Assessing Substance Use Disorder Symptoms with a Checklist among Primary Care Patients with Opioid Use Disorder and/or Long-Term Opioid Treatment: An Observational Study.

BACKGROUND: Primary care (PC) offers an opportunity to treat opioid use disorders (OUD). The Substance Use Symptom Checklist ("Checklist") can assess DSM-5 substance use disorder (SUD) symptoms in PC. OBJECTIVE: To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA). DESIGN: Observational study using item response theory (IRT) and differential item functioning (DIF) analyses of measurement consistency across age, sex, race and ethnicity, and receipt of treatment. PATIENTS: Electronic health records (EHR) data were extracted for all adult PC patients visiting KPWA 3/1/15-8/30/2020 who had ≥ 1 Checklist documented and indication of either (a) clinically-recognized OUD (i.e., documented OUD diagnosis and/or OUD medication treatment) or (b) LTOT in the year prior to the checklist. MAIN MEASURE: The Checklist includes 11 items reflecting DSM-5 criteria for SUD. We described the prevalence of 2 SUD symptoms reported on the Checklist (consistent with mild-severe DSM-5 SUD). Analyses were conducted in the overall sample and in two subsamples (clinically-recognized OUD and LTOT only). KEY RESULTS: Among 2007 eligible patients, 39.9% endorsed ≥ 2 SUD symptoms (74.3% in the clinically-recognized OUD subsample and 13.1% in LTOT subsample). IRT indicated that a unidimensional model for the 11 checklist items had excellent fit (comparative fit index = 0.998) with high item-level discrimination parameters for the overall sample and both subsamples. DIF across age, race and ethnicity, and treatment was observed for one item each, but had minimal impact on expected number of criteria (0-11) patients endorse. CONCLUSIONS: The Substance Use Symptom Checklist measured SUD symptoms consistent with DSM-5 conceptualization (scaled, unidimensional) in patients with clinically-recognized OUD and LTOT and had similar measurement properties across demographic subgroups. The Checklist may support symptom assessment in patients with OUD and diagnosis in patients with LTOT.

Reductions in World Health Organization risk drinking level are associated with improvements in sleep problems among individuals with alcohol use disorder.

AIMS: Among individuals with alcohol use disorder (AUD), sleep disturbances are pervasive and contribute to the etiology and maintenance of AUD. However, despite increased attention toward the relationship between alcohol use and sleep, limited empirical research has systematically examined whether reductions in drinking during treatment for AUD are associated with improvements in sleep problems. METHODS: We used data from a multisite, randomized, controlled trial that compared 6 months of treatment with gabapentin enacarbil extended-release with placebo for adults with moderate-to-severe AUD (N = 346). The Timeline Follow-back was used to assess WHO risk drinking level reductions and the Pittsburgh Sleep Quality Index was used to assess sleep quality over the prior month at baseline and the end of treatment. RESULTS: Sleep problem scores in the active medication and placebo groups improved equally. Fewer sleep problems were noted among individuals who achieved at least a 1-level reduction (B = -0.99, 95% confidence interval (CI) [-1.77, -0.20], P = .014) or at least a 2-level reduction (B = -0.80, 95% CI [-1.47, -0.14], P = .018) in WHO risk drinking levels at the end of treatment. Reductions in drinking, with abstainers excluded from the analysis, also predicted fewer sleep problems at the end of treatment (1-level: B = -1.01, 95% CI [-1.83, -0.20], P = .015; 2-level: B = -0.90, 95% CI [-1.59, -0.22], P = .010). CONCLUSIONS: Drinking reductions, including those short of abstinence, are associated with improvements in sleep problems during treatment for AUD. Additional assessment of the causal relationships between harm-reduction approaches to AUD and improvements in sleep is warranted.

Equivalence of Alcohol Use Disorder Symptom Assessments in Routine Clinical Care When Completed Remotely via Online Patient Portals Versus In Clinic via Paper Questionnaires: Psychometric Evaluation.

