking

a b s t r a c t Background: An ongoing debate regarding the nature of nicotine dependence (ND) is whether the same instrument can be applied to measure ND among adults and adolescents. Using a hierarchical item response model (IRM), we examined evidence for a common continuum underlying ND symptoms among adults and adolescents. Method: The analyses are based on two waves of interviews with subsamples of parents and adolescents from a multi-ethnic longitudinal cohort of one thousand and thirty-nine 6–10th graders from the Chicago Public Schools (CPS). Adults and adolescents who reported smoking cigarettes the last 30 days prior to waves 3 and 5 completed three common instruments measuring ND symptoms and one item measuring loss of autonomy. Results: A stable continuum of ND, first identified among adolescents, was replicated among adults. However, some symptoms, such as tolerance and withdrawal, differed markedly across adults and adolescents. The majority of mFTQ items were observed within the highest levels of ND, the NDSS items within the lowest levels, and the DSM-IV items were arrayed in the middle and upper third of the continuum of dependence severity. Loss of autonomy was positioned at the lower end of the continuum. We propose a ten-symptom measure of ND for adolescents and adults. Conclusions: Despite marked differences in the relative severity of specific ND symptoms in each group, common instrumentation of ND can apply to adults and adolescents. The results increase confidence in the ability to describe phenotypic heterogeneity in ND across important developmental periods. © 2011 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Tobacco use, most commonly in the form of cigarette smoking, is one of the leading causes of preventable disease and death in the United States (CDC, 2008). Despite various adverse effects of smoking, over 46 million adults reported smoking in 2008 (CDC, 2009) highlighting the need to improve understanding the onset, course, and treatment of chronic smoking, perhaps best indexed by nicotine dependence (ND). The most widely used instruments to assess ND are based on a conceptualization of nicotine dependence developed for adult smokers. The majority of instruments administered to adolescents are the same or slightly modified ver-

∗ Corresponding author at: Brown University, Butler Hospital, 324 Blackstone Boulevard, Providence, RI 2906, United States. Tel.: +1 401 455 6294; fax: +1 401 455 6424. E-mail address: david [email protected] (D.R. Strong). 0376-8716/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.drugalcdep.2011.07.003

sions of those developed for adults. Two issues remain unresolved: (1) how to integrate information from various instruments commonly used to assess ND, and (2) whether ND instruments perform similarly among adults and adolescents. Current clinical practice for the diagnosis of ND is guided by the Diagnostic and Statistical Manual of Mental Disorders IV (DSMIV) (APA, 1994), which incorporates a psychobiological approach to conceptualizing dependence disorders (Edwards and Gross, 1976) and provides a widely accepted threshold for diagnosing smokers as dependent. Given that any of the seven symptoms characterizing physiological, psychological and psychosocial impairment can lead to diagnosis, if at least three symptoms have been experienced, the DSM-IV has been criticized as conceptually heterogeneous. The Fagerstrom Tolerance Questionnaire (FTQ; Fagerstrom, 1978) and its revisions for adults (FTND, Heatherton et al., 1991) and adolescents (mFTQ, Prokhorov et al., 1996) measure primarily physical rather than psychological symptoms of dependence and are used both as continuous and categorical measures, with

D.R. Strong et al. / Drug and Alcohol Dependence 120 (2012) 88–98

threshold of dependence defined by a specific cut-off score. The FTQ-based instruments have gained support as predictors of withdrawal (Bailey et al., 2009) and difficulty with smoking cessation (e.g., Alterman et al., 1999; Breslau and Johnson, 2000). The Nicotine Dependence Syndrome Scale (NDSS) was designed to broaden the continuous assessment of ND beyond diagnostic instruments and measures of physical symptoms, such as the FTQ (Shiffman et al., 2004). The NDSS captures five symptom domains reflecting the Edwards and Gross (1976) conceptualization of a dependence syndrome: drive (i.e., craving and withdrawal), priority (i.e., preference of smoking over other potential reinforcers), tolerance (i.e., reduced sensitivity to nicotine), continuity (i.e., regularity of smoking patterns), and stereotypy (i.e., other events, such as moods or environment, do not disturb smoking patterns). The NDSS further extends the range of ND assessment and is associated with outcomes such as difficulty abstaining, strength of urges to smoke when deprived, withdrawal during acute abstinence, and long-term cessation (Shiffman et al., 2004). Since smokers with a diagnosis of ND experience varying degrees of severity, clinical assessments benefit from the availability of continuous assessments over categorical ones (Ginestet et al., 2008). Attempts to assess ND among adolescent smokers led to the development of the Hooked on Nicotine Checklist (HONC; DiFranza et al., 2002), a 10-item instrument designed specifically to measure loss of autonomy over tobacco, a symptom believed to be the core feature of ND among young smokers. Loss of autonomy, described as “the recurrent and periodic compulsion to use tobacco” (DiFranza et al., 2002), is argued to be a critical threshold signaling ND and to be more clinically useful than symptoms derived from the DSM-IV (DiFranza, 2010). Guidelines for scoring the HONC specify that endorsement of a single item defines a youth as dependent. However, investigations placing loss of autonomy alongside other symptoms of ND that reflect loss of control, such as difficulty quitting and reduced latencies to smoking the first cigarette of the day, are needed to evaluate how this presumably low-level symptom of dependence relates to other symptoms and discriminates among adult and adolescent smokers. Further, evaluation is needed to determine the degree to which adopting a threshold for ND based upon this symptom obscures phenotypic variability observed among adult and adolescent smokers (Hughes and Shiffman, 2008). Recent studies among adolescents using methods based on Item Response Theory (IRT) suggest that the DSM-IV, mFTQ, and NDSS and loss of autonomy generate complementary information and, when combined, increase the range and precision of information about the severity of ND in adolescence (MacPherson et al., 2008; Strong et al., 2009). Insights into the nature of ND among adolescents were gained by linking symptoms from individual instruments to a common latent continuum of ND. However, such studies have not yet been implemented among adults and loss of autonomy has not been included along with a broad range of symptoms either among adults or adolescents. Emerging evidence among adults suggests that many of the commonly used measures of ND, e.g., the FTND, the Cigarette Dependence Scale (CDS; Etter et al., 2003) and the NDSS, each separately map onto a unidimensional construct and support the concurrent validity of these measures (Courvoisier and Etter, 2008; MacPherson et al., 2008; Strong et al., 2009). Moderate concurrent relationships suggest the potential for complementary information. However, an integrated approach remains to be implemented and the overlap across symptom domains using a common continuum of ND has not been assessed. In this study, we replicate and extend an earlier analysis of a common continuum of ND underlying symptom responses implemented among adolescents (Strong et al., 2009) in an adult sample

