Publication details

Prediction of depression risk by discriminant analysis in Czech adolescents

Authors

KLIMUSOVÁ Helena BUREŠOVÁ Iva

Type Conference abstract
MU Faculty or unit

Faculty of Arts Rector's Office

Citation
Description Adolescence is a period of vulnerability to depressive symptoms. The presented study aimed to identify a set of adolescent familial and behavioral-emotional factors predicting depression during this developmental stage. The study was conducted on the sample of the 1092 Czech adolescents, aged 12 - 16 years (m = 14.00, sd = 0.95); the proportion of the boys and girls was 47,5% and 52,5% respectively. The questionnaires were administered in the school setting, including Children's Depression Inventory (CDI) for the assessment of the presence and severity of specific depressive symptoms. The cut-off score of 20 points and/or presence of suicidal ideation indicated by item 9 were used as a criterion for the risk of clinical depression; 369 adolescents (33.8% of our sample) met the criterion. Stepwise linear dicsriminant analysis was utilized to construct a predictive model to identify individuals who have a higher risk of depression. The predictors, preliminary selected on the base of significant differences between high- and low-risk groups, were self-reported school grades, school aspirations, family enviroment variables, self-harm behavior, subculture identification, and relationship with peers. Six predictor variables were included in the final model: self-harm behavior (prior incidence of any kind of self-harm behavior); relationship with mother (poor); school grades (poor); gender (girls being more at risk); relationship with peers (poor); and identification with a subculture (e.g. emo, gothic). The discriminant analysis yielded a statistically significant function (lambda = 0.808; Chi-sq = 232.0, df = 6, p < 0.001). This function showed that the total rate of correct prediction was 76.2% (55.8% for high-risk group and 86.6% for low-risk group). The calculated discriminate function based on the six predictor variables may be useful for detecting adolescents at high risk of depression and taking preventive measures.
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