ObjectiveTo investigate symptom features distinguishing depressive disorder from insomnia disorder with depressive symptoms across different age groups, and to provide evidence for refined clinical differential diagnosis.MethodsThis retrospective cross-sectional study enrolled patients who visited Hangzhou Seventh People’s Hospital between January 2016 and October 2024 and completed assessments via the “Good Sleep 365” platform. Based on DSM-5 diagnostic criteria, two psychiatrists classified participants into two diagnostic groups: depressive disorder and insomnia disorder with depressive symptoms. The final sample included 1,873 patients: 190 adolescents, 1,253 adults, and 430 older adults. After an 8:2 training-validation split, feature selection and model training were performed within the training set, and final performance was evaluated on the validation set. Age-specific logistic regression models were constructed using Pittsburgh Sleep Quality Index (PSQI) component scores and item-level data from the 9-Item Patient Health Questionnaire (PHQ-9) and 15-Item Patient Health Questionnaire (PHQ-15), with feature importance analyses performed.ResultsThe two groups differed in demographic characteristics and total scale scores, although their overall clinical presentations showed substantial overlap. Depressed mood, fatigue, impaired concentration, and sleep-related symptoms consistently emerged across age groups, demonstrating relatively stable discriminative value, while distinct age-specific symptom patterns were also observed. Model performance varied across age groups, with the highest AUC observed in adults (0.8216), followed by older adults (0.7446) and adolescents (0.6229).ConclusionDepressive disorder and insomnia disorder with depressive symptoms exhibit identifiable differences in symptom structure that are age-related. Symptom-level evaluation across age groups may provide complementary information for clinical differential diagnosis between these two conditions.
Differentiation between depressive disorder and insomnia disorder with depressive symptoms across age groups using machine learning
Hongjing Mao

