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.
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.
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.
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.
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.BACKGROUNDPrimary 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.To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA).OBJECTIVETo test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA).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.DESIGNObservational 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.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.PATIENTSElectronic 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.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).MAIN MEASUREThe 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).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.KEY RESULTSAmong 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.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.CONCLUSIONSThe 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.
•Cravings were positively associated with probability of cannabis use.•EMA measurements of craving were uniquely associated with probability of use.•EMA measurement of craving may be useful for ...clinicians and researchers.
Rates of problematic cannabis use have nearly doubled over the last decade, and peak onset for cannabis use disorders occurs during young adulthood. Craving for cannabis is hypothesized to be an important factor that maintains cannabis use among people who desire to stop or reduce their use, including many young adults. Previous studies that used single timepoint assessment methods to demonstrate a link between craving and cannabis use have found mixed predictive utility of measurements. The impermanent, or time-varying nature of craving may be responsible for mixed findings, leading to inaccuracies in retrospective recall and greater difficulty measuring craving and detecting its association with cannabis use. The current study compared intensive longitudinal assessments and single timepoint assessments predicting cannabis use among young adults with problematic cannabis use who reported a desire to reduce their use. Participants (N = 80) completed a baseline craving questionnaire and intensive longitudinal assessments of momentary craving and cannabis use up to four times per day for 14 days. Results suggested that averaged momentary craving predicted cannabis use above-and-beyond craving measured at baseline. An increase of one SD above the sample-mean for averaged momentary craving increased the probability of cannabis use by 367 %, while a one SD increase in baseline craving was only associated with a 49 % increase. Findings suggest that asking young adults who want to cut back on their cannabis use about their craving at a single timepoint may not be as clinically useful as tracking cravings repeatedly in near real-time and in ecologically valid contexts.
Objective: In a randomized trial for women with alcohol use disorders (AUD), the efficacy of Female-Specific Cognitive Behavioral Therapy (FS-CBT) was compared with Gender-Neutral CBT (GN-CBT; ...Epstein et al., 2018). The current study examined whether putative mechanisms of change differed between treatment conditions, using a novel statistical approach. Both treatments were hypothesized to work by increasing use of alcohol-related coping skills (coping) and confidence to abstain from drinking (confidence), but FS-CBT additionally targeted female-salient mechanisms: anxiety, depression, sociotropy (i.e., overinvestment in others' opinion of oneself), autonomy, and social networks supportive of abstinence. Method: Ninety-nine women with AUD (55 in GN-CBT, 44 in FS-CBT) completed self-report assessments at baseline and 0, 6, and 12 months posttreatment. Multilevel vector autoregression estimation was used to analyze associations between putative mechanisms of change, and network models of those associations were generated using network analysis. Results: Across conditions, higher confidence and coping were directly associated with less drinking; autonomy was directly and indirectly associated with drinking. Additionally, network analysis indicated that although variation in depression was associated with change in other variables specifically for GN-CBT, sociotropy was associated with change specifically in FS-CBT. Conclusions: Women receiving CBT-AUD changed their drinking through increased confidence to abstain and greater use of coping skills. Autonomy played a central role in behavior change across treatment conditions. Participants receiving treatment tailored to women also changed through decreases in sociotropy and increases in social support for abstinence. For women who received standard CBT, changes in depression were important to clinical improvement.
What is the public health significance of this article?
This study examined the mechanisms that lead to behavior change among women receiving female-specific and gender-neutral cognitive-behavioral therapy for alcohol use disorder (AUD), using a novel statistical approach. Results support and extend previous research findings by (a) demonstrating that increasing a woman's self-confidence to avoid drinking and increasing her use of alcohol-related coping skills is central to change in AUD treatment, (b) demonstrating the importance of personal autonomy as an additional mechanism of change in treating women's AUD, and (c) showing that the two treatment conditions led to improvements via both overlapping and divergent mechanisms.
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.
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.
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.
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.
Substance use disorders (SUDs) are underdiagnosed in healthcare settings. The Substance Use Symptom Checklist (SUSC) is a practical, patient-report questionnaire that has been used to assess SUD ...symptoms based on Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria. This study evaluates the test-retest reliability of SUSCs completed in primary and mental health care settings.
