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Since DSM-IV was published in 1994, its approach to substance use disorders has come under scrutiny. Strengths were identified (notably, reliability and validity of dependence), but concerns have also arisen. The DSM-5 Substance-Related Disorders Work Group considered these issues and recommended revisions for DSM-5. General concerns included whether to retain the division into two main disorders (dependence and abuse), whether substance use disorder criteria should be added or removed, and whether an appropriate substance use disorder severity indicator could be identified. Specific issues included possible addition of withdrawal syndromes for several substances, alignment of nicotine criteria with those for other substances, addition of biomarkers, and inclusion of nonsubstance, behavioral addictions.This article presents the major issues and evidence considered by the work group, which included literature reviews and extensive new data analyses. The work group recommendations for DSM-5 revisions included combining abuse and dependence criteria into a single substance use disorder based on consistent findings from over 200,000 study participants, dropping legal problems and adding craving as criteria, adding cannabis and caffeine withdrawal syndromes, aligning tobacco use disorder criteria with other substance use disorders, and moving gambling disorders to the chapter formerly reserved for substance-related disorders. The proposed changes overcome many problems, while further studies will be needed to address issues for which less data were available.
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Reviews and Overviews
Mechanisms of Psychiatric Illness
DSM-5 Criteria for Substance Use Disorders:
Recommendations and Rationale
Deborah S. Hasin, Ph.D.
Charles P. OBrien, M.D., Ph.D.
Marc Auriacombe, M.D.
Guilherme Borges, Sc.D.
Kathleen Bucholz, Ph.D.
Alan Budney, Ph.D.
Wilson M. Compton, M.D., M.P.E.
Thomas Crowley, M.D.
Walter Ling, M.D.
Nancy M. Petry, Ph.D.
Marc Schuckit, M.D.
Bridget F. Grant, Ph.D.
Since DSM-IV was published in 1994, its
approach to substance use disorders has
come under scrutiny. Strengths were iden-
tied (notably, reliability and validity of
dependence), but concerns have also
arisen. The DSM-5 Substance-Related Dis-
orders Work Group considered these issues
and recommended revisions for DSM-5.
General concerns included whether to
retain the division into two main disorders
(dependence and abuse), whether sub-
stance use disorder criteria should be added
or removed, and whether an appropriate
substance use disorder severity indicator
could be identied. Specic issues in-
cluded possible addition of withdrawal
syndromes for several substances, align-
ment of nicotine criteria with those for
other substances, addition of biomarkers,
and inclusion of nonsubstance, behavioral
This article presents the major issues and
evidence considered by the work group,
which included literature reviews and
extensive new data analyses. The work
group recommendations for DSM-5 revi-
sions included combining abuse and
dependence criteria into a single sub-
stance use disorder based on consistent
ndings from over 200,000 study partic-
ipants, dropping legal problems and
adding craving as criteria, adding canna-
bis and caffeine withdrawal syndromes,
aligning tobacco use disorder criteria
with other substance use disorders, and
moving gambling disorders to the chap-
ter formerly reserved for substance-
related disorders. The proposed changes
overcome many problems, while further
studies will be needed to address issues for
which less data were available.
(Am J Psychiatry 2013; 170:834851)
DSM is the standard classication of mental disorders
used for clinical, research, policy, and reimbursement
purposes in the United States and elsewhere. It therefore
has widespread importance and inuence on how disor-
ders are diagnosed, treated, and investigated. Since its rst
publication in 1952, DSM has been reviewed and revised
four times; the criteria in the last version, DSM-IV-TR, were
rst published in 1994. Since then, knowledge about
psychiatric disorders, including substance use disorders,
has advanced greatly. To take the advances into account,
a new version, DSM-5, was published in 2013. In 2007, APA
convened a multidisciplinary team of experts, the DSM-5
Substance-Related Disorders Work Group (Table 1), to
identify strengths and problems in the DSM-IV approach to
substance use disorders and to recommend improvements
for DSM-5.
Using a set of 2006 reviews (1) as a starting point, the
work group noted weaknesses, highlighted gaps in knowl-
edge, identied data sets to investigate possible solutions,
encouraged or conducted analyses to ll knowledge
gaps, monitored relevant new publications, and formulated
interim recommendations for proposed changes. The work
group elicited input on proposed changes through com-
mentary (2), expert advisers, the DSM-5 web site (receiving
520 comments on substance use disorders), and presenta-
tions at over 30 professional meetings (see Table S1 in the
data supplement that accompanies the online edition of
this article). This input led to many further analyses and
The revisions proposed for DSM-5 aimed to overcome
the problems identied with DSM-IV, thereby providing
an improved approach to substance use disorders. To this
end, the largest question was whether to keep abuse and
dependence as two separate disorders. This issue, which
applies across substances (alcohol, cannabis, etc.), had the
most data available. Other cross-substance issues included
the additionor removal of criteria, the diagnostic threshold,
severity indicator(s), course speciers, substance-induced
disorders, and biomarkers. Substance-specic issues in-
cluded new withdrawal syndromes, the criteria for nicotine
disorders, and neurobehavioral disorder associated with pre-
natal alcohol exposure. Additional topics for consideration
involved gambling and other putative non-substance-
related behavioral addictions. This article presents the
This article is featured in this months AJP Audio and is an article that provides Clinical Guidance (p. A16)
834 Am J Psychiatry 170:8, August 2013
evidence that the work group considered on these issues
and the resulting recommendations.
Overarching Issues
Should Abuse and Dependence Be Kept as Two
Separate Diagnoses?
The DSM-IV criteria for substance abuse and de-
pendence are shown in Figure 1. Dependence was diag-
nosed when three or more dependence criteria were met.
Among those with no dependence diagnosis, abuse was
diagnosed when at least one abuse criterion was met. The
division into two disorders was guided by the concept
that the dependence syndromeformed one dimension
of substance problems, while social and interpersonal
consequences of heavy use formed another (3, 4). Al-
though the dimensions were assumed to be related (3, 4),
DSM-IV placed dependence above abuse in a hierarchy
by stipulating that abuse should not be diagnosed when
dependence was present. The dependence diagnosis
represented a strength of the DSM-IV approach to sub-
stance use disorders: it was consistently shown to be
highly reliable (5) and was validated with antecedent
and concurrent indicators such as treatment utilization,
impaired functioning, consumption, and comorbidity
However, other aspects of the DSM-IV approach were
problematic. Some issues pertained to the abuse diagnosis
and others pertained to the DSM-IV-stipulated relation-
ship of abuse to dependence. First, when diagnosed
hierarchically according to DSM-IV, the reliability and
validity of abuse were much lower than those for
dependence (5, 10). Second, by denition, a syndrome
requires more than one symptom, but nearly half of all
abuse cases were diagnosed with only one criterion, most
often hazardous use (11, 12). Third, although abuse is
often assumed to be milder than dependence, some abuse
criteria indicate clinically severe problems (e.g., substance-
related failure to fulll major responsibilities). Fourth,
common assumptions about the relationship of abuse and
dependence were shown to be incorrect in several studies
(e.g., that abuse is simply a prodromal condition to de-
pendence [1317] and that all cases of dependence also
met criteria for abuse, a concern particularly relevant to
women and minorities [1820]).
The problems pertaining to the DSM-IV hierarchy of
dependence over abuse also included diagnostic orphans
(2124), the case of two dependence criteria and no abuse
criteria, potentially a more serious condition than abuse but
ineligible for a diagnosis. Also, when the abuse criteria were
analyzed without regard to dependence, their test-retest
reliability improved considerably (5), suggesting that the
hierarchy, not the criteria, led to their poor reliability.
Finally, factor analyses of dependence and abuse criteria
(ignoring the DSM-IV hierarchy) showed that the criteria
formed one factor (25, 26) or two highly correlated factors
(2734), suggesting that the criteria should be combined to
represent a single disorder.
To further investigate the relationship of abuse and
dependence criteria, the work group and other researchers
used item response theory analysis, which builds on factor
analysis, to better understand how items (in this case, the
criteria) relate to each other. Item response theory models
indicate criterion severity (inversely related to frequency:
rarely endorsed criteria are considered more severe) and
discrimination (how well the criterion differentiates between
respondents with high and low severity of the condition).
The results from these analyses are often presented
graphically (Figure 2), where each curve represents a crite-
rion. Curves toward the right indicate criteria of greater
severity; steeper slopes indicate better discrimination (see
Table S2 in the online data supplement for more detail
about Figure 2).
TABLE 1. DSM-5 Substance-Related Disorders Work Group
Name Degree(s) Specialization Country
Charles OBrien (chair)
M.D., Ph.D. Addiction psychiatry USA
Marc Auriacombe M.D. Addiction psychiatry France
Guilherme Borges Sc.D. Epidemiology Mexico
Kathleen Bucholz Ph.D. Epidemiology USA
Alan Budney Ph.D. Substance use disorder treatment, marijuana USA
Wilson Compton
M.D., M.P.E Epidemiology, addiction psychiatry USA
Thomas Crowley
M.D. Psychiatry USA
Bridget F. Grant
Ph.D., Ph.D. Epidemiology, biostatistics, survey research USA
Deborah S. Hasin Ph.D. Epidemiology of substance use and psychiatric disorders USA
Walter Ling M.D. Addiction psychiatry USA
Nancy M. Petry Ph.D. Substance use and gambling treatment USA
Marc Schuckit M.D. Genetics and comorbidity USA
In addition to the scientists listed here who were members during the entire duration of the process, a list of consultants and advisers who
served on various subcommittees and contributed substantially to the discussion is contained in the ofcial publication of DSM-5.
Also a DSM-5 Task Force member.
Co-chair, 20072011.
Am J Psychiatry 170:8, August 2013 835
Table 2 lists the 39 articles on the item response theory
studies that were examined or conducted by the work
group, which include over 200,000 study participants. Two
main ndings arose, with similar results across substances,
countries, adults, adolescents, patients and nonpatients.
First, unidimensionality was found for all DSM-IV criteria
for abuse and dependence except legal problems, indi-
cating that dependence and the remaining abuse criteria
all indicate the same underlying condition. Second, while
severity rankings of criteria varied somewhat across studies,
abuse (red curves in Figure 2) and dependence (black curves
in Figure 2) criteria were always intermixed across the
severity spectrum, similar to the curves shown in Figure 2.
Collectively, this large body of evidence supported re-
moving the distinction between abuse and dependence.
Substance use prevalence, attitudes, and norms vary
across groups, settings, and cultures (7274). Therefore,
the work group examined the studies listed in Table 2 in
detail for evidence of age, gender, or other cultural bias in
the DSM-5 substance use disorder criteria. Such differ-
ences are identied in an item response theory frame-
work by testing for differential item functioning (i.e.,
whether the likelihood of endorsing a criterion differs by
group after accounting for mean group differences in
the underlying substance use disorders trait). With the
exception of legal problems, the criteria did not consis-
tently indicate differential item functioning across studies.
Even where differential item functioning was found (e.g.,
see references 35 and 36), no evidence of differential
functioning of the total score (i.e., the underlying sub-
stance use disorders trait) was found. Thus, consistent
gender or cultural bias was not found, although the extent
of the changes proposed for DSM-5 criteria for substance
use disorders suggested that there would be value in
additional research using different analytic strategies to
examine whether gender, age, or ethnic bias exists in the
DECISION: For DSM-5, combine abuse and dependence
criteria into one disorder (Figure 1), with two additional
changes indicated below.
Should Any Diagnostic Criteria Be Dropped?
If any criteria can be removed while retaining diagnostic
accuracy, the set will be easier to use in clinical practice.
The work group considered whether two criteria could be
dropped: legal problems and tolerance.
Legal problems. Reasons to remove legal problems from
the criteria set included very low prevalence in adult
samples (31, 35, 37, 38, 41, 57) and in many (58, 61, 69)
although not all (58, 60, 68) adolescent samples, low
discrimination (28, 36, 57, 64, 66, 69, 75), poor t with other
substance use disorder criteria (28, 32, 35, 47, 51, 76), and
little added information in item response theory analyses
(28, 37, 41, 44). Some clinicians were concerned that
dropping legal problems would leave certain patients
undiagnosed, an issue specically addressed among heavy
alcohol, cannabis, cocaine, and heroin users in metha-
done and dual-diagnosis psychiatric settings (57). None of
these patients reported substance-related legal problems
as their only criterion or losta DSM-5 substance use
disorder diagnosis without this criterion. Thus, legal pro-
blems are not a useful substance use disorder criterion,
FIGURE 1. DSM-IV and DSM-5 Criteria for Substance Use Disorders
Substance Use
Hazardous use X –X
Social/interpersonal problems related to use X –X
Neglected major roles to use X –X
Legal problems X ––
Withdrawald–X X
Tolerance – X X
Used larger amounts/longer X X
Repeated attempts to quit/control use X X
Much time spent using X X
Physical/psychological problems related to use X X
Activities given up to use X X
Craving – – X
One or more abuse criteria within a 12-month period and no dependence diagnosis; applicable to all substances except nicotine, for which
DSM-IV abuse criteria were not given.
Three or more dependence criteria within a 12-month period.
Two or more substance use disorder criteria within a 12-month period.
Withdrawal not included for cannabis, inhalant, and hallucinogen disorders in DSM-IV. Cannabis withdrawal added in DSM-5.
836 Am J Psychiatry 170:8, August 2013
although such problems may be an important treatment
focus in some settings.
Tolerance. Concerns about the tolerance criterion in-
cluded its operationalization, occasional poor t with
other criteria (51), occasional differential item functioning
(68), and relevance to the underlying disorder (77). How-
ever, most item response theory articles on substance
use disorder criteria (Table 2) did not nd anything
unique about tolerance relative to the other criteria.
DECISION: Drop legal problems as a DSM-5 diagnostic
Should Any Criteria Be Added?
If new criteria increase diagnostic accuracy, the set will
be improved by their addition. The work group considered
two criteria for possible addition: craving and consumption.
Craving. Support for craving as a substance use disorder
criterion comes indirectly from behavioral (7882), imag-
ing, pharmacology (83), and genetics studies (84). Some
believe that craving and its reduction is central to diag-
nosis and treatment (83, 85), although not all agree (86, 87).
Craving is included in the dependence criteria in ICD-10,
so adding craving to DSM-5 would increase consistency
between the nosologies.
Item response theory analyses of data from general
population and clinical samples in the United States and
elsewhere (42, 45, 47, 49, 57, 88) were used to determine
the relationship of craving to the other substance use
disorder criteria and whether its addition improved the
diagnosis. Craving was measured using questions about
a strong desire or urge to use the substance, or such
a strong desire to use that one couldnt think of anything
else. Across studies, craving t well with the other criteria
and did not perturb their factor loadings, severity, or
discrimination. Differential item functioning was generally
no more pronounced for craving than for other criteria. In
general population samples (e.g., the blue curve in
Figure 2), craving fell within the midrange of severity
(42). In clinical samples, craving was in the mid-to-lower
FIGURE 2. Information Characteristic Curves from Item Response Theory Analysis of DSM-IV Alcohol Abuse and Dependence
Criteria, Required to Persist Across 3 Years of Follow-Up
–1 –0.8 –0.6 –0.4 –0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4
Probability of Criterion Endorsement
Latent Trait Severity
Used larger amounts/longer
Repeated attempts to
quit/control use
Much time spent using
Activities given up to use
problems related to use
Neglected major roles to use
Hazardous use
Social/interpersonal problems
related to use
Red curves: DSM-IV abuse criteria. Black curves: DSM-IV dependence criteria. Blue curve: Craving.
Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 2 (20042005), conducted by the National
Institute on Alcohol Abuse and Alcoholism. Participants were noninstitutionalized civilians age 20 years and older (N=34,653). The NESARC
had a multistage design and oversampled blacks, Hispanics, and young adults. Analyses were conducted with Mplus (version 6.12, Los
Angeles, Muthén & Muthén, 2011) and incorporated sample weights to adjust standard errors appropriately. See supplementary Table S2 for
more detail on this analysis.
Am J Psychiatry 170:8, August 2013 837
TABLE 2. Item Response Theory Studies on DSM-5 Substance Use Disorder Criteria
Authors, Year
(Source) Substance Country
Year of
Adult, general
Saha et al.,
2006 (35)
Alcohol USA NESARC 20,846 AUDADIS-IV 20012002 Current Yes
Saha et al.,
2007 (36)
Alcohol USA NESARC 20,846 AUDADIS-IV 20012002 Current Yes
Gillespie et al.,
2007 (31)
Cannabis USA Adult twins 1,491 SCID 1990s Lifetime Yes
Lynskey and
2007 (37)
Amphetamine USA NESARC 2,025 AUDADIS-IV 20012002 Lifetime Yes
Cannabis USA NESARC 8,933 AUDADIS-IV 20012002 Lifetime Yes
Cocaine USA NESARC 2,672 AUDADIS-IV 20012002 Lifetime Yes
Hallucinogens USA NESARC 2,525 AUDADIS-IV 20012002 Lifetime Yes
Inhalants USA NESARC 728 AUDADIS-IV 20012002 Lifetime Yes
Opioids USA NESARC 2,060 AUDADIS-IV 20012002 Lifetime Yes
Sedatives USA NESARC 1,896 AUDADIS-IV 20012002 Lifetime Yes
Tranquilizers USA NESARC 1,487 AUDADIS-IV 20012002 Lifetime Yes
Compton et al.,
2009 (38)
Cannabis USA NESARC 1,603 AUDADIS-IV 20012002 Current Yes
McBride et al.,
2010 (39)
Nicotine USA NESARC 6,185 AUDADIS-IV 20012002
Yes (dependence only)
Saha et al.,
2010 (40)
Nicotine USA NESARC 7,852 AUDADIS-IV 20012002
Current Yes (dependence only)
et al.,
2010 (41)
Alcohol Israel Household 1,160 AUDADIS-IV 20072009 Current
Keyes et al.,
2011 (42)
Alcohol USA NLAES 18,352 AUDADIS-IV 19911992 Current Yes
Kerridge et al.,
2011 (43)
Hallucinogens USA NESARC 2,176 AUDADIS-IV 20012002 Lifetime Yes
Inhalants USA NESARC 664 AUDADIS-IV 20012002 Lifetime Yes
Saha et al.,
2012 (44)
Amphetamine USA NESARC 1,750 AUDADIS-IV 20012002 Lifetime Yes
Cocaine USA NESARC 2,528 AUDADIS-IV 20012002 Lifetime Yes
Opioids USA NESARC 1,815 AUDADIS-IV 20012002 Lifetime Yes
Sedatives USA NESARC 1,609 AUDADIS-IV 20012002 Lifetime Yes
Tranquilizers USA NESARC 1,301 AUDADIS-IV 20012002 Lifetime Yes
et al., 2011
Nicotine Israel Household 727 AUDADIS-IV 20072009 Lifetime Yes
Wu et al.,
2011 (46)
Opioids USA NSDUH 2,824 Survey-specic
2007 Current Yes
Mewton et al.,
2011 (47)
Alcohol Australia NSMHWB 7,746 CIDI version 2.0
1997 Current Yes
Gilder et al.,
2011 (48)
Alcohol USA American
530 SSAGA 1990s Lifetime Yes
Casey et al.,
2012 (49)
Alcohol USA NESARC 22,177 AUDADIS-IV 20042005 Current Yes
Wu et al.,
2012 (50)
Cannabis USA NSDUH 6,917 Survey-specic
2008 Current Yes
Adult, clinical
or mixed
et al., 2004 (51)
Alcohol USA Clinical 372 CIDISAM 1990s Lifetime Yes
Cannabis USA Clinical 262 CIDISAM 1990s Lifetime Yes
Cocaine USA Clinical 225 CIDISAM 1990s Lifetime Yes
Wu et al.,
2009 (52)
Cocaine USA Clinical 366 DSM-IV checklist 20012003 Current Yes (dependence only)
Opioids USA Clinical 354 DSM-IV checklist 20012003 Current Yes (dependence only)
Wu et al.,
2009 (53)
Alcohol USA Clinical 462 DSM-IV checklist 20012003 Current Yes (dependence only)
Cannabis USA Clinical 311 DSM-IV checklist 20012003 Current Yes (dependence only)
Borges et al.,
2010 (54)
Alcohol Multinational ED 3,191 Adapted CIDI 19952003 Current Yes
Alcohol Argentina ED 662 Adapted CIDI 2001 Current Yes
Alcohol Mexico ED 547 Adapted CIDI 19961997 Current Yes
Alcohol Poland ED 1,098 Adapted CIDI 20022003 Current Yes
Alcohol USA ED 884 Adapted CIDI 19951996 Current Yes
838 Am J Psychiatry 170:8, August 2013
TABLE 2. Item Response Theory Studies on DSM-5 Substance Use Disorder Criteria (continued)
Authors, Year
(Source) Substance Country
Year of
Borges et al.,
2011 (55)
Alcohol Argentina,
Poland, USA
ED 3,191 CIDI 19952003 Current Yes
et al., 2011
Alcohol USA COGA 8,605 SSAGA 19891996 Lifetime Yes
Hasin et al.,
2012 (57)
Alcohol USA Clinical 543 PRISM 19941999 Current Yes
Cannabis USA Clinical 340 PRISM 19941999 Current Yes
Cocaine USA Clinical 483 PRISM 19941999 Current Yes
Opioids USA Clinical 364 PRISM 19941999 Current Yes
Harford et al.,
2009 (58)
Alcohol USA NSDUH 133,231 Survey-specic
20022005 Current Yes
Strong et al.,
2009 (59)
Nicotine USA 6th10th
296 DSM-IV nicotine
2003 Current Yes (dependence only)
Wu et al.,
2009 (60)
Opioids USA NSDUH 1,290 Survey-specic
2006 Current Yes
Beseler et al.,
2010 (61)
Alcohol USA College
353 11-item self-
(based on
DSM criteria)
2007 Current Yes
Rose and
2010 (62)
Nicotine USA NSDUH 2,758 Survey-specic
19951998 Current Yes (dependence only)
Wu et al.,
2010 (63)
Hallucinogens USA NSDUH 1,548 Survey-specic
20042006 Current Yes
Hagman and
Cohn, 2011
Alcohol USA College
396 Survey-specic
2010 Current Yes
Mewton et al.,
2011 (65)
Alcohol Australia NSMHWB 853 CIDI version 2.0
1997 Current Yes (little evidence for
DSM-IV abuse/
distinction in young
Piontek et al.,
2011 (66)
Cannabis France SHCDDP 3,641 M-CIDI 2008 Current Yes
Strong et al.,
2012 (67)
Nicotine USA 6th10th
and relatives
556 DSM-IV nicotine
2003 Current Yes (dependence only)
clinical or
Martin et al.,
2006 (28)
Alcohol USA Clinical 464 SCID 2002 Lifetime Yes
Cannabis USA Clinical 417 SCID 2002 Lifetime Yes
Gelhorn et al.,
2008 (68)
Alcohol USA Mixed 5,587 CIDI-SAM 19932007 Lifetime Yes
Hartman et al.,
2008 (69)
Cannabis USA Mixed 5,587 CIDI-SAM 19932007 Lifetime Yes
Perron et al.,
2010 (70)
Inhalants USA Clinical 279 DIS-IV 2004 Lifetime Yes
Chung et al.,
2012 (71)
Nicotine USA Clinical 471 SCID 19902009 Lifetime Yes
NESARC=National Epidemiological Survey on Alcohol and Related Conditions; NLAES=National Longitudinal Alcohol Epidemiologic Survey;
NSDUH=National Survey on Drug Use and Health; NSMHWB=National SurveyofMentalHealthandWell-Being(Australia);ED=emergencydepart-
ment; COGA=Collaborative Study on the Genetics of Alcoholism; SHCDDP=Survey on Health and Consumption during the Day of Defense Preparation.
AUDADIS-IV=Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV; CIDI=Composite International Diagnostic Interview;
SAM=substance abuse module; SSAGA=Semi-Structured Assessment for the Genetics of Alcoholism; PRISM=Psychiatric Research Interview for
Substance and Mental Disorders; mFTQ=Modied Fagerström Tolerance Questionnaire; NDSS=Nicotine Dependence Syndrome Scale;
DIS=NIMH Diagnostic Interview Schedule.
Am J Psychiatry 170:8, August 2013 839
range of severity, likely because of high prevalence (57).
Some studies suggested that craving was redundant with
other criteria (47, 49). Using visual inspection to compare
item response theory total information curves for the
DSM-5 substance use disorder criteria with and without
craving produced inconsistent results (42, 47, 88). Using
statistical tests to compare total information curves, the
addition of craving to the dependence criteria did not
signicantly add information (45, 57). However, when
craving and the three abuse criteria were added, total
information was increased signicantly for nicotine,
alcohol, cannabis, and heroin, although not for cocaine
use disorders (45, 57). Clinicians expressed enthusiasm
about adding craving at work group presentations and on
the DSM-5 web site. In the end, while the psychometric
benet in adding a craving criterion was equivocal, the
view that craving may become a biological treatment
target (a nonpsychometric perspective) prevailed. While
awaiting the development of biological craving indicators,
clinicians and researchers can assess craving with ques-
tions like those used in the item response theory studies
(42, 45, 47, 49, 57, 88).
Consumption. The work group considered adding quantity
or frequency of consumption as a criterion. A putative
TABLE 3. Agreement Between DSM-IV Abuse/Dependence and DSM-5 Substance Use Disorders at Different Diagnostic
Sample (source) Sample Size Prevalence Kappa
National Epidemiologic Survey on Alcohol and
Related Conditions (6)
Drinkers, last 12 months
DSM-IV alcohol 0.10
DSM-5, $2 criteria 0.11 0.73
DSM-5, $3 criteria 0.06 0.73
Collaborative studies on genetics of alcoholism
nonproband adults (56)
Drinkers, lifetime 6,673
DSM-IV alcohol 0.43
DSM-5, $2 criteria 0.43 0.80
DSM-5, $3 criteria 0.32 0.74
Cannabis users, lifetime 4,569
DSM-IV cannabis 0.35
DSM-5, $2 criteria 0.33 0.82
DSM-5, $3 criteria 0.26 0.75
Cross-national emergency departments (54)
Drinkers, last 12 months
DSM-IV alcohol 0.21
DSM-5, $2 criteria 0.21 0.80
DSM-5, $3 criteria 0.15 0.79
Metropolitan clinical sample (N=663) (57)
Drinkers, last 12 months
DSM-IV current alcohol 46.9
DSM-5, $2 criteria 48.7 0.94
DSM-5, $3 criteria 45.7 0.96
DSM-5, $4 criteria 42.8 0.92
Cannabis users, last 12 months
DSM-IV cannabis 21.1
DSM-5, $2 criteria 19.6 0.85
DSM-5, $3 criteria 16.4 0.83
DSM-5, $4 criteria 13.4 0.73
Cocaine users, last 12 months
DSM-IV cocaine 52.9
DSM-5, $2 criteria 54.5 0.93
DSM-5, $3 criteria 51.7 0.96
DSM-5, $4 criteria 48.9 0.93
Heroin users, last 12 months
DSM-IV heroin 40.0
DSM-5, $2 criteria 41.6 0.95
DSM-5, $3 criteria 39.2 0.97
DSM-5, $4 criteria 36.5 0.96
Any use within prior 12 months.
840 Am J Psychiatry 170:8, August 2013
criterion of ve or more drinks per occasion for men and
four or more drinks for women t well with other criteria in
the U.S. general population (36), as did at least weekly
cannabis use and daily cigarette use (38, 40). However,
issues included worsening of model t (41), unclear utility
among cannabis users (66), and lack of a uniform cross-
national alcohol indicator (54). Quantifying other illicit
drug consumption patterns is even more difcult.
DECISION: Do not add consumption. Add craving or
a strong desire or urge to use the substanceto the DSM-5
substance use disordercriteria (Figure 1). Encourage further
research on the role of craving among substance use
disorder criteria.
What Should the Diagnostic Threshold Be?
The studies in Table 2 and others (8991) demonstrate
that the substance use disorders criteria represent a di-
mensional condition with no natural threshold. However,
a binary (yes/no) diagnostic decision is often needed.
To avoid a marked perturbation in prevalence without
justication, the work group sought a threshold for DSM-5
substance use disorders that would yield the best
agreement with the prevalence of DSM-IV substance
abuse and dependence disorders combined. To determine
this threshold, data from general population and clinical
samples were used to compute prevalences and agree-
ment (kappa) between DSM-5 substance use disorders
and DSM-IV dependence or abuse, examining thresholds
of two or more to four or more DSM-5 criteria (Table 3). As
shown, prevalence was very similar, and agreement (ranging
from very good to excellent) appeared maximized with the
threshold of two or more criteria, so it was selected. Another
recent large independently conducted study further sup-
ported this threshold (92).
Concerns that the threshold of two or more criteria is too
low have been expressed in the professional (93, 94) and
lay press (95), at presentations, and on the DSM-5 web site
(e.g., that it produces an overly heterogeneous group or
that those at low severity levels are not truecases). These
understandable concerns were weighed against the com-
peting need to identify all cases meriting intervention,
including milder cases, for example, those presenting in
primary care. Table 3 shows that a concern that millions
morewould be diagnosed with the DSM-5 threshold (95)
is unfounded if DSM-5 substance use disorder criteria are
assessed and decision rules are followed (rather than
assigning a substance use disorder diagnosis to any sub-
stance user). Additional concerns about the threshold
should be addressed by indicators of severity, which
clearly indicate that cases vary in severity.
An important exception to making a diagnosis of DSM-5
substance use disorder with two criteria pertains to the
supervised use of psychoactive substances for medical
purposes, including stimulants, cocaine, opioids, nitrous
oxide, sedative-hypnotic/anxiolytic drugs, and cannabis in
some jurisdictions (96, 97). These substances can produce
tolerance and withdrawal as normal physiological adapta-
tions when used appropriately for supervised medical
purposes. With a threshold of two or more criteria, these
criteria could lead to invalid substance use disorder
diagnoses even with no other criteria met. Under these
conditions, tolerance and withdrawal in the absence of
other criteria do not indicate substance use disorders and
should not be diagnosed as such.
DECISION: Set the diagnostic threshold for DSM-5
substance use disorders at two or more criteria.
How Should Severity Be Represented?
