This article explores staff work patterns in an Australian residential aged care facility and the implications for high‐quality care. Rarely available minute by minute, time and motion, and ethnographic data demonstrate that nurses and care staff engage in high degrees of multitasking and mental switching between residents. Mental switching occurs up to 18 times per hour (every 3 min); multitasking occurs on average for 37 min/h. Labor process theory is used to examine these outcomes and to explore the (...) concepts of high demand and high commitment as core components of work intensification. These conditions of work result in high levels of cognitive burden and stress on staff in managing the multitasking and mental switching, exacerbated by lack of knowledge about residents associated with labor force casualization. These new interpretations of data in relation to mental and manual labor can contribute to understanding, and, therefore, problem solving, in the aged care sector. (shrink)

The study aim was 2-fold (i) to describe and compare the in-season variations of acute: chronic workload ratio (ACWR) coupled, ACWR uncoupled, and exponentially weighted moving average (EWMA) through session-rated perceived exertion (s-RPE), total distance (TD), high-speed running distance (HSRD), and sprint distance across different periods of a professional soccer season (early, mid, and end-season) between starters and non-starters; (ii) to analyze the relationship the aforementioned measures across different periods of the season for starters and non-starters. Twenty elite soccer players (...) (mean ± SD age, 29.4 ± 4.4 y; height, 1.8 ± 0.1 m; and body mass, 74.8 ± 2.3 kg). They were divided into starter and non-starter groups and were evaluated for 20 weeks. ACWR had general changes throughout the season. At the beginning and end of the mid-season, the highest ACWR was observed in three parameters: s-RPE, TD, and HSRD. ACWR and EWMA through sprint distance were higher at the beginning of the early-season than at any other time of the season.The ACWR coupled of s-RPE shows a significant higher value for non-starters than starters (p = 0.015;g = −1.01 [−1.98, −0.09]) and the ACWR coupled of TD shows a significant higher value for starters than non-starters in early-season (p < 0.01;g = 3.01 [1.78, 4.46]) and shows a significant higher value for non-starters than starters in mid-season (p < 0.01;g = −2.52 [−3.83, −1.39]), and end-season (p < 0.01;g = −2.57 [−3.89, −1.43]). While the EWMA of TD shows a significant higher value for starters than non-starters in early-season (p < 0.01;g = 2.25 [1.17, 3.49]) and mid-season (p < 0.01;g = 2.42 [1.31, 3.71]), and shows a significant higher value for non-starters than starters in end-season (p < 0.01;g = −2.23 [−3.47, −1.16]). Additionally, we found some correlations between external and internal load measures during three periods of the in-season. The study’s main finding was that the indexes of ACWR and EWMA were useful to detect differences between period and between playing status with the exception for the sprint variable. In addition, the necessary work for non-starter players’ improvement is not done during training, and these players lose their readiness as the season progresses. Consequently, these players perform poorly during the match. Therefore, coaches and their staff should consider devising new activities to keep non-starter players physically fit. This deficit must be accounted for in training because they compete in fewer matches and have less burden than starters. (shrink)