We identified 1194 patients who completed two SUSCs 1–21 days apart as part of routine care after reporting daily cannabis use and/or any past-year other drug use on behavioral health screens. Test-retest reliability of SUSC scores was evaluated within the full sample, subsamples who completed both checklists in primary care (n=451) or mental health clinics (n=512) where SUSC implementation differed, and subgroups defined by sex, insurance status, age, and substance use reported on behavioral health screens.
In the full sample, test-retest reliability was high for indices reflecting the number of SUD symptoms endorsed (ICC=0.75, 95% CI:0.72–0.77) and DSM-5 SUD severity (kappa=0.72, 95% CI:0.69–0.75). These reliability estimates were higher in primary care (ICC=0.81, 95% CI:0.77–0.84; kappa=0.79, 95% CI:0.75–0.82, respectively) than in mental health clinics (ICC=0.74, 95% CI:0.70–0.78; kappa=0.73, 95% CI:0.68–0.77). Reliability differed by age and substance use reported on behavioral health screens, but not by sex or insurance status.
The SUSC has good-to-excellent test-retest reliability when completed as part of routine primary or mental health care. Symptom checklists can reliably measure symptoms consistent with DSM-5 SUD criteria, which may aid SUD-related care in primary care and mental health settings.
•1194 patients reported DSM-5 SUD symptoms on Substance Use Symptom Checklists (SUSCs).•SUSCs had high test-retest reliability across settings and demographic subgroups.•Reliability was higher in primary care, where assessment processes were standardized.•SUSCs provide test-retest reliable information about symptoms consistent with DSM-5 SUD.
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.
At least 1‐ and 2‐level reductions in the World Health Organization (WHO) drinking risk levels by the end of treatment were associated with significant improvements at the end of treatment for physical health and quality of life outcomes. The WHO drinking risk level reductions capture considerable improvement in how patients feel and function in alcohol clinical trials.
•OUD treatment engagement and outcomes measures are quantified in a tribal community.•Clients in the tribal community being treated for OUD received MOUD at high rates.•The Cascade of Care may ...highlight where service delivery changes are needed.•Modifying the Cascade of Care may identify relevant cultural information for tribes.
American Indian communities in Minnesota have been disproportionately impacted by the opioid use disorder (OUD) epidemic, which tribal communities have taken numerous steps to address. The Cascade of Care is a public health framework for measuring population-level OUD risk, treatment engagement, treatment retention, and recovery outcomes, which can help communities monitor the impact of responses to the OUD epidemic and identify where treatment- and recovery-related barriers and facilitators may exist. However, no studies have quantified the Cascade of Care stages within tribal communities and the extent to which these stages can be quantified using existing data sources is unknown. We utilized data from the Minnesota Drug and Alcohol Abuse Normative Evaluation System (DAANES) to quantify OUD Cascade of Care stages for an American Indian tribal nation in Minnesota and for the entire state. DAANES data indicated 269 individuals in the tribal community received treatment for opioid-related problems in 2018. Among them, an estimated 65–99 % initiated medications for OUD and an estimated 13–41 % were retained in treatment for at least 180 days. Existing state-level data can provide information about Cascade of Care stages for American Indian communities, particularly with regard to treatment admission, initiation of medications for OUD, and treatment retention. Additional data sources are needed to measure population-level OUD risk, recovery, and cultural and contextual factors that may impact treatment and recovery.
Interest in studying mechanisms of behavior change (MOBCs) in substance use disorder (SUD) treatments has grown considerably in the past two decades. Much of this work has focused on identifying ...which variables statistically mediate the effect of SUD treatments on clinical outcomes. However, a fuller conceptualization of MOBCs will require greater understanding of questions that extend beyond traditional mediation analysis, including better understanding of when MOBCs change during treatment, when they are most critical to aiding the initiation or maintenance of change, and how MOBCs themselves arise as a function of treatment processes.
In the present study, we review why these MOBC-related questions are often minimally addressed in empirical research and provide examples of data analytic methods that may address these issues. We highlight several recent studies that have used such methods and discuss how these methods can provide unique theoretical insights and actionable clinical information.
Several statistical approaches can enhance the field's understanding of the timing and development of MOBCs, including growth-curve modeling, time-varying effect modeling, moderated mediation analysis, dynamic systems modeling, and simulation methods.
Adopting greater diversity in methods for modeling MOBCs will help researchers better understand the timing and development of key change variables and will expand the theoretical precision and clinical impact of MOBC research. Advances in research design, measurement, and technology are key to supporting these advances.
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