Psychiatric diagnoses, somatic disorders, and emergency dispatches among individuals who used a national suicide crisis line.

Crisis line responders initiate emergency dispatches by activating 911 or other local emergency services when individuals are determined to be at imminent risk for undesired outcomes. This study examined the association of characteristics, psychiatric diagnoses, and somatic symptoms with emergency dispatches in a national sample. Veterans Crisis Line data were used to identify contacts (i.e., calls, texts, chats, emails) that were linked with medical records and had a medical encounter in the year prior to contact. Hierarchical logistic regression clustered by responders was used to identify the association among demographics, psychiatric diagnoses, and somatic disorders, and emergency dispatches. Analyses examined 247,340 contacts from 2017 to 2020, with 27,005 (10.9%) emergency dispatches. Odds of an emergency dispatch increased with each diagnosis (three diagnoses Adjusted Odds Ratio [AOR] (95% CI) = 1.88 [1.81,1.95]). Odds were highest among individuals with substance use disorders (SUD) (alcohol AOR (95% CI) = 1.85 [1.80,1.91]; drugs AOR (95% CI) = 1.63 [1.58, 1.68]), which may be a result of intoxication or overdose during contact, requiring further research. Having more psychiatric and somatic conditions was associated with greater odds of an emergency dispatch, indicating that comorbidity contributed to the need for acute care.

Reasons for contacting a crisis line and the initiation of emergency dispatches.

OBJECTIVE: To better understand processes of mental health crisis line utilization by examining associations between reasons for contacting a crisis line with the initiation of emergency dispatches (i.e., activation of 911 or local emergency services) in a national sample. METHODS: Contacts (i.e., calls, texts, email, and chats) to the Veterans Crisis Line (VCL) across 2017-2020 were used to examine associations among stated reasons for the contact and the use of an emergency dispatch. Hierarchical logistic regression models were used to determine the odds of an emergency dispatch by reason for the contact. RESULTS: Suicidal thoughts/crisis were present in 61.5% of contacts that ended in emergency dispatches and were associated with the largest adjusted odds of a dispatch, (Adjusted Odds Ratio [AOR] [95% CI] = 9.34 [9.21, 9.48]), followed by homicidal thoughts/crisis (AOR [95% CI] = 3.84 [3.73, 3.95]), and third-party concerns (AOR [95% CI] = 2.42 [2.37, 2.47]). Substance use/ addiction (AOR [95% CI] = 2.14 [2.10, 2.18]), abuse and violence (AOR [95% CI] = 1.89 [1.82, 1.96]), and physical health (AOR [95% CI] = 1.87 [1.84, 1.91]) were also associated with increased odds of a dispatch. CONCLUSIONS: Emergency dispatches are primarily used in response to imminent suicide risk but are also used in other potentially violent or lethal circumstances such as homicides, violence or abuse, and other crises. These findings highlight the role that crisis lines play in emergency service delivery, and the need to better understand how they are utilized under real world circumstances.

Where Do Adults in the United States Obtain Cannabis? A Nationally Representative Study Examining the Relationships Between Sociodemographic Factors, Cannabis Use Characteristics and Sources of Cannabis.

OBJECTIVE: Characterization of population subgroups based on where they acquire cannabis is unexplored. We examine relationships between sociodemographic characteristics, cannabis use modality, risky cannabis use, and source of cannabis. METHOD: Analyzing a representative sample (unweighted n = 8,089) of U.S. adults living in medical cannabis-permitting states with past-year cannabis use from the 2021 National Survey on Drug Use and Health, we determined source of last cannabis used. Outcome groups were purchased from a dispensary, purchased from another source, or nonpurchased source. Incorporating the complex survey design, descriptive statistics and adjusted multinomial logistic regressions evaluated associations between sociodemographic, individual cannabis use characteristics, and source of cannabis. Secondary analyses described cannabis purchasing characteristics among the subsample who last purchased cannabis. RESULTS: Purchasing from a dispensary was the most common source of cannabis (42.5%). Significant relationships between sociodemographic characteristics, cannabis use modality, risky cannabis use, and source of cannabis were found. Recent cannabis initiates and those with cannabis vaporizer use had an increased likelihood of purchasing cannabis from a dispensary. Purchasing from a nondispensary source was most likely among those with daily cannabis use, past-month blunt use, past-year driving under the influence, cannabis use disorder, and cannabis and alcohol co-use. Among those purchasing cannabis, joints and other forms of cannabis were more likely to be purchased from a dispensary than purchased from other sources. CONCLUSIONS: We identified key sociodemographic and cannabis use characteristics that may influence where individuals obtain cannabis, which are important for cannabis behavior surveillance and cannabis use prevention and intervention strategies to consider.

