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Abstract Background School attendance problems (SAPs), whether absenteeism or dropout, are strongly associated with poor outcomes for adolescents. We examined multiple variables that influence SAPs to identify potential leverage points for improving school attendance. Methods Self-reported SAPs and demographic information was collected from 392 adolescents in adolescents presenting to the general hospital for psychological services. PHQ-9 and GAD-7 were applied to assess the severity of depressive and anxious symptoms. We constructed logistic regression analysis and the Chi-Square Automatic Interaction Detection (CHAID) segmentation analysis via SPSS Decision Tree to identifying risk factors for the development of SAPs in adolescents. Results SAPs were self-reported by 252 (64.3%) adolescents. The SAPs group and non-SAPs group showed a significant difference in age, PHQ9 total scores, GAD7 total scores, schools, siblings, residence, parental marital quality, general health, regular exercise, and regular diet. A post hoc comparison between the two groups showed that the frequency of SAPs was significantly higher in the moderately-severe and severe depressive groups compared with other three groups (none, mild, moderate). The frequency of SAPs in severe anxious groups was significantly different from the none-anxious group. According to the binary logistic regression analysis, the depressive severity, siblings, residence, marital quality of parents, general health, and regular diet were correlated with the SAPs among adolescents. The adjusted OR of SAPs according to moderately-severe depressive symptoms was 10.84 (95%CI: 1.967–59.742) and severe depressive symptoms was 6.659 (95%CI: 1.147–38.666). In the decision tree model, PHQ-9 severity was extracted as the first splitting variable, with regular exercise and residence as the second, and siblings as the third. The ROC curves for predicting SAPs showed a fair diagnostic accuracy of the model with AUCs of CHAID model (0.705,95%CI:0.652–0.759, P = 0.000) and logistic regression model (0.777,95%CI:0.729–0.824, P = 0.000). Conclusion Our study provides insights into the associations between depressive symptoms and poor school attendance and identifies a number of risk factors associated with SAPs. Effective intervention by mental health practitioners, more attention by policy makers, and further research in this area are urgently needed for adolescents. |
