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. Author manuscript; available in PMC: 2023 Nov 1.
Published in final edited form as: J Psychiatr Res. 2022 Sep 21;155:387–394. doi: 10.1016/j.jpsychires.2022.09.016

Construct validity of DSM-5 cannabis use disorder diagnosis and severity levels in adults with problematic substance use

David S Fink a, Dvora Shmulewitz a,b, Zachary L Mannes a,c, Malka Stohl a, Ofir Livne a,c, Melanie Wall a,b,d, Deborah S Hasin a,b,c,*
PMCID: PMC9590423  NIHMSID: NIHMS1841229  PMID: 36182768

Abstract

The DSM-5 definition of cannabis use disorder (CUD) differs from DSM-IV by combining abuse and dependence criteria (without the legal criterion) and including withdrawal and craving criteria. Information on construct validity of the DSM-5 CUD diagnosis and severity levels is lacking. The aim of this study was to examine the construct validity of DSM-5 CUD and its severity levels through their associations with a set of concurrent validators. Adults with problematic substance use were recruited from two settings: a research setting in an urban medical center and a suburban inpatient addiction treatment program. Participants who reported past-year cannabis use (n=392) were included in this study. A semi-structured, clinician-administered diagnostic interview ascertained DSM-5 CUD criteria and a set of validators, including cannabis use variables, other psychopathology, and functional impairment. Regression models estimated the associations of the validators with binary DSM-5 CUD and CUD severity levels. Results indicated that binary DSM-5 CUD and all CUD severity levels were associated with cannabis use validators, including number of days used, self-reporting that cannabis use was a major problem, and greater cannabis craving. Binary CUD and severe CUD were associated with other psychiatric disorders and social impairment. Findings add information about the validity of DSM-5 CUD diagnosis and severity levels, with severe CUD receiving the strongest support from its association with multiple validators across all domains, as distinct from the mild and moderate CUD measures that were associated with cannabis-specific validators alone. Adults with severe CUD are likely to require more intensive treatment to bolster physical, psychiatric, and social functioning, whereas the mild and moderate severity thresholds provide useful information for identifying less severe disorders for prevention and brief intervention.

Keywords: DSM-5, Diagnosis, Cannabis use disorder, Cannabis use disorder severity, Concurrent validity

1. Introduction

Cannabis is a widely-used psychoactive substance, with an estimated 188 million people worldwide using cannabis in 2017, corresponding to 3.8% of the global population aged 15–64 (United Nations, 2019). In 2019, 48.2 million people, or about 18% of the United States (US) population aged 12 years and older used cannabis in the past year (Substance Abuse and Mental Health Services Administration, 2020). Rates of cannabis use have increased across all US adult age groups over the past two decades (Compton et al., 2016; Hasin, 2018; Substance Abuse and Mental Health Services Administration, 2020). Although many individuals can use cannabis without harm, others experience acute cognitive/motor impairment (Sofuoglu et al., 2010; Volkow et al., 2016), vehicle crashes (Hartman et al., 2015; Li et al., 2012), respiratory symptoms (Ghasemiesfe et al., 2018), and cannabis use disorder (CUD) (Hasin et al., 2016; Hasin et al., 2013). Past-year CUD is consistently associated with other substance use disorders (SUD), psychiatric disorders, and disability across different functional domains, with the highest burden of psychosocial and health problems found among people with severe CUD (Hasin et al., 2016).

The diagnostic criteria for substance use disorders (SUD) underwent considerable revision in the Diagnostic and Statistical Manual of Mental Disorders – 5th Edition (DSM-5). Starting with DSM-III, the categories of substance abuse and substance dependence were differentiated using specific diagnostic criteria (American Psychiatric Association, 1980). DSM-III-R (revised), DSM-IV, and DSM-IV-TR (revised) used similar sets of diagnostic criteria and maintained the SUD distinction between abuse and dependence. However, as research on the psychometric properties of the SUD diagnoses progressed, the biaxial abuse-dependence paradigm was shown to have limitations, including weak reliability and validity of abuse, incorrect assumptions about a hierarchical relationship between abuse and dependence, and the problem of diagnostic orphans (i.e., individuals with symptoms for whom neither diagnosis applied) (Hasin et al., 2013). To address these problems, DSM-5 eliminated the distinction between substance abuse and dependence by combining their diagnostic criterion into a new unified SUD diagnosis. This was defined by the same 11 SUD criterion formerly used to diagnose abuse and dependence except that craving was added and legal problems removed. A large evidence base of epidemiological and clinical research supported this change (Dawson et al., 2010; Hagman and Cohn, 2011; Hasin and Beseler, 2009; Hasin et al., 2013). In addition, while cannabis withdrawal was omitted from earlier DSMs due to lack of sufficient evidence, DSM-5 added cannabis withdrawal to the CUD criteria based on studies conducted after publication of DSM-IV (Budney et al., 2004; Hasin et al., 2013). DSM-5 SUD diagnoses, including CUD, have a threshold of 2 of 11 criterion. Though previous DSMs permitted assessing SUD severity based on symptom count (Hasin and Glick, 1992), DSM-5 was the first version to formally define severity, including mild (2–3 criteria), moderate (4–5 criteria), and severe (≥6 criteria).

