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Objective: To assess (i) the impact of self-reported fatigue on functioning in daily life, and (ii) the association with sociodemographics, physical capacity, and work ability among people with post-COVID-19. Design: A cross-sectional study. Subjects: Adults reporting post-COVID-19 symptoms for at least 2 months. Methods: Participants were recruited through social media and responded to an online survey between October 2021 and February 2022 regarding sociodemographics, COVID-19 symptoms, comorbidities, physical and mental fatigue, aerobic capacity, and work ability. Descriptive statistics and logistic regression analyses were used. Results: A total of 614 participants (88% women, mean age 47 years, on average 13 months of symptoms) were included. A majority (≥ 84%) reported both physical fatigue and mental fatigue, according to the Fatigue Severity Scale and Mental Fatigue Scale. The fatigue impacted motivation, physical functioning, work, family, or social life, and increased sensitivity to stress and concentration difficulties. Among the factors, work ability had the strongest association with both physical fatigue and mental fatigue; odds ratio: 0.650 and 0.473, p

Abstract Background Assessments of arm motor function are usually based on clinical examinations or self-reported rating scales. Wrist-worn accelerometers can be a good complement to measure movement patterns after stroke. Currently there is limited knowledge of how accelerometry correlate to clinically used scales. The purpose of this study was therefore to evaluate the relationship between intermittent measurements of wrist-worn accelerometers and the patient’s progression of arm motor function assessed by routine clinical outcome measures during a rehabilitation period. Methods Patients enrolled in in-hospital rehabilitation following a stroke were invited. Included patients were asked to wear wrist accelerometers for 24 h at the start (T1) and end (T2) of their rehabilitation period. On both occasions arm motor function was assessed by the modified Motor Assessment Scale (M_MAS) and the Motor Activity Log (MAL). The recorded accelerometry was compared to M_MAS and MAL. Results 20 patients were included, of which 18 completed all measurements and were therefore included in the final analysis. The resulting Spearman’s rank correlation coefficient showed a strong positive correlation between measured wrist acceleration in the affected arm and M-MAS and MAL values at T1, 0.94 (p

Objective: To investigate (i) to what extent physiotherapists (PTs) working in stroke rehabilitation in various parts of the stroke care chain have implemented interventions according to the national guidelines for stroke (NGS), (ii) facilitating and hindering factors for the implementation, and (iii) differences between various care settings. Design: A cross-sectional study. Subjects: 148 PTs working in stroke rehabilitation in various parts of the care chain in Sweden. Methods: Data were collected by a web-based survey. Results: Task-specific training for walking (80–98%), impaired motor function (64–100%) and fall prevention (73–92%) were most implemented. Factors that facilitated implementation were: important to comply with the NGS, that PTs had confidence to perform the interventions, and that interventions were clearly described. Limited time, lack of resources, no clear goals or routines at the workplace hindered the implementation. Significant differences (p

Objective: To explore the associations between fatigue impact and (a) personal and stroke-related characteristics, (b) functional impairments and (c) work-related factors among individuals who have returned to work after stroke. Design: A cross-sectional exploratory study. Subjects: 87 working stroke survivors. Methods: This study comprises data from a postal survey targeting work ability and perceived stroke-related consequences 1 year after stroke. Fatigue was evaluated using the Fatigue Severity Scale (FSS). Factors associated with having fatigue (FSS total score ≥ 4) were identified using univariable and multivariable logistic regression analyses. Three domain-specific multivariable models and 1 final combined model were created. Results: Fatigue was reported by 43% of the participants. Several factors representing all the investigated domains were associated with fatigue. In the final combined regression model, self-perceived low cognitive functioning, low decision control at work and high quantitative job demands had the strongest independent effects on the odds of having fatigue. Conclusion: Among people who were working 1 year after stroke, fatigue was associated with both personal and stroke-related characteristics as well as functional impairments and work-related factors. This highlights the complex nature of post-stroke fatigue. Fatigue management interventions should have a comprehensive approach and also consider the work environment.