Table 1 Sociodemographic variables, school type, familial background, and suicidal behaviour. Females Males Total (n = 2,743) (n = 2,769) (n = 5,512) 14.77 (0.72) 14.88 (0.74) 14.82 (0.73) Characteristics Age, mean (SD), y Nationality, % German Other School type*, % Gymnasium Realschule Hauptschule Förderschule Family composition, % 2 Parents 1 Parent 1 Parent and a partner Other Kaess et al. BMC Public Health 2011, 11:597 http://www.biomedcentral.com/1471-2458/11/597 between self-harm with or without the intent to die. All variables were assessed as binominal variables with the categories “yes” or “no”. To assess a broad range of emotional and behavioural problems potentially asso- ciated with suicidal behaviour, the German version [26] of the Youth Self-Report (YSR) [27], a self-report ver- sion of the Child Behaviour Checklist (CBCL) [28], was administered. This self-report questionnaire consists of 8 scales, including withdrawn (YSR 1), somatic com- plaints (YSR 2), anxious/depressed (YSR 3), social pro- blems (YSR 4), thought problems (YSR 5), attention problems (YSR 6), delinquent behaviour (YSR 7), aggres- sive behaviour (YSR 8), and the summary scales of inter- nalizing and externalizing problems as well as an YSR total score of emotional and behavioural problems. Statistical analyses Gender differences in the YSR syndrome scales were tested with t-tests. To analyse the association of gender and emotional and behavioural problems with suicidal thoughts and suicide attempts, a sequence of logistic regression models were estimated for each of the two dependent variables. Emotional and behavioural pro- blems were operationalized by the raw scores of the eight syndrome scales of the YSR. For the assessment of the goodness of fit of the models two different measures were used. The pseudo-R2is the fraction of information of the dependent variable that is explained by the inde- pendent variables [29]. The Bayes Information Criterion (BIC) allows comparison of models according to their estimated ability to predict new data [30]. The model with the minimum BIC is the best model to predict future data. To test the hypotheses that one model is significant better than another we used the likelihood- ratio test (LR-test). For all calculations the statistical software Stata 11 was used. Results Table 1 presents the sample classified into separate male and female groups as well as the total amount of partici- pating students. For each of these groups, the table reports socio-demographic variables, school types and familial background. Suicidal thoughts were reported by 14.51% of the students, while there were higher rates in female (19.80%) than in male (9.28%) adolescents. A his- tory of at least one suicide attempt was found in 7.84% of the participants, but again, in 10.83% of the girls and only in 4.88% of the boys. In summary, the prevalence rates of suicidal behaviour in female students were twice as high as the prevalence rates for the male students suggesting a strong influence of gender on suicidal thoughts and suicide attempts. Mean scores of behavioural and emotional problems as measured by the YSR scales are presented in table 2. Page 3 of 7 88.69 11.31 35.79 32.58 28.81 2.81 75.11 14.61 9.05 1.23 89.49 10.51 38.79 33.25 25.41 2.55 74.08 14.76 9.90 1.27 87.90 12.10 32.83 31.92 32.18 3.07 76.14 14.47 8.19 1.20 * After four years of elementary school the German school system branches into three types of secondary schools. The so called “Hauptschule” (Secondary General School which takes five years after Primary School) prepares pupils for vocational training, whereas the “Realschule” (Intermediate Secondary School) concludes with a general certificate of secondary education after six years. Eight years of “Gymnasium” provide pupils with a general university entrance qualification Female students reported significantly higher scores on the scales measuring withdrawn, somatic complaints, anxious/depressed, thought problems, attention pro- blems, as well as in the score for internalizing problems, and also in the YSR total score (p < .01 for all). For male students we found elevated scores in social pro- blems, delinquent behaviour, and in the score for exter- nalizing problems (p < .01 for all). The only scale that showed no significant gender difference was aggressive behaviour. Goodness of fit for the sequence of logistic regression models to predict suicidal thoughts is summarized in table 3. Gender alone explains 2.7% of the information (model 1), while emotional and behavioural problems explain 30% (model 2). By adding gender to the emo- tional and behavioural problems only an additional 0.3% of information can be explained (model 3). This small amount is still significant due to the large sample size (LR-test of model 2 vs. model 3: c2(1) = 12.31, p = .0004). This model is also the one with the smallest BIC and therefore is the one that we should use to predict suicidal thoughts. Including the interaction of gender with emotional and behavioural problems in model 4 - corresponding to the hypothesis that the association of emotional and behavioural problems with suicidal thoughts is different for males and females - does not result in a significant increase in prediction (LR-test of model 3 vs. model 4: c2(8) = 10.2, p = .251). Looking at the estimated coefficients for the best model (model 3),