Characteristics of visitors at first aid stations.

<p>*in minutes.</p><p>**<i>p</i><0.001, compared to substance-related visits to first aid stations.</p><p>***missing data.</p

Most common individual substance-related incidents and odds ratio (OR) among first aid station visitors (%).

<p>Alc = alcohol. Amp = amphetamines. Can = cannabis. Coc = cocaine. Ecs = ecstasy.</p><p>More than one symptom can occur in combination with each substance.</p><p>Reference category for the logistic regression analysis is not reporting use of each of the substances.</p><p>95% CI = 95% confidence interval (lower-upper).</p><p>ORs are available only for variables included in the forward stepwise model.</p

Most common multiple-substance-use problems and odds ratios (ORs) among first-aid station visitors (%).

<p>Alc = alcohol. Amp = amphetamines. Can = cannabis. Coc = cocaine. Ecs = ecstasy.</p><p>More than one symptom can occur in combination with the two combined substances.</p><p>Reference category for the logistic regression analysis is not reporting the use of each combination of the substances.</p><p>95% CI = 95% confidence interval (lower-upper).</p><p>ORs are available only for variables included in the forward stepwise model.</p

Number and risk of first-aid visits and serious incidents associated with using different substances individually.

<p>For each substance, the risk of visiting a first aid station was calculated by dividing the number of first aid visits (FAVs) related to that substance by the number of FAVs for that cohort.</p><p>CI = 95% confidence interval. Confidence interval for relative risk (RR) of a serious incident (SI) was calculated using Morris and Gardner's <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029620#pone.0029620-Morris1" target="_blank">[46]</a> formula.</p><p>The category <i>no substance</i> is the reference category for the SI risk ratios.</p

Number and risk of first aid visits and serious incidents associated with using different combinations of substances.

<p>For each combination of substances, the risk of visiting a first aid station was calculated by dividing the number of first aid visits (FAVs) rrelated to that combination by the number of FAVs for that cohort.</p><p>CI = 95% confidence interval. Confidence interval for relative risk (RR) of a serious incident (SI) was calculated using Morris and Gardner's <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029620#pone.0029620-Morris1" target="_blank">[46]</a> formula.</p><p>The category <i>no substance use</i> is the reference category for the SI risk ratios.</p

Additional file 1: of Modelling intentions to provide smoking cessation support among mental health professionals in the Netherlands

List of original survey items and response options. (XLSX 17 kb

Additional file 2: of Modelling intentions to provide smoking cessation support among mental health professionals in the Netherlands

Covariance matrices of the fitted structural equation models. (XLSX 50 kb

Country specific classification tree models.

<p>Note: Country specific classification tree models for the Czech Republic (top-left), Italy (top-right), Netherlands (bottom-left) and Sweden (bottom-right). The variables in the numbered boxes indicate the splitting variables identified in the recursive partitioning analysis. The cut-off value for each split, and the number of participants involved in each split is indicated next to the arrows diverting participants from the splitting variable. The six grey area's in the bottom of the lowest boxes (“terminal nodes”), and the “p” in these boxes indicates the proportion of participants in each partitioned area with scores of 7 or higher on the CAST. “n” in the lowest boxes indicates the number of participants in each of the terminal nodes.</p

Ten models with optimal fit.

<p>Note: Variables correspond to those described in the section ‘Bivariate analysis’. AIC is Akaike Information Criterion, Nagelkerke R² provides a goodness-of-fit index between 0–1.</p><p>Ten models with optimal fit.</p

Performance statistics of the generic classification tree model.

<p>Note: Accuracy indicates the proportion of correctly classified cases, with associated confidence interval; No information rate (NIR) is 1-[proportion of CAST≥7] in the sample; Difference between model accuracy and NIR tested using a one-sided binomial test; Sensitivity = [number of correctly classified CAST ≥7]/[number of CAST ≥7 in sample]; Specificity = [number of correctly classified CAST <7]/[number of CAST <7 in sample]; Positive predictive value = [number of correctly classified CAST ≥7]/[all classified CAST ≥7]; Negative predictive value = [number of correctly classified CAST <7]/[all classified CAST <7]. The country datasets contain both participants from the training and the validation dataset.</p><p>Performance statistics of the generic classification tree model.</p