Assessing the diagnostic utility of the Cannabis Use Disorder Identification Test - Revised (CUDIT-R) among veterans with medical and non-medical cannabis use.

BACKGROUND: Few studies examine the utility of the Cannabis Use Disorder Identification Test - Revised (CUDIT-R) in relation to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, (DSM-5) criteria for cannabis use disorder (CUD). This study assesses the performance of the CUDIT-R among a sample of Veterans with and without medical cannabis use. METHODS: We approached and consented primary care patients presenting to one of three Department of Veterans Affairs (VA) Medical Centers. Veterans with at least monthly cannabis use and complete CUD data at baseline were included in this analysis (n=234). CUDIT-R scores were compared against Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (DSM-5) CUD as the standard to calculate measures of validity (sensitivity, specificity), identify optimal CUDIT-R cutoff values, and assess the diagnostic proficiency of the CUDIT-R using receiver operating characteristic (ROC) curves. We further stratified analyses by active medical cannabis card holder status and DSM-5 CUD severity (any, moderate, and severe). RESULTS: Among the entire sample, 38.9% qualified for any DSM-5 CUD, with 10.7% and 3.0% meeting criteria for moderate and severe CUD, respectively. We identified optimal CUDIT-R scores at 10 for any DSM-5 CUD (sensitivity=0.58; specificity=0.80), at 12 for moderate CUD (sensitivity=0.72; specificity=0.82), and at 14 for severe CUD (sensitivity=0.71; specificity=0.87). ROC curves showed higher CUDIT-R validity among non-card holders compared with medical cannabis card holders. CONCLUSION: The present study identified optimal CUDIT-R cutoff scores for Veterans who use cannabis. Varying DSM-5 validity measures inform the need for population-specific CUDIT-R cutoff values.

Analysis of veterans crisis line data: Temporal factors associated with the initiation of emergency dispatches.

PURPOSE: To identify temporal patterns of emergency dispatches as initiated by Veteran Crisis Line (VCL) responders and among moderate- and high-risk contacts. METHODS: Incidence rate ratios (IRRs) were used to examine the incidence of emergency dispatches among all 1,437,543 VCL contacts across 2019-2020. RESULTS: Emergency dispatches were initiated in 57,077 (4.0%) contacts. IRRs were elevated during Labor Day, IRR (95% CI) = 1.33 (1.15-1.54), and Independence Day, IRR (95% CI) = 1.22 (1.05-1.43), weekends, Saturdays, IRR (95% CI) = 1.04 (1.01-1.08), Sunday (reference), and 6 pm to 11:59 pm, IRR (95% CI) = 1.06 (1.04-1.09). IRRs for moderate- and high-risk contacts were higher on Memorial Day, IRR (95% CI) = 1.16 (1.00-1.33), Sunday (reference), and 6 pm to 11:59 pm (reference). CONCLUSIONS: The initiation of emergency dispatches fluctuates over time and were highest during Labor Day and Independence Day, weekends, and evenings. Moderate- and high-risk contact also fluctuate over time and were highest on Memorial Day, Sundays, and midnight to 5:59 am. VCL policy makers can use knowledge of temporal fluctuations to allocate public health resources for increased efficiency and greatest impact; however, additional research on temporal stability and generalizability is needed.

Testing adaptive interventions to improve PTSD treatment outcomes in Federally Qualified Health Centers: Protocol for a randomized clinical trial.

