By Dennis M. Donovan PhD, G. Alan Marlatt PhD
This finished scientific source and textual content is grounded in state of the art wisdom concerning the biopsychosocial techniques excited about addictive behaviors. provided are research-based, eminently useful concepts for assessing the therapy wishes and ongoing scientific results of people who've issues of substance use and nonchemical addictions. From best participants, the ebook exhibits how one can weave evaluation in the course of the complete technique of care, from the preliminary screening to intervention, relapse prevention, and posttreatment tracking.
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Additional info for Assessment of Addictive Behaviors, Second Edition
Assessment for Relapse Prevention 19 Distal Personal Factors An important element in the prediction of behavior is what the individual brings into the situation, in his or her hereditary makeup, personal background characteristics, and behavioral competencies. Such distal personal background variables may lead to patterns of behavior that expose the individual to a greater risk of alcohol, drugs, or involvement in other addictive behaviors initially, to increased problems in these areas, and to subsequent relapse.
If an individual had an initial relapse, there was a high risk for a subsequent relapse; however, there was no evidence that the subsequent relapse occurred within the same category of reasons as the initial episode. Negative affect relapses and craving–cued relapses were found to be more severe than social pressure relapses. , 1980) have found considerable overlap across addictive behaviors, each has its own set of relatively specific relapse precipitants. As an example, Hodgins and el-Guebaly (2004) found that the two most highly endorsed reasons for relapse among pathological gamblers were optimism about winning and a need for money.
An expanded model of Marlatt’s relapse precipitant taxonomy has been recommended (Donovan, 1996b; Stout, Longabaugh, & Rubin, 1996). It would allow the inclusion of multiple variables exerting differential levels of influence across a range of time varying in proximity to the relapse event. A number of these recommendations have been incorporated recently into a reconceptualized cognitive-behavioral model of relapse that focuses on the dynamic interactions between multiple risk factors and situational determinants (Witkiewitz & Marlatt, 2004).