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that includes some of the adolescents’ own parents. We can begin to determine whether the same ND structure fits responses to symptom measures obtained either from adult or adolescent smokers. The current study has five specific aims: (a) to link both individual symptoms and combined symptom measures from the DSM-IV, the mFTQ (Prokhorov et al., 1996), and the NDSS to a common unidimensional continuum of ND in an adult sample using an item response model (IRM); (b) to replicate the continuum across two waves of assessment among these adults; (c) to compare ND symptoms across adolescents and adults; (d) to evaluate loss of autonomy within the context of other symptoms of ND among adults and adolescents; and (e) to validate the latent continuum by relating concurrent ND to extensiveness of smoking among adults and adolescents across a one-year period. By linking symptoms to a common continuum, we hope to align descriptions of the ND phenotype across adult and adolescent smokers. 2. Methods The analyses are based on two waves of interviews with subsamples of parents and adolescents from a multi-ethnic longitudinal cohort of one thousand and thirty-nine 6–10th graders from the Chicago Public Schools (CPS). More primary analyses are reported for adults than for adolescents since justification for a single continuum and replication over repeated waves of analyses based on the adolescent sample were previously reported in Strong et al. (2009). Analyses in the current study are extended using a hierarchical item response model (Wainer et al., 2007) to accommodate cross-sample comparisons, as described below. 2.1. Data collection Details of the two-stage design implemented to select efficiently the target sample of adolescent smokers for follow-up are described in Kandel et al. (2005, 2007). In Phase I (Spring 2003), 15,763 students in grades 6–10 were sampled from 43 public schools in the CPS (completion rate 83.1%). The sample was designed to provide approximately equal numbers of adolescents from the three major ethnic groups: non-Hispanic white, non-Hispanic African American, and Hispanic. Responses to the school survey were used to select the target sample: 1106 tobacco users who reported having started using tobacco within the prior 12 months and 130 non-tobacco users susceptible of starting to smoke. Tobacco users included all nonHispanic whites and non-Hispanic African-Americans who started using tobacco 0–12 months earlier, all Hispanics who started 0–6 months earlier, and 25% of Hispanics who started 7–12 months earlier, because there were more Hispanics than other racial/ethnic groups. A small number (8.2%) of susceptible non-smokers, who satisfied 2 of 3 criteria per Pierce et al. (1996), were selected to preclude labeling the study as an exclusive study of smokers. In Phase II, on average 9 weeks after each school survey, 1039 students and one of their parents (86.8% mothers) agreed to participate in the longitudinal follow-up (84.1% of 1236 targeted youths) consisting of three annual computerized household interviews with youths and parents, each about 90 min long (Waves 1, 3, 5). Shorter Waves 2 and 4 interviews, at bi-annual intervals, were restricted to the adolescents. Completion rates at each successive wave were 96% of the original youth-parent dyads (W3 N = 999, W5 N = 1001). The National Opinion Research Center (NORC) of the University of Chicago collected the data. All procedures for obtaining parental consent and youth assent were approved by the Institutional Review Boards of the New York State Psychiatric Institute and Columbia University. Data from W3 and W5 were used in the analysis. 2.2. Symptoms of nicotine dependence Three scales were used to measure nicotine dependence among parents and adolescents: 2.2.1. DSM-IV nicotine dependence. The instrument used to measure DSM-IV (APA, 1994) ND was designed for adolescents and young adults (Dierker et al., 2007; Sledjeski et al., 2007). The 11-item scale measured seven dependence criteria in the 12 months preceding W1 and the period since each prior assessment at W3 and W5 (average Cronbach alpha = 0.74) for adults and the 6 months preceding each assessment for adolescents. 2.2.2. Modified Fagerstrom Tolerance Questionnaire (mFTQ). The mFTQ (Prokhorov et al., 1996) ascertained seven behaviors and experiences when smoking in the 30 days prior to each wave. A five-level quantity smoked variable was defined from the item on number of cigarettes smoked daily: ≤1, 2–5, 6–15,16–25, >25 cigarettes per day (average Cronbach alpha = 0.59). 2.2.3. Nicotine Dependence Syndrome Scale (NDSS). This 17-item scale asked respondents to rate how true (coded 1–5 for “Not true at all” to “Extremely true”) each

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D.R. Strong et al. / Drug and Alcohol Dependence 120 (2012) 88–98

statement was for them in the past 30 days (Shiffman et al., 2004). Items represent five domains: drive, priority, continuity, stereotypy, and tolerance (average Cronbach alpha = 0.83). 2.2.4. Loss of autonomy over tobacco. A single item indexed this symptom: “Do you feel that you are addicted to or hooked on cigarettes?” Response options included ‘Definitely Not,’ ‘Probably Not,’ ‘Perhaps,’ ‘Probably Yes’ and ‘Definitely Yes,’ coded 1–5. 2.3. Analytical samples The analytical samples were restricted to respondents who had smoked in the last 30 days at W3 (N = 270 adults, 253 adolescents) or W5 (N = 260 adults, 296 adolescents). A majority of adults (n = 231) and adolescents (n = 161) participated at both waves of assessments. Of the adults, 96% were female, 25.9% at W3 were the parents of smokers included in the adolescent sample and 25.4% at W5. 2.4. Analysis plan The initial analyses were designed to establish the degree to which each of the DSM-IV, mFTQ, and NDSS provided information about a common continuum of ND among the adults. Results of parallel analyses among the adolescents were previously reported in Strong et al. (2009). The second analysis examined the relationship of the loss of autonomy symptom to the continuum among adults and adolescents. We used confirmatory factor analytic (CFA) models to evaluate the degree to which the three scales provided unique or overlapping information about the levels of ND observed across the two waves of assessment. With a focus on a single primary dimension across the three measures of ND, we fit an item response model (IRM) based on item response theory, which was extended to model additional variability unique to each of the three instruments by organizing symptoms into three ‘testlets’ (Thissen, 1993; Wainer et al., 2007). We used this hierarchical IRM to evaluate: (1) the relative severity of symptoms from each of the three measures; (2) the ability to replicate the relationships of symptoms to levels of ND at each wave; (3) where, along the continuum, loss of autonomy over tobacco may emerge; and (4) the ability to compare adults’ and adolescents’ symptom reports using the same continuum of ND. Using a two-parameter logistic item response model (Birnbaum, 1968), the discrimination (‘a’ parameter) of each symptom describes the strength of the relationship between changes in levels of ND and changes in the likelihood of symptom endorsement (i.e., slope or factor loading). The symptom severity (‘b’ parameter) is defined by the point on a latent severity continuum at which the symptom has a 50% likelihood of being endorsed. By incorporating the ‘testlets’ for each instrument, a hierarchical IRM can be constructed to allow evaluation of the primary dimension of ND, with control for additional variability that may be specific to each individual instrument (Wainer et al., 2007). Since the NDSS allows five levels of response for each symptom, additional nonparametric option-response analyses were conducted using the TestGraf98 (Ramsay, 2000). The NDSS symptom reports were dominated by the initial response (not true at all), which had more than a 50% likelihood of endorsement throughout most of the range of ND, justifying dichotomous scoring. We proceeded with NDSS symptoms using a dichotomized format and scored responses in line with positive relationships with total scores (i.e., any endorsement of “not very true” or higher was coded positively). Scoring of three symptoms (items #11, #12, and #13, Table 2) was reversed. 2.5. Analyses 2.5.1. Unidimensionality and local independence in adults. We conducted a series of CFA of categorical responses in the adult sample using robust weighted least squares analysis comparing the fit of three models: (a) a single primary dimension (1-factor model); (b) a model that allowed three related dimensions defined by the DSM-IV, mFTQ, and NDSS; (c) a hierarchical bifactor model that included a primary dimension of nicotine dependence and three secondary factors reflecting each instrument. By fitting a hierarchical bifactor model, we could evaluate the degree of influence (i.e., local dependence) of the variability specific to each instrument (e.g., similarly phrased symptoms) that may bias estimates of relationships with the primary dimension of ND (Reise et al., 2007). We present three indices for testing the fit of each model: the Comparative Fit Index (CFI: Bentler, 1990), the Tucker Lewis Index (TLI: Bentler and Bonnett, 1980), and the root mean square error of approximation (RMSEA: Steiger, 1990). Suggested cut-offs for model fit are CFI ≥ 0.96, TLI ≥ 0.95, and RMSEA ≤ 0.05 (Yu, 2002). Browne and Cudeck (1993) proposed that RMSEA values of 0.05 or less indicate a ‘close fit’, values between 0.05 and 0.09 indicate ‘reasonable fit’, and values of 0.10 and greater demonstrate ‘poor fit.’ When fit indices suggested the superiority of a hierarchical over a unidimensional model in describing the data, we added a random effect term to our IRM to reflect the common variability within the DSM-IV, mFTQ, and NDSS questions or ‘testlets’, when estimating relationships to a common continuum of ND (Thissen, 1993; Wainer et al., 2007). This testlet model (SCORIGHT; Wang et al., 2004) uses Bayesian methods (Gelman et al., 1995) for obtaining estimates of the ‘a’ and ‘b’ parameters by generating samples from the posterior distribution of each of the model parameters