Since publication of DSM-5, little research has examined the construct validity of the DSM-5 CUD diagnosis, even though over 20% of all people who use cannabis have CUD (Hasin et al., 2016; Hasin et al., 2015b; Leung et al., 2020), with CUD levels as high as 33% among people reporting daily or weekly cannabis use (Leung et al., 2020). The construct validity and clinical utility of the 3-level severity categorization, intended to identify individuals with varying CUD severity and differences in the extent of impairment and disability, has been debated (Fazzino et al., 2014a; b; Wakefield and Schmitz, 2015). For example, concerns about the DSM-5 threshold of 2+ criteria include that individuals in the mild category could reflect nonproblematic to subclinical cases of cannabis problem severity (Compton et al., 2013; Dacosta-Sánchez et al., 2019; Denis et al., 2015; Ehlers et al., 2015; Goldstein et al., 2015; Kerridge et al., 2013; Martin et al., 2011; Mewton et al., 2011; Mewton et al., 2013). Indeed, a difference of only one or two criteria can determine the presence or absence of a diagnosis, which indicates that low severity can affect reliability, which is less often the case for severe disorders (Hasin et al., 2020). Given the relative size of the CUD population who are symptomatically mild or moderate, a better understanding of the construct validity of the 3-level severity categorization is needed. Such a study is informed by concepts such as the nomological network (Cronbach & Meehl, 1955) and the multitrait-multimethod matrix (Campbell & Fiske, 1959), which have been utilized in numerous previous validation studies of substance use disorders ((Hasin and Paykin, 1999; Hasin et al., 1997; Hasin et al., 2022; Kendler, 1990; Krueger et al., 2004; Mannes et al., 2021; Shmulewitz et al., 2022; Shmulewitz et al., 2021).

Specifically, little data exist on the convergent and discriminant validity of DSM-5 CUD (i.e., the extent to which DSM-5 CUD and its severity levels are related or unrelated to other constructs or measures, respectively). Information is needed on whether clinical characteristics, considered to be related to CUD (e.g., the extent of cannabis use, impairment, comorbidity, functioning) are significant validators of DSM-5 CUD and differentiate between the 3-level DSM-5 CUD severity groups (mild, moderate, severe). Therefore, the purpose of the present study was to examine the association between DSM-5 CUD diagnosis and its severity levels with a set of concurrent validators, including separate measures of cannabis craving and consumption, psychiatric disorders, and functional impairment. We did so in a sample of 392 adults pre-screened for evidence of problematic substance use research

2. Methods

2.1. Sample and procedures

Adults with problematic substance use age ≥18 years were recruited from two settings: a clinical research setting in an urban medical center (n=438) and a suburban inpatient addiction treatment program (n=150), as described elsewhere (Gorfinkel et al., 2021; Hasin et al., 2020; Livne et al., 2021; Shmulewitz et al., 2022; Shmulewitz et al., 2021). Potential participants were informed about the study through advertisements (medical center) or hospital staff (inpatient addiction treatment) (Gorfinkel et al., 2021). To be eligible for study enrollment, all participants were required to screen positive for potentially problematic substance use: binge drinking or illicit drug use (e.g., non-medical use of cannabis, cocaine, heroin, prescription opioids) in the prior 30 days or 30 days prior to inpatient admission, and endorsement of ≥1 DSM-5 SUD criterion. The present analytical sample was limited to participants who reported cannabis use six or more times in the past 12 months (n=392). Exclusion criteria included: non-English speaking; homicidal, suicidal, or psychotic ideation; plans to leave the area (since the parent study included 3-and 6-month follow-up); and cognitive, hearing, or visual impairment precluding ability to participate. Participants gave written informed consent after study procedures were explained by study coordinators. The investigation was carried out in accordance with the latest version of the Declaration of Helsinki and procedures were approved by the Institutional Review Boards of South Oaks Hospital and the New York State Psychiatric Institute. At baseline, trained interviewers administered the Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 version (PRISM-5) (Hasin et al., 2020), which is a valid and reliable semi-structured, computer assisted interview assessing psychiatric disorders for adults (Hasin et al., 2006; Hasin et al., 2020; Hasin et al., 1998; Hasin et al., 1996; Torrens et al., 2004). Participants also completed a computerized self-administered questionnaire (SAQ) and were compensated $50 for their time. Interviewers had graduate degrees and clinical experience, and underwent rigorous PRISM-5 training, including workshops, practice interviewing, role-playing, certification, and supervision (Hasin et al., 2020). Supervisors maintained quality assurance by listening to recordings of 10% of the interviews to ensure that standardized interviewing practices were maintained, meeting with interviewers to discuss issues that arose.

2.2. Measures

2.2.1. Past-year DSM-5 cannabis use disorder

The 11 DSM-5 CUD criteria were assessed among participants who used cannabis at least six times in the past year. DSM-5 CUD criteria include: 1) withdrawal, 2) tolerance, 3) increasing quantity or frequency of use/longer episodes of use, 4) persistent desire or unsuccessful attempt to decrease/control use, 5) a great deal of time spent obtaining, using, or recovering from effects of cannabis, 6) social, occupational, or recreational activities given up or reduced because of use, 7) continued cannabis use despite knowledge of using causing or exacerbating a medical condition, 8) recurrent difficulties to fulfill major role obligations, 9) recurrent use in hazardous situations, 10) craving/strong desire to consume cannabis, 11) continued use despite interpersonal problems caused by cannabis use. The PRISM-5 produces DSM-5 CUD diagnoses via computer algorithm, and classifies participants based on disorder severity: No CUD (0–1 criteria), Mild CUD (2–3 criteria), Moderate CUD (4–5 criteria), and Severe CUD (≥6 criteria) disorder. DSM-5 CUD was positive if participants endorsed ≥2 of 11 CUD criteria. PRISM-5 CUD diagnostic measures demonstrate good to excellent reliability (Hasin et al., 2020), and have been used as validators of non-clinician interviews used in a national survey (Hasin et al., 2015a). Further information about the PRISM-5 and study procedures is found elsewhere (Hasin et al., 2020).