BACKGROUND: The National Institute on Alcohol Abuse and Alcoholism (NIAAA) recommends the paper-based or computerized Alcohol Symptom Checklist to assess alcohol use disorder (AUD) symptoms in routine care when patients report high-risk drinking. However, it is unknown whether Alcohol Symptom Checklist response characteristics differ when it is administered online (eg, remotely via an online electronic health record [EHR] patient portal before an appointment) versus in clinic (eg, on paper after appointment check-in). OBJECTIVE: This study evaluated the psychometric performance of the Alcohol Symptom Checklist when completed online versus in clinic during routine clinical care. METHODS: This cross-sectional, psychometric study obtained EHR data from the Alcohol Symptom Checklist completed by adult patients from an integrated health system in Washington state. The sample included patients who had a primary care visit in 2021 at 1 of 32 primary care practices, were due for annual behavioral health screening, and reported high-risk drinking on the behavioral health screen (Alcohol Use Disorder Identification Test-Consumption score ≥7). After screening, patients with high-risk drinking were typically asked to complete the Alcohol Symptom Checklist-an 11-item questionnaire on which patients self-report whether they had experienced each of the 11 AUD criteria listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) over a past-year timeframe. Patients could complete the Alcohol Symptom Checklist online (eg, on a computer, smartphone, or tablet from any location) or in clinic (eg, on paper as part of the rooming process at clinical appointments). We examined sample and measurement characteristics and conducted differential item functioning analyses using item response theory to examine measurement consistency across these 2 assessment modalities. RESULTS: Among 3243 patients meeting eligibility criteria for this secondary analysis (2313/3243, 71% male; 2271/3243, 70% White; and 2014/3243, 62% non-Hispanic), 1640 (51%) completed the Alcohol Symptom Checklist online while 1603 (49%) completed it in clinic. Approximately 46% (752/1640) and 48% (764/1603) reported ≥2 AUD criteria (the threshold for AUD diagnosis) online and in clinic (P=.37), respectively. A small degree of differential item functioning was observed for 4 of 11 items. This differential item functioning produced only minimal impact on total scores used clinically to assess AUD severity, affecting total criteria count by a maximum of 0.13 criteria (on a scale ranging from 0 to 11). CONCLUSIONS: Completing the Alcohol Symptom Checklist online, typically prior to patient check-in, performed similarly to an in-clinic modality typically administered on paper by a medical assistant at the time of the appointment. Findings have implications for using online AUD symptom assessments to streamline workflows, reduce staff burden, reduce stigma, and potentially assess patients who do not receive in-person care. Whether modality of DSM-5 assessment of AUD differentially impacts treatment is unknown.

Treatment retention and reductions in blood alcohol concentration (BAC) during the first 90 days of a telehealth program for alcohol use disorder.

Background: Alcohol use disorder (AUD) treatments, including medications, are increasingly offered via telehealth.Objective: This study characterizes 90-day treatment retention and changes in objectively measured blood alcohol concentration (BAC) in a large cohort receiving AUD telehealth.Methods: Patients received AUD treatment through Ria, a virtual (telehealth) program offering AUD treatment that is tailored to patient goals (e.g. abstinence or controlled drinking). Patients were encouraged to complete breathalyzer readings twice daily for measurement-based care. We characterized rates of 90-day treatment retention (i.e. completing a BAC reading or medical/coaching encounter on the 90th day or later) and used growth curve analyses to model changes in daily estimated peak BAC over 90 days.Results: Of 4121 patients (51.5% women), 50.1% had 90-day treatment retention (n = 2066, 52.2% women). Most patients received prescriptions for AUD medications (84.6%) and completed encounters with medical providers (86.7%) and coaches (86.1%). Patients with 90-day retention provided 184,817 BAC readings in the first 90 days. Growth curve analyses revealed significant reductions in daily estimated peak BAC (p < .001) from a mean of 0.092 (day 1) to 0.038 (day 90). Similar magnitudes of BAC reduction were observed for men and women and for patients with abstinence and controlled drinking goals.Conclusion: Telehealth appears to be a viable approach to delivering AUD treatments in a manner that promotes drinking reductions. Telehealth approaches can yield reductions in objectively measured BAC, including for some patient subgroups that have historically faced greater stigma in AUD treatment settings, such as women and people with non-abstinence drinking goals.