BACKGROUND: Posttraumatic stress disorder (PTSD) disproportionately affects low-income individuals and is untreated in 70% of those affected. One third of low-income Americans are treated in Federally Qualified Health Centers (FQHCs), which do not have the capacity to provide all patients with first-line treatments such as Prolonged Exposure (PE). To address this problem, FQHCs could use low-intensity interventions (e.g., Clinician-Supported PTSD Coach: CS PTSD Coach) and medium-intensity interventions (e.g., PE for Primary Care: PE-PC) to treat PTSD with fewer resources. However, some patients will still require high-intensity treatments (e.g., full-length PE) for sustained clinical benefit. Thus, there is a critical need to develop stepped-care models for PTSD in FQHCs. METHOD: We are conducting a Sequential, Multiple Assignment, Randomized Trial (SMART) with 430 adults with PTSD in FQHCs. Participants are initially randomized to CS PTSD Coach or PE-PC. After four sessions, early responders step down to lower frequency interaction within their assigned initial treatment strategy. Slow responders are re-randomized to either continue their initial treatment strategy or step up to Full PE for an additional eight weeks. The specific aims are to test the effectiveness of initiating treatment with PE-PC versus CS PTSD Coach in reducing PTSD symptoms and to test the effectiveness of second-stage strategies (continue versus step-up to Full PE) for slow responders. CONCLUSIONS: This project will provide critical evidence to inform the development of an effective stepped-care model for PTSD. Testing scalable, sustainable sequences of PTSD treatments delivered in low-resource community health centers will improve clinical practice for PTSD.

Cognitive behavioral therapy for insomnia to reduce cannabis use: Results from a pilot randomized controlled trial.

BACKGROUND: Individuals with regular cannabis use demonstrate adverse health outcomes, yet infrequently seek treatment. Insomnia, a common co-occurring complaint, could be targeted to reduce cannabis use and improve functioning in these individuals. In an intervention development study, we refined and tested the preliminary efficacy of a telemedicine-delivered CBT for insomnia tailored to individuals with regular cannabis use for sleep (CBTi-CB-TM). METHODS: In this single-blind randomized trial, fifty-seven adults (43 women, mean age 37.6 ± 12.8 years) with chronic insomnia and cannabis use for sleep ≥3 times/week received CBTi-CB-TM (n = 30) or sleep hygiene education (SHE-TM, n = 27). Participants completed self-reported assessments of insomnia (Insomnia Severity Index [ISI]) and cannabis use (Timeline Followback [TLFB] and daily diary data) at pre-treatment, post-treatment, and 8-week follow-up. RESULTS: ISI scores improved significantly more in the CBTi-CB-TM compared to SHE-TM condition (ß = -2.83, se=0.84, P = 0.004, d=0.81). At 8-week follow-up, 18/30 (60.0 %) CBTi-CB-TM compared to 4/27 (14.8 %) SHE-TM participants were in remission from insomnia (X2 =12.8, P = 0.0003). The TLFB showed a small reduction in past 30-day cannabis use for both conditions (ß = -0.10, se=0.05, P = 0.026); CBTi-CB-TM participants demonstrated greater post-treatment reductions in the % of days cannabis was used within 2 h of bedtime (-29.1 ± 7.9 % fewer days vs. 2.6 ± 8.0 % more days, P = 0.008). CONCLUSIONS: CBTi-CB-TM is feasible, acceptable, and demonstrated preliminary efficacy for improving sleep and cannabis-related outcomes among non-treatment-seeking individuals with regular cannabis use for sleep. Although sample characteristics limit generalizability, these findings support the need for adequately powered randomized controlled trials with longer follow-up periods.

Driving under the influence of cannabis, alcohol, and illicit drugs among adults in the United States from 2016 to 2020.

OBJECTIVE: Driving under the influence (DUI) of substances increases motor vehicle crash risk. Understanding current national trends of driving under the influence of alcohol (DUIA), cannabis (DUIC), and drugs other than cannabis (DUID) can inform public health efforts. Herein, we provide updated trends among United States (US) adults regarding DUIA, DUIC, DUID, and DUI of any substance. METHOD: We used nationally-representative National Survey on Drug Use and Health (2016-2020) data to derive prevalence estimates of past-year DUIC, DUIA, DUID, and DUI of any substance among non-institutionalized US adults and among those reporting respective past-year  substance use. Prevalence estimates and adjusted logistic regressions characterized temporal trends of these behaviors among US adults, among those with respective past-year substance use, and among stratified demographic subpopulations. RESULTS: Over 1 in 10 US adults reported DUI of any substance annually from 2016 to 2020.DUIA was most prevalent among all US adults (8.7% in 2017); however, this behavior is decreasing (AOR:0.96; 95%CI:0.94,0.98). No change in DUIC among the US adult population was found, but a decrease was found among those with past-year cannabis use (AOR:0.95; 95%CI:0.93,0.98), which coincided with a 29.1% increase in past-year cannabis use. There were no significant changes in overall DUID; however, females, those ages 26-34 and 65 or older with past-year use displayed increasing trends. DUI of any substance decreased among the US adult population. CONCLUSIONS: DUI remains a salient public health concern in the US and results indicate population subgroups who may benefit from impaired driving prevention interventions.

