Stage of change of cigarette smoking in drug dependent patients.

Nicotine cessation programmes in Switzerland, which are commonly based on the stage of change model of Prochaska and DiClemente (1983), are rarely offered to patients with illicit drug dependence. This stands in contrast to the high smoking rates and the heavy burden of tobacco-related problems in these patients. The stage of change was therefore assessed by self-administered questionnaire in 100 inpatients attending an illegal drug withdrawal programme. Only 15% of the patients were in the contemplation or decision stage. 93% considered smoking cessation to be difficult or very difficult. These data show a discrepancy between the motivation to change illegal drug consumption habits and the motivation for smoking cessation. The high proportion of patients remaining in the precontemplation stage for smoking cessation, in spite of their motivation for illicit drug detoxification, may be due to the perception that cessation of smoking is more difficult than illicit drug abuse cessation.

Geological realism in hydrogeological and geophysical inverse modeling: A review

Scientific curiosity, exploration of georesources and environmental concerns are pushing the geoscientific research community toward subsurface investigations of ever-increasing complexity. This review explores various approaches to formulate and solve inverse problems in ways that effectively integrate geological concepts with geophysical and hydrogeological data. Modern geostatistical simulation algorithms can produce multiple subsurface realizations that are in agreement with conceptual geological models and statistical rock physics can be used to map these realizations into physical properties that are sensed by the geophysical or hydrogeological data. The inverse problem consists of finding one or an ensemble of such subsurface realizations that are in agreement with the data. The most general inversion frameworks are presently often computationally intractable when applied to large-scale problems and it is necessary to better understand the implications of simplifying (1) the conceptual geological model (e.g., using model compression); (2) the physical forward problem (e.g., using proxy models); and (3) the algorithm used to solve the inverse problem (e.g., Markov chain Monte Carlo or local optimization methods) to reach practical and robust solutions given today's computer resources and knowledge. We also highlight the need to not only use geophysical and hydrogeological data for parameter estimation purposes, but also to use them to falsify or corroborate alternative geological scenarios.