Practical Assessment of Alcohol Use Disorder in Routine Primary Care: Performance of an Alcohol Symptom Checklist.

BACKGROUND: Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated. OBJECTIVE: To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care. DESIGN: Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity. PATIENTS: Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020. MAIN MEASURE: Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs. KEY RESULTS: Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11). CONCLUSIONS: Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD.

Practical assessment of DSM-5 alcohol use disorder criteria in routine care: High test-retest reliability of an Alcohol Symptom Checklist.

BACKGROUND: Alcohol use disorder (AUD) is underdiagnosed and undertreated in medical settings, in part due to a lack of AUD assessment instruments that are reliable and practical for use in routine care. This study evaluates the test-retest reliability of a patient-report Alcohol Symptom Checklist questionnaire when it is used in routine care, including primary care and mental health specialty settings. METHODS: We performed a pragmatic test-retest reliability study using electronic health record (EHR) data from Kaiser Permanente Washington, an integrated health system in Washington state. The sample included 454 patients who reported high-risk drinking on a behavioral health screen and completed two Alcohol Symptom Checklists 1 to 21 days apart. Subgroups of these patients who completed both checklists in primary care (n = 271) or mental health settings (n = 79) were also examined. The primary measure was an Alcohol Symptom Checklist on which patients self-reported whether they experienced each of the 11 AUD criteria within the past year, as defined by the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5). RESULTS: Alcohol Symptom Checklists completed in routine care and documented in EHRs had excellent test-retest reliability for measuring AUD criterion counts (ICC = 0.79, 95% CI: 0.76 to 0.82). Test-retest reliability estimates were also high and not significantly different for the subsamples of patients who completed both checklists in primary care (ICC = 0.82, 95% CI: 0.77 to 0.85) or mental health settings (ICC = 0.74, 95% CI: 0.62 to 0.83). Test-retest reliability was not moderated by having a past two-year AUD diagnosis, nor by the age or sex of the patient completing it. CONCLUSIONS: Alcohol Symptom Checklists can reliably and pragmatically assess AUD criteria in routine care among patients who screen positive for high-risk drinking. The Alcohol Symptom Checklist may be a valuable tool in supporting AUD-related care and monitoring AUD criteria longitudinally in routine primary care and mental health settings.

An Alcohol Symptom Checklist identifies high rates of alcohol use disorder in primary care patients who screen positive for depression and high-risk drinking.

BACKGROUND: Although alcohol use disorder can complicate depression management, there is no standard process for assessing AUD symptoms (i.e., AUD diagnostic criteria) in primary care for patients who screen positive for depression. This study characterizes the association between depressive symptoms and high-risk drinking reported by primary care patients on screening measures in routine care. Then, using data from a novel clinical program, this study characterizes the association between depressive symptoms and AUD symptoms reported by primary care patients with high-risk drinking via an Alcohol Symptom Checklist. METHODS: In this cross-sectional study, electronic health record data were obtained from patients who visited 33 Kaiser Permanente Washington primary care clinics between 03/2018 and 02/2020 and completed depression (PHQ-2) and alcohol consumption (AUDIT-C) screening measures as part of routine care (N = 369,943). Patients who reported high-risk drinking (AUDIT-C scores 7-12) also completed an Alcohol Symptom Checklist where they reported the presence or absence of 11 AUD criteria as defined by the DSM-5 (N = 8,184). Generalized linear models estimated and compared the prevalence of high-risk drinking (AUDIT-C scores 7-12) and probable AUD (2-11 AUD symptoms on Alcohol Symptom Checklists) for patients with and without positive depression screens. RESULTS: Patients who screened positive for depression had a 131% higher prevalence of high-risk drinking than those who screened negative (5.2% vs. 2.2%; p < 0.001). Among patients with high-risk drinking, positive depression screens were associated with a significantly higher prevalence of probable AUD (69.8% vs. 48.0%; p < 0.001), with large differences in the prevalence of probable AUD observed with increasing PHQ-2 scores (e.g., probable AUD prevalence of 37.6%, 55.3% and 65.2%, for PHQ-2 scores of 0, 1, and 2, respectively). Although the overall prevalence of high-risk drinking was higher for male patients, similar patterns of association between depression screens, high-risk drinking, and AUD symptoms were observed for male and female patients. CONCLUSIONS: Patients with positive depression screens are more likely to have high-risk drinking. Large percentages of patients with positive depression screens and high-risk drinking report symptoms consistent with AUD to healthcare providers when given the opportunity to do so using an Alcohol Symptom Checklist.

