Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Clinical Reader Edward Day, Institute of Mental Health, University of Birmingham, UK
- Second opponent: Professor Eva Skovlund, Department of Public Health and Nursing, Norwegian University of Science and Technology
- Third member and chair of the evaluation committee: Associate Professor Nils Eiel Steen, Faculty of Medicine, University of Oslo
Chair of the Defence
Associate Professor Pål Zeiner, Faculty of Medicine, University of Oslo
Principal Supervisor
Professor Thomas Clausen, Faculty of Medicine, University of Oslo
Summary
Opioid maintenance treatment (OMT) is the most commonly used treatment for opioid use disorders in Norway with more than 7000 patients yearly. The patients in Norwegian OMT programme are monitored annually using a questionnaire including questions regarding their treatment status, drug use and other life circumstances.
In the thesis “Annual assessment data from the Norwegian opioid maintenance programme: A methodological perspective” statistician Marianne Riksheim Stavseth and colleagues at the Norwegian Centre for Addiction Research, University of Oslo, have studied several aspects of the annual assessment data. In addition to two clinical papers, the thesis contains two methodological papers describing the consequences of advanced statistical methods to a wider audience.
Based on aggregate data collected between 2002 and 2011, several marked changes in the Norwegian OMT programme were observed, e.g. a shift in the main substitution medicine from methadone to buprenorphine. A study of factors related to criminal engagement among patients in OMT, showed that having a full or part-time job, being a student and living under stable conditions contributed to reduced criminal activity.
Ignoring the presence of missing data and failing to handle it may result in distorted clinical conclusions, both regarding effect estimates and the associated confidence intervals. The choice of variable selection procedure may also influence clinical conclusions, as it affects which covariates are selected and the effect sizes. Increased awareness concerning the importance of handling missing data and performing variable selection will be crucial in a world where science is being questioned while more and more data is collected.
Additional information
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