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. Author manuscript; available in PMC: 2023 May 1.
Published in final edited form as: Drug Alcohol Depend. 2022 Mar 17;234:109411. doi: 10.1016/j.drugalcdep.2022.109411

Validity of the DSM-5 tobacco use disorder diagnostics in adults with problematic substance use

Dvora Shmulewitz a,b,*, Eliana Greenstein b, Malka Stohl b, David S Fink b, Stephanie Roncone b, Claire Walsh b, Efrat Aharonovich b, Deborah S Hasin a,b,c
PMCID: PMC9035622  NIHMSID: NIHMS1792308  PMID: 35338898

Abstract

Background

DSM-5 tobacco use disorder (TUD) nosology differs from DSM-IV nicotine dependence (ND) by including craving and DSM-IV abuse criteria, a lower threshold (≥2 criteria), and severity levels (mild; moderate; severe). We assessed concurrent and prospective validity of the DSM-5 TUD diagnosis and severity and compared validity with DSM-IV ND diagnosis.

Methods

The sample included U.S. adults with current problematic substance use and past year cigarette smoking (N=396). Baseline assessment collected information on DSM-IV ND and DSM-5 TUD criteria, smoking-related variables, and psychopathology. Over the following 90 days, electronic daily assessments queried smoking and cigarette craving. Variables expected to be related to TUD were validators: cigarette consumption, cigarette craving scale, Fagerström Test for Nicotine Dependence, and psychiatric disorders. Regression models estimated the association of each validator with DSM-5 TUD and severity levels, and differential association between DSM-5 TUD and DSM-IV ND diagnoses.

Results

DSM-5 TUD and DSM-IV ND were associated with most baseline validators (p-values<0.05), with significantly stronger associations with DSM-5 TUD for number of days smoked (p=.023) and cigarette craving scale (p=.007). Baseline DSM-5 TUD and DSM-IV ND predicted smoking and craving on any given day during follow-up, with stronger associations for DSM-5 TUD (association difference [95% CI%]: any smoking, 0.53 [0.27, 0.77]; number of cigarettes smoked, 1.36 [0.89, 1.78]; craving scale, 0.19 [0.09, 0.28]). Validators were associated with TUD severity in a dose-dependent manner.

Conclusion

DSM-5 TUD diagnostic measures as operationalized here demonstrated concurrent and prospective validity. Inclusion of new criteria, particularly craving, improved validity and clinical relevance.

Keywords: DSM-5, tobacco use disorder, nicotine dependence, concurrent validity, prospective validity

1. INTRODUCTION

Tobacco use and dependence cause substantial preventable morbidity and mortality worldwide (Center for Disease Control and Prevention, 2021; Ng et al., 2014; U.S. Burden of Disease Collaborators, 2018; U.S. Department of Health and Human Services, 2014; World Health Organization, 2021) and are associated with decreased functioning and huge economic costs (Ekpu & Brown, 2015; U.S. Department of Health and Human Services, 2014; World Health Organization, 2021). Individuals with nicotine dependence (ND) often have trouble cutting down or quitting use. Thus, a valid measure of ND is important for developing effective strategies to reduce tobacco use. The most widely used systems for diagnosing ND include the Fagerström Test for Nicotine Dependence (FTND) (Heatherton et al., 1991) and the Diagnostic and Statistical Manual of Mental Disorders (DSM) (Agrawal et al., 2011).

The 4th edition of the DSM (DSM-IV) defined ND as ≥3 of 7 dependence criteria. This definition was used widely, in large, important studies (Bidwell et al., 2016; Chang et al., 2019; Grant et al., 2004; Grant et al., 2020; Saha et al., 2010; Schmitz et al., 2003). In 2013, major changes in the 5th edition (DSM-5) included: adding 4 new criteria (3 abuse criteria and craving); lowering the threshold to ≥2; adding a severity indicator based on number of endorsed criteria; and changing the name to tobacco use disorder (TUD) (Hasin et al., 2013). These changes aligned TUD with other substance use disorders (SUD) and addressed key problems with DSM-IV ND (Hasin et al., 2013; Shmulewitz et al., 2013): lack of craving, considered central to TUD (Baker et al., 2012; DiFranza et al., 2010; Hughes et al., 2011; Sayette, 2016); under-diagnosis (Baker et al., 2012); and lack of severity gradings (Baker et al., 2012; Hughes et al., 2011).