Cannabis smoking, tobacco cigarette smoking, and adenomyosis risk.

OBJECTIVE: To investigate cannabis smoking and tobacco cigarette smoking in relation to adenomyosis risk. DESIGN: We used data from a case-control study of adenomyosis conducted among enrollees ages 18-59 years of an integrated health care system in Washington State. The case-control study used 2 control groups given the challenge of selecting noncases when cases are diagnosed by hysterectomy. SUBJECTS: Cases (n = 386) were enrollees with incident, pathology-confirmed adenomyosis diagnosed between April 1, 2001, and March 31, 2006. The 2 control groups comprised hysterectomy controls (n = 233) with pathology-confirmed absence of adenomyosis and population controls (n = 323) with an intact uterus selected randomly from the health care system population and frequency matched to cases on age. EXPOSURE: Detailed data on cannabis and tobacco cigarette smoking history were ascertained through in-person structured interviews, allowing estimation of joint-years of cannabis smoking and pack-years of tobacco cigarette smoking. MAIN OUTCOME MEASURES: Odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between cannabis smoking, tobacco cigarette smoking, and adenomyosis were estimated using multivariable unconditional logistic regression. Analyses were adjusted for age, reference year, menarche age, education, and pack-years of cigarette smoking (or joint-years of cannabis smoking). RESULTS: No association was observed between cannabis smoking history and adenomyosis risk. However, we did observe the suggestion of an association between ever tobacco cigarette smoking and adenomyosis risk, comparing cases to hysterectomy controls (OR, 1.3; 95% CI, 0.9-1.9) and population controls (OR, 1.2; 95% CI, 0.8-1.8). Our data suggested a 50% increased odds of adenomyosis with >15 pack-years of smoking (vs. never smoking), comparing cases to hysterectomy controls (OR, 1.5; 95% CI, 0.9-2.6; Ptrend=.135). The suggestion of a 40% increased adenomyosis odds was observed with smoking >5-15 pack-years (vs. never smoking), comparing cases to population controls (OR, 1.4; 95% CI, 0.8-2.4; Ptrend=0.136). CONCLUSION: In the first study of cannabis smoking and adenomyosis risk, no association was observed. However, our data suggested an increased odds of adenomyosis with history of tobacco cigarette smoking. Further research is warranted to replicate our results given the substantial morbidity with adenomyosis and frequency of cigarette smoking and recreational and medical cannabis use.

Adverse Surgical Outcomes Linked to Co-occurring Smoking and Risky Alcohol Use Among General Surgery Patients.

OBJECTIVE: To assess associations between co-occurring preoperative smoking and risky alcohol use on the likelihood of adverse surgical outcomes. BACKGROUND: Risky alcohol use and smoking are the known surgical risk factors with a high co-occurrence and additive adverse effects on multiple organ systems that impact surgical health, yet no research has evaluated the impact of co-occurrence on surgical outcomes. METHODS: This investigation analyzed 200,816 patients from the Michigan Surgical Quality Collaborative database between July 1, 2012, to December 31, 2018. Patients were classified based on past year risky alcohol use (>2 drink/day) and cigarette smoking into 4 groups: (1) risky alcohol and smoking, (2) risky alcohol only, (3) smoking only, and (4) no risky alcohol/smoking. We fitted logistic regression models, applying propensity score weights incorporating demographic, clinical, and surgical factors to assess associations between alcohol and smoking and 30-day postoperative outcomes; surgical complications, readmission, reoperation, and emergency department (ED) visits. RESULTS: Risky alcohol and smoking, risky alcohol only, and smoking only were reported by 2852 (1.4%), 2840 (1.4%), and 44,042 (22%) patients, respectively. Relative to all other groups, the alcohol and smoking group had greater odds of surgical complications, readmission, and reoperation. Relative to the no alcohol and smoking group, the alcohol only group higher odds of reoperation and smoking only group had higher odds of emergency department visits. CONCLUSIONS: The combination of smoking and risky drinking conferred the highest likelihood of complications, readmission, and reoperation before surgery. Co-occurring alcohol and smoking at the time of surgery warrants special attention as a patient risk factor and deserves additional research.