using two separate Markov chains (Markov chain Monte Carlo: MCMC). To generate evidence for the convergence of the Gibbs sampler before drawing inferences, we allowed 20,000 iterations (Sinharay, 2004) and compared results using the F-test convergence criterion of less than 1.2 to indicate reasonable convergence (Gelman and Rubin, 1992). 2.5.2. Replication of the model over time among adults and adolescents. To assess the stability of the IRM over the two waves of assessment, we evaluated differences in the estimates of symptom characteristics obtained from each wave (see also Strong et al., 2009 for adolescents). If the IRM was stable, the estimates of symptom characteristics from each wave would be similar. We employed a twostep differential item functioning (DIF) approach using Version 2.0 of IRTLRDIF (Thissen, 2001) to compute likelihood ratio testing of nested IRM models and corroborated differences in symptom characteristics with statistically significant DIF using the more intensive Bayesian hierarchical IRM (Wang et al., 2008). We employed the Benjamini–Hochberg procedure (Benjamini and Hochberg, 1995) to adjust decisions about significance while taking into account the number of significant findings across tests. Symptoms identified as having DIF using likelihood ratio testing were evaluated one at a time in Bayesian hierarchical IRMs to generate posterior samples of symptom parameter values for adults and adolescents, using the remaining symptoms as an anchor to ensure equating of levels of ND. To compare parameters, we repeatedly computed the differences of 10,000 independent random draws from posterior distributions obtained for each subsample and then counted the frequency of differences > 0 (Wang et al., 2008). DIF was assigned when more than 95% of differences were larger than 0 (i.e., probability of no difference < 5%). Estimates of uniform differences (i.e., symptoms with no difference in discrimination) between subgroups are presented using a standard effect size analogous to Cohen’s d (d = badult − badolescent ). We established a priori that the magnitude of bias in the severity of symptoms needed to exceed 0.50 (a medium effect) before we attributed significance to differences in symptom performance (Steinberg and Thissen, 2006). Differences in discrimination resulted in non-uniform differences in symptom responses across levels of ND and were evaluated using a visual inspection of item response curves to determine the potential impact on observed levels of ND (Steinberg and Thissen, 2006). Given potential tradeoffs in the model, with some symptoms potentially more discriminating and others less discriminating among adults or adolescents, it is difficult to determine the significance of DIF on a particular instrument using results from individual symptoms alone (Wainer et al., 2007). Therefore, the net effect of DIF within each testlet was evaluated to determine whether a raw summed score from each instrument could be used to compare directly levels of ND among adults and adolescents. We generated expected scores from each instrument by using different discrimination and severity parameters from adolescents and adults (Chang and Mazzeo, 1994; Wainer et al., 2007). 2.5.3. Comparison of adult and adolescent reports of nicotine dependence. At each wave, adult and adolescent smokers provided responses to the same symptoms. We employed the DIF approach described above to compare adult and adolescent responses at W3 and replicated all DIF analyses using W5 responses. While we analyzed all 31 symptoms among adults, when comparing adults and adolescents we limited the comparisons to 27 symptoms, removing symptoms identified as poorly discriminating levels of ND within adolescents (Strong et al., 2009), where loss of autonomy was not considered. DIF analysis allowed for comparisons of adult and adolescent responses to each symptom, with control for levels of ND across respondent groups (Steinberg and Thissen, 2006).

3. Results 3.1. Descriptive analyses The analytical samples include adults and adolescents who smoked at least one cigarette within the last 30 days at W3 or W5 wave. At W3, the 270 adults were on average 42.4 years old (SD = 7.18); 37% were non-Hispanic whites, 43% non-Hispanic African Americans, 20% Hispanics; 67% smoked daily, 78% smoked 15 or fewer cigarettes per day, and 44% met criteria for dependence on the DSM-IV (symptom count: meanW3 = 3.22, SDW3 = 1.94). At W5, the 260 adults were on average 43.1 years old (SD = 6.86); 68% smoked daily, 73% smoked 15 or fewer cigarettes per day, and 43% met criteria for dependence on the DSM-IV (symptom count: meanW5 = 3.23; SDW5 = 1.92). Adolescents were 15.9 years old (S.D. = 1.3) on average at W3 and 16.9 years old (S.D. = 1.2) at W5. At W3, 13.8% smoked daily, 14.6% smoked 6 or more cigarettes per day in the last 30 days, and 35.3% met criteria for DSM-IV nicotine dependence; at W5 the percentages were 21.0%, 17.2%, and 34.5%, respectively.

D.R. Strong et al. / Drug and Alcohol Dependence 120 (2012) 88–98 Table 1 Results from confirmatory factor analysis of 7 DSM-IV, 7 mFTQ, and 17 NDSS symptoms (31 symptoms) to assess unidimensional, a multidimensional (three factors), and a hierarchical bifactor model in which a general factor is evaluated along with three orthogonal factors representing groups of DSM-IV, mFTQ, and NDSS items among adults. Model A Unidimensional Wave 3 (N = 270) 0.868 CFI TLI 0.919 RMSEA 0.101 Wave 5 (N = 260) 0.855 CFI TLI 0.910 0.125 RMSEA

Model B Multidimensional

Model C Hierarchical

0.909 0.944 0.080

0.951 0.969 0.060

0.909 0.943 0.094

0.946 0.966 0.073

Note. CFI = Comparative Fit Index; TLI = Tucker Lewis Index; RMSEA = root mean square error of approximation.

3.2. Combined index of nicotine dependence symptoms among adults 3.2.1. Unidimensionality and local dependence. CFA of W3 and W5 adult responses to all 31 ND symptoms (7 DSM-IV; 7 mFTQ; 17 NDSS) suggested that a single strong primary factor was associated with variability among symptoms across each of the two waves. Eigenvalues for the first factor were 12.9 and 13.4, and for the second factor 2.7 and 3.4 at W3 and W5, respectively. Median symptom loading on the first factor was 0.65 (Inter Quartile Range = 0.56–0.76) and 0.63 (Inter Quartile Range = 0.48–0.77) at W3 and W5, respectively. Table 1 presents fit indices for each of the three models. Factor loadings can be obtained from Table 2 using appropriate formulas (Takane and de Leeuw, 1987). The hierarchical model provided the strongest fit indices. The multidimensional model with three related factors produced strong correlations among the factors that were on average .70 (SD = .11) and .62 (SD = .19) at W3 and W5, respectively. The loading of each symptom within unidimensional models changed on average only by 0.02 (SD = .06) and 0.06 (SD = .07) at W3 and W5, respectively, after controlling for the influence of multiple secondary dimensions in the hierarchical CFA model. The results support the potential utility of a primary dimension of ND and suggest the superiority of a hierarchical over a unidimensional IRM. 3.2.2. Linking symptoms to the continuum. The level of ND severity for each DSM-IV, mFTQ, and NDSS symptom as estimated by the hierarchical IRM is indexed by the b values presented in Table 2. These severity estimates are scaled with 0 representing the average level of ND and allow direct comparisons of symptom differences in standard deviation units (SD = 1). Multiple category items are assigned coefficients for each increased response option so that mFTQ item #1 gets three coefficients (moving from category 1 to category 2, from 2 to 3, and from 3 to 4), but only one common slope estimate. Positive values reflect symptoms likely to be endorsed among those with above average levels of ND; negative values reflect symptoms likely to be endorsed among those with below average levels of ND. ND symptoms with the lowest severity level or b values included ‘loss of control over smoking’ (NDSS #4), ‘smoking 2–5 cigarettes per day’ (mFTQ #1) and ‘smoking the same number of cigarettes day to day’ (NDSS #10). ND symptoms with the highest severity levels included ‘difficulty refraining from smoking in forbidden places’ (mFTQ #5) and reports of ‘smoking 16 or more cigarettes per day’ (mFTQ #1), along with ‘neglecting important activities due to smoking’ (DSM-IV #6). The full range of symptom severity is listed in Table 2.