2.2.2. Cannabis-specific concurrent validators assessed in the SAQ

Number of cannabis use days in the past 30 days was assessed using a question from the Addiction Severity Index (ASI) (McLellan et al., 1992), which is widely used in research and clinical settings in self-administered format (Bultler et al., 2001; Rosen et al., 2000). Cannabis craving severity was assessed using the Marijuana Craving Questionnaire–short form (MCQ-SF), a 12-item self-report questionnaire for subjective assessment of the respondent’s feelings and thoughts about cannabis “right now” (i.e., as they were when completing the questionnaire) (Heishman et al., 2009; Heishman et al., 2001). Each of the 12 items were rated on a Likert-type scale from 1 (Strongly Disagree) to 7 (Strongly Agree). The scale covers 4 factors: compulsivity (inability to control cannabis use), emotionality (use of cannabis anticipating relief from withdrawal or negative mood), expectancy (anticipating positive outcomes from consuming cannabis), and purposefulness (intention and planning to use cannabis for positive outcomes). Factor scores for each participant were calculated by summing the means of the three items in each of the factors, yielding a score ranging from 4 to 28, with higher scores indicating greater craving. (PhenX Toolkit, 2012). Subjectively-assessed problematic use was assessed using a binary variable indicating whether participants felt that cannabis was a major problem for them. This was based on a question from the ASI (McLellan et al., 1992).

2.2.3. DSM-5 psychiatric disorder concurrent validators

Past 12-month DSM-5 Major Depressive Disorder (MDD), Post-Traumatic Stress Disorder (PTSD), Borderline Personality Disorder (BPD), and Antisocial Personality Disorder (ASPD) were assessed using a PRISM-5 module for each disorder (Mannes et al., 2020). The PRISM-5 has been used to assess psychiatric conditions in multiple studies, and demonstrates strong reliability and validity among adults reporting substance use (Hasin et al., 2006; Hasin et al., 1996; Morgello et al., 2006; Ramos-Quiroga et al., 2015; Torrens et al., 2004).

The Patient Health Questionnaire (PHQ-9) was used as an alternative depression measure. It assesses self-reported depressive symptoms over the past two weeks, is widely used and has excellent reliability and validity, including in SUD populations (Delgadillo et al., 2011; Kroenke et al., 2001; Löwe et al., 2004). Response options to each of the nine items ranges from 0 “not at all” to 3 “nearly every day.” Responses were summed (total score 0–27), and the summary score converted to a 5-level count variable as follows: 1=0–4 (minimal or no problems); 2=5–9 (mild problems); 3=10–14 (moderate problems); 4=15–19 (moderately severe problems); and 5= ≥20, (severe problems) (Kroenke et al., 2001).

2.2.4. Physical, psychosocial and drug use concurrent validators

Physical impairment and mental impairment was assessed using the Medical Outcomes Study Short Form 12-Item (SF-12), which measures functioning in eight subdomains (i.e., general health, physical functioning, role physical, bodily pain, vitality, social functioning, role emotional, and mental health). Using SF-12 scoring guidelines, composite Physical Component Summary (PCS) and Mental Component Summary (MCS) scores were calculated from the subdomains to indicate the extent to which physical, work, and social activities or accomplishments were negatively impacted by physical or mental health issues in the prior four weeks. PCS and MCS scores are valid, reliable, widely used, and were associated with DSM-5 AUD in general population studies (Grant et al., 2015; Kirouac et al., 2017; Rubio et al., 2013). To facilitate interpretation for each composite score, functional impairment was defined as scoring in the bottom 25th percentile, following other studies (Aharonovich et al., 2017). Social impairment was assessed using the Social Adjustment Scale Self-Report (SAS-SR). This widely used, reliable, self-report measure assesses functioning in the prior two weeks across work/school, social/leisure time, and familial relationships (Weissman and Bothwell, 1976; Weissman et al., 2001; Weissman et al., 1978). Each item is assessed on a 5-point scale, with higher scores indicating greater impairment. Using established scoring guidelines, the scale was scored as the mean of the responses within the domains of (1) employment and/or educational responsibilities (2) social and leisure activities, (3) relationships with extended family, (4) role as a marital partner, (5) parental role, and (6) role within the family unit, including perceptions about economic functioning (range, 1–5). Role areas not relevant to the respondent’s situation are skipped (Weissman and Bothwell, 1976). Additionally, ASI questions were used to generate four variables indicating on how many days in the past month the following problems occurred: employment (inability to find work, problems with present job that jeopardized the job), family (serious conflicts), other social issues excluding family (e.g., loneliness, inability to socialize, dissatisfaction with friends), or legal (engaged in illegal activities for profit). Degree of consequences and severity of drug use during the past 12 months was assessed using the Drug Abuse Screening Test – version 10 (DAST-10) (Skinner, 1982). The DAST-10 consists of 10 items, with binary (yes/no) responses, that sum to yield a score of 0–10, with standard categorization [0 = no problems (score: 0); 1 = low problems (score: 1, 2); 2 =moderate problems (score: 3–5); 3 = substantial problems (score: 6–8); 4 = severe problems (score: 9, 10)](NIDA CTN Common Data Elements, 2014). The DAST-10 has high internal consistency and modest to good sensitivity and specificity (Yudko et al., 2007).

2.2.5. Sociodemographic and other concurrent substance use variables

Sociodemographic characteristics included age, sex (male; female); race/ethnicity (non-Hispanic White; non-Hispanic Black; Hispanic; Other [Asian, Native Hawaiian/Pacific Islander, American Indian, Native Alaskan, and any combination not including Hispanic]); education level (no college; at least some college), current employment (unemployed, any employment [full or part-time]), marital status (unmarried; married/living with partner), housing status (homeless or group home; stably housed), and recruitment setting (inpatient; community). Other substance use (alcohol, tobacco, crack/cocaine, heroin, stimulants, sedatives, non-prescription opioids, and sedatives) for each substance other than cannabis was indicated by PRISM-5 items, with variables indicating past-month use.

2.3. Statistical analysis

First, participants were stratified by DSM-5 CUD and severity (0=no CUD, 1=mild CUD, 2=moderate CUD, 3=severe CUD) and compared on sociodemographic characteristics and concurrent cannabis use validators, DSM-5 psychiatric validators, and physical, psychosocial, and drug use validators. Second, we examined the association between DSM-5 CUD and each severity level, and each concurrent validator through a series of adjusted multivariable logistic regression models reporting adjusted odds ratios (aOR) and 95% confidence intervals (CI) for each validator. CUD was modeled as the outcome in all analyses for ease of interpretation of results, although no assumption on directionality of relationships were made. All models were adjusted for age, sex, education, race/ethnicity, and participant type (patient/community). An aOR less than 1.0 indicates lower odds of CUD or CUD severity level among those with vs without the concurrent validator (negative association) while an aOR greater than 1.0 indicates higher odds of CUD or CUD severity level (positive association) among those with vs without the validator. Third, to investigate whether CUD severity levels capture a unidimensional or multidimensional phenomenon, such that the importance of criteria differs by CUD severity, DSM-5 CUD criteria distributions were examined across the four CUD severity levels (none, mild, moderate, severe). All analyses were conducted using SAS 9.4.

3. Results

3.1. Sociodemographics and substance use by CUD (Table 1)

Table 1.

Demographic characteristics by DSM-5 cannabis use disorder (CUD) severity level (N = 392).

Demographic characteristics DSM-5 Cannabis Use Disorder Severity
Total
(n=392)		 Any CUD
(n=262)		 No disorder
(n=130)		 Mild CUD
(n=81)		 Moderate CUD
(n=75)		 Severe CUD
(n=106)
% or
M (SD)		 % or
M (SD)		 % or
M (SD)		 % or
M (SD)		 % or
M (SD)		 % or
M (SD)
Age, M (SD) 41.2 (13.4) 40.1 (13.6) 43.4 (12.2) 42.7 (13.5) 39.1 (14.6) 38.9 (13.5)
Sex
 Male 71.4 71.4 71.5 74.1 78.7 64.2
 Female 28.6 28.6 28.5 25.9 21.3 35.8
Race/ethnicity
 Non-Hispanic White 25.8 20.2 36.9 23.5 18.7 18.9
 Non-Hispanic Black 46.9 48.9 43.1 55.6 42.7 48.1
 Hispanic 19.9 21.8 16.2 12.3 30.7 22.6
 Other1 7.4 9.2 3.8 8.6 8.0 10.4
Marital status
 Married/living with partner 19.6 19.5 20.0 17.3 17.3 22.6
 Unmarried 80.4 80.5 80.0 82.7 82.7 77.4
Education
 No college 53.3 53.3 46.9 54.3 57.3 57.5
 Some college or more 46.7 46.7 53.1 45.7 42.7 42.5
Current employment
 Full or part-time 29.3 29.8 28.5 32.1 25.3 31.1
 Unemployed 70.7 70.2 71.5 67.9 74.7 68.9
Housing status
 Stably housed 93.1 93.5 92.3 90.1 96.0 94.3
 Homeless or group home 6.9 6.5 7.7 9.9 4.0 5.7
Recruitment setting
 Community 78.3 83.2 68.5 81.5 81.3 85.8
 Inpatient 21.7 16.8 31.5 18.5 18.7 14.2
Other substance use
 Alcohol 94.6 93.9 96.2 95.1 90.7 95.3
 Tobacco 78.3 78.6 77.7 81.5 78.7 76.4
 Cocaine 55.6 48.5 70.0 63.0 40.0 43.4
 Heroin 26.5 20.6 38.5 23.5 16.0 21.7
 Stimulants 14.5 14.9 13.8 14.8 13.3 16.0
 Sedatives 26.8 28.2 23.8 21.0 28.0 34.0
 Non-prescription opioids 30.1 29.0 32.3 25.9 30.7 30.2
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1

Other includes Asian, Native Hawaiian/Pacific Islander, American Indian, and Native Alaskan

Of the 392 participants, 46.9% were non-Hispanic Black, 19.9% Hispanic, and 25.8% non-Hispanic White. Most participants were male (71%), had less than college education (53%), unmarried (80%), and unemployed (71%), with a mean age of 41 years (standard deviation [SD]=13.4). Among the participants, 66.8% met criteria for past 12-month DSM-5 CUD (n=262), with 20.7%, 19.1%, and 27.0% meeting criteria for mild, moderate, and severe CUD, respectively. Cocaine and heroin use was much more common in participants with no or mild CUD than those with moderate or severe CUD.

