焦虑
萧条(经济学)
社会心理的
心理学
心理干预
精神科
心理健康
临床心理学
宏观经济学
经济
作者
Mengyi Chen,Wei Bai,Ling Zhang,Sha Sha,Zhaohui Su,Teris Cheung,Robert Smith,Gábor S. Ungvári,Todd Jackson,Qing-E Zhang,Yu‐Tao Xiang
摘要
ABSTRACT Background Depression and anxiety are global public health challenges among older adults. Square dancing, a popular activity for older Chinese adults, is believed to relieve these disturbances. This study compared the prevalence, severity, and network structures of depression and anxiety among older square dancers versus non‐dancers (i.e., those who do not engage in square dancing). Methods Propensity score matching (PSM) created square dancer and non‐dancer groups using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Depressive and anxiety symptoms were assessed with the 10‐item Center for Epidemiological Studies Depression Scale (CESD‐10) and the 7‐item Generalized Anxiety Disorder Scale (GAD‐7), respectively. Central symptoms and bridge symptoms were estimated in each group using expected influence (EI) and bridge EI, respectively. Results The study included 401 square dancers and a matched sample of 1163 non‐dancers. The prevalence and severity of depression and anxiety were significantly lower among square dancers compared to non‐dancers. In contrast, network structures of depressive and anxiety symptoms were similar between the two groups. “Uncontrollable worrying” and “Felt sadness” were the most central symptoms, and “Nervousness”, “Bothered by things” and “Felt nervous/fearful” were key bridge symptoms across both groups. Conclusion Participation in square dancing is associated with reduced overall prevalence and severity of depression and anxiety among older adults, but is not associated with a unique network structure of these syndromes compared to non‐participation. Consequently, psychosocial interventions developed for depression and anxiety based on the network structure of non‐dancers may also be applicable for square dancers who experience anxiety and depression.
科研通智能强力驱动
Strongly Powered by AbleSci AI