Longitudinal associations between activity pacing, fatigue, and physical activity in adults with multiple sclerosis

PURPOSE: The purpose of this study was to evaluate how activity pacing relates to physical activity and health-related quality of life over a one year period in a sample of adults with multiple sclerosis. METHODS: 68 adults with multiple sclerosis (mean age= 42 ± 11 years) filled in questionnaires on their active engagement in pacing decisions and perceived difficulty in preventing overactivity (5-point Activity Pacing and 2-point Risk of Overactivity Questionnaire), fatigue (7-point Fatigue Severity Scale), physical activity (adapted Short Questionnaire to Assess Health-Enhancing Physical Activity) and health-related quality of life (RAND-12 Health Survey) post rehabilitation and at one year follow up, as part of the Rehabilitation, Sports and Active lifestyle study (a nationwide multi-centre program aimed at stimulating and promoting an active lifestyle in rehabilitation in the Netherlands). Multilevel modelling was used to analyse the associations between activity pacing, fatigue, physical activity and health-related quality of life. RESULTS: No associations were found between activity pacing and physical activity (β = -0.21; p > 0.05), and between activity pacing and health-related quality of life (β = -0.10; p > 0.05) at long-term. Fatigue was negatively related to health-related quality of life (β = -0.35; p < 0.001). Perceived risk of overactivity moderated the association between fatigue and health-related quality of life (β = -0.13; p = 0.039). CONCLUSIONS: These findings suggest that persons who experience decreases in health-related quality of life with increased fatigue, are more likely to be engaging in ‘overactive’ behaviour. The lack of associations between activity pacing and physical activity, and between activity pacing and health-related quality of life suggests there is no clear strategy among persons with MS that is successful in improving physical activity and quality of life either in short or long-term when no interventions are introduced

Implementation fidelity trajectories of a health promotion program in multidisciplinary settings: managing tensions in rehabilitation care.

Although the importance of evaluating implementation fidelity is acknowledged, little is known about heterogeneity in fidelity over time. This study aims to generate insight into the heterogeneity in implementation fidelity trajectories of a health promotion program in multidisciplinary settings and the relationship with changes in patients' health behavior.This study used longitudinal data from the nationwide implementation of an evidence-informed physical activity promotion program in Dutch rehabilitation care. Fidelity scores were calculated based on annual surveys filled in by involved professionals (n = ± 70). Higher fidelity scores indicate a more complete implementation of the program's core components. A hierarchical cluster analysis was conducted on the implementation fidelity scores of 17 organizations at three different time points. Quantitative and qualitative data were used to explore organizational and professional differences between identified trajectories. Regression analyses were conducted to determine differences in patient outcomes.Three trajectories were identified as the following: 'stable high fidelity' (n = 9), 'moderate and improving fidelity' (n = 6), and 'unstable fidelity' (n = 2). The stable high fidelity organizations were generally smaller, started earlier, and implemented the program in a more structured way compared to moderate and improving fidelity organizations. At the implementation period's start and end, support from physicians and physiotherapists, professionals' appreciation, and program compatibility were rated more positively by professionals working in stable high fidelity organizations as compared to the moderate and improving fidelity organizations (p < .05). Qualitative data showed that the stable high fidelity organizations had often an explicit vision and strategy about the implementation of the program. Intriguingly, the trajectories were not associated with patients' self-reported physical activity outcomes (adjusted model β = - 651.6, t(613) = - 1032, p = .303).Differences in organizational-level implementation fidelity trajectories did not result in outcome differences at patient-level. This suggests that an effective implementation fidelity trajectory is contingent on the local organization's conditions. More specifically, achieving stable high implementation fidelity required the management of tensions: realizing a localized change vision, while safeguarding the program's standardized core components and engaging the scarce physicians throughout the process. When scaling up evidence-informed health promotion programs, we propose to tailor the management of implementation tensions to local organizations' starting position, size, and circumstances.The Netherlands National Trial Register NTR3961 . Registered 18 April 2013

RehabMove 2018: UNRAVELLING FATIGUE AND ACTIVITY PACING IN MAINTAINING A PHYSICALLY ACTIVE LIFESTYLE AFTER STROKE REHABILITATION

PURPOSES: 1) To identify fatigue trajectories after stroke rehabilitation, 2) to determine which factors are associated with trajectory membership before discharge, and 3) to investigate how fatigue and activity pacing are related to physical activity after stroke rehabilitation. METHODS: Stroke patients(N=303) were followed from baseline(T0:3-6 weeks before discharge) to 14(T1), 33(T2) and 52(T3) weeks after discharge from rehabilitation in the Rehabilitation, Sports and Active lifestyle study. Latent Class analysis was conducted to determine fatigue trajectories(T1-T3) using self-reported data of the Fatigue Severity Scale. Binomial regression analyses were performed to determine personal and health-related factors and behaviours of activity pacing associated with trajectory membership at T0. Multilevel analyses were used to investigate how self-reported physical activity levels were related to fatigue and activity pacing after rehabilitation(T1-T3). RESULTS: Three fatigue trajectories were identified: high(N=167), low(N=33) and recovery(N=6). Compared with the low fatigue trajectory, stroke patients in the high fatigue trajectory were less likely to be highly educated(p=.023), experienced a lower quality of life(p=.004) and were more aware of their activity pacing(p=.015). Sustained physical activity was related to less fatigue(p=.006) and less awareness of activity pacing(p=.002) after rehabilitation. CONCLUSIONS: This study identified three fatigue trajectories after stroke rehabilitation. Low education level, low quality of life scores, and high awareness of activity pacing before discharge identified stroke patients in the high fatigue trajectory. Lower levels of physical activity after stroke rehabilitation were related to a higher awareness of activity pacing, but without advice on activity pacing patients did not succeed to reduce their fatigue. These findings highlight the need to focus on the potential of activity pacing in today’s rehabilitation practice

The course of fatigue and physical activity from discharge up to 5-7 years post stroke rehabilitation and the role of activity pacing behaviour: a longitudinal mixed-methods study.

Purposes: The course of fatigue and physical activity (PA) from discharge up to 5-7 years post stroke rehabilitation may be influenced by activity pacing behaviour (how people divide their energy and daily PA during the day). This study aims (1) to explore how people after stroke perceive their course of fatigue and PA post rehabilitation and (2) to explore participants’ experience of activity pacing behaviour, and its barriers and facilitators. Methods: People after stroke (N=303) were followed from 3-6 weeks before discharge (T0) to 14 (T1), 33 (T2) and 52 (T3) weeks after rehabilitation in the longitudinal cohort study Rehabilitation, Sports and Active lifestyle (ReSpAct 1.0). Latent Class analyses were used to characterize diversity in the course of fatigue and PA (trajectories from T0-T3), based on questionnaire data. Based on these trajectories and participants’ characteristics (gender and age), a heterogeneous subsample of the ReSpAct 1.0 study (N=20) will be invited, around 5-7 years post stroke rehabilitation, to fill in a short questionnaire and to participate in a semi-structured interview on how they experience their course of fatigue and PA and how they divide their energy and daily PA during the day. The qualitative data will be combined with individual fatigue and PA trajectories and data on activity pacing behaviour into a longitudinal mixed-methods study. Audiotapes of the interviews will be transcribed verbatim. Both a thematic inductive and a deductive analysis (based on the Behaviour Change Wheel Taxonomy, centred on activity pacing behaviour) will be performed.Results: Three fatigue trajectories were identified: (1) stable high (N=163), (2) stable low (N=41) and (3) recovery (N=2). Three PA trajectories were identified: (1) moderately active (N=196), (2) active (N=35) and (3) strongly improved PA (N=4). Further results will be presented during the ISBNPA2020 conference.Discussion: We found a large diversity in fatigue and PA trajectories post stroke rehabilitation (T0-T3). Further findings of this study will provide a deeper understanding of the diversity in perceived fatigue in people after stroke and the role of activity pacing behaviour to obtain/maintain a physically active lifestyle