Who improves in trauma-focused treatment: A cluster analysis of treatment response in VA patients undergoing PE and CPT.

BACKGROUND: Although most veterans with posttraumatic stress disorder (PTSD) benefit from evidence-based treatments, questions persist concerning the profiles of those at risk for poor outcomes. To help address these gaps, this study analyzed a large clinical cohort of veterans receiving prolonged exposure (PE) or cognitive processing therapy (CPT). METHODS: Cluster analysis using Ward's method with Euclidian distances identified clinically meaningful subgroups of veterans in a national cohort (n = 20,848) using variables maintained in the electronic medical record. The clusters were then compared via one-way analysis of variance and Tukey's HSD on indicators of treatment progress including PTSD symptom change, clinical recovery, clinically significant change, remission, and treatment completion. RESULTS: Effect size differences on clinical outcome measures for PE and CPT were negligible. Less than half of veterans achieved at least a 15-point reduction in PCL-5 score and half completed treatment. We identified 10 distinct clusters. Higher rates of PTSD service-connected disability were linked to poorer outcomes across multiple clusters, especially when combined with Post-Vietnam service era. Non-White race was also linked with poorer clinical outcomes. Factors associated with better outcomes included a greater proportion of female veterans, especially when combined with recent service era, and longer PTSD diagnosis duration. CONCLUSIONS: This study suggests the need to improve PTSD treatment outcomes for non-White and male veterans, examine treatment response in Post-Vietnam era veterans, and consider ways in which the service connection process could hinder treatment response. The results from this study also indicate the benefits of integrating elements of clinical complexity into an analytic approach.

Telemedicine-delivered cognitive-behavioral therapy for insomnia in alcohol use disorder (AUD): study protocol for a randomized controlled trial.

BACKGROUND: Alcohol use disorder (AUD) is a leading preventable cause of morbidity and mortality, but relapse rates are high even with available treatments. Insomnia is a robust predictor of relapse and pilot studies have shown that CBT for insomnia improves insomnia and daytime functioning in adults with AUD and insomnia. The impact of CBT for insomnia on relapse, however, is unclear. This trial will compare telemedicine-delivered CBT for insomnia (CBT-TM) with sleep hygiene education (SHE-TM) on improving insomnia/sleep, daytime symptom, and drinking outcomes in treatment-seeking AUD adults with insomnia. The study will also determine the effects of treatment on sleep mechanisms and their association with clinical outcomes. METHODS: This is a single-site randomized controlled trial with planned enrollment of 150 adults meeting criteria for both AUD and chronic insomnia. Eligible participants will be randomized 1:1 to 6 sessions of telemedicine-delivered Cognitive Behavioral Therapy for Insomnia (CBT-TM) or Sleep Hygiene Education (SHE-TM) with clinical assessments conducted at pre-treatment, post- treatment, and at 3, 6, and 12 months post-treatment. Overnight polysomnography will be conducted before and after treatment. Primary clinical outcomes will include post-treatment scores on the Insomnia Severity Index and the General Fatigue subscale of the Multidisciplinary Fatigue Inventory, and the percent of days abstinent (PDA) on the interview-administered Time Line Follow Back. EEG delta activity, derived from overnight polysomnography, will be the primary endpoint to assess the sleep homeostasis mechanism. DISCUSSION: This adequately powered randomized controlled trial will provide clinically relevant information about whether targeting insomnia is effective for improving treatment outcomes among treatment-seeking adults with AUD. Additionally, the study will offer new scientific insights on the impact of an evidence-based non-medication treatment for insomnia on a candidate mechanism of sleep dysfunction in this population - sleep homeostasis. TRIAL REGISTRATION: CClinicalTrials.gov NCT # 04457674 . Registered on 07 July 2020.

A nationally representative sample of veteran and matched non-veteran college students: Mental health symptoms, suicidal ideation, and mental health treatment.

