Journal of affective disorders · 2024
Personality traits and depressive symptoms among Chinese older people: A network approach.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Li Jia, Zhang Jihong
Аннотация
BACKGROUND: The present study aims to investigate the network structure of depressive symptoms, the interrelationships between individual personality traits and depressive symptoms, and gender differences among Chinese older people aged 60 and above.
METHOD: We performed network analyses with a regularized Graphical Gaussian Model and a case-dropping bootstrap approach. A sample of 4876 older Chinese people aged 60+ was included in the analyses. We investigated the central symptoms in the depression network and the bridge nodes that connect personality facets and depressive symptoms. Gender differences were investigated by testing the global strength, network invariance, and edge weights.
RESULTS: Sadness and depressed mood were the most central depressive symptoms, while somatic symptoms such as restless sleep were the least central. Neurotic facets, particularly "worry a lot" and "get nervous easily", played significant bridging roles in the web of personality traits and depressive symptoms. Gender differences were observed in three edges among different personality traits (rude-worried, original-worried, and forgiving-nervous).
LIMITATION: The study adopts a cross-sectional dataset, and therefore, cannot track the network changes over time or conclude a causal relationship.
DISCUSSION: The study calls for more focus and prioritization on sadness, depressed mood and neurotic traits in the identification of depression among older Chinese people. Future researchers and practitioners should better understand of older Chinese adults' worry and nervousness to develop appropriate practices and policies.
METHOD: We performed network analyses with a regularized Graphical Gaussian Model and a case-dropping bootstrap approach. A sample of 4876 older Chinese people aged 60+ was included in the analyses. We investigated the central symptoms in the depression network and the bridge nodes that connect personality facets and depressive symptoms. Gender differences were investigated by testing the global strength, network invariance, and edge weights.
RESULTS: Sadness and depressed mood were the most central depressive symptoms, while somatic symptoms such as restless sleep were the least central. Neurotic facets, particularly "worry a lot" and "get nervous easily", played significant bridging roles in the web of personality traits and depressive symptoms. Gender differences were observed in three edges among different personality traits (rude-worried, original-worried, and forgiving-nervous).
LIMITATION: The study adopts a cross-sectional dataset, and therefore, cannot track the network changes over time or conclude a causal relationship.
DISCUSSION: The study calls for more focus and prioritization on sadness, depressed mood and neurotic traits in the identification of depression among older Chinese people. Future researchers and practitioners should better understand of older Chinese adults' worry and nervousness to develop appropriate practices and policies.