Peer providers and linkage with buprenorphine care after hospitalization: A retrospective cohort study.

Background: People with opioid use disorder (OUD) are increasingly started on buprenorphine in the hospital, yet many patients do not attend outpatient buprenorphine care after discharge. Peer providers, people in recovery themselves, are a growing part of addiction care. We examine whether patients who received a low-intensity, peer-delivered intervention during hospitalization had a greater rate of linking with outpatient buprenorphine care relative to those not seen by a peer. Methods: This was a retrospective cohort study of adults with OUD who were started on buprenorphine during hospitalization. The primary outcome was receipt of a buprenorphine prescription within 30 days of discharge. Secondary outcomes included attendance at a follow-up visit with a buprenorphine provider within 30 days and hospital readmission within 90 days. Modified Poisson regression analyses tested for differences in the rate ratios (RR) of each binary outcome for patients who were versus were not seen by a peer provider. Peer notes in the electronic health record were reviewed to characterize peer activities. Results: 111 patients met the study inclusion criteria, 31.5% of whom saw a peer provider. 55.0% received a buprenorphine prescription within 30 days of hospital discharge. Patients with versus without peer provider encounters did not significantly differ in the rates of receiving a buprenorphine prescription (RR = 1.06, 95% CI: 0.74-1.51), hospital readmission (RR = 1.45, 95% CI: 0.80-2.64), or attendance at a buprenorphine follow-up visit (RR = 1.03, 95% CI: 0.68-1.57). Peers most often listened to or shared experiences with patients (68.6% of encounters) and helped facilitate medical care (60.0% of encounters). Conclusions: There were no differences in multiple measures of buprenorphine follow-up between patients who received this low-intensity peer intervention and those who did not. There is need to investigate what elements of peer provider programs contribute to patient outcomes and what outcomes should be assessed when evaluating peer programs.

Stability of Drinking Reductions and Long-term Functioning Among Patients with Alcohol Use Disorder.

BACKGROUND: The World Health Organization (WHO) categorizes alcohol consumption according to grams consumed into low-, medium-, high-, and very-high-risk drinking levels (RDLs). Although abstinence has been considered the ideal outcome of alcohol treatment, reductions in WHO RDLs have been proposed as primary outcomes for alcohol use disorder (AUD) trials. OBJECTIVE: The current study examines the stability of WHO RDL reductions and the association between RDL reductions and long-term functioning for up to 3 years following treatment. DESIGN AND PARTICIPANTS: Secondary data analysis of patients with AUD enrolled in the COMBINE Study and Project MATCH, two multi-site, randomized AUD clinical trials, who were followed for up to 3 years post-treatment (COMBINE: n = 694; MATCH: n = 806). MEASURES: Alcohol use was measured via calendar-based methods. We estimated all models in the total sample and among participants who did not achieve abstinence during treatment. KEY RESULTS: One-level RDL reductions were achieved by 84% of patients at the end of treatment, with 84.9% of those individuals maintaining that reduction at a 3-year follow-up. Two-level RDL reductions were achieved by 68% of patients at the end of treatment, with 77.7% of those individuals maintaining that reduction at a 3-year follow-up. One- and two-level RDL reductions at the end of treatment were associated with significantly better mental health, quality of life (including physical quality of life), and fewer drinking consequences 3 years after treatment (p < 0.05), as compared to no change or increased drinking. CONCLUSION: AUD patients can maintain WHO RDL reductions for up to 3 years after treatment. Patients who had WHO RDL reductions functioned significantly better than those who did not reduce their drinking. These findings are consistent with prior reports suggesting that drinking reductions, short of abstinence, yield meaningful improvements in patient health, well-being, and functioning.

Understanding measures of racial discrimination and microaggressions among American Indian and Alaska Native college students in the Southwest United States.

BACKGROUND: Racial discrimination, including microaggressions, contributes to health inequities, yet research on discrimination and microaggressions has focused on single measures without adequate psychometric evaluation. To address this gap, we examined the psychometric performance of three discrimination/microaggression measures among American Indian and Alaska Native (AI/AN) college students in a large Southwestern city. METHODS: Students (N = 347; 65% female; ages 18-65) completed the revised-Everyday Discrimination Scale, Microaggressions Distress Scale, and Experiences of Discrimination measure. The psychometric performance of these measures was evaluated using item response theory and confirmatory factor analyses. Associations of these measures with age, gender, household income, substance use, and self-rated physical health were examined. RESULTS: Discrimination and microaggression items varied from infrequently to almost universally endorsed and each measure was unidimensional and moderately correlated with the other two measures. Most items contributed information about the overall severity of discrimination and collectively provided information across a continuum from everyday microaggressions to physical assault. Greater exposure to discrimination on each measure had small but significant associations with more substance use, lower income, and poorer self-rated physical health. The Experiences of Discrimination measure included more severe forms of discrimination, while the revised-Everyday Discrimination Scale and the Microaggressions Distress Scale represented a wider range of severity. CONCLUSIONS: In clinical practice, these measures can index varying levels of discrimination for AI/ANs, particularly for those in higher educational settings. This study also informs the measurement of racial discrimination and microaggressions more broadly.

Can Alcohol Use Disorder Recovery Include Some Heavy Drinking? A Replication and Extension up to 9 Years Following Treatment.

BACKGROUND: Recent research indicates some individuals who engage in heavy drinking following treatment for alcohol use disorder fare as well as those who abstain with respect to psychosocial functioning, employment, life satisfaction, and mental health. The current study evaluated whether these findings replicated in an independent sample and examined associations between recovery profiles and functioning up to 6 years later. METHODS: Data were from the 3-year and 7- to 9-year follow-ups of subsamples initially recruited for the COMBINE study (3-year follow-up: n = 694; 30.1% female, 21.0% non-White; 7- to 9-year follow-up: n = 127; 38.9% female, 27.8% non-White). Recovery at 3 years was defined by latent profile analyses including measures of health functioning, quality of life, employment, alcohol consumption, and cannabis and other drug use. Functioning at the 7- to 9-year follow-up was assessed using single items of self-rated general health, hospitalizations, and alcohol consumption. RESULTS: We identified 4 profiles at the 3-year follow-up: (i) low-functioning frequent heavy drinkers (13.9%), (ii) low-functioning infrequent heavy drinkers (15.8%), (iii) high-functioning heavy drinkers (19.4%), and (iv) high-functioning infrequent drinkers (50.9%). At the 7- to 9-year follow-up, the 2 high-functioning profiles had the best self-rated health, and the high-functioning heavy drinking profile had significantly fewer hospitalizations than the low-functioning frequent heavy drinking profile. CONCLUSIONS: Previous findings showing heterogeneity in recovery outcomes were replicated. Most treatment recipients functioned well for years after treatment, and a subset who achieved stable recovery engaged in heavy drinking and reported good health outcomes up to 9 years after treatment. Results question the long-standing emphasis on drinking practices as a primary outcome, as well as abstinence as a recovery criterion in epidemiologic and treatment outcome research and among stakeholder groups and funding/regulatory agencies. Findings support an expanded recovery research agenda that considers drinking patterns, health, life satisfaction, and functioning.

Consumption outcomes in clinical trials of alcohol use disorder treatment: Consideration of standard drink misestimation.

Background. The Food and Drug Administration recently added a new clinical endpoint for evaluating the efficacy of alcohol use disorder (AUD) treatment that is more inclusive of treatment goals besides abstinence: no heavy drinking days (NHDD). However, numerous critiques have been noted for such binary models of treatment outcome. Further, there is mounting evidence that participants inaccurately estimate the quantities of alcohol they consume during drinking episodes (i.e., drink size misestimation), which may be particularly problematic when using a binary criterion (NHDD) compared to a similar, continuous alternative outcome variable: percent heavy drinking days (PHDD). Yet, the impact of drinking misestimation on binary (e.g., NHDD) versus continuous outcome variables (e.g., PHDD) has not been studied. Objectives. Using simulation methods, the present study examined the potential impact of drink size misestimation on NHDD and PHDD. Methods. Data simulations were based on previously published findings of the amount of error in how much alcohol is actually poured when estimating standard drinks. We started with self-reported daily drinking data from COMBINE study participants with complete data (N = 888; 68.1% male), then simulated inaccuracy in those estimations based on literature on standard drink size misestimation. Results. Clinical trial effect sizes were consistently lower for NHDD than for PHDD. Drink size misestimation further lowered effect sizes for NHDD and PHDD. Conclusions. Drink size misestimation may lead to inaccurate conclusions about drinking outcomes and the comparative effectiveness of AUD treatments, including inflated type-II error rates, particularly when treatment "success" is defined by binary outcomes such as NHDD.

Modeling empathy as synchrony in clinician and patient vocally encoded emotional arousal: A failure to replicate.

Empathy is a well-defined active ingredient in clinical encounters. To measure empathy, the current gold standard is behavioral coding (i.e., trained coders attribute overall ratings of empathy to clinician behaviors within an encounter), which is labor intensive and subject to important reliability challenges. Recently, an alternative measurement has been proposed: capturing empathy as synchrony in vocally encoded arousal, which can be measured as the mean fundamental frequency of the voice (mean F0). This method has received preliminary support by one study (Imel, Barco, et al., 2014). We aimed to replicate this study by using 2 large samples of clinical interactions (alcohol brief motivational interventions with young adults, N = 208; general practice consultations, N = 204). Audio files were segmented to identify respective speakers and mean F0 was measured using speech signal processing software. All sessions were independently rated by behavioral coders using 2 validated empathy scales. Synchrony between clinician and patient F0 was analyzed using multivariate multilevel models and compared with high and low levels of empathy derived from behavioral coding. Findings showed no support for our hypothesis that mean F0 synchrony between clinicians and patients would be higher in high-empathy sessions. This lack of replication was consistent for both clinical samples, both behavioral coding instruments, and using measures of F0 synchrony occurring at both the session-level and minute-level. We considered differences in culture and language, patients' characteristics, and setting as explanations for this failure to replicate. Further replication testing and new developments regarding measurement methods and modeling are needed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Effects of Initiating Abstinence from Alcohol on Daily Craving and Negative Affect: Results from a Pharmacotherapy Clinical Trial.

BACKGROUND: Craving and negative affect are distressing and commonly experienced during alcohol use disorder (AUD) treatment. Patients may assume that initiating abstinence will intensify their cravings and negative affect despite limited empirical data to support this assumption. This study extends and replicates, under improved methodological conditions, previous work that found reductions in daily craving associated with initiating abstinence. METHODS: Seventy-eight adults (80.8% male, 57.1% Caucasian) in a clinical trial testing prazosin for AUD provided daily reports of drinking, craving, and negative affect for up to 12 weeks (mean = 64.77 daily reports). Participants were classified into 3 subgroups based on whether and when they initiated 14 days of continuous abstinence, including (i) "abstinence initiators" who quit drinking during treatment (n = 17), (ii) "already abstainers" who were abstinent at the start of treatment (n = 20), and (iii) "continued drinkers" who never initiated abstinence (n = 41). The timing and degree of change in craving and negative affect were compared across these groups using multivariate growth curve modeling. RESULTS: All participant subgroups reported gradual reductions in craving over the course of treatment, with "abstinence initiators" reporting additional sudden reductions in craving upon initiating abstinence from alcohol. "Continued drinkers" reported higher levels of craving than "already abstainers" throughout the full course of treatment. Negative affect followed a different pattern of change, with "abstinence initiators" experiencing gradual reductions in negative affect after initiating abstinence but no changes prior to or immediately upon initiating abstinence, and with "already abstainers" and "continued drinkers" experiencing no changes in negative affect over time. CONCLUSIONS: Initiating abstinence is associated with immediate reductions in craving, followed by gradual reductions in both craving and negative affect. Results provide insight into the timing and magnitude of changes in theoretically and clinically important variables and may help patients anticipate when to expect improvement in craving and negative effect.

