The effect of personality on withdrawal severity and taper outcome in benzodiazepine dependent patients.
BACKGROUND: Personality psychopathology exerts a significant and independent effect on the course of benzodiazepine (BZ) discontinuation, worsening the subjective severity of withdrawal symptoms and significantly increasing the occurrence of early taper failures. METHOD: One hundred and seventy-one patients participating in a BZ discontinuation programme were administered several personality measures prior to taper. Patients were stabilized for 3 weeks at their baseline BZ dosage and then tapered off 25% per week over 4 weeks, with the option to extend up to 6 weeks if necessary. RESULTS: High levels of passivity and dependency as assessed by the MMPI Dependence subcluster, and at a trend level high Eysenck Neuroticism and high TPQ Harm Avoidance contributed significantly to the prediction of benzodiazepine withdrawal severity. Though there was a high correlation between personality measures, psychopathology and adjusted BZ dose, the effects of personality on withdrawal severity was significant, particularly in the initial phases of BZ taper, when taper severity was still relatively mild. CONCLUSIONS: These findings indicate that clinical decisions on how to manage BZ tapering should be guided by personality assessments, in addition to the usual considerations of BZ dosage, residual psychopathology, duration of treatment, etc. The potential for difficulty with discontinuation related to personality traits should be one of the factors weighted in the risk-benefit assessment made in the planning of benzodiazepine treatment for patients with anxious symptomatology.[1]References
- The effect of personality on withdrawal severity and taper outcome in benzodiazepine dependent patients. Schweizer, E., Rickels, K., De Martinis, N., Case, G., García-España, F. Psychological medicine. (1998) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg
