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Summary: Background: Symptom fluctuations within and between individuals with long COVID are widely reported, but the extent to which severity varies following different types of activity and levels of exertion, and the timing of symptoms and recovery, have not previously been quantified. We aimed to characterise timing, severity, and nature of symptom fluctuations in response to effortful physical, social and cognitive activities, using Ecological Momentary Assessments. Methods: We recorded activity, effort, and severity of 8 core symptoms every 3 h for up to 24 days, in cohorts from both clinic and community settings. Symptom severities were jointly modelled using autoregressive and moving average processes. Findings: Consent was received from 376 participants providing ≥1 week's measurements (273 clinic-based, 103 community-based). Severity of all symptoms was elevated 30 min after all categories of activity. Increased effort was associated with increased symptom severity. Fatigue severity scores increased by 1.8/10 (95% CI: 1.6–1.9) following the highest physical exertions and by 1.5 (1.4–1.7) following cognitive efforts. There was evidence of only mild delayed fatigue 3 h (0.3, 0.2–0.5) or one day later (0.2, 0.0– 0.5). Fatigue severity increased as the day progressed (1.4, 1.0–1.7), and cognitive dysfunction was 0.2 lower at weekends (0.1–0.3). Interpretation: Cognitive, social, self-care and physical activities all triggered increased severity across every symptom, consistent with associated common pathways as potential therapeutic targets. Clear patterns of symptom fluctuations emerged that support more targeted self-management. Funding: National Institute for Health and Care Research.

Introduction: There has been a rapid adoption of telerehabilitation services, particularly during the COVID-19 pandemic, with minimal guidance or evaluation of benefit. This survey explores experiences of video consultations in a specialist outpatient neurorehabilitation service. Methods: Digital surveys were designed to evaluate experience of Attend Anywhere. Anyone could answer the survey after attending a video consultation. Setting and participants: Patients and doctors, occupational therapists, physiotherapists and speech and language therapists from a specialist outpatient neurorehabilitation service, between January and November 2020. Results: A total of 637 surveys were analysed. 74.6% of clinicians and 46.4% of patients indicated that video consultations were effective (X2=158.6, p < 0.001). Physiotherapists indicated that video consultation was not as effective as face to face (30.6%, X2=12.5, p = 0.052). Over 95% of clinicians and patients reported that they would use the video consultation system again X2=5.8, p < 0.016. Conclusions: Video consultation offers potential for improving access to healthcare for patients with complex neurological conditions.

Despite evidence that inactivity is a major factor causing ill health in people with intellectual disabilities (pwID) there are gaps in our knowledge of their physical activity (PA). To date, there is no published systematic review of their PA levels. Therefore, we performed a systematic review from January–October 2015, comprising studies from across the globe to establish PA levels, determine how they were measured, and what factors influenced PA in adults with intellectual disabilities (awID). Five databases were searched. Studies were included if written in English, peer-reviewed, had primary research data, and measured PA levels of awID. Quality was assessed using a 19-item checklist. Meta-summary of the findings was performed and a meta-analysis of factors influencing PA using multiple regression.Fifteen studies were included consisting of 3159 awID, aged 16–81 years, 54% male and 46% female. Only 9% of participants achieved minimum PA guidelines. PA levels were measured using objective and subjective methods. ID severity, living in care, gender, and age were independently significantly correlated with the number of participants achieving PA guidelines with the strongest predictor being ID severity (Beta 0.631, p