Drinking Risk Level Reductions Associated with Improvements in Physical Health and Quality of Life Among Individuals with Alcohol Use Disorder.

BACKGROUND: Abstinence and no heavy drinking days are currently the only Food and Drug Administration-approved end points in clinical trials for alcohol use disorder (AUD). Many individuals who fail to meet these criteria may substantially reduce their drinking during treatment, and most individuals with AUD prefer drinking reduction goals. One- and two-level reductions in World Health Organization (WHO) drinking risk levels have been proposed as alternative end points that reflect reduced drinking and are associated with reductions in drinking consequences, improvements in mental health, and reduced risk of developing alcohol dependence. The current study examined the association between WHO drinking risk level reductions and improvements in physical health and quality of life in a sample of individuals with alcohol dependence. METHODS: Secondary data analysis of individuals with alcohol dependence (n = 1,142) enrolled in the longitudinal, prospective COMBINE study, a multi site randomized placebo-controlled clinical trial, examining the association between reductions in WHO drinking risk levels and change in blood pressure, liver enzyme levels, and self-reported quality of life following treatment for alcohol dependence. RESULTS: One- and two-level reductions in WHO drinking risk level during treatment were associated with significant reductions in systolic blood pressure (p < 0.001), improvements in liver enzyme levels (all p < 0.01), and significantly better quality of life (p < 0.001). CONCLUSIONS: One- and two-level reductions in WHO drinking risk levels predicted significant improvements in markers of physical health and quality of life, suggesting that the WHO drinking risk level reduction could be a meaningful surrogate marker of improvements in how a person "feels and functions" following treatment for alcohol dependence. The WHO drinking risk levels could be useful in medical practice for identifying drinking reduction targets that correspond with clinically significant improvements in health and quality of life.

Clinical Validation of Reduced Alcohol Consumption After Treatment for Alcohol Dependence Using the World Health Organization Risk Drinking Levels.

BACKGROUND: Alcohol use disorder (AUD) is a highly prevalent public health problem associated with considerable individual and societal costs. Abstinence from alcohol is the most widely accepted target of treatment for AUD, but it severely limits treatment options and could deter individuals who prefer to reduce their drinking from seeking treatment. Clinical validation of reduced alcohol consumption as the primary outcome of alcohol clinical trials is critical for expanding treatment options. One potentially useful measure of alcohol treatment outcome is a reduction in the World Health Organization (WHO, International Guide for Monitoring Alcohol Consumption and Related Harm. Geneva, Switzerland, 2000) risk levels of alcohol use (very high risk, high risk, moderate risk, and low risk). For example, a 2-shift reduction in WHO risk levels (e.g., high risk to low risk) has been used by the European Medicines Agency (2010, Guideline on the Development of Medicinal Products for the Treatment of Alcohol Dependence. UK) to evaluate nalmefene as a treatment for alcohol dependence (AD; Mann et al. 2013, Biol Psychiatry 73, 706-13). METHODS: The current study was a secondary data analysis of the COMBINE study (n = 1,383; Anton et al., ) to examine the association between reductions in WHO risk levels and reductions in alcohol-related consequences and mental health symptoms during and following treatment in patients with AD. RESULTS: Any reduction in WHO risk drinking level during treatment was associated with significantly fewer alcohol-related consequences and improved mental health at the end of treatment and for up to 1 year posttreatment. A greater reduction in WHO risk drinking level predicted a greater reduction in consequences and greater improvements in mental health. CONCLUSIONS: Changes in WHO risk levels appear to be a valid end point for alcohol clinical trials. Based on the current findings, reductions in WHO risk drinking levels during treatment reflect meaningful reductions in alcohol-related consequences and improved functioning.