The DSM-5 Task Force asked work groups for severity
indicators of diagnoses (mild, moderate, or severe). Many
severity indicators are possible (e.g., levels of use, im-
pairment, or comorbidity), and the Substance-Related
Disorders Work Group sought a simple, parsimonious
approach. A count of the criteria themselves serves this
purpose well, since as the count increases so does the
likelihood of substance use disorder risk factors and
consequences (8991, 98). The work group considered
weighting the count by item response theory severity
parameters, but comparing the association of weighted
and unweighted criterion counts to consumption, func-
tioning, and family history showed no advantage for
weighting (98). Furthermore, since severity parameters
differ somewhat across samples (31), no universal set of
weights exists.
DECISION: Use a criteria count (from two to 11) as an
overall severity indicator. Use number of criteria met to
indicate mild (two to three criteria), moderate (four to
ve), and severe (six or more) disorders.
Physiological cases. DSM-IV included a specier for
physiological cases (i.e., those manifesting tolerance or
withdrawal, a DSM-III carryover), but the predictive value
of this specier was inconsistent (99106). A PubMed
search indicated that this specier was unused outside of
studies investigating its validity, indicating negligible
DECISION: Eliminate the physiological specier in
Course. In DSM-IV, six course speciers for dependence
were provided. Four of these pertained to the time frame
and completeness of remission, and two pertained to
extenuating circumstances.
In DSM-IV, the speciers for time frame and complete-
ness of remission were complex and little used. To
simplify, the work group eliminated partial remission
and divided the time frame into two categories, early and
sustained. Early remission indicates a period $3 months
but ,12 months without meeting DSM-5 substance use
disorders criteria other than craving. Three months was
selected because data indicated better outcomes for those
retained in treatment at least this long (107, 108). Sustained
Am J Psychiatry 170:8, August 2013 841
remission indicates a period lasting $12 months without
meeting DSM-5 substance use disorders criteria other than
craving. Craving is an exception because it can persist long
into remission (109, 110).
The work group noted that many clinical studies dene
remission and relapse in terms of substance use per se, not
in terms of DSM criteria. The work group did not do this in
order to remain consistent with DSM-IV criteria, and
because the criteria focus on substance-related difcul-
ties, not the extent of use, for the reasons discussed in the
section on adding criteria. In addition, a lack of consensus
on the level of use associated with a good outcome (111,
112) complicates substance use as a course specier for
the disorder.
The extenuating circumstance in a controlled environ-
mentwas unchanged from DSM-IV. DSM-IV also included
on agonist therapy(e.g., methadone or unspecied par-
tial agonists or agonist/antagonists). To update this cate-
gory, DSM-5 replaced it with on maintenance therapy
and provided specic examples.
DECISION: Dene early remission as $3 to ,12 months
without meeting substance use disorders criteria (except
craving) and sustained remission as $12 months without
meeting substance use disorders criteria (except craving).
Update the maintenance therapy category with examples
of agonists (e.g., methadone and buprenorphine), antag-
onists (e.g., naltrexone), and tobacco cessation medication
(bupropion and varenicline).
Could the Denitions of Substance-Induced Mental
Disorders Be Improved?
Substance use and other mental disorders frequently
co-occur, complicating diagnosis because many symp-
toms (e.g., insomnia) are criteria for intoxication, with-
drawal syndrome, or other mental disorders. Before
DSM-IV, the nonstandardized substance-induced mental
disorder criteria had poor reliability and validity. DSM-IV
improved this (113) via standardized guidelines to differ-
entiate between primaryand substance-inducedmen-
tal disorders. In DSM-IV, primary mental disorders were
diagnosed if they began prior to substance use or if they
persisted for more than 4 weeks after cessation of acute
withdrawal or severe intoxication. DSM-IV substance-
induced mental disorders were dened as occurring during
periods of substance intoxication or withdrawal or re-
mitting within 4 weeks thereafter. The symptoms listed for
both the relevant disorder and for substance intoxication
or withdrawal were counted toward the substance-induced
mental disorder only if they exceeded the expected severity
of intoxication or withdrawal. While severe consequences
could accompany substance-induced mental disorders (114),
remission was expected within days to weeks of abstinence
Despite these clarications, DSM-IV substance-induced
mental disorders remained diagnostically challenging
because of the absence of minimum duration and
symptom requirements and guidelines on when symp-
toms exceeded expected severity for intoxication or
withdrawal. In addition, the term primarywas confus-
ing, implying a time sequence or diagnostic hierarchy.
Research showed that DSM-IV substance-induced mental
disorders could be diagnosed reliably (113) and validly
(119) by standardizing the procedures to determine when
symptoms were greater than expected (although these
were complex) and, importantly, by requiring the same
duration and symptom criteria as the corresponding
primary mental disorder. This evidence led to the DSM-5
Substance-Related Disorders Work Group recommenda-
tion to increase standardization of the substance-induced
mental disorder criteria by requiring that diagnoses have
the same duration and symptom criteria as the corre-
sponding primary diagnosis. However, concerns from the
other DSM-5 work groups led the Board of Trustees to
aexible approach that reversed the DSM-IV standardi-
zation. This exible approach lacked specic symptom
and duration requirements and included the addition of
disorder-specic approaches crafted by other DSM-5 work
DECISIONS: 1) For a diagnosis of substance-induced
mental disorder, add a criterion that the disorder
resemblesthe full criteria for the relevant disorder. 2)
Remove the requirement that symptoms exceed expected
intoxication or withdrawal symptoms. 3) Specify that the
substance must be pharmacologically capable of pro-
ducing the psychiatric symptoms. 4) Change the name
primaryto independent.5) Adjust substance-induced
to substance/medication-induceddisorders, since the
latter were included in both DSM-IV and DSM-5 criteria
but not noted in the DSM-IV title.
Could Biomarkers Be Utilized in Making Substance
Use Disorder Diagnoses?
Because of the DSM-5 Task Force interest in biomarkers,
the Substance-Related Disorders Work Group, consulting
with outside experts, considered pharmacokinetic mea-
sures of the psychoactive substances or their metabolites,
genetic markers, and brain imaging indicators of brain
structure and function.
Many measures of drugs and associated metabolites in
blood, urine, sweat, saliva, hair, and breath have well-
established sensitivity and specicity characteristics.
However, these only indicate whether a substance was
taken within a limited recent time window and thus
cannot be used to diagnose substance use disorders.
Genetic variants within alcohol metabolizing genes
(ALDH2,ADH1B, and ADH4), genes related to neurotrans-
mission such as GABRA2 (120122), and nicotinic and
opioid receptor genes including CHRNA5 (120) and
OPRM1 (123) show replicated associations to substance
use disorders. However, these associations have small
effects or are rare in many populations and thus cannot be
used in diagnosis. Perhaps in future editions, DSM may
842 Am J Psychiatry 170:8, August 2013
include markers as predictors of treatment outcome (e.g.,
OPRM1 A118G and naltrexone response [124, 125])
Positron emission tomography (PET) imaging of brain
functioning indicates that dopamine is associated with
substance use (126, 127). However, measuring brain
dopamine markers involves radioligands, limiting their
use. Functional MRI (fMRI) produces structural and
functional data, but few fMRI or PET studies have
differentiated brain functioning predating and conse-
quent to onset of substance use disorders (128). Further-
more, brain imaging ndings based on group differences
are not specic enough to use as diagnostic markers in
individual cases. Finally, abnormalities in brain regions
and functioning that are associated with substance use
disorders overlap with other psychiatric disorders. In sum,
biomarkers are not yet appropriate as diagnostic tests for
substance use disorders. Continued research in this area is
DECISION: Do not include biomarkers.
Should Polysubstance Dependence Be Retained?
In DSM-IV, polysubstance dependence allowed diagno-
sis for multiple-substance users who failed to meet de-
pendence criteria for any one substance but had three or
more dependence criteria collectively across substances.
The category was often misunderstood as dependence on
multiple substances and was little used (129). With the new
threshold for DSM-5 substance use disorders (two or more
criteria), the category became irrelevant.
DECISION: Eliminate polysubstance dependence.
Substance-Specic Issues
Should Cannabis, Caffeine, Inhalant, and Ecstasy
Withdrawal Disorders Be Added?
Cannabis. Cannabis withdrawal was not included in DSM-
IV because of a lack of evidence. Since then, the reliability
and validity of cannabis withdrawal has been demon-
strated in preclinical, clinical, and epidemiological studies
(126, 127, 130135). The syndrome has a transient course
after cessation of cannabis use (135138) and pharmaco-
logical specicity (139141). Cannabis withdrawal is
reported by up to one-third of regular users in the general
population (131, 132, 134) and by 50%95% of heavy users
in treatment or research studies (133, 135, 142, 143). The
clinical signicance of cannabis withdrawal is demon-
strated by use of cannabis or other substances to relieve it,
its association with difculty quitting (135, 142, 144), and
worse treatment outcomes associated with greater with-
drawal severity (133, 143). In addition, in latent variable
modeling (30), adding withdrawal to other substance use
disorders criteria for cannabis improves model t.
Inhalants/hallucinogens. While some support exists for
adding withdrawal syndromes for inhalants and Ecstasy
(3,4-methylenedioxymethamphetamine) (31, 145147), the
literature and expert consultation suggest that evidence
remains insufcient to include these in DSM-5, but further
study is warranted.
Caffeine. In DSM-IV, caffeine withdrawal was included as
a research diagnosis to encourage research (148). The
accumulated evidence from preclinical and clinical studies
since the publication of DSM-IV supports the reliability,
validity, pharmacological specicity, and clinical signi-
cance of caffeine withdrawal (149152). Based on factor
analysis studies, the work group proposed modifying the
DSM-IV research criteria so that a diagnosis in DSM-5
would require three or more of the following symptoms: 1)
headache; 2) fatigue or drowsiness; 3) dysphoric mood or
irritability; 4) difculty concentrating; and 5) nausea,
vomiting, or muscle pain/stiffness (153, 154).
DSM-IV did not include caffeine dependence despite
preclinical research literature because clinical data were
lacking (155). Relatively small-sample clinical surveys
published since then and the accumulating data on the
clinical signicance of caffeine withdrawal and depen-
dence support further consideration for a caffeine use
disorder (152, 153, 156160), particularly given concerns
about youth energy drink misuse and new alcohol-caffeine
combination beverages (161, 162). However, clinical and
epidemiological studies with larger samples and more
diverse populations are needed to determine prevalence,
establish a consistent set of diagnostic criteria, and better
evaluate the clinical signicance of a caffeine use disorder.
These studies should address test-retest reliability and
antecedent, concurrent, and predictive validity (e.g.,
distress and impaired functioning).
DECISIONS: 1) Add cannabis withdrawal disorder. In-
clude withdrawal as a criterion for cannabis use disorder. 2)
Add caffeine withdrawal disorder, and include caffeine use
disorder in Section 3 (Conditions for Further Study).
Could the Nicotine Criteria Be Aligned With the
Diagnostic Criteria for the Other Substance Use
DSM-IV included nicotine dependence, but experts felt
that abuse criteria were inapplicable to nicotine (163, 164),
so these were not included. Nicotine dependence has good
test-retest reliability (165167) and its criteria indicate
a unidimensional latent trait (39, 40, 62, 67, 168). Concerns
about DSM-IV-dened nicotine dependence include the
utility of some criteria, the ability to predict treatment
outcome, and low prevalence in smokers (131, 163, 169).
Many studies therefore indicate nicotine dependence with
an alternative measure, the Fagerström Nicotine De-
pendence Scale (170, 171). DSM-IV and the Fagerström
scale measure somewhat different aspects of a common
underlying trait (67, 168, 172).
Because DSM-5 combines dependence and abuse,
studies addressed whether criteria for nicotine use
disorder could be aligned with other substance use
disorders (45, 71, 181), potentially also addressing the
Am J Psychiatry 170:8, August 2013 843
concerns about DSM-IV-dened nicotine dependence.
Smoking researchers widely regard craving as an in-
dicator of dependence and relapse (164, 173175). In-
creasing disapproval of smoking (176) and wider smoking
restrictions (177) suggest improved face validity of con-
tinued smoking despite interpersonal problems and
smoking-related failure to fulll responsibilities as to-
bacco use disorder criteria. Smoking is highly associated
with re-related and other mortality (e.g., unintentional
injuries and vehicle crashes) (173, 178180), suggesting
the applicability of hazardous use as a criterion for to-
bacco use disorders, parallel with hazardous use of other
To examine the alignment of criteria for tobacco use
disorder with those for other substance use disorders, an
item response theory analysis of the seven dependence
criteria, three abuse criteria, and craving was performed in
a large adult sample of smokers (45). The 11 criteria formed
a unidimensional latent trait intermixed across the severity
spectrum, signicantly increasing information over a model
using DSM-IV nicotine dependence criteria only. Differen-
tial item functioning was found for craving and hazardous
use, but differential total score functioning was not found.
The proposed tobacco use disorder criteria (individually
and as a set) were strongly associated with a panel of
validators, including smoking quantity and smoking shortly
after awakening (181). The tobacco use disorder criteria
were more discriminating than the DSM-IV nicotine depen-
dence criteria (181) and produced a higher prevalence than
DSM-IV criteria, addressing a DSM-IV concern (163). An
item response theory secondary analysis of 10 of the 11
criteria from adolescent and young adult substance abuse
patients (71) also revealed unidimensionality and a higher
prevalence of DSM-5 tobacco use disorder than DSM-IV
nicotine dependence (71).
DECISION: Align DSM-5 criteria for tobacco use dis-
order with criteria for the other substance use disorders.
Should Neurobehavioral Disorder Associated With
Prenatal Alcohol Exposure Be Added?
In utero alcohol exposure acts as a neurobehavioral
teratogen, with lifelong effects on CNS function and
behavior (182, 183). These effects are now known as
neurobehavioral disorder associated with prenatal alcohol
exposure. Key features include neurocognitive and behav-
ioral impairments (184) diagnosed through standardized
psychological or educational testing, caregiver/teacher
questionnaires, medical records, reports from the patient
or a knowledgeable informant, or clinician observation.
Prenatal alcohol exposure can be determined by maternal
self-report, othersreported observations of maternal
drinking during the pregnancy, and documentation in
medical or other records.
Neurobehavioral disorder associated with prenatal alco-
hol exposure was not included in DSM-IV. The proposed
diagnostic guidelines allow this diagnosis regardless of the
facial dysmorphology required to diagnose fetal alcohol
syndrome (185). Many clinical experts support the diag-
nosis (186), and clinical need is suggested by substantial
misdiagnosis, leading to unmet treatment need (186).
However, more information is needed on this disorder
before it can be included in the main diagnosis section of
the manual.
DECISION: Include neurobehavioral disorder associ-
ated with prenatal alcohol exposure in Section 3.
Issues Not Related To Substances
Should Gambling Disorder and Other Putative
Behavioral AddictionsBe Added to the Substance
Disorders Chapter?
Gambling. In DSM-IV, pathological gambling is in the
section entitled Impulse-Control Disorders Not Else-
where Classied.Pathological gambling is comorbid with
substance use disorders (187189) and is similar to
substance use disorders in some symptom presentations
(190), biological dysfunction (191), genetic liability (192),
and treatment approaches (193195). The work group
therefore concurred with a DSM-5 Task Force request
to move pathological gambling to the substance use
disorders chapter. The work group also recommended
other modications (196). The name will be changed to
Gambling Disorderbecause the term pathological is
pejorative and redundant. The criterion illegal acts to
nance gamblingwas removed for the same reasons that
legal problems were removed from substance use disor-
ders (197200; B. Grant, unpublished 2010 data). The
diagnostic threshold was reduced to four or more criteria
to improve classication accuracy (200203). A further
reduction in the threshold was considered, but this
greatly increased prevalence (189, 197) without evidence
for diagnostic improvement. Future research should
explore whether gambling disorder can be assessed using
criteria that are parallel to those for substance use
disorders (200).
Other non-substance-related disorders. The work group
consulted outside experts and reviewed literature on other
potential non-substance-related behaviors (e.g., Internet
gaming and shopping). This included over 200 publica-
tions on Internet gaming addiction, mostly Asian case
reports or series of young males. Despite the large
literature (204207), no standard diagnostic criteria and
only limited data were available on prevalence, course,
or brain functioning. Therefore, research is needed to
ascertain the unique characteristics of the disorder, the
cross-cultural reliability and validity data of diagnostic
criteria, prevalence in representative samples, natural
history, and potentially associated biological factors
(196). Research on other behavioral addictions is even
more preliminary. Disorders involving sexual behaviors or
eating were handled by other work groups.
844 Am J Psychiatry 170:8, August 2013
DECISION: Include gambling disorder in the substance
use disorders section, with changes noted above. Add
Internet gaming disorder to Section 3.
Should the Name of the Chapter Be Changed?
With the addition of gambling disorder to the chapter,
a change in the title was necessary. The Board of Trustees
assigned the title Substance-Related and Addictive Dis-
orders,despite the DSM-5 Substance-Related Disorders
Work Group having previously approved a title (by ma-
jority but not consensus) that did not include the term
addiction. This lack of agreement over the title reects an
overall tension in the eld over the terms addiction and
dependence, as seen in editorials (2, 208) advocating
addiction as a general term, reserving dependence specif-
ically for tolerance and/or withdrawal, and the more than
80 comments on these editorials that debated the pros
and cons of these terms.
Present Status and Future Directions
Since 2007, the Substance-Related Disorders Work
Group addressed many issues. The members conducted
and published analyses, and they formulated new criteria
and presented them widely for input. The DSM-5 Task
Force requested a reduction in the number of disorders
wherever possible, and the work group accomplished this.
The DSM process requires balancing many competing
needs, which is always the case when formulating new
nomenclatures. The process also entails extensive, unpaid
collaboration among a group of experts with different
backgrounds and perspectives. Scientic controversies
arose and received responses (see references 2, 47, and
209211). Conict of interest could undermine condence
in the work groups recommendations (212), but in fact, as
monitored by APA, eight of the 12 members received no
pharmaceutical industry income over the 5 years since the
work group was convened, two received less than $1,200
and two received less than $10,000 (the APA cap) in any
single year. Some individuals assume that nancial
interests advocated directly to the work group (e.g.,
pharmaceutical companies, alcohol and tobacco in-
dustries, insurers, and providers). Actually, this never
happened. While such advocacy could have occurred
surreptitiously through unsigned DSM-5 web site com-
ments, few comments stood out as particularly inuential
since they covered such a wide range of opinions. An
exception to this was the web site advocacy of nonprot
groups to include neurobehavioral disorder associated
with prenatal alcohol exposure (taken into account in
forming the disorder recommendation). Ultimately, the
work group recommendations attracted considerable
interest, and the DSM-5 process stimulated much sub-
stance use disorder research that otherwise would not
have occurred.
Implementing the 11 DSM-5 substance use disorders
criteria in research and clinical assessment should be
easier than implementing the 11 DSM-IV criteria for
substance abuse and dependence, since now only one
disorder is involved instead of two hierarchical disorders.
A checklist can aid in covering all criteria. Eventually,
reducing the number of criteria to diagnose substance use
disorders will further aid implementation, which future
studies should address.
The statistical methodology used to examine the
structure of abuse and dependence criteria was state of
the art, and the data sets analyzed were large and based on
standardized diagnostic procedures with good to excellent
reliability and validity. However, these data sets, collected
several years ago, were not designed to examine the
reliability and validity of the DSM-5 substance use
disorder diagnosis. Many studies showed that DSM-IV
dependence was reliable and valid (5), suggesting that
major components of the DSM-5 substance use disorders
criteria are reliable as well. However, eld trials using
standard methodology to minimize information variance
(213) are needed to provide information on the reliability
of DSM-5 substance use disorder diagnosis that can be
directly compared with DSM-IV (214), in addition to
studies on the antecedent, concurrent, and predictive
validity of DSM-5 substance use disorders relative to
DSM-IV dependence.
The amount of data available to address the topics dis-
cussed above varied, and new studies will be needed for
some of the more specic issues. However, major concerns
regarding the combination of abuse and dependence
criteria were conclusively addressed because an astonish-
ing amount of data was available and the results were very
consistent. The recommendations for DSM-5 substance
use disorders represent the results of a lengthy and
intensive process aimed at identifying problems in DSM-
IV and resolving these through changes in DSM-5. At
the same time, the variable amount of evidence on some of
the issues points the way toward studies aimed at
further clarications and improvements in future edi-
tions of DSM.
Received June 13, 2012; revision received Jan. 22, 2013; accepted
Feb. 11, 2013 (doi: 10.1176/appi.ajp.2013.12060782). From the New
York State Psychiatric Institute, New York; the Departments of
Psychiatry and Epidemiology, Columbia University, New York; the
Department of Psychiatry, University of Pennsylvania, Philadelphia;
the Center for Studies of Addiction, Philadelphia; the Department of
Addiction Psychiatry, Université Bordeaux Ségalen, Bordeaux,
France; the National Institute of Psychiatry, Federal District, Mexico;
the Department of Psychiatry, Washington University School of
Medicine, St. Louis; the Center for Addiction Research, Department
of Psychiatry, University of Arkansas for Medical Sciences, Little Rock;
the Division of Epidemiology, Services and Prevention Research,
National Institute on Drug Abuse, Bethesda, Md.; the Department of
Psychiatry and the Division of Substance Dependence, University of
Colorado School of Medicine, Aurora; the Department of Psychiatry
and Biobehavioral Sciences and the Integrated Substance Abuse
Am J Psychiatry 170:8, August 2013 845
Programs, University of California, Los Angeles; the Department of
Psychiatry and the Behavioral Cardiovascular Prevention Calhoun
Cardiology Center, University of Connecticut Health Center, Farm-
ington; the Department of Psychiatry, San Diego VA Medical Center,
San Diego; the Laboratory of Epidemiology and Biometry, National
Institute on Alcohol Abuse and Alcoholism, Bethesda. Address
correspondence to Dr. Hasin (
Dr. Auriacombe has received research grants or advisory board fees
from D&A Pharma, Mundipharma, and Reckitt Benckiser Pharma-
ceuticals. Dr. Budney has received consulting fees from G.W.
Pharmaceuticals. Dr. Compton has stock holdings in General Electric
and Pzer. Dr. Ling has received consulting fees or research, grant, or
travel support from Alkermes, Braeburn Pharmaceuticals, Reckitt/
Benckiser, Titan Pharmaceuticals, U.S. World Meds, and SGS North
America. The other authors report no nancial relationships with
commercial interests.
Supported by the National Institute on Alcohol Abuse and
Alcoholism (grants K05AA014223, U01AA018111), the National In-
stitute on Drug Abuse (R01DA018652), and the New York State
Psychiatric Institute (to Dr. Hasin).
The authors thank Katherine M. Keyes, Nick Giedris, and Dvora
Shmulewitz for help in preparing the manuscript and Ray Anton,
Robert Balster, Deborah Dawson, Danielle Dick, Joel Gelernter,
Marilyn Huestis, John Hughes, Tom Kosten, Henry Kranzler, Tulshi
Saha, Wim van den Brink, and Nora Volkow for their expert input.
The views and opinions expressed in this article are those of the
authors and should not be construed to represent the views of any of
the sponsoring organizations, agencies, or the U.S. government.
1. Special issue: diagnostic issues in substance use disorders: re-
ning the research agenda. Addiction 2006; 101(suppl 1):
2. OBrien C: Addiction and dependence in DSM-V. Addiction
2011; 106:866867
3. Edwards G, Gross MM: Alcohol dependence: provisional de-
scription of a clinical syndrome. BMJ 1976; 1:10581061
4. Rounsaville BJ, Spitzer RL, Williams JB: Proposed changes in
DSM-III substance use disorders: description and rationale. Am
5. Hasin D, Hatzenbuehler ML, Keyes K, Ogburn E: Substance use
disorders: Diagnostic and Statistical Manual of Mental Dis-
orders, fourth edition (DSM-IV) and International Classication
of Diseases, tenth edition (ICD-10). Addiction 2006; 101(suppl
6. Grant BF, Stinson FS, Dawson DA, Chou SP, Dufour MC,
Compton W, Pickering RP, Kaplan K: Prevalence and co-
occurrence of substance use disorders and independent mood
and anxiety disorders: results from the National Epidemiologic
Survey on Alcohol and Related Conditions. Arch Gen Psychiatry
2004; 61:807816
7. Compton WM, Thomas YF, Stinson FS, Grant BF: Prevalence,
correlates, disability, and comorbidity of DSM-IV drug abuse
and dependence in the United States: results from the Na-
tional Epidemiologic Survey on Alcohol and Related Con-
ditions. Arch Gen Psychiatry 2007; 64:566576
8. Dawson DA: Drinking patterns among individuals with and
without DSM-IV alcohol use disorders. J Stud Alcohol 2000; 61:
9. Hasin DS, Stinson FS, Ogburn E, Grant BF: Prevalence, corre-
lates, disability, and comorbidity of DSM-IV alcohol abuse and
dependence in the United States: results from the National
Epidemiologic Survey on Alcohol and Related Conditions. Arch
Gen Psychiatry 2007; 64:830842
10. Pierucci-Lagha A, Gelernter J, Feinn R, Cubells JF, Pearson D,
Pollastri A, Farrer L, Kranzler HR: Diagnostic reliability of the
Semi-structured Assessment for Drug Dependence and Alco-
holism (SSADDA). Drug Alcohol Depend 2005; 80:303312
11. Hasin D, Paykin A: DSM-IV alcohol abuse: investigation in
a sample of at-risk drinkers in the community. J Stud Alcohol
1999; 60:181187
12. Hasin D, Paykin A, Endicott J, Grant B: The validity of DSM-IV
alcohol abuse: drunk drivers versus all others. J Stud Alcohol
1999; 60:746755
13. Hasin DS, Grant B, Endicott J: The natural history of alcohol
abuse: implications for denitions of alcohol use disorders.
Am J Psychiatry 1990; 147:15371541
14. Hasin DS, Van Rossem R, McCloud S, Endicott J: Differentiating
DSM-IV alcohol dependence and abuse by course: community
heavy drinkers. J Subst Abuse 1997; 9:127135
15. Schuckit MA, Smith TL, Landi NA: The 5-year clinical course of
high-functioning men with DSM-IV alcohol abuse or de-
pendence. Am J Psychiatry 2000; 157:20282035
16. Schuckit MA, Smith TL: A comparison of correlates of DSM-IV
alcohol abuse or dependence among more than 400 sons of
alcoholics and controls. Alcohol Clin Exp Res 2001; 25:18
17. Grant BF, Stinson FS, Harford TC: Age at onset of alcohol use
and DSM-IV alcohol abuse and dependence: a 12-year follow-
up. J Subst Abuse 2001; 13:493504
18. Hasin DS, Hatzenbueler M, Smith S, Grant BF: Co-occurring
DSM-IV drug abuse in DSM-IV drug dependence: results from
the National Epidemiologic Survey on Alcohol and Related
Conditions. Drug Alcohol Depend 2005; 80:117123
19. Hasin DS, Grant BF: The co-occurrence of DSM-IV alcohol
abuse in DSM-IV alcohol dependence: results of the National
Epidemiologic Survey on Alcohol and Related Conditions on
heterogeneity that differ by population subgroup. Arch Gen
Psychiatry 2004; 61:891896
20. Grant BF, Compton WM, Crowley TJ, Hasin DS, Helzer JE, Li TK,
Rounsaville BJ, Volkow ND, Woody GE: Errors in assessing
DSM-IV substance use disorders. Arch Gen Psychiatry 2007;
64:379380, author reply 381372
21. Hasin D, Paykin A: Dependence symptoms but no diagnosis:
diagnostic orphansin a community sample. Drug Alcohol
Depend 1998; 50:1926
22. Hasin D, Paykin A: Dependence symptoms but no diagnosis:
diagnostic orphansin a 1992 national sample. Drug Alcohol
Depend 1999; 53:215222
23. Pollock NK, Martin CS: Diagnostic orphans: adolescents with
alcohol symptom who do not qualify for DSM-IV abuse or
dependence diagnoses. Am J Psychiatry 1999; 156:897901
24. McBride O, Adamson G, Bunting BP, McCann S: Characteristics
of DSM-IV alcohol diagnostic orphans: drinking patterns,
physical illness, and negative life events. Drug Alcohol Depend
2009; 99:272279
25. Krueger RF, Nichol PE, Hicks BM, Markon KE, Patrick CJ, Iacono
WG, McGue M: Using latent trait modeling to conceptualize
an alcohol problems continuum. Psychol Assess 2004; 16:
26. Hasin DS, Muthuen B, Wisnicki KS, Grant B: Validity of the bi-
axial dependence concept: a test in the US general population.
Addiction 1994; 89:573579
27. Proudfoot H, Baillie AJ, Teesson M: The structure of alcohol
dependence in the community. Drug Alcohol Depend 2006;
28. Martin CS, Chung T, Kirisci L, Langenbucher JW: Item response
theory analysis of diagnostic criteria for alcohol and cannabis
use disorders in adolescents: implications for DSM-V. J Abnorm
Psychol 2006; 115:807814
29. Harford TC, Muthén BO: The dimensionality of alcohol abuse
and dependence: a multivariate analysis of DSM-IV symptom
items in the National Longitudinal Survey of Youth. J Stud
Alcohol 2001; 62:150157
30. Agrawal A, Lynskey MT: Does gender contribute to hetero-
geneity in criteria for cannabis abuse and dependence?
846 Am J Psychiatry 170:8, August 2013
results from the National Epidemiological Survey on Alcohol
and Related Conditions. Drug Alcohol Depend 2007; 88:
31. Gillespie NA, Neale MC, Prescott CA, Aggen SH, Kendler KS:
Factor and item-response analysis DSM-IV criteria for abuse of
and dependence on cannabis, cocaine, hallucinogens, seda-
tives, stimulants and opioids. Addiction 2007; 102:920930
32. Teesson M, Lynskey M, Manor B, Baillie A: The structure of
cannabis dependence in the community. Drug Alcohol De-
pend 2002; 68:255262
33. Blanco C, Harford TC, Nunes E, Grant B, Hasin D: The latent
structure of marijuana and cocaine use disorders: results from
the National Longitudinal Alcohol Epidemiologic Survey
(NLAES). Drug Alcohol Depend 2007; 91:9196
34. Grant BF, Harford TC, Muthén BO, Yi HY, Hasin DS, Stinson FS:
DSM-IV alcohol dependence and abuse: further evidence of
validity in the general population. Drug Alcohol Depend 2007;
35. Saha TD, Chou SP, Grant BF: Toward an alcohol use disorder
continuum using item response theory: results from the Na-
tional Epidemiologic Survey on Alcohol and Related Con-
ditions. Psychol Med 2006; 36:931941
36. Saha TD, Stinson FS, Grant BF: The role of alcohol consump-
tion in future classications of alcohol use disorders. Drug
Alcohol Depend 2007; 89:8292
37. Lynskey MT, Agrawal A: Psychometric properties of DSM
assessments of illicit drug abuse and dependence: results from
the National Epidemiologic Survey on Alcohol and Related
Conditions (NESARC). Psychol Med 2007; 37:13451355
38. Compton WM, Saha TD, Conway KP, Grant BF: The role of
cannabis use within a dimensional approach to cannabis use
disorders. Drug Alcohol Depend 2009; 100:221227
39. McBride O, Strong DR, Kahler CW: Exploring the role of a nic-
otine quantity-frequency use criterion in the classication of
nicotine dependence and the stability of a nicotine de-
pendence continuum over time. Nicotine Tob Res 2010; 12:
40. Saha TD, Compton WM, Pulay AJ, Stinson FS, Ruan WJ, Smith
SM, Grant BF: Dimensionality of DSM-IV nicotine dependence
in a national sample: an item response theory application.
Drug Alcohol Depend 2010; 108:2128
41. Shmulewitz D, Keyes K, Beseler C, Aharonovich E, Aivadyan C,
Spivak B, Hasin D: The dimensionality of alcohol use dis-
orders: results from Israel. Drug Alcohol Depend 2010; 111:
42. Keyes KM, Krueger RF, Grant BF, Hasin DS: Alcohol craving and
the dimensionality of alcohol disorders. Psychol Med 2011; 41:
43. Kerridge BT, Saha TD, Smith S, Chou PS, Pickering RP, Huang B,
Ruan JW, Pulay AJ: Dimensionality of hallucinogen and
inhalant/solvent abuse and dependence criteria: implications
for the Diagnostic and Statistical Manual of Mental Disorders,
fth edition. Addict Behav 2011; 36:912918
44. Saha TD, Compton WM, Chou SP, Smith S, Ruan WJ, Huang B,
Pickering RP, Grant BF: Analyses related to the development of
DSM-5 criteria for substance use related disorders: 1. Toward
amphetamine, cocaine and prescription drug use disorder
continua using item response theory. Drug Alcohol Depend
2012; 122:3846
45. Shmulewitz D, Keyes KM, Wall MM, Aharonovich E, Aivadyan C,
Greenstein E, Spivak B, Weizman A, Frisch A, Grant BF, Hasin D:
Nicotine dependence, abuse and craving: dimensionality in an
Israeli sample. Addiction 2011; 106:16751686
46. Wu LT, Woody GE, Yang C, Pan JJ, Blazer DG: Abuse and
dependence on prescription opioids in adults: a mixture cat-
egorical and dimensional approach to diagnostic classica-
tion. Psychol Med 2011; 41:653664
47. Mewton L, Slade T, McBride O, Grove R, Teesson M: An eval-
uation of the proposed DSM-5 alcohol use disorder criteria
using Australian national data. Addiction 2011; 106:941950
48. Gilder DA, Gizer IR, Ehlers CL: Item response theory analysis of
binge drinking and its relationship to lifetime alcohol use
disorder symptom severity in an American Indian community
sample. Alcohol Clin Exp Res 2011; 35:984995
49. Casey M, Adamson G, Shevlin M, McKinney A: The role of
craving in AUDs: dimensionality and Differential Functioning
in the DSM-5. Drug Alcohol Depend 2012; 125:7580
50. Wu LT, Woody GE, Yang C, Pan JJ, Reeve BB, Blazer DG: A
dimensional approach to understanding severity estimates
and risk correlates of marijuana abuse and dependence in
adults. Int J Methods Psychiatr Res 2012; 21:117133
51. Langenbucher JW, Labouvie E, Martin CS, Sanjuan PM, Bavly L,
Kirisci L, Chung T: An application of item response theory
analysis to alcohol, cannabis, and cocaine criteria in DSM-IV. J
Abnorm Psychol 2004; 113:7280
52. Wu LT, Pan JJ, Blazer DG, Tai B, Brooner RK, Stitzer ML, Patkar
AA, Blaine JD: The construct and measurement equivalence
of cocaine and opioid dependences: a National Drug Abuse
Treatment Clinical Trials Network (CTN) study. Drug Alcohol
Depend 2009; 103:114123
53. Wu LT, Pan JJ, Blazer DG, Tai B, Stitzer ML, Brooner RK, Woody
GE, Patkar AA, Blaine JD: An item response theory modeling of
alcohol and marijuana dependences: a National Drug Abuse
Treatment Clinical Trials Network study. J Stud Alcohol Drugs
2009; 70:414425
54. Borges G, Ye Y, Bond J, Cherpitel CJ, Cremonte M, Moskalewicz
J, Swiatkiewicz G, Rubio-Stipec M: The dimensionality of alco-
hol use disorders and alcohol consumption in a cross-national
perspective. Addiction 2010; 105:240254
55. Borges G, Cherpitel CJ, Ye Y, Bond J, Cremonte M, Moskalewicz
J, Swiatkiewicz G: Threshold and optimal cut-points for alcohol
use disorders among patients in the emergency department.
Alcohol Clin Exp Res 2011; 35:12701276
56. McCutcheon VV, Agrawal A, Heath AC, Edenberg HJ, Hesselbrock
VM, Schuckit MA, Kramer JR, Bucholz KK: Functioning of alcohol
use disorder criteria among men and women with arrests for
driving under the inuence of alcohol. Alcohol Clin Exp Res
2011; 35:19851993
57. Hasin DS, Fenton MC, Beseler C, Park JY, Wall MM: Analyses
related to the development of DSM-5 criteria for substance use
related disorders: 2. Proposed DSM-5 criteria for alcohol,
cannabis, cocaine and heroin disorders in 663 substance
abuse patients. Drug Alcohol Depend 2012; 122:2837
58. Harford TC, Yi HY, Faden VB, Chen CM: The dimensionality of
DSM-IV alcohol use disorders among adolescent and adult
drinkers and symptom patterns by age, gender, and race/
ethnicity. Alcohol Clin Exp Res 2009; 33:868878
59. Strong DR, Kahler CW, Colby SM, Griesler PC, Kandel D: Linking
measures of adolescent nicotine dependence to a common
latent continuum. Drug Alcohol Depend 2009; 99:296308
60. Wu LT, Ringwalt CL, Yang C, Reeve BB, Pan JJ, Blazer DG:
Construct and differential item functioning in the assessment
of prescription opioid use disorders among American ado-
lescents. J Am Acad Child Adolesc Psychiatry 2009; 48:
61. Beseler CL, Taylor LA, Leeman RF: An item-response theory
analysis of DSM-IV alcohol-use disorder criteria and binge
drinking in undergraduates. J Stud Alcohol Drugs 2010; 71:
62. Rose JS, Dierker LC: DSM-IV nicotine dependence symptom
characteristics for recent-onset smokers. Nicotine Tob Res
2010; 12:278286
63. Wu LT, Pan JJ, Yang C, Reeve BB, Blazer DG: An item re-
sponse theory analysis of DSM-IV criteria for hallucinogen
Am J Psychiatry 170:8, August 2013 847
abuse and dependence in adolescents. Addict Behav 2010;
64. Hagman BT, Cohn AM: Toward DSM-V: mapping the alcohol
use disorder continuum in college students. Drug Alcohol
Depend 2011; 118:202208
65. Mewton L, Teesson M, Slade T, Cottler L: Psychometric per-
formance of DSM-IV alcohol use disorders in young adulthood:
evidence from an Australian general population sample. J Stud
Alcohol Drugs 2011; 72:811822
66. Piontek D, Kraus L, Legleye S, Bühringer G: The validity of DSM-
IV cannabis abuse and dependence criteria in adolescents and
the value of additional cannabis use indicators. Addiction
2011; 106:11371145
67. Strong DR, Schonbrun YC, Schaffran C, Griesler PC, Kandel D:
Linking measures of adult nicotine dependence to a common
latent continuum and a comparison with adolescent patterns.
Drug Alcohol Depend 2012; 120:8898
68. Gelhorn H, Hartman C, Sakai J, Stallings M, Young S, Rhee SH,
Corley R, Hewitt J, Hopfer C, Crowley T: Toward DSM-V: an item
response theory analysis of the diagnostic process for DSM-IV
alcohol abuse and dependence in adolescents. J Am Acad
Child Adolesc Psychiatry 2008; 47:13291339
69. Hartman CA, Gelhorn H, Crowley TJ, Sakai JT, Stallings M,
Young SE, Rhee SH, Corley R, Hewitt JK, Hopfer CJ: Item re-
sponse theory analysis of DSM-IV cannabis abuse and de-
pendence criteria in adolescents. J Am Acad Child Adolesc
Psychiatry 2008; 47:165173
70. Perron BE, Vaughn MG, Howard MO, Bohnert A, Guerrero E:
Item response theory analysis of DSM-IV criteria for inhalant-
use disorders in adolescents. J Stud Alcohol Drugs 2010; 71:
71. Chung T, Martin CS, Maisto SA, Cornelius JR, Clark DB: Greater
prevalence of proposed DSM-5 nicotine use disorder com-
pared to DSM-IV nicotine dependence in treated adolescents
and young adults. Addiction 2012; 107:810818
72. World Health Organization: ATLAS on substance use: (2010):
resources for the prevention and treatment of substance use
disorders. Geneva, World Health Organization, 2010 (http://
73. United Nations Ofce on Drugs and Crime (UNODC): World
Drug Report 2009. United Nations, 2009 (http://www.unodc.
74. World Health Organization: Global Status Report on Alcohol and
Health, 2011. Geneva, World Health Organization, 2011 (http://
75. Lagenbucher JW: Alcohol abuse: adding content to category.
Alcohol Clin Exp Res 1996; 20(suppl):270A275A
76. Svanum S: Alcohol-related problems and dependence: an
elaboration and integration. Int J Addict 1986; 21:539558
77. Perkins KA: Chronic tolerance to nicotine in humans and its
relationship to tobacco dependence. Nicotine Tob Res 2002;
78. OBrien CP, Childress AR, Ehrman R, Robbins SJ: Conditioning
factors in drug abuse: can they explain compulsion? J Psy-
chopharmacol 1998; 12:1522
79. Miller NS, Goldsmith RJ: Craving for alcohol and drugs in ani-
mals and humans: biology and behavior. J Addict Dis 2001; 20:
80. Weiss F: Neurobiology of craving, conditioned reward and
relapse. Curr Opin Pharmacol 2005; 5:919
81. Heinz A, Beck A, Grüsser SM, Grace AA, Wrase J: Identifying the
neural circuitry of alcohol craving and relapse vulnerability.
Addict Biol 2009; 14:108118
82. Water s AJ, Shi ffman S , Sa yet te M A, Pa ty J A, Gwal tney CJ ,
Balabanis MH: Cue-provoked craving and nicotine replacement
therapy in smoking cessation. J Consult Clin Psychol 2004; 72:
83. OBrien CP: Anticraving medications for relapse prevention:
a possible new class of psychoactive medications. Am J Psy-
chiatry 2005; 162:14231431
84. Foroud T, Wetherill LF, Liang T, Dick DM, Hesselbrock V,
Kramer J, Nurnberger J, Schuckit M, Carr L, Porjesz B, Xuei X,
Edenberg HJ: Association of alcohol craving with alpha-
synuclein (SNCA). Alcohol Clin Exp Res 2007; 31:537545
85. Tiffany ST, Wray JM: The clinical signicance of drug craving.
Ann NY Acad Sci 2012; 1248:117
86. Munafò MR, Hitsman B: Whats the matter with cue-induced
craving? a commentary on Perkins. Addiction 2010; 105:
87. Perkins KA: Does smoking cue-induced craving tell us anything
important about nicotine dependence? Addiction 2009; 104:
88. Cherpitel CJ, Borges G, Ye Y, Bond J, Cremonte M, Moskalewicz
J, Swiatkiewicz G: Performance of a craving criterion in DSM
alcohol use disorders. J Stud Alcohol Drugs 2010; 71:674684
89. Hasin DS, Beseler CL: Dimensionality of lifetime alcohol abuse,
dependence and binge drinking. Drug Alcohol Depend 2009;
90. Beseler CL, Hasin DS: Cannabis dimensionality: dependence,
abuse and consumption. Addict Behav 2010; 35:961969
91. Hasin DS, Liu X, Alderson D, Grant BF: DSM-IV alcohol de-
pendence: a categorical or dimensional phenotype? Psychol
Med 2006; 36:16951705
92. Peer K, Rennert L, Lynch KG, Farrer L, Gelernter J, Kranzler HR:
Prevalence of DSM-IV and DSM-5 alcohol, cocaine, opioid, and
cannabis use disorders in a largely substance dependent
sample. Drug Alcohol Depend 2013; 127:215219
93. Martin CS, Chung T, Langenbucher JW: How should we revise
diagnostic criteria for substance use disorders in the DSM-V? J
Abnorm Psychol 2008; 117:561575
94. Martin CS, Steinley DL, Vergés A, Sher KJ: The proposed 2/11
symptom algorithm for DSM-5 substance-use disorders is too
lenient. Psychol Med 2011; 41:20082010
95. Urbina I: Addiction diagnoses may rise under guideline changes.
New York Times. May 11, 2012 (
96. Wall MM, Poh E, Cerdá M, Keyes KM, Galea S, Hasin DS: Ado-
lescent marijuana use from 2002 to 2008: higher in states with
medical marijuana laws, cause still unclear. Ann Epidemiol
2011; 21:714716
97. Cerdá M, Wall M, Keyes KM, Galea S, Hasin D: Medical mari-
juana laws in 50 states: investigating the relationship between
state legalization of medical marijuana and marijuana use,
abuse and dependence. Drug Alcohol Depend 2012; 120:
98. Dawson DA, Saha TD, Grant BF: A multidimensional assess-
ment of the validity and utility of alcohol use disorder severity
as determined by item response theory models. Drug Alcohol
Depend 2010; 107:3138
99. Schuckit MA, Smith TL, Daeppen JB, Eng M, Li TK, Hesselbrock
VM, Nurnberger JI Jr, Bucholz KK: Clinical relevance of the
distinction between alcohol dependence with and without
a physiological component. Am J Psychiatry 1998; 155:
100. Schuckit MA, Daeppen JB, Danko GP, Tripp ML, Smith TL, Li TK,
Hesselbrock VM, Bucholz KK: Clinical implications for four
drugs of the DSM-IV distinction between substance depen-
dence with and without a physiological component. Am J
Psychiatry 1999; 156:4149
101. Schuckit MA, Danko GP, Smith TL, Hesselbrock V, Kramer J,
Bucholz K: A 5-year prospective evaluation of DSM-IV alcohol
848 Am J Psychiatry 170:8, August 2013
dependence with and without a physiological component.
Alcohol Clin Exp Res 2003; 27:818825
102. Hasin D, Paykin A, Meydan J, Grant B: Withdrawal and toler-
ance: prognostic signicance in DSM-IV alcohol dependence. J
Stud Alcohol 2000; 61:431438
103. Lejoyeux M, Claudon M, McLoughlin M, Adès J: Comparison of
alcohol-dependent patients with and without physiological
dependence. Eur Addict Res 2001; 7:198201
104. Langenbucher J, Chung T, Morgenstern J, Labouvie E, Nathan
PE, Bavly L: Physiological alcohol dependence as a specier
of risk for medical problems and relapse liability in DSM-IV. J
Stud Alcohol 1997; 58:341350
105. Carroll KM, Rounsaville BJ, Bryant KJ: Should tolerance and
withdrawal be required for substance dependence disorders?
Drug Alcohol Depend 1994; 36:1522
106. de Bruijn C, van den Brink W, de Graaf R, Vollebergh WA: Al-
cohol abuse and dependence criteria as predictors of a chronic
course of alcohol use disorders in the general population. Al-
cohol Alcohol 2005; 40:441446
107. Hubbard R, Simpson D, Woody G: Treatment research:
accomplishments and challenges. J Drug Issues 2009; 39:
108. Simpson DD, Joe GW, Broome KM: A national 5-year follow-up
of treatment outcomes for cocaine dependence. Arch Gen
Psychiatry 2002; 59:538544
109. Bedi G, Preston KL, Epstein DH, Heishman SJ, Marrone GF,
Shaham Y, de Wit H: Incubation of cue-induced cigarette
craving during abstinence in human smokers. Biol Psychiatry
2011; 69:708711
110. Pickens CL, Airavaara M, Theberge F, Fanous S, Hope BT,
Shaham Y: Neurobiology of the incubation of drug craving.
Trends Neurosci 2011; 34:411420
111. Miller PG, Miller WR: What should we be aiming for in the
treatment of addiction? Addiction 2009; 104:685686
112. Tiffany ST, Friedman L, Greeneld SF, Hasin DS, Jackson R:
Beyond drug use: a systematic consideration of other out-
comes in evaluations of treatments for substance use dis-
orders. Addiction 2012; 107:709718
113. Hasin D, Samet S, Nunes E, Meydan J, Matseoane K, Waxman
R: Diagnosis of comorbid psychiatric disorders in substance
users assessed with the Psychiatric Research Interview for
Substance and Mental Disorders for DSM-IV. Am J Psychiatry
2006; 163:689696
114. Aharonovich E, Liu X, Nunes E, Hasin DS: Suicide attempts in
substance abusers: effects of major depression in relation
to substance use disorders. Am J Psychiatry 2002; 159:1600
115. Gilder DA, Wall TL, Ehlers CL: Comorbidity of select anxiety and
affective disorders with alcohol dependence in southwest
California Indians. Alcohol Clin Exp Res 2004; 28:18051813
116. Nunes EV, Rounsaville BJ: Comorbidity of substance use with
depression and other mental disorders: from Diagnostic and
Statistical Manual of Mental Disorders, fourth edition (DSM-IV)
to DSM-V. Addiction 2006; 101(suppl 1):8996
117. Schuckit MA, Smith TL, Danko GP, Pierson J, Trim R,
Nurnberger JI, Kramer J, Kuperman S, Bierut LJ, Hesselbrock V:
A comparison of factors associated with substance-induced
versus independent depressions. J Stud Alcohol Drugs 2007;
118. Brown SA, Inaba RK, Gillin JC, Schuckit MA, Stewart MA, Irwin
MR: Alcoholism and affective disorder: clinical course of de-
pressive symptoms. Am J Psychiatry 1995; 152:4552
119. Torrens M, Serrano D, Astals M, Pérez-Domínguez G, Martín-
Santos R: Diagnosing comorbid psychiatric disorders in
substance abusers: validity of the Spanish versions of the
Psychiatric Research Interview for Substance and Mental
Disorders and the Structured Clinical Interview for DSM-IV. Am
J Psychiatry 2004; 161:12311237
120. Hartz SM, Bierut LJ: Genetics of addictions. Clin Lab Med 2010;
121. Gelernter J, Kranzler HR: Genetics of alcohol dependence.
Hum Genet 2009; 126:9199
122. Gelernter J, Kranzler HR: Genetics of drug dependence. Dia-
logues Clin Neurosci 2010; 12:7784
123. Kranzler HR, Edenberg HJ: Pharmacogenetics of alcohol and
alcohol dependence treatment. Curr Pharm Des 2010; 16:
124. Oslin DW, Berrettini W, Kranzler HR, Pettinati H, Gelernter J,
Volpicelli JR, OBrien CP: A functional polymorphism of the
mu-opioid receptor gene is associated with naltrexone response
in alcohol-dependent patients. Neuropsychopharmacology 2003;
125. Anton RF, Oroszi G, OMalley S, Couper D, Swift R, Pettinati H,
Goldman D: An evaluation of mu-opioid receptor (OPRM1) as
a predictor of naltrexone response in the treatment of alcohol
dependence: results from the Combined Pharmacotherapies
and Behavioral Interventions for Alcohol Dependence (COM-
BINE) study. Arch Gen Psychiatry 2008; 65:135144
126. Goldstein RZ, Volkow ND: Dysfunction of the prefrontal cortex
in addiction: neuroimaging ndings and clinical implications.
Nat Rev Neurosci 2011; 12:652669
127. Martinez D, Kim JH, Krystal J, Abi-Dargham A: Imaging the
neurochemistry of alcohol and substance abuse. Neuro-
imaging Clin N Am 2007; 17:539555, x
128. Norman AL, Pulido C, Squeglia LM, Spadoni AD, Paulus MP,
Tapert SF: Neural activation during inhibition predicts initia-
tion of substance use in adolescence. Drug Alcohol Depend
2011; 119:216223
129. Schuckit MA, Danko GP, Raimo EB, Smith TL, Eng MY,
Carpenter KK, Hesselbrock VM: A preliminary evaluation of
the potential usefulness of the diagnoses of polysubstance
dependence. J Stud Alcohol 2001; 62:5461
130. Budney AJ, Hughes JR, Moore BA, Vandrey R: Review of the
validity and signicance of cannabis withdrawal syndrome.
Am J Psychiatry 2004; 161:19671977
131. Budney AJ, Hughes JR: The cannabis withdrawal syndrome.
Curr Opin Psychiatry 2006; 19:233238
132. Agrawal A, Pergadia ML, Lynskey MT: Is there evidence for
symptoms of cannabis withdrawal in the National Epidemio-
logic Survey on Alcohol and Related Conditions? Am J Addict
2008; 17:199208
133. Chung T, Martin CS, Cornelius JR, Clark DB: Cannabis with-
drawal predicts severity of cannabis involvement at 1-year
follow-up among treated adolescents. Addiction 2008; 103:
134. Hasin DS, Keyes KM, Alderson D, Wang S, Aharonovich E, Grant
BF: Cannabis withdrawal in the United States: results from
NESARC. J Clin Psychiatry 2008; 69:13541363
135. Copersino ML, Boyd SJ, Tashkin DP, Huestis MA, Heishman SJ,
Dermand JC, Simmons MS, Gorelick DA: Cannabis withdrawal
among non-treatment-seeking adult cannabis users. Am J
Addict 2006; 15:814
136. Budney AJ, Moore BA, Vandrey RG, Hughes JR: The time course
and signicance of cannabis withdrawal. J Abnorm Psychol
2003; 112:393402
137. Milin R, Manion I, Dare G, Walker S: Prospective assessment of
cannabis withdrawal in adolescents with cannabis de-
pendence: a pilot study. J Am Acad Child Adolesc Psychiatry
2008; 47:174178
138. Kouri EM, Pope HG Jr: Abstinence symptoms during with-
drawal from chronic marijuana use. Exp Clin Psychopharma-
col 2000; 8:483492
Am J Psychiatry 170:8, August 2013 849
139. Budney AJ, Vandrey RG, Hughes JR, Moore BA, Bahrenburg B:
Oral delta-9-tetrahydrocannabinol suppresses cannabis with-
drawal symptoms. Drug Alcohol Depend 2007; 86:2229
140. Haney M, Hart CL, Vosburg SK, Nasser J, Bennett A, Zubaran C,
Foltin RW: Marijuana withdrawal in humans: effects of oral
THC or divalproex. Neuropsychopharmacology 2004; 29:158
141. Lichtman AH, Martin BR: Marijuana withdrawal syndrome in
the animal model. J Clin Pharmacol 2002; 42(suppl):20S27S
142. Levin KH, Copersino ML, Heishman SJ, Liu F, Kelly DL, Boggs
DL, Gorelick DA: Cannabis withdrawal symptoms in non-
treatment-seeking adult cannabis smokers. Drug Alcohol De-
pend 2010; 111:120127
143. Cornelius JR, Chung T, Martin C, Wood DS, Clark DB: Cannabis
withdrawal is common among treatment-seeking adolescents
with cannabis dependence and major depression, and is as-
sociated with rapid relapse to dependence. Addict Behav
2008; 33:15001505
144. Budney AJ, Vandrey RG, Hughes JR, Thostenson JD, Bursac Z:
Comparison of cannabis and tobacco withdrawal: severity and
contribution to relapse. J Subst Abuse Treat 2008; 35:362368
145. Cottler LB, Leung KS, Abdallah AB: Test-re-test reliability of
DSM-IV adopted criteria for 3,4-methylenedioxymethamphet-
amine (MDMA) abuse and dependence: a cross-national study.
Addiction 2009; 104:16791690
146. Perron BE, Glass JE, Ahmedani BK, Vaughn MG, Roberts DE, Wu
LT: The prevalence and clinical signicance of inhalant with-
drawal symptoms among a national sample. Subst Abuse
Rehabil 2011; 2011:6976
147. Ridenour TA, Bray BC, Cottler LB: Reliability of use, abuse, and
dependence of four types of inhalants in adolescents and
young adults. Drug Alcohol Depend 2007; 91:4049
148. Hughes J: Caffeine withdrawal, dependence, and abuse, in
Diagnostic and Statistical Manual of Mental Disorders, 4th ed.
Washington, DC, American Psychiatric Association, 1994, pp
149. Juliano LM, Grifths RR: A critical review of caffeine with-
drawal: empirical validation of symptoms and signs, incidence,
severity, and associated features. Psychopharmacology (Berl)
2004; 176:129
150. Juliano LM, Grifths RR: Caffeine-related disorders, in Kaplan
and Sadocks Comprehensive Textbook of Psychiatry, 9th ed.
Edited by Sadock BJ, Sadock VA, Ruiz P. Philadelphia, Lippincott,
2009, pp 12961308
151. Grifths R, Reissig C: Substance abuse: caffeine use disorders,
in Psychiatry, 3rd ed. Edited by Tasman A, Kay J, Lieberman
JA, First MB, Maj M. Chichester, UK, Wiley, 2008, pp
152. Ogawa N, Ueki H: Clinical importance of caffeine dependence
and abuse. Psychiatry Clin Neurosci 2007; 61:263268
153. Juliano LM, Evatt DP, Richards BD, Grifths RR: Characteriza-
tion of individuals seeking treatment for caffeine dependence.
Psychol Addict Behav 2012; 26:948954
154. Evans SM, Grifths RR: Caffeine withdrawal: a parametric
analysis of caffeine dosing conditions. J Pharmacol Exp Ther
1999; 289:285294
155. Hughes JR, Oliveto AH, Helzer JE, Higgins ST, Bickel WK: Should
caffeine abuse, dependence, or withdrawal be added to DSM-
IV and ICD-10? Am J Psychiatry 1992; 149:3340
156. Satel S: Is caffeine addictive? a review of the literature. Am J
Drug Alcohol Abuse 2006; 32:493502
157. Strain EC, Mumford GK, Silverman K, Grifths RR: Caffeine
dependence syndrome: evidence from case histories and ex-
perimental evaluations. JAMA 1994; 272:10431048
158. Hughes JR, Oliveto AH, Liguori A, Carpenter J, Howard T: En-
dorsement of DSM-IV dependence criteria among caffeine
users. Drug Alcohol Depend 1998; 52:99107
159. Svikis DS, Berger N, Haug NA, Grifths RR: Caffeine de-
pendence in combination with a family history of alcoholism
as a predictor of continued use of caffeine during pregnancy.
Am J Psychiatry 2005; 162:23442351
160. Bernstein GA, Carroll ME, Thuras PD, Cosgrove KP, Roth ME:
Caffeine dependence in teenagers. Drug Alcohol Depend
2002; 66:16
161. Reissig CJ, Strain EC, Grifths RR: Caffeinated energy drinks:
a growing problem. Drug Alcohol Depend 2009; 99:110
162. Howland J, Rohsenow DJ, Calise TV, Mackillop J, Metrik J: Caf-
feinated alcoholic beverages: an emerging public health
problem. Am J Prev Med 2011; 40:268271
163. Hughes JR, Helzer JE, Lindberg SA: Prevalence of DSM/ICD-
dened nicotine dependence. Drug Alcohol Depend 2006; 85:
164. Hughes JR, Baker T, Breslau N, Covey L, Shiffman S: Applica-
bility of DSM criteria to nicotine dependence. Addiction 2011;
106:894895, discussion 895897
165. Grant BF, Dawson DA, Stinson FS, Chou PS, Kay W, Pickering R:
The Alcohol Use Disorder and Associated Disabilities Interview
Schedule-IV (AUDADIS-IV): reliability of alcohol consumption,
tobacco use, family history of depression, and psychiatric di-
agnostic modules in a general population sample. Drug Alco-
hol Depend 2003; 71:716
166. Pierucci-Lagha A, Gelernter J, Chan G, Arias A, Cubells JF,
Farrer L, Kranzler HR: Reliability of DSM-IV diagnostic criteria
using the Semi-Structured Assessment for Drug Dependence
and Alcoholism (SSADDA). Drug Alcohol Depend 2007; 91:
167. Lachner G, Wittchen HU, Perkonigg A, Holly A, Schuster P,
Wunderlich U, Türk D, Garczynski E, Pster H: Structure, con-
tent and reliability of the Munich-Composite International
Diagnostic Interview (M-CIDI) substance use sections. Eur Ad-
dict Res 1998; 4:2841
168. Strong DR, Kahler CW, Abrantes AM, MacPherson L, Myers MG,
Ramsey SE, Brown RA: Nicotine dependence symptoms
among adolescents with psychiatric disorders: using a Rasch
model to evaluate symptom expression across time. Nicotine
Tob Res 2007; 9:557569
169. DiFranza J, Ursprung WW, Lauzon B, Bancej C, Wellman RJ,
Ziedonis D, Kim SS, Gervais A, Meltzer B, McKay CE, OLoughlin
J, Okoli CT, Fortuna LR, Tremblay M: A systematic review of the
Diagnostic and Statistical Manual diagnostic criteria for nico-
tine dependence. Addict Behav 2010; 35:373382
170. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO: The
Fagerström Test for Nicotine Dependence: a revision of the
Fagerström Tolerance Questionnaire. Br J Addict 1991; 86:
171. Fagerström KO, Schneider NG: Measuring nicotine depen-
dence: a review of the Fagerström Tolerance Questionnaire.