3.2. Adjusted analysis of concurrent validators by DSM-5 CUD (Table 2 and Table 3)

Table 2.

Prevalence and correlates of DSM-5 cannabis use disorder (CUD) diagnostic subgroup among 392 respondents

Variable DSM-5 CUD severity
No CUD
(n=130)		 Any CUD
(n=262)		 Any vs. no CUD
% (n) or M (SD) % (n) or M (SD) aOR (95% CI)
Cannabis validators
Days used cannabis in past month1 - M (SD) 6.5 (9.7) 19.8 (10.8) 1.11 (1.08, 1.14)
Cannabis use considered a problem - % (n) 13.1 (17) 51.9 (136) 7.15 (3.94, 12.97)
Cannabis craving scale2 10.0 (5.0) 17.0 (5.9) 1.23 (1.17, 1.30)
DAST-103 2.3 (1.2) 2.4 (0.9) 1.29 (1.03, 1.62)
Trouble at work, days in the past month1 - M (SD) 7.9 (12.3) 6.1 (10.5) 0.99 (0.97, 1.01)
Trouble with family, days in the past month1 - M (SD) 1.8 (5.3) 2.2 (5.7) 1.02 (0.98, 1.06)
Trouble with friends, days in the past month1 - M (SD) 1.1 (3.1) 1.0 (3.0) 1.02 (0.95, 1.10)
Legal trouble, days in the past month1 - M (SD) 1.9 (6.0) 1.3 (4.3) 0.98 (0.94, 1.02)
Psychiatric validators
DSM-5 Major Depressive Disorder - % (n) 36.9 (48) 40.5 (106) 1.43 (0.89, 2.30)
DSM-5 Post-Traumatic Stress Disorder - % (n) 23.1 (30) 19.8 (52) 0.96 (0.56, 1.65)
DSM-5 Borderline Personality Disorder - % (n) 32.3 (42) 44.3 (116) 2.05 (1.26, 3.35)
DSM-5 Antisocial Personality Disorder - % (n) 27.7 (36) 30.2 (79) 1.26 (0.76, 2.08)
PHQ-9 depression scale4 - M (SD) 2.2 (1.2) 2.2 (1.2) 1.03 (0.85, 1.25)
Functional validators
Social impairment4 - M (SD) 2.4 (0.7) 2.3 (0.7) 1.09 (0.79, 1.51)
Physical impariment5 - % (n) 22.3 (29) 26.7 (70) 1.41 (0.82, 2.41)
Mental impairment5 - % (n) 29.2 (38) 23.3 (61) 0.88 (0.52, 1.49)
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DSM-5=Diagnostic and Statistical Manual of Mental Disorders – 5; M=mean; SD=standard deviation; aOR=adjusted odds ratio.

Notes: Adjusted odds ratios (aORs) were derived from separate logistic regression models adjusted for age, sex, race/ethnicity, education, and participant type.

1

Count variable, ranging from 0 to 30 days.

2

Count scale ranging from 4 to 28, with higher values indicating greater current craving.

3

Drug Abuse Screening Test-10 (count variable, 0=no problems to 4=severe problems).

4

Count variable, ranging from 1 to 5.

5

Binary variable (lowest 25th percentile)

Table 3.

Prevalence and correlates of DSM-5 cannabis use disorder (CUD) diagnostic subgroup among 392 respondents

