Prediction of depression risk by discriminant analysis in Czech adolescents
| Autoři | |
|---|---|
| Rok publikování | 2016 |
| Druh | Konferenční abstrakty |
| Fakulta / Pracoviště MU | |
| Citace | |
| Popis | 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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