A Randomized Trial of Personalized Cognitive-Behavior Therapy for Alcohol Use Disorder in a Public Health Clinic - Coates, Jason M.; Gullo, Matthew J.; Feeney, Gerald F. X.; Young, Ross M.; Connor, Jason P. (Frontiers in Psychiatry, 2018)
Background: Tailored psychological interventions based on individual risk factors are likely to improve treatment for Alcohol Use Disorders (AUDs). Key risk factors for poor treatment outcome include alcohol craving, positive expectations of alcohol consumption, and impulsivity. Design: Pragmatic randomised Cognitive-Behavioural Treatment (CBT) trial. Setting: Public hospital alcohol and drug clinic. Participants: Three-hundred seventy-nine patients (65% male; Ageyears M = 44.32, SD = 10.75)) seeking treatment for AUD. Procedure: Patients were randomly allocated into treatment as usual (TAU) or targeted treatment. Patients in targeted treatment were allocated one of three treatment modules focusing on craving, positive expectancy, or impulsivity based on assessment results. Treatment included eight, one hour, sessions of CBT over 12 weeks delivered by clinical psychologists. Hypotheses: Targeted treatment was expected to have fewer drinking days and consume less alcohol during the treatment period than TAU. Improvement in targeted mechanisms was predicted to be greatest for patients within matched conditions. Results: Patients attended an average of 4.4 sessions with 93 (25%) completing the whole 12-week treatment blockepisode. The mean proportion of drinking days between sessions was 5% with an average consumption of 64 grams of ethanol. No significant effect of targeted treatment was identified on drinking days or consumption. The craving (b = -18.97, 95%CI = -31.44, -6.51) and impulsivity (b = -26.65, 95% CI = -42.09, -11.22) modules demonstrated significant reductions in their targeted constructs over treatment, above TAU. Only reduction in craving was associated with reduced drinking days (exp(b) = 0.958, p = 0.003) and alcohol consumption (exp(b) = 0.962, p = 0.02). Significant indirect effects for the targeted craving module through craving reduction were identified for reduction in drinking days (β = -0.72, 95% CI = -1.50, -0.158) and alcohol consumption (β = -0.78, 95%CI = -1.72, -0.11). Conclusions: In the context of a public health service, the effectiveness of individualised treatment targeting risk mechanisms identified during pre-treatment assessment was not confirmed. Some evidence was found for improved treatment response to the implementation of a manualised craving module when pre-treatment craving was high.