Variable DSM-5 CUD severity
No CUD
(n=130)		 Mild CUD
(n=81)		 Mild CUD vs. no disorder Moderate CUD
(n=75)		 Moderate CUD vs. no disorder Severe CUD
(n=106)		 Severe CUD vs. no disorder
% (n) or M (SD) % (n) or M (SD) aOR (95% CI) % (n) or M (SD) aOR (95% CI) % (n) or M (SD) aOR (95% CI)
Cannabis validators
Days used cannabis in past month1 - M (SD) 6.5 (9.7) 17.4 (11.2) 1.10 (1.06, 1.13) 19.8 (11.4) 1.11 (1.08, 1.15) 21.6 (9.8) 1.13 (1.09, 1.16)
Cannabis use considered a problem - % (n) 13.1 (17) 35.8 (29) 3.86 (1.90, 7.86) 46.7 (35) 6.15 (2.98, 12.68) 67.9 (72) 13.59 (6.82, 27.08)
Cannabis craving scale2 10.0 (5.0) 15.2 (5.7) 1.18 (1.12, 1.25) 17.5 (5.9) 1.26 (1.18, 1.34) 17.9 (5.7) 1.27 (1.20, 1.35)
DAST-103 2.3 (1.2) 2.1 (1.0) 0.91 (0.68, 1.21) 2.4 (1.0) 1.32 (0.96, 1.81) 2.6 (0.8) 1.98 (1.44, 2.72)
Trouble at work, days in the past month1 - M (SD) 7.9 (12.3) 5.9 (10.4) 0.98 (0.96, 1.01) 4.1 (9.0) 0.96 (0.93, 0.99) 7.7 (11.3) 1.00 (0.98, 1.02)
Trouble with family, days in the past month1 - M (SD) 1.8 (5.3) 1.3 (4.3) 0.99 (0.92, 1.05) 2.4 (5.7) 1.03 (0.98, 1.08) 2.7 (6.7) 1.03 (0.99, 1.09)
Trouble with friends, days in the past month1 - M (SD) 1.1 (3.1) 1.2 (4.1) 1.02 (0.93, 1.13) 0.5 (1.5) 0.89 (0.75, 1.07) 1.5 (2.9) 1.05 (0.97, 1.14)
Legal trouble, days in the past month1 - M (SD) 1.9 (6.0) 1.4 (5.0) 0.99 (0.93, 1.05) 1.4 (4.5) 0.98 (0.92, 1.04) 1.1 (3.6) 0.97 (0.91, 1.03)
Psychiatric validators
DSM-5 Major Depressive Disorder - % (n) 36.9 (48) 27.2 (22) 0.79 (0.42, 1.50) 33.3 (25) 1.05 (0.55, 2.01) 55.7 (59) 2.85 (1.59, 5.11)
DSM-5 Post-Traumatic Stress Disorder - % (n) 23.1 (30) 12.3 (10) 0.53 (0.24, 1.18) 12.0 (9) 0.57 (0.25, 1.31) 31.1 (33) 1.89 (1.00, 3.55)
DSM-5 Borderline Personality Disorder - % (n) 32.3 (42) 38.3 (31) 1.64 (0.88, 3.05) 38.7 (29) 1.64 (0.86, 3.11) 52.8 (56) 2.94 (1.63, 5.30)
DSM-5 Antisocial Personality Disorder - % (n) 27.7 (36) 23.5 (19) 0.93 (0.47, 1.81) 26.7 (20) 0.94 (0.47, 1.86) 37.7 (40) 2.00 (1.09, 3.66)
PHQ-9 depression scale4 - M (SD) 2.2 (1.2) 1.9 (1.0) 0.78 (0.60, 1.03) 2.2 (1.2) 1.03 (0.80, 1.33) 2.5 (1.2) 1.26 (1.00, 1.59)
Functional validators
Social impairment4 - M (SD) 2.4 (0.7) 2.1 (0.6) 0.62 (0.39, 0.98) 2.4 (0.7) 1.23 (0.79, 1.92) 2.5 (0.7) 1.55 (1.04, 2.32)
Physical impariment5 - % (n) 22.3 (29) 25.9 (21) 1.17 (0.59, 2.32) 25.3 (19) 1.53 (0.74, 3.18) 28.3 (30) 1.59 (0.83, 3.06)
Mental impairment5 - % (n) 29.2 (38) 17.3 (14) 0.63 (0.30, 1.31) 21.3 (16) 0.75 (0.36, 1.54) 29.2 (31) 1.26 (0.67, 2.37)
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DSM-5=Diagnostic and Statistical Manual of Mental Disorders – 5; M=mean; SD=standard deviation; aOR=adjusted odds ratio.

Notes: Adjusted odds ratios (aORs) were derived from separate logistic regression models adjusted for age, sex, race/ethnicity, education, and participant type.

1

Count variable, ranging from 0 to 30 days.

2

Count scale ranging from 4 to 28, with higher values indicating greater current craving.

3

Drug Abuse Screening Test-10 (count variable, 0=no problems to 4=severe problems).

4

Count variable, ranging from 1 to 5.

5

Binary variable (lowest 25th percentile)

Binary DSM-5 CUD and each severity level was associated with number of cannabis use days, craving severity, and considering cannabis use a major problem. After adjusting for age, sex, education, race/ethnicity, and participant recruitment setting, a one-day increase in the number of cannabis use days in the past month was associated with higher odds of any CUD as well as mild, moderate, and severe CUD (aOR range: 1.10–1.13). Compared to participants with no CUD, participants with any CUD (aOR=7.15; 95% CI=3.94, 12.97), mild CUD (aOR=3.86; 95% C=1.90, 7.86), moderate CUD (aOR=6.15; 95% CI=2.98, 12.68), and severe CUD (aOR=13.59; 95% CI=6.82, 27.08) had higher odds of considering their cannabis use a major problem. Finally, a one-unit increase in the craving severity scale was associated with 1.23 (95% CI=1.17, 1.30), 1.18 (95% CI=1.12, 1.25), 1.26 (95% CI=1.18, 1.34), and 1.27 (95% CI=1.20, 1.35) higher odds of any, mild, moderate, and severe CUD, respectively. A one-unit increase in the DAST-10 was associated with only any CUD (aOR=1.23; 95% CI=1.03, 1.62) and severe CUD (aOR=1.98; 95% CI=1.44, 2.72), but not with mild nor moderate CUD. Although a one-day increase in number of days reporting trouble with work was associated with decreased odds of moderate CUD, no CUD severity level was associated with number of days reporting trouble with family, trouble with friends, or legal troubles during the past 30 days.

In terms of concurrent psychiatric validators, any CUD was associated with only higher odds of BPD, whereas severe CUD was associated with MDD, PTSD, BPD, APD, and a one-unit increase in the PHQ-9 depression screener (Tables 2 and 3). Neither mild nor moderate CUD was associated with any of the mental health validators. In terms of functional validators, a one-unit increase in social impairment was associated with higher odds of severe CUD (aOR=1.55; 95% CI=1.04, 2.32) but lower odds of mild CUD (aOR=0.62; 95% CI=0.39, 0.98).

3.3. DSM-5 CUD criteria by CUD severity level (Table 4)

Table 4.

Past-year DSM-5 CUD criteria by prevalence or endorsement among past-year cannabis users.

DSM-5 CUD severity
Overall1 (n=392) No disorder
(n=130)		 Mild
(n=81)		 Moderate
(n=75)		 Severe
(n=106)
% Rank % Rank % Rank % Rank % Rank
59.7 1. Craving 12.3 1. Try stop 65.4 1. Craving 85.3 1. Craving 96.2 1. Craving
54.3 2. Try stop 11.5 2. Craving 60.5 2. Try stop 77.3 2. Larger/longer 90.6 2. Withdrawal
48.0 3. Larger/longer 2.3 3. Larger/longer 39.5 3. Larger/longer 72.0 3. Try stop 89.6 3. Larger/longer
42.1 4. Tolerance 1.5 4. Withdrawal (tie) 27.2 4. Tolerance 65.3 4. Tolerance 88.7 4. Try stop
37.0 5. Withdrawal 1.5 4. Tolerance (tie) 17.3 5. Withdrawal (tie) 44.0 5. Withdrawal 86.8 5. Tolerance
31.4 6. Phys/psych 0.8 6. Phys/psych (tie) 17.3 5. Phys/psych (tie) 30.7 6. Phys/psych 80.2 6. Phys/psych
24.0 7. Give up 0.8 6. Hazardous Use (tie) 7.4 7. Neglect role (tie) 20.0 7. Give up 71.7 7. Give up
20.4 8. Neglect role 0.0 8. Time spent (tie) 7.4 7. Hazardous Use (tie) 18.7 8. Neglect role 56.6 8. Phys/psych
16.3 9. Hazardous Use 0.0 8. Give up (tie) 3.7 9. Give up 16.0 9. Hazardous use 42.5 9. Neglect role
12.5 10. Time spent 0.0 8. Neglect role (tie) 2.5 10. Time spent 14.7 10. Social 38.7 10. Time spent
12.0 11. Social 0.0 8. Social (tie) 0.0 11. Social 8.0 11. Time spent 34.0 11. Social
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Note: “Try stop”=persistent desire/attempts to stop/cut down on use; “Phys/psych”=continued use despite recurrent/persistent substance-related physical or psychological problems; “Social”=continued use despite recurrent/persistent substance-related interpersonal problems; “Neglect role”=recurrent substance-related neglect of work/school/home responsibilities; “Larger longer”=recurrent use in larger quantities or for longer than intended; “Time spent”=excessive time spent in obtaining/using/recovering from substance; “Give up”=important activities given up in favor of substance use.

1

Overall includes all participants who endorsed using cannabis 6 or more times in the past 12 months.

One potential source of variation across CUD severity levels is the prevalence of past-year DSM-5 CUD criteria among participants with no, mild, moderate, and severe CUD. Three of the most commonly endorsed criteria were the same across all CUD severity levels: persistent desire/attempts to stop/cut down on use, craving, and recurrent use in larger quantities or for longer than intended (larger/longer). Despite little difference in the ranking of DSM-5 criteria among the four CUD groups, the prevalence of criteria differed substantially between the groups. In the no CUD group, for example, only two criteria (persistent desire/attempts to stop/cut down on use [try to stop] and craving) were endorsed by more than 10% of participants (12.3% and 11.5%, respectively). In contrast, these same two criteria were endorsed by over 60% of the mild CUD group, over 70% in the moderate CUD group, and by nearly 90% of participants in the severe CUD group. Moreover, the number of criteria endorsed by 50% or more of participants in the group doubled with increasing CUD severity, increasing from two criteria in the mild CUD group (craving, try to stop) to four criteria in the moderate CUD group (craving, larger/longer, try stop, tolerance) and to eight criteria in the severe CUD group (craving, withdrawal, larger/longer, try stop, tolerance, physical/psychological problems, give up important activities, and neglect work/school/home responsibilities).

4. Discussion

In this study, the construct validity of DSM-5 CUD measures was examined in 392 adults with problematic substance use who currently used cannabis. The prevalence of any past 12-month DSM-5 CUD was 67%. Using the DSM-5 CUD severity indicators, 20.7% met criteria for mild CUD, 19.1% moderate, and 27.0% severe CUD. Our analysis produced 3 major findings, all of which provided support for the construct validity of the DSM-5 CUD diagnosis.

First, DSM-5 CUD and severity levels were shown to have construct validity with regard to several clinical measures; the mild and moderate CUD diagnoses were associated with concurrent cannabis-specific validators, and severe CUD associated with multiple concurrent validators across all domains, including psychiatric disorders, disability and functional impairment. This suggests that in a sample of individuals who all had problems with substances, some of those endorsing two to five criteria received a diagnosis of DSM-5 CUD despite having no greater risk of disability and functional impairment than others in the sample who used cannabis but did not receive a CUD diagnosis. Although this finding suggests that diagnoses of mild and moderate CUD may be poor indicators for inclusion in pharmacological treatment trials for CUD, the clinical utility of DSM-5 severity levels has received support from various studies (Hasin et al., 2016). Indeed, we found that a relatively high number of participants who met criteria for mild and moderate CUD considered their cannabis use a major problem; compared to participants with no CUD, participants with mild, moderate, and severe CUD had 3.86, 6.15, and 13.59 higher odds of considering their cannabis use a major problem, respectively. This finding may indicate that perceptions about problematic cannabis use are influenced by factors that are important to patients but not captured in this study, such as a perceived discordance between one’s own level of cannabis use relative to the cannabis use of their friends and peers.

