MEASURE DEVELOPMENT OF AN ASSESSMENT OF \u27HITTING BOTTOM\u27 FOR INDIVIDUALS WITH ALCOHOL PROBLEMS

Alcohol problems are a serious public health concern but few individuals with alcohol problems and alcohol use disorders (AUDs) ever receive formal treatment (SAMHSA, 2009). To understand and address this phenomenon, it is important to understand why individuals decide to seek treatment, which may help clinicians facilitate treatment entry and completion among individuals with AUDs. Research on reasons individuals cite for seeking treatment and their success in recovering from AUDs suggests that hitting bottom\u27 may be important (e.g., Sobell, Sobell, Toneatto, & Leo, 1993). Accordingly, evaluating the concept of \u27hitting bottom\u27 may provide insight into why individuals seek and complete treatment; however, \u27hitting bottom\u27 has never been operationally defined. Consequently, the goal of this multi-phase study was to address this gap in the field by developing a measure of \u27hitting bottom. Literature review and both qualitative and quantitative data analyses informed the development of a preliminary measure of \u27hitting bottom. Feedback about the measure was obtained from experts in the field (N = 9; 11% Female). The final, 114 item measure, called the Noteworthy Aspects of Drinking Important to Recovery (NADIR) measure, was administered via web-based survey to individuals self-identified as moderate to heavy drinkers across the United States (N = 402; 46.6% Female, 24.6% Hispanic, average Alcohol Use Disorders Identification Test (AUDIT) 16.3 (SD = 8.3)). Exploratory factor analyses, item response theory, and confirmatory factor analyses were performed to analyze the factor structure of the NADIR. The final confirmatory factor model of the NADIR measure included 60 of the original 114 items, provided an adequate fit to the data, and consisted of four domain specific factors (social network, health problems, situational and environmental circumstances, and existential issues domains) and two higher order factors (cognitive appraisal and importance/influence). The factors of the NADIR measure showed concurrent validity with measures of drinking quantity and frequency, as well as drinking consequences and the AUDIT. Future research should empirically evaluate the predictive validity of the NADIR and identify if and for whom \u27hitting bottom,\u27 as measured by the NADIR, may be important for facilitating treatment entry or self-change

EXPLORING CLINICALLY USEFUL DEFINITIONS OF TREATMENT SUCCESS FOR INDIVIDUALS WITH ALCOHOL USE DISORDER

Given the widespread costs associated with alcohol use disorder (AUD; World Health Organization, 2011), it is unsurprising that many treatments exist for AUD. Moreover, many treatments have been rigorously studied via experimental research designs. In such research, treatment success has been defined predominantly as abstinence from alcohol or, more recently, no heavy drinking days. Consumption-based definitions of treatment success, rather than alternative non-consumption based definitions, have dominated in the field for at least two reasons. First, there are multiple measures of similar non-consumption constructs (e.g., quality of life, psychosocial functioning), and very little research has been conducted to direct researchers toward the best non-consumption measures to use among AUD populations. Second, it is assumed that non-consumption measures are insensitive and, therefore, consumption must be used as a surrogate measure for more clinically meaningful non-consumption measures. The present research study empirically addressed these two barriers that have thwarted attempts to shift toward including non-consumption variables in our definitions of treatment success. Using secondary data analysis of data collected from the COMBINE Study (Anton et al., 2006) and Project MATCH (Project MATCH Research Group, 1997), the present study conducted several tests of measurement stability, reliability, validity, sensitivity, and specificity. To test measurement stability the current study examined effect sizes and measurement invariance across time to test if non-consumption measures may be viable options for comparing pre- and post-treatment scores on these measures. The present study also conducted analyses on psychometric properties of extant measures: internal consistency reliability, construct validity, convergent validity. Finally, receiver operating characteristic curve analyses were conducted of total scale scores, subscales, and individual items when available and appropriate to test the sensitivity and specificity of non-consumption measures in detecting post-treatment and 12-month outcomes. The Brief Symptom Inventory (BSI), Beck Depression Inventory (BDI), and the brief World Health Organization Quality of Life measure (WHOQOL-BREF) were invariant across time and performed the best overall across all psychometric and sensitivity/specificity analyses conducted in the present manuscript. All other measures examined in the current study had at least some promising results, with the sole exception of the Addiction Severity Index (ASI), which had weak findings across all analyses. Moreover, some non-consumption measures (e.g., Drinker Inventory of Consequences, Obsessive-Compulsive Drinking Scale) had baseline to post-treatment effect sizes as large as some consumption-based outcome effect sizes. The results of the present study have identified gold standard measures for assessing mental health and quality of life. Future research should use the BSI, BDI, and WHOQOL-BREF to examine clinically-relevant changes beyond consumption outcomes. The present findings also indicate that consumption measures may not be needed to serve as surrogates for these clinically relevant constructs. These findings represent the possibility of a paradigm shift in the field of AUD treatment research evaluation to incorporate non-consumption outcomes

Association between physical pain and alcohol treatment outcomes: The mediating role of negative affect