Objective To assess mental health symptoms, suicidal ideation/behaviors, and treatment among a nationally representative probability sample of student veterans. Participants: Student veterans enrolled in post-secondary educational institutions and matched comparison students. Methods: Sampled participants completed an online survey (n = 1,838). Analyses accounted for the complex sample design and non-response. Results: Substantial percentages of student veterans screened positive for: depression (36.9%, 95% CI: 31.1-42.7), PTSD (35.7%, 95% CI 29.9-41.5), anxiety (29.5%, 95% CI 26.8-32.2), and suicidal ideation (14.6%, 95% CI 12.1-17.1), with student veterans having odds ratios between 1.7 to 2.4 for positive screens compared to non-veteran students. Only 41.5% (95% CI 33.0-50.0) of student veterans with positive screens received treatment, although they had 50% higher odds of receiving treatment than non-veteran students. Conclusions: Student veterans have high rates of mental health symptoms and low rates of treatment. However, they are more likely to receive treatment than comparison students.

Prevalence and Correlates of Cannabis Use and Cannabis Use Disorder Among U.S. Veterans: Results From the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III).

OBJECTIVE: The authors sought to estimate the prevalence of past-12-month and lifetime cannabis use and cannabis use disorder among U.S. veterans; to describe demographic, substance use disorder, and psychiatric disorder correlates of nonmedical cannabis use and cannabis use disorder; and to explore differences in cannabis use and cannabis use disorder prevalence among veterans in states with and without medical marijuana laws. METHODS: Participants were 3,119 respondents in the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) who identified as U.S. veterans. Weighted prevalences were calculated. Logistic regression analyses tested associations of nonmedical cannabis use and cannabis use disorder with demographic and clinical correlates and examined whether prevalence differed by state legalization status. RESULTS: The prevalences of any past-12-month cannabis use and cannabis use disorder were 7.3% and 1.8%, respectively. Lifetime prevalences were 32.5% and 5.7%, respectively. Past-12-month and lifetime cannabis use disorder prevalence estimates among nonmedical cannabis users were 24.4% and 17.4%, respectively. Sociodemographic correlates of nonmedical cannabis use and use disorder included younger age, male gender, being unmarried, lower income, and residing in a state with medical marijuana laws. Nonmedical cannabis use and use disorder were associated with most psychiatric and substance use disorders examined. CONCLUSIONS: Among veterans, the odds of nonmedical cannabis use and use disorder were elevated among vulnerable subgroups, including those with lower income or psychiatric disorders and among survey participants residing in states with medical marijuana laws. The study findings highlight the need for clinical attention (e.g., screening, assessment) and ongoing monitoring among veterans in the context of increasing legalization of cannabis.

Pain, cannabis use, and physical and mental health indicators among veterans and nonveterans: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III.

ABSTRACT: Chronic pain is associated with mental and physical health difficulties and is prevalent among veterans. Cannabis has been put forth as a treatment for chronic pain, and changes in laws, attitudes, and use patterns have occurred over the past 2 decades. Differences in prevalence of nonmedical cannabis use and cannabis use disorder (CUD) were examined across 2 groups: veterans or nonveterans and those reporting or not reporting recent pain. Data from the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013; n = 36,309) were analyzed using logistic regression. Prevalence differences (PDs) for 3 cannabis outcomes (1) past-year nonmedical cannabis use, (2) frequent (≥3 times a week) nonmedical use, and (3) DSM-5 CUD were estimated for those reporting recent moderate to severe pain (veterans or nonveterans) and veterans reporting or not reporting recent pain. Difference in differences was calculated to investigate PDs on outcomes associated with residence in a state with medical cannabis laws (MCLs). Associations between physical and mental health and cannabis variables were tested. The results indicated that the prevalence of recent pain was greater among veterans (PD = 7.25%, 95% confidence interval (CI) [4.90-9.60]). Among veterans, the prevalence of frequent cannabis use was greater among those with pain (PD = 1.92%, 98% CI [0.21-3.63]), and among veterans residing in a state with MCLs, the prevalence of CUD was greater among those reporting recent pain (PD = 3.88%, 98% CI [0.36-7.39]). Findings failed to support the hypothesis that cannabis use improves mental or physical health for veterans with pain. Providers treating veterans with pain in MCL states should monitor such patients closely for CUD.

