Sex differences in the network structures of depressive symptom profiles in Asian patients with depressive disorders: findings from the Research on Asian Psychotropic Patterns for Antidepressants, Phase 3
Notice bibliographique
Résumé
BACKGROUND: Depression is a complex mental health disorder with highly heterogeneous symptoms that vary significantly across individuals, influenced by various factors, including sex and regional contexts. Network analysis is an analytical method that provides a robust framework for evaluating the heterogeneity of depressive symptoms and identifying their potential clinical implications. OBJECTIVE: To investigate sex-specific differences in the network structures of depressive symptoms in Asian patients diagnosed with depressive disorders, using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3, which was conducted in 2023. METHODS: A network analysis of 10 depressive symptoms defined according to the National Institute for Health and Care Excellence guidelines was performed. The sex-specific differences in the network structures of the depressive symptoms were examined using the Network Comparison Test. Subgroup analysis of the sex-specific differences in the network structures was performed according to geographical region classifications, including East Asia, Southeast Asia, and South or West Asia. RESULTS: A total of 998 men and 1,915 women with depression were analysed in this study. The analyses showed that all 10 depressive symptoms were grouped into a single cluster. Low self-confidence and loss of interest emerged as the most central nodes for men and women, respectively. In addition, a significant difference in global strength invariance was observed between the networks. In the regional subgroup analysis, only East Asian men showed two distinct clustering patterns. In addition, significant differences in global strength and network structure were observed only between East Asian men and women. CONCLUSION: The study highlights the sex-specific differences in depressive symptom networks across Asian countries. The results revealed that low self-confidence and loss of interest are the main symptoms of depression in Asian men and women, respectively. The network connections were more localised in men, whereas women showed a more diverse network. Among the Asian subgroups analysed, only East Asians exhibited significant differences in network structure. The considerable effects of neurovegetative symptoms in men may indicate potential neurobiological underpinnings of depression in the East Asian population.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».