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Multiple Sclerosis Fatigue Self-Management: Strategies and Influencing Factors 5 Years After a Multimodal
ShienPei C Silverman1, Bishan Yang2, Felicia Mata-Greve2
1From the Research Department, Veterans Affairs Portland Health Care System, Portland, OR.
Background:
Fatigue: Take Control (FTC) is a multimodal self-management program. Results of a previous clinical trial showed its effectiveness at improving fatigue related to multiple sclerosis (MS). The objectives of this study were to use the very long-term data from the FTC study to understand fatigue management strategies used 5 years after enrollment, identify facilitators and barriers to utilizing strategies, and explore the potential relationships between the strategy used and fatigue outcomes.
Methods:
This study adopted a cross-sectional survey design. A subset of the original FTC clinical trial participants was invited to complete the Modified Fatigue Impact Scale for fatigue severity measurement and a 17-item questionnaire about their fatigue management strategies 5 years after enrollment. Descriptive statistics and content analysis were used to analyze quantitative and qualitative data using the COM-B (capability, opportunity, motivation-behavior) model for behavior change as a framework.
Results:
Planning daily activities and prioritizing tasks were the fatigue management strategies most often reported. Facilitators to utilizing management strategies included access to enabling devices, paid professional help, companions, and maintaining a positive attitude. Barriers to implementing strategies included high cost, the presence of other health problems, and temperature sensitivity. Internal focused strategies showed a trend toward reducing fatigue impact when controlled for typology group assignment.
Conclusions:
Future work may focus on promoting low-cost strategies to help people with MS manage fatigue. Internal factors (eg, motivation) play an important role in influencing the application of MS fatigue self-management strategies. Future clinical trials with larger sample sizes that assess the applicability of the COM-B model are warranted.
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