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

Author:

Ensari Ipek1,Motl Robert W1,McAuley Edward1,Mullen Sean P1,Feinstein Anthony2

Affiliation:

1. University of Illinois at Urbana-Champaign, USA

2. University of Toronto, Canada

Abstract

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.

Publisher

SAGE Publications

Subject

Neurology (clinical),Neurology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3