Evaluation of seasonal variations for the seasonal pattern assessment in mood disorder patients and healthy controls

评估情绪障碍患者和健康对照组的季节性变化及其季节性模式评估

阅读:2

Abstract

BACKGROUND: Seasonal disturbances were common in mood disorders patients. The global seasonality score (GSS), derived from the Seasonal Pattern Assessment Questionnaire (SPAQ), was widely used to assess seasonality and related symptoms. This study aimed to establish the structure of the Chinese version of SPAQ. We examined the stability of seasonal pattern assessment across four seasons when administering SPAQ. The prevalence of seasonal affective disorder was estimated using SPAQ criteria. METHODS: We recruited 596 mood disorder patients and 138 healthy controls (HC), with 121 patients and 37 HC followed up over four seasons. An exploratory factor analysis examined the GSS factor structure. We evaluated correlations between GSS symptom dimensions and "the degree of problems due to seasonal changes" and used intraclass correlation coefficient reliability (ICCR) to assess the consistency of symptom dimensions across seasons. RESULTS: Approximately a quarter of mood disorder patients met the criteria for seasonal affective disorder. The Chinese SPAQ revealed a two-factor structure: psychological and food-related symptoms among patients. The GSS showed a significant correlation (r = 0.64) with the degree of problems due to seasonal changes in mood disorder patients, while energy level and sleep significantly correlated with GSS (r > 0.75) in HC. Reporting reliability (ICCR > 0.4) was acceptable for GSS and mood/energy levels in patients across seasons. CONCLUSIONS: Seasonal variations were observed in reporting the symptom dimensions of the seasonal pattern assessment, while the GSS remained relatively stable in both mood disorder patients and HC. SPAQ is a useful tool for measuring seasonality, irrespective of the season of administration.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。