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Objective: Cannabis use disorder diagnoses are increasing among U.S. adults and are more prevalent among people with comorbid psychiatric disorders. Recent changes in cannabis laws, increasing cannabis availability, and higher-potency cannabis may have placed people with cannabis use and psychiatric disorders at disproportionately increasing risk for cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine whether trends in cannabis use disorder prevalence among VHA patients differ by whether they have psychiatric disorders., Methods: VHA electronic health records from 2005 to 2019 (N range, 4,332,165-5,657,277) were used to identify overall and age-group-specific (<35, 35-64, and ≥65 years) trends in prevalence of cannabis use disorder diagnoses among patients with depressive, anxiety, posttraumatic stress, bipolar, or psychotic spectrum disorders and to compare these to corresponding trends among patients without any of these disorders. Given transitions in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM)., Results: Greater increases in prevalence of cannabis use disorder diagnoses were observed among patients with psychiatric disorders compared to those without (difference in prevalence change, 2005-2014: 1.91%, 95% CI=1.87-1.96; 2016-2019: 0.34%, 95% CI=0.29-0.38). Disproportionate increases in cannabis use disorder prevalence among patients with psychiatric disorders were greatest among those under age 35 between 2005 and 2014, and among those age 65 or older between 2016 and 2019. Among patients with psychiatric disorders, the greatest increases in cannabis use disorder prevalences were observed among those with bipolar and psychotic spectrum disorders., Conclusions: The findings highlight disproportionately increasing disparities in risk of cannabis use disorder among VHA patients with common psychiatric disorders. Greater public health and clinical efforts are needed to monitor, prevent, and treat cannabis use disorder in this population., Competing Interests: Dr. Saxon receives royalties from UpToDate. Dr. Hasin has received support from Syneos Health.The other authors report no financial relationships with commercial interests.

Objective: The diagnostic criteria for opioid use disorder, originally developed for heroin, did not anticipate the surge in prescription opioid use and the resulting complexities in diagnosing prescription opioid use disorder (POUD), including differentiation of pain relief (therapeutic intent) from more common drug use motives, such as to get high or to cope with negative affect. The authors examined the validity of the Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 opioid version, an instrument designed to make this differentiation., Methods: Patients (N=606) from pain clinics and inpatient substance treatment who ever received a ≥30-day opioid prescription for chronic pain were evaluated for DSM-5 POUD (i.e., withdrawal and tolerance were not considered positive if patients used opioids only as prescribed, per DSM-5 guidelines) and pain-adjusted POUD (behavioral/subjective criteria were not considered positive if pain relief [therapeutic intent] was the sole motive). Bivariate correlated-outcome regression models indicated associations of 10 validators with DSM-5 and pain-adjusted POUD measures, using mean ratios for dimensional measures and odds ratios for binary measures., Results: The prevalences of DSM-5 and pain-adjusted POUD, respectively, were 44.4% and 30.4% at the ≥2-criteria threshold and 29.5% and 25.3% at the ≥4-criteria threshold. Pain adjustment had little effect on prevalence among substance treatment patients but resulted in substantially lower prevalence among pain treatment patients. All validators had significantly stronger associations with pain-adjusted than with DSM-5 dimensional POUD measures (ratios of mean ratios, 1.22-2.31). For most validators, pain-adjusted binary POUD had larger odds ratios than DSM-5 measures., Conclusions: Adapting POUD measures for pain relief (therapeutic intent) improved validity. Studies should investigate the clinical utility of differentiating between therapeutic and nontherapeutic intent in evaluating POUD diagnostic criteria.

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 (&lt;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 &lt;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 &lt;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 &lt;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.

Objective: The authors sought to determine the association of cannabis indicators with self-reported psychotic disorders in the U.S. general population., Methods: Participants were from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; 2001-2002; N=43,093) and NESARC-III (2012-2013; N=36,309). Logistic regression was used to estimate standardized prevalences of past-year self-reported psychotic disorders within each survey and to evaluate the association of past-year self-reported psychotic disorders with indicators of nonmedical cannabis use (any use; frequent use [at least three times/week], daily/near-daily use, and DSM-IV cannabis use disorder) compared with those with no past-year nonmedical cannabis use. Whether the strength of associations differed between surveys was indicated by difference-in-difference tests (between-survey contrasts) and ratios of odds ratios between surveys., Results: Self-reported psychotic disorders were significantly more prevalent among participants with any nonmedical cannabis use than those without (2001-2002: 1.65% compared with 0.27%; 2012-2013: 1.89% compared with 0.68%). In 2001-2002, self-reported psychotic disorders were unrelated to either frequent use or daily/near-daily use. However, in 2012 - 2013, compared with nonusers, self-reported psychotic disorders were more common among participants with frequent use and those with daily/near-daily nonmedical cannabis use (2012-2013: 2.79% and 2.52%, respectively, compared with 0.68% among nonusers). Self-reported psychotic disorders were significantly more prevalent among participants with cannabis use disorder than nonusers in both surveys (2001-2002: 2.55% compared with 0.27%; 2012 - 2013: 3.38% compared with 0.68%). The strength of these associations did not change over time., Conclusions: Data from the U.S. general population, especially more recent data, suggest associations between self-reported psychotic disorder and frequent nonmedical cannabis use and cannabis use disorder. Clinicians and policy makers should consider these relationships when monitoring patients and formulating programs.