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3.2.3. Replication of the model over time. The combined DSMIV, mFTQ and NDSS symptoms were evaluated for differences in discrimination (a parameter) and severity (b parameter) over assessments. This DIF analysis allowed each severity and each discrimination estimate to be isolated and tested across waves while controlling for all other symptoms (Thissen, 1991). None of the 31 symptoms exhibited statistically significant DIF in severity with effect sizes > 0.50 (Cohen’s d = bW5 − bW3 ) or discrimination across waves (see Table 2) and no further evaluation of DIF from each wave was conducted. 3.2.4. Linking loss of autonomy to the continuum. To examine the relationship of reports of “feeling addicted to or hooked on nicotine” to the continuum, we added this symptom to the IRM model along with the 31 symptoms of the other three ND measures. Fig. 1 displays the five response options for this item and Table 2 lists estimates of its severity relative to other symptoms (bW3 for ‘Probably Not’ through ‘Definitely Yes’ ranged from −1.39 to −0.21). This symptom had low severity estimates, with those endorsing the item falling below the 40th percentile for smokers. Despite several response options, respondents predominantly used the lowest and highest options. Additional response options did not appear to offer unique information about ND levels (Fig. 1(a)). DIF analyses suggested discrimination and severity estimates were similar at W3 and W5 (see Table 2). 3.2.5. Linking ND scales to the model and the selection of an informative subset of items. To summarize the performance of each instrument, we computed a test information function of the DSMIV, mFTQ, NDSS, and loss of autonomy across levels of ND at the final assessment (W5) (see Fig. 2). The test information function is a direct reflection of the standard error of each instrument and indicates where at each point of the latent continuum each instrument provides the most information about ND. Symptoms with higher discrimination yield more information. Instruments that cover more symptoms (i.e., NDSS) potentially contribute more information about levels of ND than measures with fewer symptoms (i.e., DSM-IV, mFTQ, loss of autonomy). No single instrument captured the full range of ND. The five-level loss of autonomy symptom provided information within the lowest levels of ND. Overall, the NDSS included multiple symptoms targeting similar levels of ND and provided the most information within the lowest 50% of adults in this sample. The majority of mFTQ items were observed within the highest levels of ND and the DSM-IV items were arrayed in the middle and upper third of the continuum of dependence severity. An instrument designed to assess a broad range of ND using symptoms from all three instruments would include the most informative symptoms within the lowest (ND < 0) and the highest (ND > 0) 50% of the distribution. The lowest group included ‘smoking regularly throughout the day’ (NDSS #8), ‘Need to smoke more to be satisfied’ (NDSS #16), ‘Can smoke much more now’ (NDSS #17), and ‘Worry that you will run out’ (NDSS #7). The second group of symptoms in adults with highest levels of ND included being ‘Unable to quit’ (DSM #4), ‘Withdrawal’ (DSM #2), ‘Use despite problems’ (DSM #7), ‘Time to first cigarette’ (mFTQ #3), ‘Smoking if ill in bed (mFTQ #6), and ‘Neglect important activities’ (DSM #6). Thus, a 10-item instrument consisting of these ten items would capture a broad range of ND. 3.3. Comparison of symptom reports by adults and adolescents After excluding symptoms found to perform poorly among adolescents, we compared adult and adolescent responses to the 7 DSM-IV, 6 mFTQ (without mFTQ #2), and 14 NDSS (without NDSS #3, #10, #16) found previously to provide consistent information about levels of ND among adolescents (Strong et al., 2009),

Symptoms

Adults Wave 3 (n = 270) %

b

%

1.26 1.78 1.38 1.20 1.35 1.15 2.00 2.35 1.23 1.50 1.00 0.88 1.40 1.02 1.58 2.24 2.06

−0.21 −0.78 −0.17 −2.11 0.66 1.66 −0.12 −1.04 −1.32 −1.51 −0.56 0.02 −1.28 −1.33 −0.73 −0.27 −0.18

3.85

1.12 (1.54)

– −1.50 −0.99 −0.74 −0.21

b

d

G2 (df)

% difference > 0 a

b

42.9 33.7 49.0 27.6 15.3 3.4 14.3

−1.07 −0.79 0.31 0.58 0.00 −0.42 0.24

33.10 12.60 1.70 4.90 0.00 3.60 1.60

11.4 93.8 – 40.7 – – –

98.9 99.9 – 99.9 – – –

6.50(5)

55.6

0.92

29.50

86.0

100.0

59.9

1.10

30.40

75.4

100.0

0.70(2) 3.30(4)

94.8 16.0

– 0.29

– 1.10

– 61.1

– 90.1

97.3 17.1

– 0.30

– 1.60

– 68.9

– 91.6

48.0 17.0 15.0 24.0

0 −0.13 0.02 −0.10 0.43 −0.05 0.13

1.30(2) 3.70(2) 4.30(2) 1.30(2)

20.5 21.2 4.8 13.0

– – 0.97 1.18

23.10 9.80 11.50 25.30

99.6 92.2 53.0 74.1

99.7 67.2 97.0 97.3

26.2 17.3 6.1 6.2

0.30 – 0.50 1.49

7.90 11.80 5.10 24.40

66.8 96.3 78.4 81.9

91.9 54.5 92.4 100.0

55.0 69.0 48.0 85.0 41.0 23.0 52.0 77.0 78.0 84.0 59.0 56.0 73.0 75.0 70.0

−0.08 −0.15 −0.30 −0.54 0.23 0.49 −0.12 −0.04 0.16 0.22 −0.05 0.29 −0.25 0.20 −0.04

2.10(2) 1.70(2) 4.50(2) 5.10(2) 2.70(2) 3.40(2) 1.70(2) 0.20(2) 1.10(2) 1.80(2) 2.30(2) 2.10(2) 1.70(2) 1.30(2) 1.80(2)

47.6 45.0 38.0 66.2 39.4 14.7 22.5 51.3 59.6 59.6 59.6 37.8 64.6 63.4 61.1

– 0.01 – 0.57 – −0.48 0.73 0.01 0.08 – −0.46 – −0.26 0.00 −0.32

18.30 0.30 – 4.40 25.90 3.30 16.50 0.00 0.30 – 18.50 10.30 1.60 1.80 13.90

98.8 – – 76.8 99.6 – 88.0 – – – 94.2 99.8 – – 70.2

83.7 – – 96.3 67.6 – 100.0 – – – 98.7 76.1 – – 96.0

49.0 48.0 42.6 64.3 33.3 14.6 27.6 54.8 68.6 69.0 60.2 46.6 72.1 73.5 60.2

−0.30 −0.06 – – 0.09 0.12 0.41 0.05 0.04 – – – −0.52 −0.31 −0.15

15.40 0.90 – 13.60 2.80 0.90 4.90 0.60 2.30 – 20.90 8.60 14.40 4.30 8.80

86.4 – – 98.8 63.5 – 69.0 – – – 99.3 98.9 69.2 63.0 59.8

97.4 – – 95.0 68.4 – 99.9 – – – 97.2 64.8 99.0 82.0 83.7

57.0

−0.03

4.30(2)

47.6

−0.45

18.90

71.9

63.0

49.0

–

36.10

96.7

100.0

3.99 (1.47)

–

5.20(4)