Trends in Incident Varenicline Prescribing Among Veterans Following the US Food and Drug Administration Drug Safety Warnings.

Objective: To evaluate national trends in incident varenicline and nicotine replacement therapy (NRT) prescribing among Department of Veterans Affairs (VA) beneficiaries before and after US Food and Drug Administration (FDA) warnings regarding neuropsychiatric side effects with varenicline use.Methods: All adult VA patients identified as smokers from 2007 to 2019 (N = 3,600,947) were determined and monthly counts of new varenicline and NRT users were calculated. An interrupted time-series analysis estimated the effect of the FDA warnings on varenicline and NRT prescribing overall and among Veterans with and without mental health disorders.Results: The incident use rate of varenicline decreased from a peak of 6.2 per 1,000 veteran smokers in October 2007 to 1.0 by July 2009 following the first FDA warning (pre-warning monthly slope = -0.27; P = .03). New NRT use increased from 10.7 per 1,000 veteran smokers in October 2007 to a peak of 12.6 per 1,000 in July 2009 (slope change = 0.71; P = .01), suggesting potential substitution. Following removal of the FDA boxed warning in December 2016, varenicline prescribing increased but did not return to pre-warning levels by December 2019. Among veterans with and without mental health disorders, varenicline use decreased 90% and 88%, respectively, following the first FDA warning, and both groups had comparable rates of new NRT use.Conclusions: Following the first FDA warning, incident use of varenicline declined significantly among veterans both with and without mental health disorders. Despite removal of the FDA boxed warning in December 2016, new use of varenicline had not returned to pre-warning levels 3 years following the removal.

Shorter and longer-term risk for non-fatal suicide attempts among male U.S. military veterans after discharge from psychiatric hospitalization.

Although there are key differences in shorter-term (days 1-90) and longer-term (days 91-365) risk factors for suicide after discharge from inpatient psychiatry, there are no comparable data on non-fatal suicide attempts. Risk factors for non-fatal attempts in the first 90 days after discharge were compared with those over the remainder of the year to identify temporal changes in risk. Records were extracted from 208,554 male veterans discharged from Veterans Health Administration acute psychiatric inpatient units from 2008 through 2013. Proportional hazard regression models identified correlates of non-fatal attempts for 1-90 days and 91-365 days; adjusted piecewise proportional hazards regression compared risk between these time frames. 5010 (2.4%) veterans made a non-fatal attempt, 1261 (0.60%) on days 1-90 and 3749 (1.78%) on days 91-365. Risk across both time frames was highest among younger veterans ages 18-59, and those hospitalized with a suicide attempt or suicidal ideation. It was lowest among those with a dementia diagnosis. Risk estimates were generally stable over time but increased among those with substance use disorders and decreased among those with sleep disturbance and discharged against medical advice. Estimates of some risk factors for non-fatal attempts change over time in the year after discharge and differ from those that change for suicide. Different preventive approaches may be needed to reduce shorter and longer-term risk for non-fatal attempts and suicide in the year after discharge.

Shorter- and Longer-Term Risk for Suicide Among Male US Military Veterans in the Year After Discharge From Psychiatric Hospitalization.

OBJECTIVE: Risk for suicide is highest in the first 3 months (days 1-90) after discharge from acute psychiatric hospitalization yet remains elevated for the remainder of the year (days 91-365). The purpose of this study was to compare risk factors for suicide in the first 90 days to those over the remainder of the year to identify changes across time frames. METHODS: The study included 316,707 male veterans discharged from Veterans Health Administration acute psychiatric inpatient units from 2008 through 2013. Proportional hazard regression models were used to identify predictors of suicide death in the first 90 days and in days 91-365, defined via ICD-10 codes. Adjusted piecewise proportional hazard regression was used to compare risk across time frames. RESULTS: Among the 1,037 veterans (< 1%) who died by suicide, 471 (45%) died between days 1 and 90 and 566 (55%) died between days 91 and 365. There was little change regarding the strength of risk factors over time, with two exceptions: risk increased among those aged 18-29 years compared to those aged ≥ 65 years (days 1-90: hazard ratio [HR] = 0.83; 95% CI, 0.57-1.20 vs days 91-365: HR = 1.42; 95% CI, 1.03-1.97; P < .05), whereas, risk associated with suicidal ideation decreased (days 1-90: HR = 1.89; 95% CI, 1.57-2.28 vs days 91-365: HR = 1.40; 95% CI, 1.17-1.66, P < .05). CONCLUSIONS: The strength of association between common risk factors and suicide remains relatively stable during the year following psychiatric hospitalization. However, risk among veterans aged 19-29 years increased over time, whereas risk among those with suicidal ideation decreased.