Objective: Little is known about change over time in the prevalence of World Health Organization (WHO) risk drinking levels (very high, high, moderate, low) and their association with health conditions, overall and by gender. The authors used two sets of nationally representative U.S. survey data to determine whether changes over time varied by gender and to examine whether health conditions related to alcohol were associated with WHO risk drinking level within each survey, and whether these associations differed by gender., Methods: Data on current drinkers from the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N=26,655) and the 2012-2013 NESARC-III (N=25,659) were analyzed using logistic regression. Prevalence differences between surveys were estimated for each drinking level overall and by gender. Within each survey, prevalence differences by WHO risk drinking level were estimated for alcohol use disorder (AUD), drug use disorders, functional impairment, liver disease, and depressive and anxiety disorders., Results: In the 2012-2013 survey, the prevalences of moderate, high, and very high risk drinking were 5.9%, 3.2%, and 3.5%, respectively, representing significant increases from the prevalences in the 2001-2002 survey, which were 1.0%, 0.6%, and 0.9%, respectively. The increase for very high risk drinking among men (0.5%) was smaller than the increase among women (1.4%). Within both surveys, compared with low risk, health conditions were significantly associated with very high risk (range of prevalence differences, 2.2%-57.8%), high risk (2.6%-41.3%), and moderate risk (0.6%-29.8%) drinking. Associations were similar by gender, except that there were stronger effects for AUD in men and for functional impairment and depressive and anxiety disorders in women., Conclusions: The increase in potentially problematic drinking levels among U.S. adults emphasizes the need for better prevention and treatment strategies. The study results support the validity of the WHO risk drinking levels, which show clinical utility as nonabstinent drinking reduction treatment goals. Such goals could engage more people in treatment, improving public health by decreasing personal and societal consequences of risk drinking.

Objective: Given changes in U.S. marijuana laws, attitudes, and use patterns, individuals with pain may be an emerging group at risk for nonmedical cannabis use and cannabis use disorder. The authors examined differences in the prevalence of nonmedical cannabis use and cannabis use disorder among U.S. adults with and without pain, as well as whether these differences widened over time., Methods: Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, 2001-2002; N=43,093) and NESARC-III (2012-2013; N=36,309) were analyzed using logistic regression. Risk differences of past-year nonmedical cannabis use, frequent (at least three times a week) nonmedical use, and DSM-IV cannabis use disorder were estimated for groups with and without moderate to severe pain, and these risk differences were tested for change over time., Results: Any nonmedical cannabis use was more prevalent in respondents with than without pain (2001-2002: 5.15% compared with 3.74%; 2012-2013: 12.42% compared with 9.02%), a risk difference significantly greater in the 2012-2013 data than in the 2001-2002 data. The prevalence of frequent nonmedical cannabis use did not differ by pain status in the 2001-2002 survey, but was significantly more prevalent in those with than without pain in the 2012-2013 survey (5.03% compared with 3.45%). Cannabis use disorder was more prevalent in respondents with than without pain (2001-2002: 1.77% compared with 1.35%; 2012-2013: 4.18% compared with 2.74%), a significantly greater risk difference in the data from 2012-2013 than from 2001-2002., Conclusions: The results suggest that adults with pain are a group increasingly vulnerable to adverse cannabis use outcomes, warranting clinical and public health attention to this risk. Psychiatrists and other health care providers treating patients with pain should monitor such patients for signs and symptoms of cannabis use disorder.

Objective: The authors sought to determine whether cannabis use is associated with a change in the risk of incident nonmedical prescription opioid use and opioid use disorder at 3-year follow-up., Method: The authors used logistic regression models to assess prospective associations between cannabis use at wave 1 (2001-2002) and nonmedical prescription opioid use and prescription opioid use disorder at wave 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions. Corresponding analyses were performed among adults with moderate or more severe pain and with nonmedical opioid use at wave 1. Cannabis and prescription opioid use were measured with a structured interview (the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV version). Other covariates included age, sex, race/ethnicity, anxiety or mood disorders, family history of drug, alcohol, and behavioral problems, and, in opioid use disorder analyses, nonmedical opioid use., Results: In logistic regression models, cannabis use at wave 1 was associated with increased incident nonmedical prescription opioid use (odds ratio=5.78, 95% CI=4.23-7.90) and opioid use disorder (odds ratio=7.76, 95% CI=4.95-12.16) at wave 2. These associations remained significant after adjustment for background characteristics (nonmedical opioid use: adjusted odds ratio=2.62, 95% CI=1.86-3.69; opioid use disorder: adjusted odds ratio=2.18, 95% CI=1.14-4.14). Among adults with pain at wave 1, cannabis use was also associated with increased incident nonmedical opioid use (adjusted odds ratio=2.99, 95% CI=1.63-5.47) at wave 2; it was also associated with increased incident prescription opioid use disorder, although the association fell short of significance (adjusted odds ratio=2.14, 95% CI=0.95-4.83). Among adults with nonmedical opioid use at wave 1, cannabis use was also associated with an increase in nonmedical opioid use (adjusted odds ratio=3.13, 95% CI=1.19-8.23)., Conclusions: Cannabis use appears to increase rather than decrease the risk of developing nonmedical prescription opioid use and opioid use disorder.