0.95

36.80

50.0

100.0

0.89

44.20

62.0

100.0

1.85

56.0 70.0 55.0 87.0 36.0 19.0 55.0 78.0 77.0 82.0 61.0 50.0 78.0 75.0 68.0 59.0 56.0

a

%

99.6 98.5 – 100.0 – – –

1.19

0.95 0.90 1.39 0.76

% difference > 0

90.1 98.8 – 84.2 – – –

1.8

50.0 17.0 19.0 27.0

(df)

28.00 27.80 3.40 6.30 5.70 4.40 5.40

32.0 32.0 65.0 50.0 22.0 3.0 28.0

0.76 1.20

d

Adolescents Wave 5 DIF (n = 296)

−1.14 − −0.33 0.68 0.24 0.64 0.66

0.83 0.98 −0.61 0.06 1.58 3.57 1.14

67.0 1.43

%

G2

45.9 35.2 52.4 24.8 16.0 4.8 13.0

0.82 1.44 1.70 2.10 1.22 1.28 1.30

67.0 1.38

−0.19 −0.07 0.13 −0.08 −0.11 0.39 −0.08

(df)

Adolescents Wave 3 DIF (n = 253)

2.20(2) 3.40(2) 2.70(2) 2.50(2) 2.40(2) 1.50(2) 0.20(2)

37.0 30.0 63.0 48.0 22.0 4.0 28.0

– −1.86 1.77 3.54 4.78 −1.03 – −0.49 0.46 1.79 0.04 2.10 1.49 1.56

d

G2

0.29 0.19 0.54 0.33 −0.03

0.26 −0.12 0.02 −0.07

Note. a = Discrimination; b = Symptom severity; d = Cohen’s effect size estimate for DIF reported unless non-uniform DIF was identified; G2 = Likelihood Ratio Test with 2, 4, or 5 degrees of freedom and values ≥ 6.0, 9.5, 11.1 considered significant (p < 0.05), respectively. Standardized effect sizes are not provided for symptoms with significantly different discrimination estimates (e.g. non-uniform DIF) as evidenced by more than 95% of posterior sampled comparisons greater than zero. a Items with multiple response options report means rather than percentage endorsed and initial response options do not have severity estimates.

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DSM-IV 1. Tolerance 2. Withdrawal 3. Impaired control 4. Unable to quit 5. Great deal time spent using tobacco 6. Neglect important activities 7. Use despite physical or psychological problems mFTQ ¯ 1. Daily quantity smokeda (x) 2–5 6–15 16–25 >25 2. Inhaling smoke ¯ 3. Time to first cigarettea (x) Between 31 and 60 min Between 6 and 30 min Within the first 5 min 4. First is most difficult to give up 5. Difficulty refraining 6. Smoking if ill in bed 7. Smoking more during first 2 h NDSS 1. Need to smoke to feel less restless 2. After a few hours, crave cigarettes 3. Cravings like in the grip of an unknown force 4. Feel a sense of control over smoking (reversed) 5. Avoid places that do not allow smoking 6. Rather not travel by airplane due to nonsmoking 7. Worry that you will run out of cigarettes 8. Smoke regularly throughout the day 9. Smoke same on weekends as on weekdays 10. Smoke same number day to day 11. Number changes day to day 12. Normal not to have another for hours 13. Number you smoke influenced by other things 14. Number you smoke not affected much by other things 15. Amount you smoke has increased 16. Need to smoke a lot more to be satisfied 17. Can smoke much more now before you feel anything Loss of autonomy ¯ 1. Feel addicted to or hooked on cigarettesa (x) SD Probably Not Perhaps Probably Yes Definitely Yes

a

Replication at Wave 5 (n = 260)

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Table 2 This table provides a descriptive summary of symptom frequency (%) for adults and adolescents at waves 3 and 5, respectively. For adults at Wave 3, we present item response model estimated discrimination (a) and severity (b) for each symptom from the DSM-IV, mFTQ, NDSS and loss of autonomy. Differential Item Functioning (DIF) results include standard effect size estimates (d) for differences in symptom severity, multiple degree of freedom likelihood ratio tests (G2 ), and follow-up Bayesian tests of the percentage of times comparisons of random draws from posterior estimates of a and b symptom parameters differed (% Difference > 0). DIF analyses assessed replication of symptom characteristics from adult responses (W3 and W5) and compared adolescent and adult symptom responses at Wave 3 and at Wave 5.

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Fig. 1. Probability of endorsing response options with increasing degrees of severity on the loss of autonomy symptom (‘Feeling Hooked on Cigarettes’) among adults and adolescents among Wave 3 smokers. As levels of nicotine dependence increase, smokers became less likely to report ‘Definitely Not’. Additional graded responses did not reflect additional distinctions among smokers and responses and were dichotomized prior to making comparisons between adults and adolescents.

plus the loss of autonomy symptom. Response frequencies for W3 and W5 are presented in Table 2 and more elaborate psychometric properties of the DSM-IV, mFTQ, and NDSS symptoms among adolescents are presented in Strong et al. (2009). In this prior study, we described how W3 and W5 responses to ND symptoms were best characterized dichotomously among adolescents. Similarly, in the current study, when examining the additional loss of autonomy symptom among these same adolescents, we find little evidence of added information from the multiple response options. Dichotomizing the loss of autonomy symptom would not result in substantial loss of information regarding levels of ND among adults or adolescents. Prior to DIF analysis, adult and adolescent responses to the mFTQ #1 were dichotomized at ‘>1 cigarette each day’ and mFTQ #3 at reports of ‘smoking < 30 min after waking’ to be consistent with previous analyses of adolescent responses (Strong et al., 2009). Below, we describe the symptoms from each instrument with no significant DIF among adults and adolescents, those with uniform DIF in severity alone (b), and those with non-uniform DIF, or differences in discrimination (a). Four of the seven DSM-IV symptoms evidenced similar relationships to levels of ND across adolescent and adult smokers at both the W3 and W5 assessments. However, we found evidence of uniform DIF on DSM-IV symptoms of ‘tolerance’, ‘withdrawal’, and ‘unable to quit’. Adolescents were significantly more likely to report DSM-IV symptoms of ‘tolerance’ and ‘withdrawal’ at lower levels of ND than adults (d range = −1.07 to −1.14), and being ‘unable to quit’ at significantly higher levels of ND than adults (d range = 0.58–0.68). As regards the mFTQ, ‘time to first cigarette’ (mFTQ #3) maintained consistent relationships with ND across adolescents and adults at both W3 and W5. Reports of ‘smoking more than one cigarette each day’ (mFTQ #1), ‘smoking if ill in bed’ (mFTQ #6), and ‘smoking more in the first two hours of the day’ (mFTQ #7), each had significant uniform DIF. These symptoms were associated with higher levels of ND for adolescents than adults (d range = 0.50–1.49). Two mFTQ symptoms had significant nonuniform DIF at either the W3 or W5 assessments: ‘reporting that the first cigarette is the most difficult to give up’ (mFTQ #4) showed relatively stronger relationship to overall levels of ND among adolescents than adults only at W3; ‘difficulty refraining’ (mFTQ #5) was slightly more discriminating among adults than adolescents only at Wave 5.

Six of the 14 NDSS symptoms maintained consistent relationships with ND across adolescents and adults at both W3 and W5. These included symptoms describing ‘craving’ (NDSS #2) and ‘tolerance’ (NDSS #15), reporting that ‘smoking was not affected by other things’ (NDSS #14), ‘smoking regularly throughout the day’ (NDSS #8), ‘smoking the same on weekends and weekdays’ (NDSS #9), and ‘preferring not to travel by airplane’ (NDSS #6). One item, ‘Worrying that you will run out of cigarettes’ (NDSS #7), evidenced uniform DIF at both waves and was associated consistently with higher levels of ND among adolescents than adults (d range = 0.41–0.73). By contrast, while reporting that ‘the number of cigarettes you smoke is influenced by other things’ (NDSS #13) also evidenced significant uniform DIF only at W5, this symptom was endorsed at lower levels of ND among adolescents than adults (d = −0.26 to −0.52). Six symptoms generated non-uniform DIF at the W3 or W5 assessments: ‘smoke more to feel less restless’ (NDSS #1), ‘feel a sense of control’ (NDSS #4), ‘avoid friends who do not smoke’ (NDSS #5), ‘number changes day-to-day’ (NDSS #11), normal not to have one for hours’ (NDSS #12), ‘smoke more now before you feel anything’ (NDSS #17).

Fig. 2. Test information functions for the DSM-IV, mFTQ, NDSS and loss of autonomy measures among adults at Wave 5. By including several well discriminating symptoms, the NDSS provides substantial information about the lowest levels of nicotine dependence. Both mFTQ and DSM-IV provide information within regions of the continuum not captured by the NDSS symptoms.

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higher NDSS scores in the lower regions of the continuum (i.e., ND < 0). Conversely, adolescents’ scores on the mFTQ are expected to be lower than adults’ throughout all but the mid-range of ND (ND = 0–1). Expected true score curves also depict the level of ND within which scores on each measure would be expected to rise. For example, the NDSS scores increase rapidly throughout the lower regions of ND (ND = −1 to 0) while DSM-IV and mFTQ scores rise primarily throughout higher levels of ND (ND > 0). These results suggest the potential for complementarity in measurement from the NDSS, DSM-IV and mFTQ instruments. As noted above, sets of symptoms from each instrument may generate more efficient information about the broad continuum of ND than any instrument alone. 3.4. Concurrent validity among adults and adolescents

Fig. 3. Expected true score curves for DSM-IV, mFTQ, and NDSS for adults and adolescents at Wave 5. These curves display the net effect of Differential Item Functioning (DIF) on the relationship between scores from each measure and levels of nicotine dependence. Adolescents would be expected to show more DSM-IV symptoms throughout the higher range of ND, lower scores on mFTQ in all but the central ranges of ND and higher NDSS scores throughout the lower ranges of ND.

The loss of autonomy item also exhibited significant uniform DIF at both W3 (d = 0.95) and W5 (d = 0.89), with adolescents reporting loss of autonomy at higher levels of ND than adults. 3.3.1. Impact of DIF on ND scales among adults and adolescents. We computed sets of expected true score curves that depict separately the relationships between increases in the summed scores of items within each of the three scales and increases in levels of ND for adults and adolescents. The net effect of DIF on the expected true scores on each of the three ND measures in each group is depicted in Fig. 3. Adolescents are expected to report more DSM-IV symptoms than adults beginning within the region of the continuum associated with above average levels of ND (i.e., ND > 0) and to receive

There was a strong linear relationship at each wave between estimated levels of ND with levels of current cigarettes per day among adults (polyserial correlations = 0.73, 0.66, ps < .05) and adolescents (polyserial correlations = 0.66, 0.73, ps < 0.05). ND levels were also related to current frequency of smoking among adults (polyserial correlations = 0.64, 0.65, ps < .05) and adolescents (polyserial correlations = 0.55, 0.69, ps < .05). Prior to evaluating patterns of change in ND over time, we identified adults (n = 231) and adolescents (n = 161) who reported smoking within the past 30-days at both W3 and W5. We then used the Bayesian hierarchical IRM for the symptoms from the three scales to generate the posterior distribution of ND scores that were placed on the same scale by adjusting for DIF across adults and adolescents. Using a DIF-adjusted IRM-based score for ND allowed direct comparison of ND across waves and across adults and adolescents. Compared to adults, adolescents reported lower levels of ND symptoms at W3 (d = −0.53, SD = 0.89), differences that were similar one year-later at W5 (d = −0.47, SD = 0.91). On average, adults (mean change = 0.37, SD = 6.67) and adolescents (mean change = 0.46, SD = 6.69) experienced only small changes in levels of ND over the one-year interval although there was a high degree of individual variability. We assessed the predictors of changes in ND among adults and adolescents who reported smoking at both waves. We estimated linear models controlling for gender (B = 0.09, SE = 0.09, p < 0.29), race/ethnicity [African-American (B = 0.14, SE = 0.07, p < 0.05) and Hispanic (B = 0.00, SE = 0.08, p = 0.97) versus white], number of cigarettes smoked per day at W3 (B = 0.04, SE = 0.01, p < 0.001) and at W5 (B = 0.03, SE = 0.01, p < 0.001). This latter term, conditional on levels of cigarettes per day at W3, was significantly related to change in ND. Further, we observed a significant difference in the relationship between changes in the number of cigarettes smoked per day and changes in ND between adults and adolescents (B = 0.02, SE = 0.01, p < 0.02). This interaction effect indicated that changes in number of cigarettes smoked per day were associated with larger changes in ND for adolescents than adults. To assess the advantage of adjusting for observed DIF, we compared the assessment of change in ND derived using a raw count of symptoms from each wave with the DIF adjusted posterior ND scores. The observed difference in the magnitude of change in ND between adults and adolescents based on DIF-adjusted ND scores was statistically significant but was significantly reduced (BDIFadj = 0.23; 95%CI = 0.07–0.40, p < 0.05) compared to assessments based on a count of symptoms, (Bcount = 0.44; 95%CI = 0.22–0.66, p < 0.05). These results support the concurrent validity of ND given the expected positive relationships with changes in the number of cigarettes smoked per day. Fig. 4 presents W3 and W5 levels of ND among adults and adolescents characterized by varying levels of changes in the number of cigarettes they smoked over the one-year interval. Each panel

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Fig. 4. W3 and W5 levels of nicotine dependence (ND) among (A) adults (n = 231) and (B) adolescents (n = 160) reporting decreasing smoking, smoking the same amount or increasing smoking in the past 30-days. Points above the centerline represent increases in ND and points below the centerline represent decreases in levels of ND.

includes a centerline with departures above the line signifying increases and departures below signifying decreases in ND levels from W3 to W5. Although overall patterns of change in the number of cigarettes smoked per day and corresponding changes in ND were similar across adults and adolescents, the magnitude of changes in ND differed significantly. When decreasing by fewer than 10 cigarettes, adolescents had moderate (d = −0.48) but higher decreases than adults (d = −0.28) in levels of ND. When increasing by greater than 10 cigarettes, adolescents reported greater increases in ND than adults, with average changes of d = 1.33 and −0.08, respectively. As shown in the far right panels of Fig. 4, larger increases in smoking (more than 10 cigarettes) tended to be concentrated among adolescents with lower initial levels of ND at W3 (ND < 0) and were associated with larger increases in ND at W5 (observations are well above the center line). However, adults who reported similarly large increases in smoking had relatively higher W3 levels of ND (ND > 0) and exhibited relatively modest changes in ND at W5. Given the variability in ND at W3, this difference between adults and adolescents did not appear to result from differences in baseline values or from a restricted range artifact. W5 indices of ND appear to be sensitive to changes in extensiveness of smoking across a range of initial levels of smoking and ND a year earlier. 4. Discussion and conclusion This study extends to adults efforts to link widely used ND instruments to a stable common continuum of ND first observed among adolescents (Strong et al., 2009) and considers the position of loss of autonomy on the continuum among adolescents and adults. We characterized the relative severity of individual symptoms of ND among adults, established loss of autonomy as a low-level symptom of ND for adults and adolescents, and assessed the impact of observed qualitative differences between the endorsement by adults and adolescents of symptoms on three ND instruments across two waves of assessments. We identified symptoms across each ND instrument, such as tolerance, withdrawal difficulty quitting, and smoking quantity, which differed significantly in endorsement across adults and adolescents despite

consistent relationships to ND within each group. Using comparable ND scores, adolescents reported larger changes in ND over time than adults given similar changes in the number of cigarettes they smoked each day, suggesting that adolescents may be more sensitive than adults to the effects of nicotine. Despite a number of differences in the level of ND within which adults and adolescents report certain symptoms, the net effect of these symptom-level differences on total scores from each instrument could be adjusted to generate directly comparable adult and adolescent measures of ND. The results increase confidence in the ability to use symptoms from common instruments to describe phenotypic heterogeneity in ND across important developmental periods.

4.1. There is a common latent continuum underlying the DSM-IV, FTQ and NDSS among adults similar to that observed among adolescents Consistent with the adolescent data, symptoms measured by the DSM-IV, mFTQ and NDSS covered complementary ranges of ND; the combined index of ND replicated across waves of assessment, had good reliability, strong relationships with concurrent smoking and expanded phenotypic assessment of ND. The majority of mFTQ symptoms were observed within the highest levels of ND. As in other samples (MacPherson et al., 2008; Strong et al., 2009), the ‘inhale’ symptom and ‘smoking more in the first hours of the day’ were less discriminating than other mFTQ symptoms. The severity of DSM-IV symptoms followed an expected pattern for adults, as described for adolescents in Kandel et al. (2007), with four symptoms evidencing statistically similar relationships to levels of ND for both adults and adolescents. The four least severe DSM-IV symptoms (impaired control, difficulty quitting, tolerance and withdrawal) are the most likely to be observed at or below the diagnostic threshold. The DSM-IV provided a broad range of additional symptoms, including ‘use despite problems’ and ‘a great deal of time spent,’ marking high levels of ND severity, and ‘neglecting important activities’ being endorsed at only the highest levels of ND severity.

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As a complement to the more severe symptoms from the DSM-IV and mFTQ, the NDSS provided several symptoms that discriminated among smokers within the lower ranges of ND. ‘Smoking regularly,’ ‘craving,’ and ‘needing to smoke more to feel satisfied’ were among the most discriminating NDSS symptoms within the lowest ranges of ND. The most informative NDSS symptoms were from subscales measuring tolerance, drive to smoke, as well as prioritizing smoking over other behaviors. While the drive and tolerance subscales have been found to provide comparable measurement of ND among daily and non-daily smoking adolescents, NDSS symptoms targeting continuity of smoking (e.g., NDSS #11: ‘number changes day-to-day’) were more discriminating among non-daily than daily smoking adolescents, suggesting differences in characterizing one’s behavior among recent-onset non-daily smokers (Rose and Dierker, 2010a,b). The potential influence of differential assessment of what constitutes a change in consumption patterns given the very different numbers of cigarettes smoked per day typical of regular and intermittent smokers and of smokers of different ages may account for the differential relationships of self-reported continuity of smoking to levels of ND across adolescent and adult smokers. Further examination of differences in smoking behavior among different groups of smokers with more or less regular patterns of smoking and of the relationship of selfreported continuity to levels of ND among adolescent and adults is needed. 4.2. Loss of autonomy is a low-level symptom of ND We evaluated the position of the loss of autonomy symptom on the severity continuum of ND. Smokers who endorsed “feeling addicted to or hooked on cigarettes” were placed within the lowest levels of ND. Smokers within this range would not be likely to smoke more than 2–5 cigarettes each day. However, adolescents were less likely to report loss of autonomy compared to adults with similarly low levels of ND. Adolescents may underestimate the degree to which they are at risk for becoming addicted to nicotine. The data also suggest that adopting recommendations for using loss of autonomy as a diagnostic threshold for ND (DiFranza, 2010) would limit the assessment of variability in levels of ND (c.f. Hughes and Shiffman, 2008) and would result in a different threshold for assigning a ND diagnosis among adolescents and adults. The evaluation of loss of autonomy was limited by the use of one question, although DiFranza indicates that the 10 items in the Hooked on Nicotine Checklist are interchangeable and that endorsement of any of the items signifies loss of autonomy and nicotine dependence (DiFranza et al., 2002; 2008). Although we did not find support for increasing the number of response options for this symptom, more extensive items may improve the assessment and the understanding of the developmental course of this symptom of ND. 4.3. Adolescents not only share similarities with adults but also show differences Identification of core features of ND from each instrument that were expressed differently by adults and adolescents suggest that the assessments of ‘cigarettes smoked each day’ and the symptoms of ‘tolerance’ and ‘withdrawal’, as indicators of ND, may be particularly vulnerable to the respondent’s age. We found significant relationships between changes in ‘number of cigarettes smoked per day’ with changes in levels of ND in both groups. Furthermore, when compared to raw symptom counts, the use of ND scores that were statistically adjusted to equate adult and adolescent measures appeared to reflect more accurately the changes in ND over time. However, similar changes in the number of cigarettes smoked over one year, whether increases or decreases, were associated with larger changes in levels of ND for adolescents than adults, regardless

of statistical adjustments. The slope is steeper among adolescents than adults. As a criterion for concurrent validity, cigarettes smoked per day may require statistical adjustment when comparing the relative strength of associations across each age group. These epidemiological findings are partially consonant with animal models of adolescent vulnerability to nicotine dependence (O’Dell, 2009). Psychobiological models based on well-controlled animal studies have identified consistently that, when compared with adults, adolescent rodents are more vulnerable to extensive and sustained consumption given similar exposure to nicotine (for review see O’Dell, 2009). Adolescent mice are more sensitive than adult mice to the effects of nicotine and experience more rewarding (positive) effects than mice first exposed to nicotine as adults. However, adolescent mice display higher tolerance to the effects of nicotine and experience fewer (negative) withdrawal signs than adults (Belluzzi et al., 2004; Levin et al., 2007; Kota et al., 2007). The enhanced positive and reduced negative effects are thought to increase the vulnerability of adolescent mice to nicotine dependence (O’Dell, 2009). Consistent with these findings, evidence from this epidemiological sample indicated that, compared with adults, adolescents’ reports of ND symptoms were more sensitive than adults’ reports to the number of cigarettes they smoked. Adolescents were also more likely to report symptoms reflecting higher tolerance, such as could ‘smoke more without feeling nauseated or dizzy’ (DSM #1), were ‘needing to smoke more to get the same effect’ (NDSS #17) and that they experienced the withdrawal syndrome when they stopped smoking or that they ‘smoked to keep from feeling bad’ (DSM-IV #2) at lower levels of ND than adults. Consistent with psychobiological models, the findings suggest an enhanced sensitivity of adolescents to nicotine exposure resulting in higher ND given the same number of cigarettes smoked per day and higher tolerance to the negative effects of smoking. However, within the DSM-IV, we observed a seeming paradox with adolescents reporting ‘tolerance’ and ‘withdrawal’ at lower levels of ND while reporting also being ‘unable to quit’ at higher levels of ND than adults. These results suggest that, because adolescents have smoked for a relatively short time, they have initiated fewer quit attempts, they have had fewer experiences with difficulties quitting, and experience fluctuations in smoking behavior that may make quitting appear easier to them than to adults. Conversely, adults may readily report ‘difficulty quitting’ given a common experience of prior failed attempts at cessation. 4.4. A combined measure enriches our understanding of ND Establishing a common metric with broad descriptions of smoking phenotypes for ND contributes to improvement in understanding the etiology, course, and treatment needs of individuals with ND across the lifespan. Our results add to a growing literature suggesting the benefits of assessing commonalities among individual symptoms of ND along a continuum (Tiffany et al., 2004). We may begin to see overlap among symptoms as opportunities for increasing the reliability of measures, for selecting a small number of symptoms to generate an efficient short-form, for identifying under-assessed regions of the continuum, for identifying an important threshold, and for signaling the need for developing new symptom questions (Reise and Waller, 2009). Researchers interested in making comparisons of ND symptom counts across age groups could generate equivalent metrics by selecting DIFfree symptoms or by using model-based scoring that incorporates the age of respondents, or other individual characteristics, when assigning item parameters and computing ND scores. For example, researchers limited to single symptom indices may consider using the ‘time to first cigarette’ mFTQ symptom given its stability across waves and across adult and adolescent respondents and its predictive validity among adults within clinical trials (Baker et al.,