Progression of cannabis withdrawal symptoms in people using medical cannabis for chronic pain.

BACKGROUND AND AIMS: Research from cohorts of individuals with recreational cannabis use indicates that cannabis withdrawal symptoms are reported by more than 40% of those using regularly. Withdrawal symptoms are not well understood in those who use cannabis for medical purposes. Therefore, we prospectively examined the stability of withdrawal symptoms in individuals using cannabis to manage chronic pain. DESIGN, SETTING, PARTICIPANTS: Using latent class analysis (LCA) we examined baseline cannabis withdrawal to derive symptom profiles. Then, using latent transition analysis (LTA) we examined the longitudinal course of withdrawal symptoms across the time points. Exploratory analyses examined demographic and clinical characteristics predictive of withdrawal class and transitioning to more or fewer withdrawal symptoms over time. A cohort of 527 adults with chronic pain seeking medical cannabis certification or re-certification was recruited between February 2014 and June 2015. Participants were recruited from medical cannabis clinic waiting rooms in Michigan, USA. Participants were predominantly white (82%) and 49% identified as male, with an average age of 45.6 years (standard deviation = 12.8). MEASUREMENTS: Baseline, 12-month and 24-month assessments of withdrawal symptoms using the Marijuana Withdrawal Checklist-revised. FINDINGS: A three-class LCA model including a mild (41%), moderate (34%) and severe (25%) symptom class parsimoniously represented withdrawal symptoms experienced by people using medical cannabis. Stability of withdrawal symptoms using a three-class LTA at 12 and 24 months ranged from 0.58 to 0.87, with the most stability in the mild withdrawal class. Younger age predicted greater severity and worsening of withdrawal over time. CONCLUSIONS: Adults with chronic pain seeking medical cannabis certification or re-certification appear to experience mild to severe withdrawal symptoms. Withdrawal symptoms tend to be stable over a 2-year period, but younger age is predictive of worse symptoms and of an escalating withdrawal trajectory.

Rates and predictors of psychotherapy receipt among U.S. veterans with comorbid posttraumatic stress disorder and substance use disorders.

Introduction: Veterans with comorbid posttraumatic stress disorder (PTSD) and substance use disorder (SUD) have complex needs and often do not receive adequate mental health treatment. The purpose of this study was to examine rates and predictors of PTSD-only, SUD-only, or PTSD and SUD psychotherapy receipt among newly diagnosed Veterans with PTSD and SUD. Design and setting: An administrative dataset including Veterans Health Administration (VHA) users. Participants: The sample comprised 32,779 United States Veterans with a new PTSD and a new SUD diagnosis in fiscal year 2015. Measurement: Multinomial logistic regression was used to identify predictors of receipt of any and adequate psychotherapy for PTSD, SUD, or PTSD and SUD across settings. Binomial logistic regression was used to identify predictors of PTSD psychotherapy among those who received any psychotherapy. Findings: A total of 13,824 (42.17%) Veterans in this sample received any PTSD- or SUD-related therapy in the year following diagnosis. Low rates of veterans received an adequate dose of PTSD-related psychotherapy (6.58%), SUD-related psychotherapy (7.72%), or both PTSD and SUD-related psychotherapy (<1%) In adjusted models, older age, service-connected disability, and psychiatric comorbidities were associated with decreased odds of treatment. Specific types of SUDs, including alcohol, cocaine, and opioid use disorders, along with receipt of diagnosis in a PTSD or SUD clinic, were associated with increased odds of treatment. Conclusions: Low rates of PTSD and SUD related psychotherapy highlight a need to better engage and retain Veterans with these disorders in care. Predictors of decreased treatment utilization, such as older age, service connection, and bipolar and major depressive disorders, may inform efforts by the VHA to further target and engage Veterans with indicated treatments.