Objective: Causes of placebo effects in antidepressant trials have been inferred from observational studies and meta-analyses, but their mechanisms have not been directly established. The goal of this study was to examine in a prospective, randomized controlled trial whether patient expectancy mediates placebo effects in antidepressant studies., Method: Adult outpatients with major depressive disorder were randomly assigned to open or placebo-controlled citalopram treatment. Following measurement of pre- and postrandomization expectancy, participants were treated with citalopram or placebo for 8 weeks. Independent samples t tests determined whether patient expectancy differed between the open and placebo-controlled groups, and mixed-effects models assessed group effects on Hamilton Depression Rating Scale (HAM-D) scores over time while controlling for treatment assignment. Finally, mediation analyses tested whether between-group differences in patient expectancy mediated the group effect on HAM-D scores., Results: Postrandomization expectancy scores were significantly higher in the open group (mean=12.1 [SD=2.1]) compared with the placebo-controlled group (mean=11.0 [SD=2.0]). Mixed-effects modeling revealed a significant week-by-group interaction, indicating that HAM-D scores for citalopram-treated participants declined at a faster rate in the open group compared with the placebo-controlled group. Patient expectations postrandomization partially mediated group effects on week 8 HAM-D., Conclusions: Patient expectancy is a significant mediator of placebo effects in antidepressant trials. Expectancy-related interventions should be investigated as a means of controlling placebo responses in antidepressant clinical trials and improving patient outcome in clinical treatment.

Objective: The authors sought to ascertain the relationship between moderate and more severe pain and prescription opioid use disorders in the noninstitutionalized U.S., Method: A structural equation model was used to assess prospectively the interdependency of pain and prescription opioid use disorder at waves 1 (2001-2002) and 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions. Pain was measured with a 5-point scale of pain-related interference in daily activities and dichotomized as "no pain" (no or little interference) or "pain" (moderate to extreme interference). Prescription opioid use disorder was assessed with a structured interview (the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV version). Other covariates included age, sex, anxiety or mood disorders, and family history of drug, alcohol, and behavioral problems., Results: In the structural equation model, pain and prescription opioid use disorders were significantly associated with one another at baseline and at 3-year follow-up. However, whereas pain at baseline was also significantly associated with prescription opioid use disorder at follow-up, prescription opioid use disorder at baseline was not associated with pain at follow-up. These associations were independent of several background demographic and clinical characteristics. The path for pain interference was associated with a 41% relative increase in the risk of developing a prescription opioid use disorder., Conclusions: Painful conditions contribute to the risk of prescription opioid use disorders. To help reduce the incidence of prescription opioid abuse and dependence among adults with moderate to severe pain, careful monitoring and consideration of nonopioid alternative treatments is warranted.

Objective: The purpose of this article was to examine the accuracy of DSM-5 proposed criteria for persistent complex bereavement disorder in identifying putative cases of clinically impairing grief and in excluding nonclinical cases. Performance of criteria sets for prolonged grief disorder and complicated grief were similarly assessed., Method: Participants were family members of U.S. military service members who died of any cause since September 11, 2001 (N=1,732). Putative clinical and nonclinical samples were derived from this community sample using cutoff scores from the Inventory of Complicated Grief and the Work and Social Adjustment Scale. Items from a self-report grief measure (Complicated Grief Questionnaire) were matched to DSM-5 persistent complex bereavement disorder, prolonged grief disorder, and complicated grief criteria. Endorsed items were used to identify cases., Results: Criteria sets varied in their ability to identify clinical cases. DSM-5 persistent complex bereavement disorder criteria identified 53%, prolonged grief disorder criteria identified 59%, and complicated grief criteria identified more than 90% of putative clinical cases. All criteria sets accurately excluded virtually all nonclinical grief cases and accurately excluded depression in the absence of clinical grief., Conclusions: The DSM-5 persistent complex bereavement disorder criteria accurately exclude nonclinical, normative grief, but also exclude nearly half of clinical cases, whereas complicated grief criteria exclude nonclinical cases while identifying more than 90% of clinical cases. The authors conclude that significant modification is needed to improve case identification by DSM-5 persistent complex bereavement disorder diagnostic criteria. Complicated grief criteria are superior in accurately identifying clinically impairing grief.