4.3 Article

Patterns and predictors of naturally occurring change in depressive symptoms over a 30-month period in multiple sclerosis

期刊

MULTIPLE SCLEROSIS JOURNAL
卷 20, 期 5, 页码 602-609

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/1352458513504251

关键词

questionnaire; longitudinal study; multiple sclerosis; relapsing-remitting multiple sclerosis; factors; predictive model; Depression; physical activity

资金

  1. National Multiple Sclerosis Society [3926A2/1]

向作者/读者索取更多资源

Background: Depressive symptoms are common in multiple sclerosis (MS), yet there is little information about the pattern and predictors of changes in depressive symptoms over time. Objective: We examined changes in depressive symptoms over a 30-month period and the demographic, clinical and behavioral predictors of such changes in relapsing-remitting MS (RRMS). Methods: 269 persons with RRMS completed the Hospital Anxiety and Depression Scale (HADS) and a demographic/clinical scale, Godin Leisure-Time Exercise Questionnaire (GLTEQ) and Patient Determined Disease Steps (PDDS) scale every 6 months over a 30-month period. Data were analyzed using latent class growth modeling (LCGM). Results: LCGM identified a two-class model for changes in HADS depression scores over time. Class 1 involved lower initial status (i.e. fewer depressive symptoms) and linear decreases in depressive symptoms over time (i.e. improving HADS scores), whereas Class 2 involved higher initial status (i.e. more depressive symptoms) and linear increases in depressive symptoms over time (i.e. worsening HADS scores). LCGM further indicated that being older (OR = 2.46; p < .05), married (OR = 2.62; p < .05), employed (OR = 4.29; p < .005) and physically active (OR = 2.71; p < .05) predicted a greater likelihood of belonging to C1 than C2. Conclusions: Depressive symptoms change over time in persons with RRMS, and the pattern of change can be predicted by modifiable and non-modifiable factors.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据