Temporal Stability of Heavy Drinking Days and Drinking Reductions Among Heavy Drinkers in the COMBINE Study.

BACKGROUND: Recently, the Food and Drug Administration (FDA) proposed to expand the options for primary end points in the development of medications for alcohol use disorder to include either abstinence from alcohol or a nonabstinent outcome: no heavy drinking days (with a heavy drinking day defined as more than 3 drinks per day for women and more than 4 drinks per day for men [>3/>4 cutoff]). The FDA also suggested that 6 months would be the most appropriate length for a clinical trial to demonstrate the stability of this nonabstinent drinking outcome. However, few alcohol clinical trials have examined the stability of nonheavy drinking during and after treatment. METHODS: In a secondary analysis of the COMBINE study data (n = 1,383), we examined transitions in heavy drinking days during the course of treatment (months 1 through 4), during the transition out of treatment (months 4 through 7), and up to 12 months afterward (months 13 through 16) using latent variable mixture models. RESULTS: Heavy drinking and nonheavy drinking were relatively stable in consecutive months (minimum agreement [kappa] = 0.64 for months 1 to 2). Most individuals were stable low-risk drinkers/abstainers or heavy drinkers by the end of treatment, as characterized by a 10% probability (or less) of transitioning out of either a no heavy drinking state or a heavy drinking state. More than two-thirds of the heavy drinkers who exceeded the heavy drinking threshold during treatment reported, on average, a 64% reduction in drinking frequency and a 38% reduction in drinking intensity from pretreatment drinking levels. CONCLUSIONS: The results show stability of no heavy drinking as an outcome within the first 4 months of treatment and that the >3/>4 drink cutoff may mask substantial reductions in alcohol consumption among some patients. Future studies should explore the clinical utility of reduction end points.

Digital technology and clinical decision making in depression treatment: Current findings and future opportunities.

Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains.

Do Alcohol Relapse Episodes During Treatment Predict Long-Term Outcomes? Investigating the Validity of Existing Definitions of Alcohol Use Disorder Relapse.

BACKGROUND: The construct of relapse is used widely in clinical research and practice of alcohol use disorder (AUD) treatment. The purpose of this study was to test the predictive validity of commonly appearing definitions of AUD relapse in the empirical literature. METHODS: Secondary analyses of data from Project MATCH and COMBINE were conducted using 7 definitions of "relapse" based on drinking quantity within a single drinking episode: any drinking; at least 4/5 drinks for women/men; at least 4.3/7.1 drinks for women/men; at least 6/7 drinks for women/men; at least 6 drinks; at least 7/9 drinks for women/men; and at least 8/10 drinks for women/men. Relapse was used to predict alcohol consumption, related consequences, and nonconsumption outcomes (quality of life, psychosocial functioning) at the end of treatment and up to 1 year posttreatment. RESULTS: Regression analyses indicated within-treatment relapse definitions significantly predicted end-of-treatment alcohol consumption and alcohol-related consequences. Heavy drinking definitions were generally more predictive than the any drinking definition, but no single heavy drinking definition was consistently a better predictor of outcomes. Relapse definitions were less predictive of longer-term alcohol-related outcomes and both shorter- and longer-term nonconsumption outcomes, including health and psychosocial functioning. CONCLUSIONS: One particular definition of relapse did not consistently stand out as the best predictor. Advances in AUD research may require reconceptualization of relapse as a multifaceted dynamic process and may consider a wider range of relevant behaviors (e.g., health and psychosocial functioning) when examining the change process in individuals with AUD.

Missing Data in Alcohol Clinical Trials with Binary Outcomes.

BACKGROUND: Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study. METHODS: We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. RESULTS: WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. CONCLUSIONS: Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes.