Barbara S. McCrady

About 70% of parents involved with the child protection system experience serious substance use problems (SAMHSA., 2015). These problems are commonly accompanied by health, mental health, and socia...

A standard component of service delivery in alcohol treatment clinics is evidence-based assessment (EBA). Although EBA is essential for selecting appropriate treatment modalities for alcohol use and associated problems, there are limitations in existing EBAs concerning evidence of cultural equivalence and utility among individuals seeking alcohol treatment. However, training in EBA, addictions, and clinical applications with diverse populations all are gaps in clinical training in doctoral programs in clinical psychology. The present work used the clinical science model to review the psychometric properties, cross-cultural utility, and measurement invariance of measures in an assessment battery used in an alcohol treatment training clinic. This article describes the results of that review, recommendations for retaining or replacing common assessment measures used in alcohol treatment clinics, and recommendations for alcohol treatment clinics interested in engaging in similar processes. Findings suggested that more research is needed to evaluate the psychometric properties of EBAs utilized in an alcohol treatment assessment battery, particularly among American Indian and Alaska Native people, and to test measurement invariance across race/ethnicity and other identity groups in alcohol treatment-seeking populations. Overall, routine reviews of cultural relevance are needed in clinical settings to stay current with the emerging literature. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Objective: Involving family members in a patient's treatment for alcohol use disorder (AUD) leads to more positive outcomes, but evidence-based family-involved treatments have not been adopted widely in AUD treatment programs. Study aims the following: (a) modify an empirically supported 12-session AUD treatment, alcohol behavioral couple therapy (ABCT) to make it shorter and appropriate for any concerned family member and (b) conduct a small clinical trial to obtain feasibility data and effect size estimates of treatment efficacy. Method: ABCT content was adapted to three-sessions following input from clinicians, patients, and family members. Patient and family member dyads were recruited from an inpatient treatment program and randomized to the new treatment, brief family-involved treatment (B-FIT), or treatment-as-usual (TAU). Drinking was assessed using the Form-90; family support and family functioning were assessed using the Family Environment Scale Conflict and Cohesion subscales and the Family Adaptability and Cohesion Evaluation Scale-IV, Communication scale. Dyads (n = 35) were assessed at baseline and 4-month follow-up. Results: On average, dyads received one of three B-FIT sessions with 6 dyads receiving no sessions due to scheduling conflicts or patient discharge. At follow-up, there was a large-to-medium effect size estimate favoring B-FIT for proportion drinking days (patient report, n = 22; Hedges' g = 1.01; patient or family report, n = 28; Hedges' g = .48). Results for family support or family functioning measures favored TAU. Conclusions: Implementation of brief family-involved treatment in inpatient AUD treatment was challenging, but preliminary data suggest the potential value of B-FIT in impacting drinking outcomes.

Clients who receive alcohol use disorder (AUD) treatment experience variable outcomes. Measuring clinical progress during treatment using standardized measures (i.e., measurement-based care) can help indicate whether clinical improvements are occurring. Measures of mechanisms of behavioral change (MOBCs) may be particularly well-suited for measurement-based care; however, measuring MOBCs would be more feasible and informative if measures were briefer and if their ability to detect reliable change with individual clients was better articulated. Three abbreviated measures of hypothesized MOBCs (abstinence self-efficacy, coping strategies, anxiety) and a fourth full-length measure (depression) were administered weekly during a 12-week randomized trial of cognitive-behavioral therapy (CBT) for women with AUD. Psychometric analyses estimated how reliably each measure distinguished within-person change from between-person differences and measurement error. Reliability coefficients were estimated for simulated briefer versions of each instrument (i.e., instruments with fewer items than the already-abbreviated instruments) and rates of reliable improvement and reliable worsening were estimated for each measure. All four measures had good reliability (.86-.90) for detecting within-person change. Many participants (41.4%-62.5%) reliably improved on MOBCs from first to last treatment session. Reliable improvement on MOBCs was associated with reductions in percentage of drinking days (PDD) at 3, 9, and 15-month follow-ups. Simulated briefer versions of each instrument retained good reliability for detecting change with only 3 (self-efficacy), 11 (coping strategies), 5 (anxiety), or 10 items (depression). Brief MOBC measures can detect reliable change for individuals in AUD treatment. Routinely measuring MOBCs may help with monitoring clinical progress. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Objective: Adolescents' drinking is influenced by their friends' drinking. However, it is unclear whether individually-targeted alcohol interventions reduce drinking in the friends of individuals who receive the intervention. This study used simulations of drinking in simulated longitudinal social networks to test whether individually-targeted alcohol interventions may be expected to spread to non-targeted individuals. Method: Stochastic actor-based models simulated longitudinal social networks where changes in drinking and friendships were modeled using parameters from a meta-analysis of high school 10th grade social networks. Social influence (i.e., how much one's friends' drinking affects their own drinking) and social selection (i.e., how much one's drinking affects who they select as friends) were manipulated at several levels. At the midpoint of each simulation, a randomly-selected heavy-drinking individual was experimentally assigned to an intervention (changing their drinking status to non-drinking) or a control condition (no change in drinking status) and the drinking statuses of that individual's friends were recorded at the end of the simulation. Results: Friends of individuals who received the intervention significantly reduced their drinking, with higher reductions occurring in networks with greater social influence. However, all effect sizes were small (e.g., average per-friend reduction of.07 on a 5-point drinking scale). Conclusions: Individually-targeted alcohol interventions may have small effects on reducing the drinking of non-targeted adolescents, with social influence being a mechanism that drives such effects. Due to small effect sizes, many adolescents may need to receive alcohol interventions to produce measurable effects on drinking outcomes for non-targeted individuals. Public Health Significance This study illustrates the potential for alcohol interventions to have "contagion" effects, where exposing an individual to an alcohol intervention may reduce their friends' drinking, despite those friends not directly receiving the intervention themselves. Although treatment contagion effects in computer simulations of social networks were generally small on a per-person basis, they may still reflect a significant public health benefit due to the large number of individuals who may be reached within friendship social networks.

Research shows fluctuations in drinking across the menstrual cycle among women with alcohol use disorder (AUD), but little work has investigated moderators of these fluctuations. This study examined drinking and craving intensity across the menstrual cycle, and the moderating effect of baseline depression and emotional distress during the midlate luteal phase and/or menses, among women receiving AUD treatment. Fifty-nine regularly cycling women reported menstrual history and baseline depression. Over 3 months of treatment, they kept daily logs of drinks, alcohol cravings, and menstruation (yes/no). Emotional distress during the midlate luteal phase and/or menses of their most recent menstrual cycle was also assessed during treatment. Menstrual cycle phase was estimated for each within-treatment day. Mixed model analyses tested main and interactive effects of menstrual cycle phase, baseline depression, and emotional distress during the midlate luteal phase and/or menses on daily drinks and craving intensity. Women drank most during the midlate luteal phase and menses compared with other phases. Among women with lower baseline depression, those with lower distress during the midlate luteal phase and/or menses reported more intense cravings during the midlate luteal phase (ΔM = .77, p = .000) and menses (ΔM = .51, p = .012); those with higher distress reported more intense cravings during menses, compared with all other phases (p < .01). Among women with higher baseline depression, craving intensity remained consistently high. Results document more drinking during the midlate luteal phase and menses and suggest that cycle-related distress and depression moderate the alcohol-menstrual association among women in AUD treatment. (PsycInfo Database Record (c) 2020 APA, all rights reserved).