J Behav Med 1989; 12:159182
172. Agrawal A, Scherrer JF, Pergadia ML, Lynskey MT, Madden PA,
Sartor CE, Grant JD, Duncan AE, Haber JR, Jacob T, Bucholz KK,
Xian H: A latent class analysis of DSM-IV and Fagerström
(FTND) criteria for nicotine dependence. Nicotine Tob Res
2011; 13:972981
173. Benowitz NL: Nicotine addiction. N Engl J Med 2010; 362:
174. Colby SM, Tiffany ST, Shiffman S, Niaura RS: Measuring nico-
tine dependence among youth: a review of available ap-
proaches and instruments. Drug Alcohol Depend 2000; 59
(suppl 1):S23S39
175. Tiffany ST, Warthen MW, Goedeker KC: The functional signi-
cance of craving in nicotine dependence. Nebr Symp Motiv
2009; 55:171197
176. National Institute on Drug Abuse: Monitoring the future: na-
tional results on adolescent drug use: overview of key ndings.
850 Am J Psychiatry 170:8, August 2013
Bethesda, Md, 2011 (
177. Colgrove J, Bayer R, Bachynski KE: Nowhere left to hide? the
banishment of smoking from public spaces. N Engl J Med
2011; 364:23752377
178. Goldstein AO, Grant E, McCullough A, Cairns B, Kurian A:
Achieving re-safe cigarette legislation through coalition-
based legislative advocacy. Tob Control 2010; 19:7579
179. Sacks JJ, Nelson DE: Smoking and injuries: an overview. Prev
Med 1994; 23:515520
180. Leistikow BN, Martin DC, Samuels SJ: Injury death excesses in
smokers: a 199095 United States national cohort study. Inj
Prev 2000; 6:277280
181. Shmulewitz D, Wall MM, Aharonovich E, Spivak B, Weizman A,
Frisch A, Grant BF, Hasin D: Validity of proposed DSM-5 di-
agnostic criteria for nicotine use disorder: results from 734
Israeli lifetime smokers. Psychol Med (Epub ahead of print, Jan
14, 2013)
182. Guerri C, Bazinet A, Riley EP: Fetal alcohol spectrum disorders
and alterations in brain and behavior. Alcohol Alcohol 2009;
183. Weinberg J, Sliwowska JH, Lan N, Hellemans KG: Prenatal
alcohol exposure: fetal programming, the hypothalamic-
pituitary-adrenal axis and sex differences in outcome. J Neu-
roendocrinol 2008; 20:470488
184. Mattson SN, Crocker N, Nguyen TT: Fetal alcohol spectrum
disorders: neuropsychological and behavioral features. Neu-
ropsychol Rev 2011; 21:81101
185. Stratton K, Howe C, Battaglia F (eds): Fetal Alcohol Syndrome:
Diagnosis, Epidemiology, Prevention, and Treatment. Wash-
ington, DC, National Academy Press, 1996
186. Interagency Coordinating Committee on Fetal Alcohol Spec-
trum Disorders (ICCFASD): Consensus Statement on Recogniz-
ing Alcohol-Related Neurodevelopmental Disorder (ARND) in
Primary Health Care of Children. Rockville, Md, 2011 (www.
187. Petry NM, Stinson FS, Grant BF: Comorbidity of DSM-IV path-
ological gambling and other psychiatric disorders: results from
the National Epidemiologic Survey on Alcohol and Related
Conditions. J Clin Psychiatry 2005; 66:564574
188. Kessler RC, Hwang I, LaBrie R, Petukhova M, Sampson NA,
Winters KC, Shaffer HJ: DSM-IV pathological gambling in the
National Comorbidity Survey Replication. Psychol Med 2008;
189. Welte J, Barnes G, Wieczorek W, Tidwell MC, Parker J: Alcohol
and gambling pathology among US adults: prevalence, de-
mographic patterns and comorbidity. J Stud Alcohol 2001; 62:
190. Petry NM: Should the scope of addictive behaviors be broad-
ened to include pathological gambling? Addiction 2006; 101
(suppl 1):152160
191. Potenza MN, Leung HC, Blumberg HP, Peterson BS, Fulbright
RK, Lacadie CM, Skudlarski P, Gore JC: An fMRI Stroop task
study of ventromedial prefrontal cortical function in patho-
logical gamblers. Am J Psychiatry 2003; 160:19901994
192. Slutske WS, Eisen S, True WR, Lyons MJ, Goldberg J, Tsuang M:
Common genetic vulnerability for pathological gambling and
alcohol dependence in men. Arch Gen Psychiatry 2000; 57:
193. Hodgins DC, Currie SR, el-Guebaly N: Motivational enhance-
ment and self-help treatments for problem gambling. J Con-
sult Clin Psychol 2001; 69:5057
194. Petry NM, Ammerman Y, Bohl J, D oersch A, Ga y H, Kadden
R, Molina C, Steinberg K: Cognitive-behavioral therapy for
pathological gamblers. J Consult Clin Psychol 2006; 74:
195. Petry NM, Weinstock J, Ledgerwood DM, Morasco B: A ran-
domized trial of brief interventions for problem and patho-
logical gamblers. J Consult Clin Psychol 2008; 76:318328
196. Petry NM, Blanco C, Auriacombe M, Borges G, Bucholz K,
Crowley TJ, Grant BF, Hasin DS, OBrien C: An overview of and
rationale for changes proposed for pathological gambling in
DSM-5. J Gambl Stud (Epub ahead of print, Mar 23, 2013)
197. Blanco C, Hasin DS, Petry N, Stinson FS, Grant BF: Sex differ-
ences in subclinical and DSM-IV pathological gambling: results
from the National Epidemiologic Survey on Alcohol and Re-
lated Conditions. Psychol Med 2006; 36:943953
198. Petry NM, Blanco C, Stincheld R, Volberg R: An empirical
evaluation of proposed changes for gambling diagnosis in the
DSM-5. Addiction 2013; 108:575581
199. Strong DR, Kahler CW: Evaluation of the continuum of gambling
problems using the DSM-IV. Addiction 2007; 102:713721
200. Denis C, Fatséas M, Auriacombe M: Analyses related to the
development of DSM-5 criteria for substance use related dis-
orders: 3. An assessment of pathological gambling criteria.
Drug Alcohol Depend 2012; 122:2227
201. Jiménez-Murcia S, Stincheld R, Alvarez-Moya E, Jaurrieta N,
Bueno B, Granero R, Aymamí MN, Gómez-Peña M, Martínez-
Giménez R, Fernández-Aranda F, Vallejo J: Reliability, validity,
and classication accuracy of a Spanish translation of a mea-
sure of DSM-IV diagnostic criteria for pathological gambling. J
Gambl Stud 2009; 25:93104
202. Stincheld R: Reliability, validity, and classication accuracy of
a measure of DSM-IV diagnostic criteria for pathological
gambling. Am J Psychiatry 2003; 160:180182
203. Stincheld R, Govoni R, Frisch GR: DSM-IV diagnostic criteria
for pathological gambling: reliability, validity, and classica-
tion accuracy. Am J Addict 2005; 14:7382
204. Fu KW, Chan WS, Wong PW, Yip PS: Internet addiction: prev-
alence, discriminant validity and correlates among adoles-
cents in Hong Kong. Br J Psychiatry 2010; 196:486492
205. Tao R, Huang X, Wang J, Zhang H, Zhang Y, Li M: Proposed
diagnostic criteria for internet addiction. Addiction 2010; 105:
206. Van Rooij AJ, Schoenmakers TM, Vermulst AA, Van den Eijnden
RJ, Van de Mheen D: Online video game addiction: identication
of addicted adolescent gamers. Addiction 2011; 106:205212
207. Weinstein A, Lejoyeux M: Internet addiction or excessive in-
ternet use. Am J Drug Alcohol Abuse 2010; 36:277283
208. OBrien CP, Volkow N, Li TK: Whats in a word? addiction ver-
sus dependence in DSM-V. Am J Psychiatry 2006; 163:764765
209. Agrawal A, Heath AC, Lynskey MT: DSM-IV to DSM-5: the im-
pact of proposed revisions on diagnosis of alcohol use dis-
orders. Addiction 2011; 106:19351943
210. OBrien C: Rationale for changes in DSM-5. J Stud Alcohol Drugs
2012; 73:705
211. Hasin D: Combining abuse and dependence in DSM-5 (letter). J
Stud Alcohol Drugs 2012; 73:702704
212. Cosgrove L, Krimsky S: A comparison of DSM-IV and DSM-5
panel membersnancial associations with industry: a perni-
cious problem persists. PLoS Med 2012; 9:e1001190
213. Endicott J, Spitzer RL: A diagnostic interview: the schedule for
affective disorders and schizophrenia. Arch Gen Psychiatry
1978; 35:837844
214. Hasin DS, Auriacombe M, Borges G, Bucholz K, Budney AJ,
Crowley T, Grant BF, OBrien C, Petry N, Schuckit M, Wall MM:
The DSM-5 eld trials and reliability of alcohol use disorder
(letter). Am J Psychiatry 2013; 170:442443
Am J Psychiatry 170:8, August 2013 851
Supplementary Material/Online Table 1. Professional meetings where the DSM-5
Substance Use Disorder Workgroup presented changes under consideration
Venue Location Date
NIDA Clinical Trials Network Steering Committee Bethesda, MD September, 2007
Columbia University, Dept. of Psychiatry Grand Rounds New York, NY January, 2009
Yale University, Dept. of Psychiatry Grand Rounds New Haven, CT February, 2009
Alcohol Research Group Oakland, CA March, 2009
American Psychiatric Association San Francisco, CA May, 2009
College on Problems of Drug Dependence Reno, NV June, 2009
Research Society on Alcoholism San Diego, CA June, 2009
American Psychological Association Toronto, Canada August, 2009
National Defense Medical Center Taipei, Taiwan September, 2009
Peking University Beijing, China September, 2009
Washington Univ., Dept. of Psychiatry Research Seminar St. Louis, MO October, 2009
SUNY Downstate, Henri Begleiter Memorial Grand
Brooklyn, NY March, 2010
American Psychiatric Association New Orleans, LA May, 2010
Research Society on Alcoholism San Antonio, TX June, 2010
College on Problems of Drug Dependence Phoenix, AZ June, 2010
American Psychological Association San Diego, CA August, 2010
NIDA Genetics Consortium Bethesda, MD November, 2010
Winter Conference on Brain Research Keystone, CO January, 2011
University of Connecticut Psychiatry Grand Rounds Farmington, CT February, 2011
NIDA Clinical Trials Network Steering Committee Bethesda, MD March, 2011
Meeting of Social Sciences Bordeaux, France March 18, 2011
American Society of Addiction Medicine Washington, DC April, 2011
American Psychological Association Washington, DC August, 2011
International Society of Addiction Medicine Oslo, Norway September, 2011
European Society for Biomedical Research on Alcoholism Vienna, Austria September, 2011
APA Institute on Psychiatric Services San Francisco, CA October, 2011
International Congress on Dual Disorders Barcelona, Spain October, 2011
American Public Health Association Washington, DC October, 2011
University of Pennsylvania, Grand Rounds Seminar Philadelphia, PA October , 2011
Yale University, Dept. of Psychiatry Grand Rounds New Haven, CT October, 2011
American Academy of Addiction Psychiatry Scottsdale, AZ December, 2011
Georgia State University Center for the Economic Analysis
of Risk
Atlanta, GA April, 2012
Columbia University Drugs and Society Seminar Series New York, NY April, 2012
Online Table 2. Proposed DSM-5 substance use disorder criteria: factor and Item Response
Theory results using criteria required to persist across three years of follow-up, N=34,653a
Criterion response model parameters
CRITERION Prevalence
Factor Loadings Severity (s.e.) Discrimination (s.e.)
DSM-IV dependence
Tolerance 3.8 .74 2.29 (.040) 2.19 (.068)
Withdrawal 4.0 .84 2.05 (.030) 2.99 (.098)
Larger/longer 7.0 .87 1.69 (.020) 3.35 (.107)
Quit/control 5.6 .76 2.03 (.033) 2.26 (.064)
Time spent 1.4 .89 2.39 (.037) 4.10 (.200)
Activities given up 0.5 .93 2.70 (.054) 4.96 (.388)
Physical/psychological problems 2.8 .91 2.08 (.026) 4.29 (.218)
DSM-IV abuse
Hazardous use 6.1 .77 1.94 (.036) 2.38 (.076)
Social/interpersonal problems 1.2 .92 2.40 (.035) 4.69 (.293)
Neglected major roles 0.5 .93 2.65 (.042) 5.21 (.364
Craving 2.2 .83 2.34 (.035) 3.02 (.120)
a Data source: National Epidemiologic Survey on Alcohol and Related Conditions, Wave 2 (2004-2005)
conducted by the National Institute on Alcohol Abuse and Alcoholism6, whose participants were non-
institutionalized civilians aged 18 and older at their Wave 1 interview in 2001-2002 (N=34,653). Sample included
current drinkers at Wave 1 (2001-2001) who participated in Wave 2. As reported in detail elsewhere6, the
NESARC had a multistage design and oversampled Blacks, Hispanics and young adults. Analyses incorporated
sample weights to adjust for the complex sample design and non-response.
Mplus version 6.12 (211) was used for the analyses. Specifically in the IRT analyses, a 2 parameter logistic Item
Response model (2-PL IRM) was used, allowing both discrimination and severity parameters to be estimated for
each item (criterion). IRT contains two somewhat interrelated assumptions, one, that the underlying latent
construct which the items measure is unidimensional, and secondly, that all the item indicators are locally
independent. Local independence is assumed present if unidimensionality is established. To ensure
unidimensionality, confirmatory factor analysis (CFA) was conducted using the weighted least squares means
and variance adjusted (WLSMV) estimator, best suited in the presence of binary indicators (0=not endorsed,
... Risky use has been well characterized in disorders such as alcohol use disorder, where driving under the influence and continued use despite alcohol-associated medical comorbidities (e.g., cirrhosis, pancreatitis) is prominent [5]. National data indicate that 6.1% of people who drink alcohol report use that is physically hazardous and 2.8% report continued use despite the psychological and physical consequences [6]. The same study showed that these criteria, particularly continued use despite consequences, were effective at discriminating between those who do and do not have an alcohol use disorder. ...
... Taken together, the majority of data on clinical presentations of risky use within humans has been primarily been examined using the YFAS. Although the rate of endorsement for risky use is heterogeneous, it is certainly higher for ultra-processed food addiction (i.e., approximately 4-59% for hazardous use, and 5-67% for continued use despite consequences), in comparison of the national data on alcohol use (i.e., 6.1% and 2.8% for hazardous use, and continued use despite consequences, respectively) [6]. Rates of endorsement are indeed higher within clinical samples, including patients diagnosed with eating disorders, obesity, and bariatric surgery candidates than non-clinical samples, which is consistent with the broader literature on food addiction within clinical samples. ...
Full-text available
Purpose of Review This narrative review examined literature on the risky use diagnostic criteria for substance use disorders as applied to ultra-processed food addiction. Empirical research on the rates of risky use in humans and evidence from animal models are reviewed. Theoretical considerations for conceptualizing the risky use criteria in food addiction and areas for future research are also discussed. Recent Findings Rates of risky use, based on the Yale Food Addiction Scale, are heterogenous across studies, though elevated in clinical samples with disordered eating. Issues regarding operational definitions of risky use may lead to elevated rates, and variability in interpretation of the hazardous use criteria. Animal models suggest that under highly controlled conditions, behaviors indicative of risky use can be observed, yet may lack generalizability to humans. Summary Future work, which examines the clinical utility and diagnostic value of the risky use criterion for ultra-processed food addiction, is warranted.
