Effect of a Tailored Activity Pacing Intervention on Fatigue and Physical Activity Behaviours in Adults with Multiple Sclerosis

Ulric S. Abonie and Florentina J. Hettinga
Additional contact information
Ulric S. Abonie: Department of Physiotherapy and Rehabilitation Sciences, University of Health and Allied Sciences, Ho, Volta Region PMB 31, Ghana
Florentina J. Hettinga: School of Sport, Rehabilitation and Exercise Science, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK

IJERPH, 2020, vol. 18, issue 1, 1-9

Abstract: Tailored activity pacing could help manage fatigue and improve physical activity. However, little is known about how to tailor activity pacing for people with multiple sclerosis. This study aims to evaluate the effect of a tailored activity pacing intervention on fatigue and physical activity behaviours in adults with multiple sclerosis. Twenty-one adults with multiple sclerosis, stratified by age and gender, are randomly allocated to either a tailored pacing or control group. Participants wear an accelerometer for seven days that measures physical activity behaviours, and self-report fatigue at the baseline and four-week follow-up. Physical activity behaviours are assessed by examining activity level (seven-day average activity counts per minute) and activity variability (seven-day average highest activity counts each day divided by activity counts on that day). The intervention improves activity levels (Mean difference = 40.91; 95% Confidence Interval [CI] (3.84–77.96); p = 0.03) and lessens activity variability (Mean difference = −0.63; 95% CI (−1.25–0.02); p = 0.04). No significant effect is found for fatigue (Mean difference = −0.36; 95% CI (−1.02–0.30); p = 0.27). This investigation shows that tailoring activity pacing based on physical activity behaviours and fatigue is effective in improving physical activity levels, without exacerbating fatigue symptoms.

Keywords: multiple sclerosis (MS); activity pacing; accelerometer; energy distribution (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/18/1/17/pdf (application/pdf)
https://www.mdpi.com/1660-4601/18/1/17/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:18:y:2020:i:1:p:17-:d:466510

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().