OBJECTIVE: Physical pain and negative affect have been described as risk factors for alcohol use following alcohol treatment. The current study was a secondary analysis of two clinical trials for alcohol use disorder (AUD) to examine the associations between pain, negative affect and AUD treatment outcomes. METHOD: Participants included 1383 individuals from the COMBINE Study (COMBINE Study Group, 2003; 31% female, 23% ethnic minorities, average age=44.4 (SD=10.2)), a multisite combination pharmacotherapy and behavioral intervention study for AUD in the United States, and 742 individuals from the United Kingdom Alcohol Treatment Trial (UKATT Research Team, 2001; 25.9% female, 4.4% ethnic minorities, average age=41.6 (SD=10.1)) a multisite behavioral intervention study for AUD in the United Kingdom. The Form-90 was used to collect alcohol use data, the Short Form Health Survey and Quality of Life measures were used to assess pain, and negative affect was assessed using the Brief Symptom Inventory (COMBINE) and the General Health Questionnaire (UKATT). RESULTS: Pain scores were significantly associated with drinking outcomes in both datasets. Greater pain scores were associated with greater negative affect and increases in pain were associated with increases in negative affect. Negative affect significantly mediated the association between pain and drinking outcomes and this effect was moderated by social behavior network therapy (SBNT) in the UKATT study, with SBNT attenuating the association between pain and drinking. CONCLUSION: Findings suggest pain and negative affect are associated among individuals in AUD treatment and that negative affect mediated pain may be a risk factor for alcohol relapse

Citation

Association between physical pain and alcohol treatment outcomes: The mediating role of negative affect. Journal of Consulting and Clinical Psychology, 83 (6)

Pain as a predictor of heavy drinking and any drinking lapses in the COMBINE study and the UK Alcohol Treatment Trial

Aims: To test the association between pain and heavy drinking lapses during and following treatment for alcohol use disorders (AUD). Design: Secondary data analysis of data from two clinical trials for AUD. Setting and participants: Participants included 1383 individuals from the Combined Pharmacotherapies and Behavioral Interventions (COMBINE) Study in the United States [69.0% male, 76.8% non-Hispanic White average age=44.4, standard deviation (SD)=10.2] and 742 individuals from the UK Alcohol Treatment Trial (UKATT) in the United Kingdom [74.1% male, 95.6% White, average age=41.6 (SD=10.1)]. Measurements: Form-90 (a structured assessment interview) was used to assess the primary outcome: time to first heavy drinking day. The Short Form Health Survey and Quality of Life measures were used to assess pain interference and pain intensity. Findings: Pain was a significant predictor of heavy drinking lapses during treatment in UKATT [odds ratio (OR)=1.19, 95% confidence interval (CI)=1.08, 1.32, P=0.0003] and COMBINE (OR=1.12, 95% CI=1.03, 1.21, P=0.009), and was a significant predictor of heavy drinking lapses following treatment in COMBINE (OR=1.163, 95% CI=1.15, 1.17, P&lt;0.00001). After controlling for other relapse risk factors (e.g. dependence severity, self-efficacy, temptation, psychiatric distress), pain remained a significant predictor of heavy drinking lapses during treatment in UKATT (OR=1.19, 95% CI=1.06, 1.34, P=0.004) and following treatment in COMBINE (OR=1.44, 95% CI=1.07, 1.92, P=0.01). Conclusions: Among people treated for alcohol use disorder, being in physical pain appears to predict heavy drinking lapses during or after treatment.</p

How Much Is Too Much? Patterns of Drinking During Alcohol Treatment and Associations With Post-Treatment Outcomes Across Three Alcohol Clinical Trials

Objective: This secondary data analysis examined patterns of drinking during alcohol treatment and associated drinking outcomes during the first year following treatment. The goal was to provide clinicians with guidance on which patients may be most at risk for negative long-term outcomes based on drinking patterns during treatment. Method: This study was an analysis of existing data (N = 3,851) from three randomized clinical trials for alcohol use disorder: the COMBINE Study (n = 1,383), Project MATCH (n = 1,726), and the United Kingdom Alcohol Treatment Trial (n = 742). Indicators of abstinence, non-heavy drinking, and heavy drinking (defined as 4/5 or more drinks per day for women/men) were examined during each week of treatment using repeated-measures latent class analysis. Associations between drinking patterns during treatment and drinking intensity, drinking consequences, and physical and mental health 12 months following intake were examined. Results: Seven drinking patterns were identified. Patients who engaged in persistent heavy drinking throughout treatment and those who returned to persistent heavy drinking during treatment had the worst long-term outcomes. Patients who engaged in some heavy drinking during treatment had better long-term outcomes than persistent heavy drinkers. Patients who reported low-risk drinking or abstinence had the best long-term outcomes. There were no differences in outcomes between low-risk drinkers and abstainers. Conclusions: Abstinence, low-risk drinking, or even some heavy drinking during treatment are associated with the best long-term outcomes. Patients who are engaging in persistent heavy drinking are likely to have the worst outcomes and may require a higher level of care