... In the Diagnostic and Statistical Manual of Mental Disorders 5th Edition , this is conceptualized as alcohol use disorder (AUD; American Psychiatric Association, 2013). AUD is intended to represent a unitary construct that consists of 11 conceivably independent symptoms (Hasin et al., 2013). However, more recent work suggests that AUD might not actually be a unitary construct and that there are distinct genetic factors associated with different symptom clusters (Kendler et al., 2012). ...
Objective: Alcohol use disorder (AUD) is an etiologically heterogeneous psychiatric disorder defined by a collection of commonly observed co-occurring symptoms. It is useful to contextualize AUD within theoretical frameworks to identify potential prevention, intervention, and treatment approaches that target personalized mechanisms of behavior change. One theoretical framework, behavioral economics, suggests that AUD is a temporally extended pattern of cost/benefit analyses favoring drinking decisions. The distribution of costs and benefits across choice outcomes is often unequally distributed over time and has different probabilities of receipt, such that delay and probability become critical variables. The present study examines the relations between different forms of economic discounting (delayed reward, delayed cost, and probabilistic reward) and individual symptoms of AUD to inform etiological models. Method: Participants (N = 732; 41% female, 4.2% Black, 88.1% White, 8% Hispanic) completed an online survey with measures of AUD symptoms and economic discounting. We examined relations between economic discounting and AUD symptoms with zero-order correlations, in separate models (factor models), and in models controlling for an AUD factor (factor-controlled models). Results: Delayed reward discounting was positively associated with the give up AUD criteria across all three levels of analysis. Probability discounting was associated with social/interpersonal problems across two out of three sets of analyses. Consistent with the broad discounting literature, effect sizes were small (range = -.15 to .13). Conclusions: These results support the idea that AUD criteria are etiologically distinct, resulting in varying AUD profiles between persons that are differentially associated with behavioral economic discounting. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... This inclusion of legal problems entails that localities with a higher police presence will tend to see higher prevalence of cannabis use disorder, which seems problematic from a mental health perspective that is concerned with health harms irrespective of varying law enforcement regimes. This indicator for legal problems is also problematic for a number of other reasons (Hasin et al., 2013), and was dropped from the 5th edition of the DSM (American Psychiatric Association, 2013). It should also be noted that the assessment by Hasin et al. (2015) did not comparatively assess the prevalence of use disorders for other drugs with the same methodology. ...
Full-text available
Researchers have associated cannabis use with risk for psychosis, cognitive impairment, and traffic accident. However, this review shows that the association between moderate cannabis use and psychosis is no stronger, and often considerably weaker, than the corresponding association for moderate tobacco use. The same holds for associations with cognitive impairment. For the risk of traffic accident, the review confirms that the risk from alcohol use is substantially stronger than the risk from cannabis use, while the corresponding risk from tobacco use appears to be almost as strong as that from cannabis use. It thus appears that the risk for psychosis, cognitive impairment, and traffic accident associated with cannabis use is generally comparable to that from tobacco use. The article discusses different interpretations of these comparative harms assessments and presents two points of methodological critique to argue that the risks associated with cannabis and other generally criminalized drugs are probably exaggerated. First, any measurement of harms associated with high escapist activities such as drug abuse will be affected by the general dysfunction associated with the underlying reason why a person settles for frequent escapism. From this perspective, cannabis and tobacco use disorder are probably both associated with underlying problems and life issues that are, in and of themselves, associated with psy-chopathology, and researchers should be careful not to conflate the selection effect from belonging to the population segment that opts for high escapist lifestyles with any (putative) harmful effect from drug use itself. Second, criminalization probably shifts the composition of the user population in the direction of more dysfunctional users. From this perspective , the association between substance use disorder and underlying problems and life issues is stronger for criminalized substances, since people who live troubled lives are less likely to be deterred by the prospect of legal problems.
Full-text available
T2D is a clinically challenging disease to predict, largely due to its complex genetic and environmental architecture that underlies its development and clinical presentation. The work presented in this thesis reflects the workflow required to determine the clinical utility and translatability of DNA methylation biomarkers and suggests that it is inappropriate to use the methylation status of cg19693031 for T2D medicine in its current form. Together, the work presented here advances our understanding of the nuclear network regulatory effects underlying the clinical presentation and reflecting the etiological heterogeneity of T2D and provides new avenues for investigation to improve the prognostication and risk stratification for diabetic patients.
Background: Use of Methamphetamine during pregnancy is significant public health concern since it affects the development of the brain and poor behavioral outcomes in children. Prenatal methamphetamine exposure (PME) may cause developmental disabilities and several gene expression and molecular pathways alterations. In the present study, DNA methylation of Propionyl-CoA Carboxylase subunit Beta (PCCB) and Protocadherin Alpha 12 (PCDHA12) genes were assessed in two groups of three-year-old children, those exposed to PME and healthy control children. Aims: Clarification of PME role in methylation level of two mitochondria function associated genes; PCCB and PCDHA12. Methods and procedures: In this study, 2629 children with PME (1531male, 1098 female) and 3523(2077male, 1446 female) control children were recruited based on maternal self-report of prenatal exposure. Genomic DNA extracted from peripheral blood and pyrosequencing was used to determine the association between prenatal MA exposure and methylation in nine CpG sites of PCCB and PCDHA12 genes. Outcomes and results: Prenatal methamphetamine exposure was associated with significant DNA hypomethylation of four out of five CpG sites in the PCCB gene and three out of four CpG sites in the PCDHA12 gene. Also, significant hypomethylation in the biding site of p53 transcription factor in PCCB gene was detected in children with PME. Conclusions and implications: Prenatal methamphetamine exposure is related to epigenetic alterations in PCCB and PCDHA12, as important mitochondria function associated genes. Detected hypomethylation in these genes was reported in neurodevelopmental and bioenergetics disabilities. It seems that PME could cause mitochondrial dysfunctions associated with developmental abnormalities. What this paper adds?
Introduction Prescription opioid use in Australia has increased over the last 3 decades. The majority of opioids are prescribed and dispensed in primary care, however, there are few studies that are specific to opioid prescribing in this setting. Evidence about the impact of key government policy strategies to optimize opioid prescribing in primary care is limited. The aim of this study is to examine the impact of recent policy changes and clinical guidelines on opioid prescribing in primary care. Methods and analysis Longitudinal analysis of people prescribed opioid analgesics using Population Level Analysis and Reporting (POLAR) data. POLAR is a primary care dataset comprising 464 primary health care practices in Victoria, Australia. People prescribed opioid analgesics between 2015 and 2020 will be included. The impact of opioid policies and guideline recommendations will be evaluated using interrupted time series models. Group based trajectory modelling and multivariate regression will be used to identify patterns of opioid cessation and the provision of corresponding non-opioid interventions. Ethics and dissemination The study has received Monash University Human Research Ethics Committee approval (ID xxxxx). Permission to access, collate and use POLAR data is granted from Outcome Health as the data custodians. The results of this study will be disseminated through publication in international journals, presented at national and international scientific conferences, and disseminated to consumers, policy makers, primary care providers and primary health networks. Protocol registration details EU PAS Register (EUPASxxxxx)
Objective: In the United States, adult cannabis use has increased over time, but less information is available on time trends in cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine change over time in cannabis use disorder diagnoses among veterans, an important population subgroup, and whether such trends differ by age group (<35 years, 35-64 years, ≥65 years), sex, or race/ethnicity. Methods: VHA electronic health records from 2005 to 2019 (range of Ns per year, 4,403,027-5,797,240) were used to identify the percentage of VHA patients seen each year with a cannabis use disorder diagnosis (ICD-9-CM, January 1, 2005-September 30, 2015; ICD-10-CM, October 1, 2015-December 31, 2019). Trends in cannabis use disorder diagnoses were examined by age and by race/ethnicity and sex within age groups. Given the transition in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM). Results: In 2005, the percentages of VHA patients diagnosed with cannabis use disorder in the <35, 35-64, and ≥65 year age groups were 1.70%, 1.59%, and 0.03%, respectively; by 2019, the percentages had increased to 4.84%, 2.86%, and 0.74%, respectively. Although the prevalence of cannabis use disorder was consistently higher among males than females, between 2016 and 2019, the prevalence increased more among females than males in the <35 year group. Black patients had a consistently higher prevalence of cannabis use disorder than other racial/ethnic groups, and increases were greater among Black than White patients in the <35 year group in both periods. Conclusions: Since 2005, diagnoses of cannabis use disorder have increased substantially among VHA patients, as they have in the general population and other patient populations. Possible explanations warranting investigation include decreasing perception of risk, changing laws, increasing cannabis potency, stressors related to growing socioeconomic inequality, and use of cannabis to self-treat pain. Clinicians and the public should be educated about the increases in cannabis use disorder in general in the United States, including among patients treated at the VHA.
Background: Patterns of opioid use vary, including prescribed use without aberrancy, limited aberrant use, and potential opioid use disorder (OUD). In clinical practice, similar opioid-related International Classification of Disease (ICD) codes are applied across this spectrum, limiting understanding of how groups vary by sociodemographic factors, comorbidities, and long-term risks. Objective: (1) Examine how Veterans assigned opioid abuse/dependence ICD codes vary at diagnosis and with respect to long-term risks. (2) Determine whether those with limited aberrant use share more similarities to likely OUD vs those using opioids as prescribed. Design: Longitudinal observational cohort study. Participants: National sample of Veterans categorized as having (1) likely OUD, (2) limited aberrant opioid use, or (3) prescribed, non-aberrant use based upon enhanced medical chart review. Main measures: Comparison of sociodemographic and clinical factors at diagnosis and rates of age-adjusted mortality, non-fatal opioid overdose, and hospitalization after diagnosis. An exploratory machine learning analysis investigated how closely those with limited aberrant use resembled those with likely OUD. Key results: Veterans (n = 483) were categorized as likely OUD (62.1%), limited aberrant use (17.8%), and prescribed, non-aberrant use (20.1%). Age, proportion experiencing homelessness, chronic pain, anxiety disorders, and non-opioid substance use disorders differed by group. All-cause mortality was high (44.2 per 1000 person-years (95% CI 33.9, 56.7)). Hospitalization rates per 1000 person-years were highest in the likely OUD group (831.5 (95% CI 771.0, 895.5)), compared to limited aberrant use (739.8 (95% CI 637.1, 854.4)) and prescribed, non-aberrant use (411.9 (95% CI 342.6, 490.4). The exploratory analysis reclassified 29.1% of those with limited aberrant use as having likely OUD with high confidence. Conclusions: Veterans assigned opioid abuse/dependence ICD codes are heterogeneous and face variable long-term risks. Limited aberrant use confers increased risk compared to no aberrant use, and some may already have OUD. Findings warrant future investigation of this understudied population.
Aim: The aim of this study was to evaluate the psychometric properties of a Swedish version of the Impaired Control Scale. Impaired control (IC) over alcohol consumption is a core symptom of alcohol use disorder and a predictor of treatment outcome, but measures of IC are not well utilised in clinical practice. Methods: The study comprised 250 individuals from a randomised controlled trial conducted at an adult outpatient addiction clinic in Sweden. The statistical analyses concern dimensionality, convergent and divergent validity, reliability, measurement invariance and sensitivity to change. Results: Regarding dimensionality, a principal component analysis of the standardised residuals from a Rasch model indicated some evidence of further dimensions underlying the responses in the Failed Control (FC) and Perceived Control (PC) parts. Two parallel items (12 and 22 respectively) seemed to drive potential multidimensionality. When these items were excluded, goodness of fit to one-dimensional models was improved. Tests of convergent and divergent validity showed that failed control had the strongest associations to impaired control and alcohol use disorder while the attempted control part was not associated with the construct of impaired control or alcohol use disorder. Conclusion: The present results show that the FC part is the most valid measure of the underlying construct of IC. In addition, FC had close to a large effect in regard to sensitivity to change. This suggests that the FC part has potential utility for use as an assessment and evaluation tool of treatment effect on impaired control of drinking.
Maternal drug testing should be performed only with explicit consent and a clear plan for interpretation and treatment.
Objective: The authors used the Psychiatric Research Interview for Substance and Mental Disorders for DSM-IV (PRISM-IV) to test the reliability of DSM-IV-defined disorders, including primary and substance-induced disorders, in substance-abusing subjects. Method: Substance-abusing patients (N= 285) from substance abuse/dual-diagnosis treatment settings and mental health treatment settings participated in test and blind retest interviews with the PRISM-IV, which includes specific guidelines for assessment of substance abusers. Results: Kappas for primary and substance-induced major depressive disorder ranged from 0.66 to 0.75. Reliability for psychotic disorders, eating disorders, anti-social personality disorder, and border-line personality disorder was in the same range. Reliability for most anxiety disorders was lower. Reliability was good to excellent (kappas ≥0.65) for most substance dependence disorders. Continuous measures (severity, age at onset) had intraclass correlation coefficients >0.70 with few exceptions. Reliability was better for primary than for substance-induced disorders, although not greatly so. Conclusion: Most DSM-IV psychiatric disorders can be assessed in substance-abusing subjects with acceptable to excellent reliability by using specifically designed procedures. Good reliability improves the likelihood of significant study results.
Although the proposition that repeated marijuana use can lead to marijuana dependence has long been accepted, only recently has evidence emerged suggesting that abstinence leads to clinically significant withdrawal symptoms. Converging evidence from human and animal studies has increased our understanding of cannabinoid dependence. One of the most powerful tools to advance this area of research is the CB1 cannabinoid receptor antagonist SR 141716A, which reliably precipitates withdrawal syndromes in mice, rats, and dogs that have been treated repeatedly with cannabinoids. In addition, the use of CB1 receptor knockout mice has revealed that not only cannabinoid dependence is mediated through a CB1 receptor mechanism of action, but CB1 receptors also modulate opioid dependence. Moreover, the results of other genetically altered mouse models suggest the existence of a reciprocal relationship between cannabinoid and opioid systems in drug dependence. Undoubtedly, these animal models will play pivotal roles in further characterizing cannabinoid dependence and elucidating the mechanisms of action, as well us developing potential pharmacotherapies for cannabinoid dependence. Journal of Clinical Pharmacology, 2002.
Although marijuana is the most commonly used illicit drug in the United States, it is not established whether withdrawal from chronic use results in a clinically significant abstinence syndrome. The present study was conducted to characterize symptoms associated with marijuana withdrawal following chronic use during a supervised 28-day abstinence period. Three groups of participants were studied: (a) current chronic marijuana users, (b) former chronic marijuana users who had not used marijuana for at least 6 months prior to the study, and (c) marijuana nonusers. Current users experienced significant increases in anxiety, irritability, physical tension, and physical symptoms and decreases in mood and appetite during marijuana withdrawal. These symptoms were most pronounced during the initial 10 days of abstinence, but some were present for the entire 28-day withdrawal period. These findings support the notion of a marijuana withdrawal syndrome in humans.
This article reviews the history of substance abuse treatment and its evaluation. The authors comment on key aspects of this history and its implications for the future. Research has been a key factor in the support of substance abuse treatment and the expansion and improvement of treatment options. Despite the progress in the field, organizational structure and functioning, ambivalence on the moral/medical basis of addiction, and narrow perspectives on evidence-based practice have presented barriers for advancement. Future improvement of treatment is seen as dependent on the partnership of researchers and real world providers, studies of evidence- based practice in a wide variety of community based settings and the consideration of complex and changing real-world environments, particularly for rural, uninsured and under-served populations.