The sedentary behaviour and physical activity patterns of survivors of a critical illness over their acute hospitalisation: An observational study

Construct validity of the Functional Status Score for the Intensive Care Unit: a prospective observational study using actigraphy in mechanically-ventilated patients

“…Schweickert et al [49] and Schaller et al [50] have shown that critically ill patients participating in early mobilisation programmes that provide more activity time than usual care have lower mortality rates, fewer days with delirium, shorter duration of mechanical ventilation, and better functional performance. Additionally, actigraphy studies have shown that patients tend to increase their activity from their hospital stay up to the post-ICU follow-up [23,51,52]. Consequently, the main hypothesis for this study was that greater time or amount of movement during the ICU stay (actigraphy) would relate to better mobility (FSS-ICU), and also, that greater inactivity time would relate to worse scores in the FSS-ICU.…”

“…A recent randomised controlled trial reported high proportions of inactivity time during the ICU stay, with 95.7% for the control group and 92.3% for the group receiving early and progressive mobilisation [32]. Moreover, Baldwin et al identified high levels of sedentary behaviour (defined as time spent lying/sitting) before awakening (98.1%) and at ICU discharge (95.7%), which were correlated with mobility assessed with the PFIT-s and the Morton Mobility Index (rho= -0.73, P < 0.001) [51]. The present study also found a moderate to strong correlation between inactivity time (defined as low intensity movement) and mobility measured with the FSS-ICU on awakening (rho= -0.62, P < 0.001) and at ICU discharge (rho= -0.79, P < 0.001).…”

“…Future research should study and report on the lack of movement of critically ill patients because, according to the current literature, patients are inactive for extended periods, which is associated with worse mobility [32,51]. There is still the challenge to measure movement in real-time to guide and inform decision-making regarding dosage and strategies for preventing immobility of critically ill patients.…”

Prediction framework for upper body sedentary working behaviour by using deep learning and machine learning techniques

“…It is important to understand what interventions are successful and why interfering to reduce sedentary behaviour among working-age adults, especially where sedentary behaviour has been identified and types of sedentary behaviour known to be most damaging to health outcomes (Zhang et al 2020 ). However, in view of its high impact on those populations and school classrooms (Baldwin et al 2020 ), sedentary behavioural interventions have focused mainly on younger population groups, especially children under eleven years old and teenagers and young people under 11 to 18 years of age. Fewer intervention studies focused on workers, older adults and short- and medium-sized students, such as university students (Giurgiu et al 2020 ).…”

A novel early mobility bundle improves length of stay and rates of readmission among hospitalized general medicine patients

“…This decline in functional status is multifactorial in origin and has been attributed to poor pain management, improper nutrition, sleep disturbances, and as an effect of the illness which precipitated the admission [2,[4][5][6][7][8]. In particular, prolonged immobilization and subsequent deconditioning is a very common cause of functional decline during hospitalization and many studies have demonstrated that hospitalized patients are mobilized infrequently and spend most of their time in bed [9][10][11][12][13]. As such, these patients are vulnerable to a host of hospitalization-related complications including the inability to preform activities of daily living, increased length of stay (LOS), frequent readmissions, and the need for discharge to rehabilitation facilities [2,[14][15][16][17][18].…”