BACKGROUND: Computerized cognitive bias modification (CBM) programs have generated promising results regarding the treatment of alcohol dependence and anxiety disorders. However, there is hardly any research yet on the implementation of alcohol-CBM into clinical practice. This article addresses the question of the optimal number of training sessions for a specific form of CBM: approach bias re-training in alcohol-dependent patients. METHODS: Participants were 111 alcohol-dependent patients of an inpatient rehabilitation clinic. In addition to treatment as usual, they took part in a 12-session CBM protocol, aimed at re-training alcohol approach tendencies, with an adapted Alcohol Approach-Avoidance Task. Learning curves and 2-level fitted mean trends were analyzed. Furthermore, parameters of the fitted mean trend and information on the most effective number of training sessions were used to predict 1-year follow-up data. RESULTS: Two-level analyses revealed 6 training sessions to be the mean optimum, yet many patients improve further after that. Prediction of the individual optimum (speed of response) and parameters of the fitted mean trends failed. The linear term of the graph describing the mean trend of training effects, but not the speed of response, predicted 1-year follow-up data. CONCLUSIONS: Suggestions for practical implementations of CBM are discussed.
BACKGROUND: Computerized cognitive bias modification (CBM) programs have generated promising results regarding the treatment of alcohol dependence and anxiety disorders. However, there is hardly any research yet on the implementation of alcohol-CBM into clinical practice. This article addresses the question of the optimal number of training sessions for a specific form of CBM: approach bias re-training in alcohol-dependent patients. METHODS:Participants were 111 alcohol-dependent patients of an inpatient rehabilitation clinic. In addition to treatment as usual, they took part in a 12-session CBM protocol, aimed at re-training alcohol approach tendencies, with an adapted Alcohol Approach-Avoidance Task. Learning curves and 2-level fitted mean trends were analyzed. Furthermore, parameters of the fitted mean trend and information on the most effective number of training sessions were used to predict 1-year follow-up data. RESULTS: Two-level analyses revealed 6 training sessions to be the mean optimum, yet many patients improve further after that. Prediction of the individual optimum (speed of response) and parameters of the fitted mean trends failed. The linear term of the graph describing the mean trend of training effects, but not the speed of response, predicted 1-year follow-up data. CONCLUSIONS: Suggestions for practical implementations of CBM are discussed.
Authors: Hollis C Karoly; Joseph P Schacht; Joanna Jacobus; Lindsay R Meredith; Charles T Taylor; Susan F Tapert; Kevin M Gray; Lindsay M Squeglia Journal: Drug Alcohol Depend Date: 2019-05-14 Impact factor: 4.492
Authors: Joanna Jacobus; Charles T Taylor; Kevin M Gray; Lindsay R Meredith; Anna M Porter; Irene Li; Norma Castro; Lindsay M Squeglia Journal: Drug Alcohol Depend Date: 2018-04-11 Impact factor: 4.492
Authors: Eric D Claus; Stefan D Klimaj; Roberta Chavez; Amber D Martinez; Vincent P Clark Journal: Alcohol Clin Exp Res Date: 2019-05-31 Impact factor: 3.455
Authors: Jeanelle Portelli; Corinde E Wiers; Xiaobai Li; Sara L Deschaine; Gray R McDiarmid; Felix Bermpohl; Lorenzo Leggio Journal: Drug Alcohol Depend Date: 2019-09-11 Impact factor: 4.492
Authors: Simon E Blackwell; Michael Browning; Andrew Mathews; Arnaud Pictet; James Welch; Jim Davies; Peter Watson; John R Geddes; Emily A Holmes Journal: Clin Psychol Sci Date: 2015-01
Authors: Katrina Prior; Elske Salemink; Reinout W Wiers; Bethany A Teachman; Monique Piggott; Nicola C Newton; Maree Teesson; Andrew J Baillie; Victoria Manning; Lauren F McLellan; Alison Mahoney; Lexine A Stapinski Journal: JMIR Res Protoc Date: 2021-07-07