Placebo, alcohol and flumazenil provocations : subjective and objective registrations in psychopharmacological experiments

Abstract: Abuse and dependency of alcohol or drugs is a major problem today, with severe implications for society as well as for the individual. Treatment is often characterised by hard work and the road to recovery is (among other problems) paved with acute and protracted withdrawal symptoms as well as relapse. Lately there has been an increased interest, and success, in the pharmacological treatment of dependency of different substances (e.g. acamprosate and naltrexone for alcohol, methadone and buprenorphine for opioids and possibly naltrexone for amphetamine and flumazenil for benzodiazepines). Essential for the investigation of promising substances are valid and reliable tools for registration of relevant subjective and objective effects during experimental treatment. Therefore, the aim of this work was to find and test suitable tools, and to study different psychopharmacological consequences, in experiments designed to affect acute and/or post-acute effects of benzodiazepines and alcohol. To study the objectives I was interested in I have performed two studies with intravenous provocations, one with placebo and alcohol and one with flumazenil, resulting in five separate reports on different topics. In this thesis, I have highlighted the importance of taking gender as well as placebo effects in account when performing pharmacological provocations on subjects treated for benzodiazepine dependence. Further, I have shown that it is possible to register acute tolerance to alcohol with an objective test previously not used in this context. I have also shown that it was possible to measure pharmacologically induced reductions in symptoms of benzodiazepine withdrawal using subjective and objective registrations. In addition, I have found that a reduction of self-rated withdrawal related aggression could be measured after intravenous flumazenil. Finally, I have pointed to the risk for loss of important information when creating indexes of multiple measures.

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