To support these changes and provide impetus for utilizing DSM-5 TUD definitions, such measures should have better reliability and validity than DSM-IV ND measures (Hasin et al., 2013; Kendler, 2013), which continue to be used (Chang et al., 2019; Grant et al., 2020; Houston-Ludlam et al., 2019; Munn-Chernoff et al., 2020; Sartor et al., 2021). DSM-5 TUD measures had moderate to excellent reliability (higher than DSM-IV ND) in U.S. general population and clinical samples (Grant et al., 2015; Hasin et al., 2020). Some studies investigated validity (Kendler, 1990) based on association of DSM-5 TUD measures with variables expected to be related. In an Israeli population sample, a symptom count measure of lifetime DSM-5 TUD showed greater validity than a DSM-IV ND count measure (Shmulewitz et al., 2013), but that study did not investigate current binary validity or DSM-5 TUD severity levels (mild; moderate; severe), which may be important for treatment decisions. In a U.S. population sample, DSM-5 TUD and severity levels were validated through associations with psychiatric disorders (Chou et al., 2016), but that study did not include smoking-related validators or compare validity to DSM-IV ND. No studies examined validity among people with problematic substance use or prospective validation, i.e., whether baseline disorder predicts future smoking-related measures.

We investigated the concurrent and prospective validity of DSM-5 TUD measures using cigarette consumption, craving, the FTND, and psychopathology as validators, in data from adults with problematic substance use (Gorfinkel et al., 2021; Hasin et al., 2020; Mannes et al., 2021; Shmulewitz et al., 2021). Such adults are relevant in the U.S. since substance use and disorders are prevalent (Substance Abuse and Mental Health Services Administration, 2020, 2021) and measures of problematic use are increasing (Compton et al., 2019; Han et al., 2020; Hasin et al., 2019; Kariisa et al., 2021; Keyes et al., 2019; Mattson et al., 2021). We addressed these questions: Is binary DSM-5 TUD associated with the validators, with stronger associations than DSM-IV ND? To what extent are DSM-5 TUD severity levels associated with the validators?

2. METHODS

2.1. Participants and Procedures

Participants were 396 adults (≥18 years old) who ever smoked ≥100 cigarettes and smoked at least once in the past year. These participants were from a convenience sample (N=588), combining community residents and inpatients from an addiction treatment program (Gorfinkel et al., 2021; Hasin et al., 2020; Shmulewitz et al., 2021). Individuals who reported binge drinking or illicit drug use (cannabis, cocaine, heroin, non-medical use of prescription opioids) in the prior 30 days or 30 days prior to inpatient admission and ≥1 DSM-5 SUD criterion were eligible. Exclusion criteria included: non-English speaking; significant cognitive, hearing, or visual impairment; currently psychotic, homicidal, or suicidal; and plans to leave the study area. Participants gave written informed consent; Institutional Review Boards of the New York State Psychiatric Institute and South Oaks Hospital approved all procedures. At baseline, participants completed a computerized self-administered questionnaire (SAQ) and trained interviewers administered the Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 version (PRISM-5) (Hasin et al., 2020). Participants were compensated $50. For 90 days after baseline, participants completed a daily electronic data assessment (EDA) of substance use and received $1 for each day, with bonuses up to $50 (Gorfinkel et al., 2021; Shmulewitz et al., 2021).

2.2. Measures

2.2.1. PRISM-5 interview

PRISM-5 is a computer-assisted interview (Columbia University, 2021) that assesses sociodemographic information and DSM-IV/−5 symptoms for psychiatric disorders (Hasin et al., 2020). PRISM-5 and earlier versions show good reliability and procedural validity for psychiatric disorders (Hasin, Samet, et al., 2006; Hasin et al., 2020; Hasin et al., 1998; Hasin, Greenstein, et al., 2015; Hasin, Shmulewitz, et al., 2015; Hasin et al., 1996; Torrens et al., 2004).

2.2.1.1. DSM-IV ND/DSM-5 TUD

Past year criteria (7 dependence, 3 abuse, and craving [Supplementary Figure 1]) were assessed. DSM-IV ND was positive if participants endorsed ≥3 dependence criteria. DSM-IV ND measures show substantial to excellent reliability (DiFranza et al., 2010; Hasin, Hatzenbuehler, et al., 2006; Hasin et al., 2020; Pierucci-Lagha et al., 2005). DSM-5 TUD was positive if participants endorsed ≥2 of 11 TUD criteria. TUD severity was defined by number of criteria endorsed: 0=none (0-1 criteria); 1=mild (2–3); 2=moderate (4–5); and 3=severe (6-11). DSM-5 TUD measures show substantial to excellent reliability (Grant et al., 2015; Hasin et al., 2020) and procedural validity (Hasin, Greenstein, et al., 2015). DSM-IV ND and DSM-5 TUD were outcomes for concurrent validation and predictors for prospective validation. For sensitivity analysis, to determine the effects of adding only craving, an alternate version of TUD was defined, as endorsing ≥2 of 8 criteria (ND plus craving).

2.2.1.2. DSM-5 concurrent validators

Past year DSM-5 alcohol use disorder (AUD) was positive with endorsement of ≥2 of 11 AUD criteria. DSM-5 SUD was assessed for cannabis, cocaine, heroin, hallucinogens, non-medical use of prescription opioids, sedatives, stimulants, and other illicit drugs. Participants with any drug-specific SUD were positive for a drug use disorder (DUD). Past year DSM-5 major depressive disorder (MDD), post-traumatic stress disorder (PTSD), borderline personality disorder (BPD), and antisocial personality disorder (ASPD) were also assessed (Mannes et al., 2021).

2.2.1.3. Other substance use

Past-month use of alcohol, cannabis, hallucinogens, cocaine, heroin, other illicit drugs, and non-medical use of prescription opioids, sedatives, and stimulants constituted control variables for psychopathology validators.

2.2.2. Self-administered questionnaire (SAQ)

Additional concurrent validators came from widely-used, reliable and valid measures related to smoking and mental health (Shmulewitz et al., 2021) in the SAQ. Number of past-month days smoked cigarettes and number of cigarettes smoked per day (CPD) were assessed with the National Cancer Institute Tobacco Use Supplement to the Current Population Survey (Chahine et al., 2011; Soulakova et al., 2012; Trinidad et al., 2011). A craving scale was assessed using the Brief Questionnaire of Smoking Urges (Cox et al., 2001; Tiffany & Drobes, 1991) (Supplemental Table 2), with higher values indicating greater craving (Shmulewitz et al., 2021). The FTND, a widely used, validated measure of past-month cigarette dependence (Baker et al., 2012; Breslau & Johnson, 2000; Colby et al., 2000a, 2000b; Foulds et al., 2006; Heatherton et al., 1991; Hughes, 2006; Hughes et al., 2011; Scharf et al., 2008; Shmulewitz et al., 2013; Transdisciplinary Tobacco Use Research Center Tobacco Dependence et al., 2007) was assessed and scored as described previously (Shmulewitz et al., 2021). The Patient Health Questionnaire (PHQ-9) (Delgadillo et al., 2011; Kroenke et al., 2001; Lowe et al., 2004) assessed nine self-reported depressive symptoms over the previous two weeks, scored as described previously (Shmulewitz et al., 2021).

2.2.3. Electronic data assessment (EDA)

For each of the 90 days after baseline, participants took an electronic survey of substance use; as done previously (Gorfinkel et al., 2021; Shmulewitz et al., 2021), those who responded on ≥1 day were included (N=394). Using any type of phone, participants called in and used an interactive voice response system or an automated texting service to answer 15-21 questions, depending on whether substances were used. Participants were encouraged to call the same time every day. Participants reported if they smoked cigarettes the previous day (yes/no). Those who smoked reported the number of cigarettes smoked (a count variable) and craving (“How much did you want to smoke cigarettes yesterday”; responses ranged from 1 “didn’t want to smoke at all” to 5 “wanted to smoke so badly you couldn’t think of anything else”). The repeated measures for each day were outcomes for prospective validity. Since inpatients were in a smoke-free environment, prospective data for inpatients started from their discharge date.

2.2.4. Covariates

Control variables included sociodemographics (age, sex, race/ethnicity, education), participant type (inpatient/community), substance use, and past two-week substance use treatment at baseline (Shmulewitz et al., 2021).

2.3. Statistical analysis

SAS 9.4 (SAS Institute Inc, 2014) software was used. Descriptives were calculated for disorders (DSM-IV ND, DSM-5 TUD), validators, and control variables, overall and by DSM-5 TUD status.

2.3.1. Differential validity of binary DSM-5 TUD and DSM-IV ND

For each concurrent validator (predictor), bivariate correlated-outcome logistic regression modeled the two disorders (outcomes) simultaneously, adjusting for sociodemographics and participant type. Generalized estimating equations accounted for within-participant correlation (Fitzmaurice et al., 1995). Odds ratios (OR) were reported, as is appropriate in this non-representative sample (Mannes et al., 2021; Shmulewitz et al., 2021) enriched for DSM-5 SUD (Bovbjerg, 2020). OR represent the odds of having disorder among those with vs. without a binary validator or with a unit increase in a count validator. The ratio of OR for DSM-5 TUD/DSM-IV ND indicated differential association. Significance was indicated by 95% confidence intervals (CI) not including 1.0.

For each prospective validator, generalized linear mixed model regression models estimated the association of disorder at baseline (predictor) with the repeated outcome measure on each of the 90 days. These models use estimation techniques that eliminate complete-case bias by incorporating all available information. DSM-5 TUD and DSM-IV ND were predictors in separate models. Models included random intercepts (for within subject correlations) and random slopes (for correlations over time) and adjusted for sociodemographics, participant type, and baseline treatment. Logistic regression was used for any cigarette use. Number of cigarettes and craving were analyzed among respondents who smoked that day, using normal regression. Regression coefficients were reported for the fixed effect of disorder on outcome on any given day, holding the random effects constant. Significance was indicated by 95% CI not including 0.0. To determine if either disorder showed greater association, 200 bootstrapped samples (DiCiccio & Efron, 1996; Efron & Tibshirani, 1986) were generated. Within each bootstrapped sample, the regression model was run for each disorder and the difference in the coefficients was calculated. Across all samples, the mean difference and 95% empirical CI was calculated. Validity differed significantly if the 95% CI did not include 0.0.

2.3.2. Validity of DSM-5 TUD severity

Following an AUD validity study (Mannes et al., 2021), multinomial logistic regression models estimated association of TUD severity levels (mild, moderate, severe) with each concurrent validator (predictor), adjusting for sociodemographics and participant type. Models compared each severity level to no disorder; severe and moderate to mild; and severe to moderate. ORs, the odds of being in each group (vs. the reference group) among those with vs. without a binary validator or with a unit increase in a count validator, were reported. Similar to the prospective validation, for each validator, generalized linear mixed model regression models estimated the association of TUD severity levels (each compared to no disorder; severe and moderate to mild; and severe to moderate) at baseline (predictor) with the repeated outcome measure on any given day of the 90 days, and regression coefficients were reported.

2.3.3. Sensitivity analysis

Analyses were repeated among past month cigarette smokers (N=365). For psychopathology validators, models were re-analyzed adjusting for other substance use, to determine that association was not due to such use. Differential validity was estimated for alternate TUD (≥2 of ND plus craving criteria) versus DSM-IV ND to determine if adding craving alone increased validity.

3. RESULTS

3.1. Sample descriptives (Supplementary Table 1)

Most of the sample was male (70%), non-White (66%), age ≥40 (61%), and from the community sample (71%); 42% had some college or more and 50% had substance use treatment. Most had DSM-5 TUD (89%): 21% mild, 30% moderate, and 38% severe; with lower prevalence for DSM-IV ND (66%). Cigarettes were smoked on average 24 days in the past month, with an average of 10 CPD. Using the FTND, 43% showed medium, high, or very high dependence (14%, 25%, and 5%, respectively). DSM-5 psychiatric disorders ranged from 24% (PTSD) to 85% (any DUD). In the EDA, the median completion rate was 83%, or 75 days (interquartile range 38.0-87.0); overall smoking prevalence was 61%, average CPD among smokers was 10 (range: 1-96), and average craving was 3 (range: 1-5).

3.2. Concurrent validity: DSM-5 TUD (Table 1)

Table 1:

Differential association of validators with DSM-5 TUD and DSM-IV ND, among past year smokers

Association with DSM-5 TUDa Association with DSM-IV NDb Difference in association
Concurrent validators (N=396) OR (95% CI) c OR (95% CI) c Ratio of OR (95% CI) d
Cigarette-related variables
  Number of days smoked cigarettes in past month 1.08 (1.05, 1.10) 1.05 (1.03, 1.07) 1.03 (1.00, 1.05)
  Nicotine craving scalee 1.08 (1.06, 1.11) 1.05 (1.03, 1.06) 1.03 (1.01, 1.06)
  Number of cigarettes smoked per day 1.10 (1.04, 1.17) 1.07 (1.03, 1.10) 1.03 (0.98, 1.09)
  Fagerström test for Nicotine Dependence scoref 2.45 (1.65, 3.64) 1.87 (1.53, 2.28) 1.31 (0.91, 1.89)
Psychopathology measures
  DSM-5 alcohol use disorderg 1.99 (1.03, 3.86) 1.94 (1.22, 3.09) 1.03 (0.58, 1.84)
  DSM-5 drug use disorderg,h 11.93 (5.81, 24.52) 8.74 (4.58, 16.67) 1.37 (0.67, 2.77)
  DSM-5 Anti-social personality disorderg 1.44 (0.68, 3.06) 1.93 (1.14, 3.24) 0.75 (0.39, 1.44)
  DSM-5 Borderline personality disorderg 3.85 (1.64, 9.03) 2.54 (1.56, 4.12) 1.52 (0.70, 3.28)
  DSM-5 major depressive disorderg 4.14 (1.74, 9.87) 2.74 (1.69, 4.44) 1.51 (0.70, 3.27)
  DSM-5 Post-traumatic stress disorderg 7.09 (1.66, 30.32) 2.39 (1.30, 4.41) 2.96 (0.75, 11.75)
  PHQ-9 score (categoriesi) 1.52 (1.00, 2.32) 1.31 (1.05, 1.63) 1.16 (0.81, 1.67)
Prospective validators (N=394) Beta (95% CI) j Beta (95% CI) j Difference in Beta (95% CI) k
  Smoked on any given day 1.19 (0.41, 1.97) 0.69 (0.16, 1.23) 0.53 (0.27, 0.77)
  Number of cigarettes smoked per smoking day 3.29 (1.41, 5.18) 2.09 (0.83, 3.35) 1.36 (0.89, 1.78)
  Craving scorel 0.55 (0.20, 0.89) 0.39 (0.16, 0.62) 0.19 (0.09, 0.28)
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TUD = tobacco use disorder; ND = nicotine dependence; OR = odds ratio; CI = confidence interval; PHQ-9 = patient health questionnaire version 9

Values in bold are significant at the p<0.05 level

a

Based on 2 or more of the 11 DSM-5 TUD criteria

b

Based on 3 or more of the 7 DSM-IV ND criteria

c

Estimated from logistic regression analysis, adjusted for gender, age, race/ethnicity, education level, and participant type. OR with 95% CI that do not include 1 are statistically significant at the p<0.05 level.

d

Difference in association indicated by the ratio of odds ratios (exponentiated coefficient for the interaction term): OR for DSM-5 TUD /OR for DSM-IV ND. Ratios with 95% CI that do not include 1 are statistically significant at the p<0.05 level.

e

sum of 10 craving items, higher values indicate greater current craving

f

5 responses, very low dependence - very high dependence

g

Reference group is No

h

includes a DSM-5 use disorder for cannabis, cocaine, heroin, hallucinogens, other drugs, and non-medical use of prescription opioids, sedatives, or stimulants

i

5 levels, no problems - severe problems

j

Estimated from GLMM regression analysis, with random slope and intercept, adjusted for gender, age, race/ethnicity, education level, participant type, and any substance use treatment at baseline. A logistic regression model was used for cigarette use on any given day. Normal regression models were used for number of cigarettes smoked on any given day and for the craving scale value on any given day. A regression coefficient (beta) with 95% CI not including 0 is statistically significant at the p<0.05 level.

k

Difference is calculated by estimating the regression coefficient (Beta) for association with each diagnosis (DSM-5 TUD, DSM-IV ND) in each of 100 bootstrapped samples, subtracting beta for DSM-IV ND from DSM-5 TUD, and generating empirical 95% confidence intervals for the difference. Differences with 95% CI that do not include 0 are statistically significant at the p<0.05 level.

l

craving ranges from 1-5, with higher scores indicating higher craving. Craving was measured and analyzed for those who used cigarettes on that day.

Greater odds of TUD were significantly associated with: a one-day increase in past-month days smoked (OR=1.08); a one-unit increase in the craving scale (OR=1.08) and items (ORs=1.57-1.84 [Supplementary Table 3]); an additional CPD (OR=1.10); a unit increase in the FTND (OR=2.45); and FTND items (ORs=1.71-6.57; Supplementary Table 3). Increased odds of TUD were associated with presence of AUD, DUD, BPD, MDD, and PTSD. DSM-5 TUD showed significantly stronger association than DSM-IV ND for number of days smoked (ratio of OR=1.03); smoking when sick in bed (ratio=2.84); craving scale (ratio=1.03); and 8 craving items (ratios=1.19-1.43). Results for the psychopathology validators were similar after adjusting for other substance use (Supplementary Table 4).

3.3. Prospective validity: DSM-5 TUD (Table 1)

Compared to participants without TUD, on any given day, participants with TUD showed greater log-odds of any smoking (β=1.2), smoked more CPD (β=3.3), and stronger craving (β=0.6). For all outcomes, the association was significantly stronger with DSM-5 TUD than DSM-IV ND (differences in β=0.19-1.36).

3.4. Concurrent validity: DSM-5 TUD severity

TUD severity levels showed associations in a generally dose-dependent manner, with the greatest associations for severe, then moderate and mild disorders (Table 2, Supplementary Table 5). Severe vs. none and mild, was associated with all concurrent validators (ORs=1.04-23.92); vs. moderate, with most validators (ORs=1.02-3.10). Moderate vs. none was associated with all smoking-related and 4/7 psychopathology validators (ORs=1.09-16.23); vs. mild, with most of the smoking-related validators (ORs=1.03-3.84). Mild vs. none was associated with some smoking-related validators (ORs=1.06-5.01). Results for the psychopathology validators remained similar after adjusting for other substance use (Supplementary Table 6).

Table 2:

Associationa of validators with DSM-5 TUD severity, among past year smokers

Mild vs none Moderate vs none Severe vs none Moderate vs mild Severe vs mild Severe vs moderate
Concurrent validators (N=396) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Cigarette-related variables
  Number of days smoked cigarettes in past month 1.06 (1.02, 1.09) 1.09 (1.05, 1.12) 1.10 (1.06, 1.13) 1.03 (1.00, 1.06) 1.04 (1.01, 1.07) 1.01 (0.98, 1.04)
  Nicotine craving scaleb 1.06 (1.03, 1.09) 1.09 (1.06, 1.12) 1.11 (1.08, 1.15) 1.03 (1.01, 1.05) 1.05 (1.03, 1.07) 1.02 (1.01, 1.04)
  Number of cigarettes smoked per day (CPD) 1.05 (0.98, 1.13) 1.11 (1.04, 1.18) 1.14 (1.07, 1.22) 1.05 (1.01, 1.10) 1.09 (1.04, 1.13) 1.03 (1.00, 1.07)
  Fagerström test for Nicotine Dependence scorec 1.74 (1.11, 2.71) 2.34 (1.52, 3.59) 3.53 (2.29, 5.42) 1.35 (1.04, 1.74) 2.03 (1.58, 2.61) 1.51 (1.24, 1.84)
Psychopathology measures
  DSM-5 Alcohol use disorderd 1.21 (0.57, 2.59) 2.07 (0.99, 4.32) 2.81 (1.36, 5.84) 1.71 (0.92, 3.17) 2.32 (1.27, 4.24) 1.36 (0.79, 2.34)
  DSM-5 Drug use disorderd,e 5.01 (2.10, 11.93) 16.23 (6.17, 42.68) 23.92 (9.03, 63.37) 3.24 (1.31, 8.02) 4.78 (1.96, 11.61) 1.47 (0.56, 3.89)
  DSM-5 Anti-social personality disorderd 0.89 (0.36, 2.24) 1.07 (0.45, 2.51) 2.43 (1.07, 5.52) 1.19 (0.58, 2.47) 2.72 (1.39, 5.34) 2.28 (1.30, 4.01)
  DSM-5 Borderline personality disorderd 2.30 (0.87, 6.09) 3.19 (1.26, 8.03) 5.82 (2.34, 14.45) 1.38 (0.73, 2.64) 2.53 (1.37, 4.67) 1.83 (1.09, 3.07)
  DSM-5 Major depressive disorderd 2.30 (0.88, 5.98) 3.75 (1.51, 9.28) 6.62 (2.71, 16.19) 1.63 (0.87, 3.05) 2.88 (1.58, 5.25) 1.77 (1.06, 2.93)
  DSM-5 Post-traumatic stress disorderd 4.29 (0.92, 20.04) 6.31 (1.41, 28.17) 9.38 (2.14, 41.06) 1.47 (0.70, 3.11) 2.19 (1.09, 4.41) 1.49 (0.85, 2.60)
  PHQ-9 score (categoriesf) 1.27 (0.87, 1.86) 1.42 (0.99, 2.04) 1.83 (1.29, 2.61) 1.12 (0.86, 1.46) 1.44 (1.12, 1.85) 1.29 (1.05, 1.59)
Prospective validators (N=394) Beta (95% CI) Beta (95% CI) Beta (95% CI) Beta (95% CI) Beta (95% CI) Beta (95% CI)
  Smoked on any given day 0.73 (−0.16, 1.63) 1.17 (0.31, 2.03) 1.59 (0.74, 2.44) 0.43 (−0.27, 1.14) 0.85 (0.18, 1.53) 0.42 (−0.19, 1.02)
  Number of cigarettes smoked per smoking day 2.09 (−0.02, 4.20) 2.50 (0.46, 4.53) 4.92 (2.93, 6.92) 0.40 (−1.24, 2.05) 2.83 (1.27, 4.39) 2.43 (1.02, 3.83)
  Craving scoreg 0.29 (−0.10, 0.68) 0.56 (0.18, 0.93) 0.73 (0.37, 1.10) 0.26 (−0.03, 0.57) 0.44 (0.16, 0.73) 0.18 (−0.08, 0.43)
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TUD = Tobacco use disorder: mild=2-3 criteria, moderate=4-5 criteria, severe=6+ criteria; OR = odds ratio; CI = confidence interval; PHQ-9 = patient health questionnaire version 9

Values in bold are significant at the p<0.05 level

a

For concomitant validators, association was estimated using multinomial logistic regression analysis, adjusted for gender, age, race/ethnicity, participant type, and education level; OR with 95% CI that do not include 1 are statistically significant at the p<0.05 leve. For prospective validators, association was estimated from GLMM regression analysis, with random slope and intercept, adjusted for gender, age, race/ethnicity, education level, participant type, and any substance use treatment at baseline. A logistic regression model was used for cigarette use on any given day and normal regression models were used for number of cigarettes smoked on any given day and for the craving scale value on any given day. A regression coefficient (beta) with 95% CI not including 0 are considered significant at the p<0.05 level.

b

sum of 10 craving items, higher values indicate greater current craving

c

5 responses, very low dependence - very high dependence

d

Reference group is No

e

includes a DSM-5 use disorder for use of any of the following substances: cannabis, cocaine, heroin, hallucinogens, other drugs, and non-medical use of prescription opioids, sedative, or stimulants

f

5 levels, no problems - severe problems

g

craving score ranges from 1-5, with higher scores indicating higher craving. Craving was measured and analyzed for those who used cigarettes on that day.

3.5. Prospective validity: DSM-5 TUD severity

Severe TUD vs. none and mild, and moderate vs. none were each associated with all three prospective outcomes (Table 2), e.g., on any given day, those with severe vs. none had greater log-odds of smoking (β=1.6), CPD (β=4.9), and craving (β=0.7). Severe vs. moderate was associated with CPD.

3.6. Sensitivity analysis

Among past-month smokers (N=365), results were similar, with stronger association for DSM-5 TUD than DSM-IV ND with number of days smoked, craving scale, craving items, and the prospective outcomes (Supplementary Table 7) and similar associations between TUD severity levels and validators (Supplementary Table 8).

Differential validity comparing alternate TUD (craving plus the ND criteria) to DSM-IV ND showed very similar results, with stronger association for alternate TUD with number of days smoked, craving scale, craving items, and the prospective outcomes (Supplementary Table 9).

4. DISCUSSION

Among adults who smoked cigarettes in the past year, binary DSM-5 TUD showed concurrent and prospective validity through significant associations with cigarette-related and psychopathology validators, and greater validity than DSM-IV ND for several validators. DSM-5 TUD severity levels also showed validity, with severe disorder associated with all validators, moderate with most, and mild with some. Thus, evidence supports the DSM-5 TUD measures.

DSM-5 TUD measures were associated with cigarette-related variables, similar to previous studies (Chung et al., 2012; Shmulewitz et al., 2021; Shmulewitz et al., 2013). Concurrent and prospective tobacco consumption and craving showed greater association with DSM-5 TUD than DSM-IV ND, likely due to the craving criterion. DSM-5 TUD was strongly related to the widely used FTND. Although some studies suggest that FTND and DSM measures capture somewhat different aspects of disorder (Brook et al., 2009; Hughes et al., 2004; Moolchan et al., 2002; Mwenifumbo & Tyndale, 2010), other studies identified underlying similarities between the two measures (Agrawal et al., 2011; Bidwell et al., 2016). Further studies should determine if FTND and DSM-5 TUD can be integrated into one diagnostic measure encompassing all relevant domains.

DSM-5 TUD measures were associated with psychopathology, as found previously (Chou et al., 2016; Grant et al., 2004), consistent with known disparities in smoking and consequences by mental health status. For example (Benowitz, 2010; Center for Disease Control and Prevention, 2020; Chou et al., 2016; Forman-Hoffman et al., 2017; Grant et al., 2004; Sagud et al., 2019; Streck et al., 2020; Williams et al., 2013), those with psychopathology are more likely to smoke, smoke more, develop use disorder, suffer from negative consequences, and have greater difficulty quitting. Targeted strategies may be needed to reduce smoking among those with psychopathology (Brook et al., 2009; Center for Disease Control and Prevention, 2020; Williams et al., 2013).

While DSM-5 TUD showed validity, the low threshold could lead to a heterogenous category, aggregating individuals across severity levels (Chung et al., 2012). Heterogeneity may affect need for and response to treatment and complicate efforts to understand disease development (Chung et al., 2012; Gelenberg et al., 2008; Meyer, 2011; Schulze & McMahon, 2004; West & Miller, 2011). Validity of the severity levels, with severe, moderate, and mild showing dose-dependent associations, may alleviate some of these concerns. For example, disorder severity can inform treatment priority and strategy (Kopak et al., 2014; Mannes et al., 2021). Brief interventions may suffice for mild disorder, while moderate/severe disorder may require more intensive therapies.

Study limitations are noted. Participants may have under-reported cigarette-related behaviors, but the EDA and SAQ were self-administered, and the EDA was daily, reducing potential bias or recall problems. As this sample was enriched for SUD, generalizability to those with lower prevalence of problematic substance use should be investigated. Yet, alcohol and drug use/disorders are prevalent in U.S. adults (Substance Abuse and Mental Health Services Administration, 2020, 2021), suggesting that results may be generally applicable. Use of other forms of tobacco or nicotine (e.g., cigars, e-cigarettes) was not assessed, but the majority of nicotine consumption in the US remains through cigarettes (Cornelius et al., 2020). Since e-cigarette use is increasing (Cornelius et al., 2020) and may lead to negative health consequences, including possible nicotine addiction, future studies should consider an e-cigarette use disorder and how to assess disorder among users of both cigarettes and e-cigarettes. In the EDA, participants could have responded at different times each day, possibly increasing response variability, and craving was assessed only among those who smoked that day. Future studies should also assess craving on non-smoking days.

5. CONCLUSIONS

In adults with past year smoking, the DSM-5 TUD diagnosis, as operationalized in the PRISM-5, is valid. The criteria added to DSM-5, especially craving, considered an important indicator of TUD and a treatment target, may increase clinical and research relevance over DSM-IV ND. DSM-5 TUD identifies more individuals who may benefit from treatment (Livne et al., 2021), while providing severity levels to inform the most appropriate intervention strategy. Using the more nuanced and valid DSM-5 diagnostic measures may help with the development of better prevention and treatment methodologies, to ultimately decrease the enormous costs of smoking and TUD.

Supplementary Material

1

Highlights.

  • DSM-5 tobacco use disorder (TUD) showed concurrent and prospective validity

  • DSM-5 TUD diagnosis showed greater validity than DSM-IV nicotine dependence

  • DSM-5 TUD severity levels (mild; moderate; severe) showed validity

  • Results support using DSM-5 measures to validly assess TUD

Acknowledgements

Support acknowledged from National Institute on Drug Abuse, USA: R01DA018652 (DSH); National Institute on Alcohol Abuse and Alcoholism, USA: 1R01AA025309 (DSH); and the New York State Psychiatric Institute, USA.

Role of funding source

The funding organizations and sponsoring agencies had no further role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Footnotes

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

Conflict of Interest

Dr. Hasin reports funding for a separate project from Syneos Health. All other authors of this manuscript have no conflicts of interest to report.

Contributors/CRediT authorship contribution statement

Dvora Shmulewitz: conceptualization, data curation, formal analysis, methodology, writing – original draft, writing – review & editing; Eliana Greenstein: data curation, project administration, writing – review & editing; Malka Stohl: data curation, software; David S. Fink: writing – review & editing; Stephanie Roncone: project administration, writing – original draft; Claire Walsh: data curation, project administration, writing – review & editing; Efrat Aharonovich: conceptualization, writing – review & editing; Deborah S. Hasin: conceptualization; funding acquisition, writing – review & editing. All authors have approved the submitted manuscript.

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