随机对照试验
医学
焦虑
干预(咨询)
物理疗法
生活质量(医疗保健)
医院焦虑抑郁量表
萧条(经济学)
认知行为疗法
临床心理学
精神科
内科学
护理部
宏观经济学
经济
作者
Robert W. Motl,Brian M. Sandroff,Lara A. Pilutti,Gary Cutter,Roberto Aldunate,Ariel Kidwell-Chandler,Rachel E. Bollaert
标识
DOI:10.1016/j.cct.2022.107056
摘要
We undertook a randomized controlled trial (RCT) that investigated the effectiveness of a theory-based, Internet-delivered, behavioral intervention focusing on physical activity promotion for immediate and sustained improvements in secondary, patient-reported outcomes (PROs) of function, symptoms, and quality of life (QOL) in multiple sclerosis (MS).Persons with MS (N = 318) were recruited from throughout the United States and randomized into behavioral intervention (n = 159) or attention/social contact control (n = 159) conditions. The conditions were administered over a 6-month period by persons who were uninvolved in screening, recruitment, random assignment, and outcome assessment. There was a 6-month follow-up period without intervention access/content. We collected PROs data every 6 months over the 12-month period. The PROs included validated measures of walking and cognitive function, symptoms of fatigue, depression, anxiety, pain, and sleep quality, and QOL. The data analysis involved a modified intent-to-treat approach using a linear mixed model in JMP Pro 16.0.There was a significant group by time interaction on Fatigue Severity Scale scores (p < .01) and physical subscale scores of the Modified Fatigue Impact Scale (p < .05). Scores on both measures decreased immediately after the 6-month period in the behavioral intervention compared with no change in the control condition, and this differential pattern of change was sustained over the 6-month follow-up. There were no group by time interactions on the other PROs.This study provides evidence for the effectiveness of a novel, widely scalable approach for physical activity promotion and fatigue management in persons with MS, yet this must be contextualized with the absence of improvements in the other PROs.
科研通智能强力驱动
Strongly Powered by AbleSci AI