Second, our observation that the burden of co-occurring mental disorders is substantially higher in people with DSM-5 CUD is consistent with previous studies (Hasin and Walsh, 2020; Hasin et al., 2016; Onaemo et al., 2021). Specifically, any DSM-5 CUD and each CUD severity level was associated with greater odds of current psychiatric disorders in the NESARC-III, a general population sample of US adults (Hasin et al., 2016). However, in contrast with results of the population-based NESARC III study, neither mild nor moderate CUD was associated with any of the mental health validators in this study. These differences likely reflect differences in base rates of psychiatric disorders and other drug use between the two studies. For example, whereas the NESARC-III found that fewer than 10% of US adults had MDD, BPD, PTSD, or APD (Blanco et al., 2017; Goldstein et al., 2016; Hasin et al., 2018), DSM-5 psychiatric disorders were substantially higher in our study, particularly among participants with no CUD, with about one-third of participants without CUD meeting criteria for MDD and BPD and about one-fourth meeting criteria for PTSD and APD. Moreover, other illicit drug use was extremely prevalent among participants with no CUD, e.g., about 70% of these participants reported cocaine use and about 39% reported heroin use. That we found an association between social impairment and severe CUD, but not mild nor moderate CUD, may therefore be attributed to the comorbidity with other serious substance problems in this sample.

Third, we found that the ranking of DSM-5 CUD criteria was similar across CUD severity levels. Of the 11 DSM-5 CUD criteria, the same 3 criterion were ranked highest in the no CUD group, mild CUD, and moderate CUD: persistent desire/attempts to stop/cut down on use (try to stop), recurrent use in larger quantities or for longer than intended (larger/longer), and craving. In addition to these 3 criteria, withdrawal was endorsed by about 90% of participants meeting severe CUD criteria, making it the 2nd highest ranked criterion at this CUD severity level. Despite little difference in the ranking of DSM-5 criteria among the four CUD groups, prevalences of the 11 CUD criteria increased in a dose-dependent fashion with CUD severity. Debate continues about whether SUDs truly are a unidimensional phenomenon or a multidimensional phenomenon, such that the importance of criteria differs by CUD severity (Boness et al., 2021; Wakefield and Schmitz, 2015; Watts et al., 2021). Our observation that the same 3 criterion were ranked highest across all CUD severity levels is consistent with considerable other evidence that CUD is a unidimensional phenomenon (Hasin et al., 2013; Kirisci et al., 2006; Shmulewitz et al., 2015). However, new manifestations of cannabis use disorder may arise over time, which may in turn affect the dimensionality of the DSM-5 CUD disorder diagnosis. Future studies will need to consider whether additional CUD diagnostic criteria are needed to adequately capture any changes to CUD and its clinical manifestation over time.

4.1. Limitations

Possibly the most notable limitation concerns the composition of the sample. The 392 participants do not represent the entire universe of people who use cannabis; however, they represent a sample enriched for SUD, which was an efficient way to study a broad range of substances. As such, generalizability of results to other samples should be investigated, including samples with lower prevalence of other problematic substance use or CUD, such as patients in primary care or psychiatric settings, and in the general population. Future validation studies conducted in more general population samples may require larger samples in order to produce more precise estimates. Second, the cross-sectional design of the current study does not provide any information about directionality of observed relationships. The complex relationships between CUD and various cannabis-related measures should be further investigated in longitudinal data such as the ABCD study. Third, with approximately one-fourth of the study participants currently in treatment for an SUD, a proportion of the sample was likely to currently be abstaining from using cannabis and receiving mental health services, which may improve symptomology and subsequent scores on measures of depressive symptoms (PHQ-9), social functioning, and mental health impairment. However, the examined validators in this study were associated with the corresponding CUD severity groups even after adjusting for recruitment settings (i.e., inpatient treatment vs a convenience non-hospitalized community sample recruited at a major medical center). Finally, our assessment of the construct validity of CUD diagnosis and its severity levels, as assessed by DSM-5, included several concomitant measures proximally related to CUD and consistent with a pre-specified nomological network. Additional validity studies with a wider array of measures that are more distal to CUD, including those that are assessed prospectively (post-CUD assessment), would provide additional evidence for construct validity CUD diagnosis and severity levels.

4.2. Conclusions and implications

In conclusion, binary DSM-5 CUD and severity levels, as operationalized in the PRISM-5, were generally shown to have validity in adults with problematic substance use who currently used cannabis. Using rigorous methodology, our study demonstrated that the concurrent cannabis use validators were associated with all CUD severity levels, while functional impairment and psychiatric comorbidity predicted severe CUD. These findings support the importance of examining CUD as a 3-level construct instead of a binary measure indicating presence of any CUD vs. none. Future investigations should further examine the criterion validity of the DSM-5 CUD 3-level severity distinctions in additional samples (primary care, mental health care, general population) and by using longitudinal designations to evaluate prospective validity, such as subsequent changes in cannabis use, mental health and functioning. In the meantime, given the high risk of disability and functional impairment among those with severe CUD, the study findings suggest a distinct clinical group with more pronounced symptomology who are likely to require treatment specifically for CUD, whereas the mild and moderate severity threshold provide useful information when the clinical and research purpose is to identify less severe cannabis-related disorders for purposes of prevention and brief intervention.

Role of the funding source

This work was supported by the National Institutes of Health (DSH, grant number R01DA018652) and the New York State Psychiatric Institute. The funding source had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; nor in the decision to submit the article for publication.

Footnotes

Conflicts of interest

Dr. Fink, Dr. Shmulewitz, Dr. Mannes, Ms. Stohl, and Dr. Wall report no conflicts of interest. Dr. Hasin reports funding for an unrelated project from Syneos Health.

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