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2007; Muscat et al., 2009). The ‘cigarettes smoked each day item may be less desirable given its differential relationships to levels of ND among adolescents and adults in the current study and in subgroups defined by gender, race, socioeconomic (Strong et al., 2001) and psychiatric risk factors (Strong et al., 2010). However, we believe that it is important to include number of cigarettes smoked as a separate item in the assessment battery, if not in an ND scale, to document that number of cigarettes smoked per day is differentially related to ND in different subgroups of the population. A more complete assessment of current ND may be accomplished by (1) locating symptoms with severity values within successive ND intervals; (2) identifying the most discriminating symptoms within each interval; (3) assembling symptoms reflecting important components of ND that minimize DIF. An example includes the ten most informative and complementary symptoms from the NDSS, DSM-IV and mFTQ described in Section 3.2.5. However, one symptom may be less useful for adolescents (NDSS #16) and could be eliminated, leaving a set of nine symptoms. Alternatively, using model-adjusted scoring, additional symptoms previously identified as having DIF may be included in instruments that combine symptom across measures or in flexible computer-based administration. By using a model-based methodology, we provide a practical method for linking multiple existing symptoms of ND and a basis for beginning to develop sets of symptoms to select efficient instruments and flexible computer-assisted assessments for a broad range of research and clinical applications among adults and adolescents.

4.5. Limitations This investigation relied upon a community sample of smokers. While increasing generalizability to a broad range of smokers, this sample will not generalize to clinical settings where higher levels of smoking and ND may predominate. The adult sample was composed almost exclusively of mothers. Although large gender differences in response to ND symptoms have not been observed in community samples of smokers (Rose et al., 2010; Saha et al., 2010; Strong et al., 2003a,b), our predominately female sample may limit generalizability of the current adult and adolescent comparisons. Since 25% of these adolescents were the children of the adults in the sample, similarities within families might have reduced our ability to estimate the magnitude of observed DIF. On the other hand, the samples were drawn from the same communities, thus controlling to some extent for sociodemographic and psychosocial factors that could account for the endorsement of ND symptoms. In additional analyses, we found that excluding parent–child dyads from the adult and adolescent samples did not affect the significance of the DIFs. Another potential limitation is that four DSM-IV criteria were measured using two questions. The assessment of a single criterion with multiple items that themselves differ in severity may be problematic (e.g., for withdrawal, equating the symptom of ‘not feeling well when stopped smoking,’ a potentially severe symptom, with ‘smoking to keep from feeling bad,’ a potentially less severe symptom). Compound items may have impacted negatively on the estimated performance of the DSM-IV symptoms and more evaluation of the improved reliability and expanded breadth of multiple symptoms used to assess single criteria is needed. Establishing a common continuum of ND facilitates exploration of the etiology, course, and treatment needs of adults and adolescents with ND. These results suggest that the same assessment can be implemented irrespective of age, in adolescence, when nicotine dependence has its onset, and in adulthood, when patterns of nicotine dependence are well established. The results also suggest that adolescent are more vulnerable than adults to experiencing symptoms of nicotine dependence upon smoking.

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Role of funding source Work on this article was partially supported by grants DA016737 from National Institute on Drug Abuse (NIDA) and ALFCU516732301A1 from Legacy (Dr. Kandel, PI) as well as American Cancer Society (ACS: 114051-CPPB; Dr. Strong). The NIDA, Legacy, and ACS 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 Authors, Kandel and Strong, designed the study. Kandel, Griesler and Schaffran collected the data. Author Schonbrun managed the literature searches and summaries of previous related work. Authors Strong and Schaffran undertook the statistical analysis, and all authors contributed to and have approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgements We thank Ayla Durst, who kindly provided assistance with the preparation and proof-reading of the manuscript. References Alterman, A.I., Gariti, P., Cook, T.G., Cnaan, A., 1999. Nicodermal patch adherence and its correlates. Drug Alcohol Depend. 53, 159–165. American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. American Psychiatric Association, Washington, DC. Belluzzi, J.D., Lee, A.G., Oliff, H.S., Leslie, F.M., 2004. Age-dependent effects of nicotine on locomotor activity and conditioned place preference in rats. Psychopharmacology 174, 389–395. Bailey, S.R., Harrison, C.T., Jeffery, C.J., Ammerman, S., Bryson, S.W., Killen, D.T., Robinson, T.N., Schatzberg, A.F., Killen, J.D., 2009. Withdrawal symptoms over time among adolescents in a smoking cessation intervention: Do symptoms vary by level of nicotine dependence? Addict. Behav. 34, 1017–1022. Benjamini, Y., Hochberg, Y., 1995. Controlling false discovery rate: A practical and powerful approach to multiple testing. J. Roy. Stat. Soc. B 57, 289–300. Baker, T.B., Piper, M.E., McCarthy, D.E., Bolt, D.M., Smith, S.S., Kim, S.Y., Colby, S., Conti, D., Giovino, G.A., Hatsukami, D., Hyland, A., Krishnan-Sarin, S., Niaura, R., Perkins, K.A., Toll, B.A., 2007. Time to first cigarette in the morning as an index of ability to quit smoking: implications for nicotine dependence. Nicotine Tob. Res. 9 (4 Suppl.), S555–S570. Bentler, P.M., 1990. Comparative fit indices in structural models. Psychol. Bull. 107, 238–246. Bentler, P.M., Bonnett, D.G., 1980. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull. 88, 588–606. Birnbaum, A., 1968. Some latent trait models and their use in inferring an examinee’s ability. In: Lord, F.M., Novick, M.R. (Eds.), Statistical Theories On Mental Test Scores. Addison-Welsley, Reading. Breslau, N., Johnson, E.O., 2000. Predicting smoking cessation and major depression in nicotine-dependent smokers. Am. J. Public Health 90, 1122–1127. Browne, M.W., Cudeck, R., 1993. Testing Structural Equation Models. Sage, Newbury Park. Center for Disease Control, 2008. Smoking-Attributable Mortality, Years of Potential Life Lost, and Productivity Losses—United States, 2000–2004. Center for Disease Control, Atlanta, GA. Chang, H.H., Mazzeo, J., 1994. The unique correspondence of item response functions and item category response functions in polytomously scored item response models. Psychometrika 59, 391–404. Courvoisier, D., Etter, J.F., 2008. Using item response theory to study the convergent and discriminant validity of three questionnaires measuring cigarette dependence. Psychol. Addict. Behav. 22, 391–401. Dierker, L.C., Donny, E., Tiffany, S., Colby, S.M., Perrine, N., Clayton, R.R., 2007. The association between cigarette smoking and DSM-IV nicotine dependence among first year college students. Drug Alcohol Depend. 86, 106–114. DiFranza, J.R., Savageau, J.A., Fletcher, K., Ockene, J.K., Rigotti, N.A., McNeill, A.D., Coleman, M., Wood, C., 2002. Measuring the loss of autonomy over nicotine use in adolescents: the DANDY (Development and Assessment of Nicotine Dependence in Youths) study. Arch. Pediatr. Adolesc. Med. 156, 397–403. DiFranza, J., 2010. A new approach to the diagnosis of tobacco addiction. Addiction 3, 381–382.

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