Purpose: To identify Health-related Quality of Life (HR-QoL) trajectories in a large heterogeneous cohort of people with a physical disability and/or chronic disease during and after rehabilitation and to determine which factors before discharge are associated with longitudinal trajectory membership. Methods: A total of 1100 people with a physical disability and/or chronic disease were included from the longitudinal cohort study Rehabilitation, Sports and Active lifestyle. All participants participated in a physical activity promotion programme in Dutch rehabilitation care. HR-QoL was assessed using the RAND-12 Health Status Inventory questionnaire at baseline (T0: 3–6 weeks before discharge) and at 14 (T1), 33 (T2) and 52 (T3) weeks after discharge from rehabilitation. A data-driven approach using Latent Class Growth Mixture modelling was used to determine HR-QoL trajectories. Multiple binomial multivariable logistic regression analyses were used to determine person-, disease- and lifestyle-related factors associated with trajectory membership. Results: Three HR-QoL trajectories were identified: moderate (N = 635), high (N = 429) and recovery (N = 36). Trajectory membership was associated with person-related factors (age and body mass index), disease-related factors (perceived fatigue, perceived pain and acceptance of the disease) and one lifestyle-related factor (alcohol consumption) before discharge from rehabilitation. Conclusions: Most of the people who participated in a physical activity promotion programme obtained a relatively stable but moderate HR-QoL. The identified HR-QoL trajectories among our heterogeneous cohort are disease-overarching. Our findings suggest that people in rehabilitation may benefit from person-centred advice on management of fatigue and pain (e.g. activity pacing) and the acceptance of the disability.

Fatigue is common in people with multiple sclerosis (MS). Activity pacing is a behavioral way to cope with fatigue and limited energy resources. However, little is known about how people with MS naturally pace activities to manage their fatigue and optimize daily activities. This study explored how activity pacing relates to fatigue and physical activity in people with MS. Participants were 80 individuals (60 females, 20 males) with a diagnosis of MS. The participants filled in questionnaires on their activity pacing, fatigue, physical activity, and health-related quality of life, 3–6 weeks before discharge from rehabilitation. The relationships between the variables were examined using hierarchical regression. After controlling for demographics, health-related quality of life, and perceived risk of overactivity, no associations were found between activity pacing and fatigue (β = 0.20; t = 1.43, p = 0.16) or between activity pacing and physical activity (β = −0.24; t = −1.61, p = 0.12). The lack of significant associations between activity pacing and fatigue or physical activity suggests that without interventions, there appears to be no clear strategy amongst people with MS to manage fatigue and improve physical activity. People with MS may benefit from interventions to manage fatigue and optimize engagement in physical activity.

The current study determined the test–retest reliability and concurrent validity of the Adapted Short QUestionnaire to ASsess Health-enhancing physical activity (Adapted-SQUASH) in adults with disabilities. Before filling in the Adapted-SQUASH twice with a recall period of 2 weeks, participants wore the Actiheart activity monitor up to 1 week. For the test–retest reliability (N = 68), Intraclass correlation coefficients (ICCs) were 0.67 (p < 0.001) for the total activity score (min x intensity/week) and 0.76 (p < 0.001) for the total minutes of activity (min/week). For the concurrent validity (N = 58), the Spearman correlation coefficient was 0.40 (p = 0.002) between the total activity score of the first administration of the Adapted-SQUASH and activity energy expenditure from the Actiheart (kcals kg⁻¹ min⁻¹). The ICC was 0.22 (p = 0.027) between the total minutes of activity assessed with the first administration of the Adapted-SQUASH and Actiheart. The Adapted-SQUASH is an acceptable measure to assess self-reported physical activity in large populations of adults with disabilities but is not applicable at the individual level due to wide limits of agreement. Self-reported physical activity assessed with the Adapted-SQUASH does not accurately represent physical activity assessed with the Actiheart in adults with disabilities, as indicated with a systematic bias between both instruments in the Bland–Altman analysis.

Human movement, rehabilitation, and allied sciences have embraced their ambitions within the cycle of “RehabMove” congresses over the past 30 years. This combination of disciplines and collaboratio...

To identify fatigue trajectories during/after stroke rehabilitation, to determine characteristics associated with trajectory membership before discharge and to investigate how these trajectories an...

Background Little is known of physical activity behaviour among adults with a disability and/or chronic disease during and up to 1 year post-rehabilitation. We aimed to explore (1) dose characteristics of physical activity behaviour among adults with physical disabilities and/or chronic diseases during that period, and (2) the effects of personal characteristics and diagnosis on the development of physical activity over time. Methods Adults with physical disabilities and/or chronic diseases (N=1256), enrolled in the Rehabilitation, Sports and Active lifestyle study, were followed with questionnaires: 3–6 weeks before (T0) and 14 (T1), 33 (T2) and 52 (T3) weeks after discharge from rehabilitation. Physical activity was assessed with the adapted version of the Short Questionnaire to ASsess Health enhancing physical activity. Dose characteristics of physical activity were descriptively analysed. Multilevel regression models were performed to assess physical activity over time and the effect of personal and diagnosis characteristics on physical activity over time. Results Median total physical activity ranged from 1545 (IQR: 853–2453) at T0 to 1710 (IQR: 960–2730) at T3 min/week. Household (495–600 min/week) and light-intensity (900–998 min/week) activities accrued the most minutes. Analyses showed a significant increase in total physical activity moderate-intensity to vigorous-intensity physical activity and work/commuting physical activity for all time points (T1–T3) compared with baseline (T0). Diagnosis, age, sex and body mass index had a significant effect on baseline total physical activity. Conclusion Physical activity is highly diverse among adults with physical disabilities and/or chronic diseases. Understanding this diversity in physical activity can help improve physical activity promotion activities.