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Aims: Employee-based flexible working hours are increasing, particularly among knowledge workers. Research indicates that women and men use work–time control (WTC; control over time off and daily hours) differently: while men work longer paid hours, women use WTC to counteract work–life interference. In a knowledge-worker sample, we examined associations between WTC and overtime, work–life interference and exhaustion and tested whether gender moderates the mediating role of overtime. Methods: The sample contained 2248 Swedish knowledge workers. Employing hierarchical regression modelling, we examined effects of control over time off/daily hours on subsequent overtime hours, work–life interference and exhaustion in general and in gender-stratified samples. Using conditional process analysis, we tested moderated mediation models. Results: Control over time off was related to less work–life interference (βmen= −0.117; 95% confidence interval (CI): −0.237 to 0.003; βwomen= −0.253; 95% CI: −0.386 to −0.120) and lower exhaustion (βmen= −0.199; 95% CI: −0.347 to −0.051; βwomen= −0.271; 95% CI: −0.443 to −0.100). For control over daily hours, estimates were close to zero. While men worked more overtime (42 min/week), we could not confirm gender moderating the indirect effect of control over time off/daily hours on work–life interference/exhaustion via overtime. Independent of gender, effects of control over time off on work–life interference were partly explained by working fewer overtime hours. Conclusions: Control over time off was related to lower exhaustion and better work–life balance (in particular for women). We found no evidence for men's work–life interference increasing with higher WTC owing to working more overtime. Knowledge workers' control over time off may help prevent work–life interference and burnout. [ABSTRACT FROM AUTHOR]

Laboratory based sleep deprivation studies demonstrate that lack of sleep impairs well-being and performance ability, but suggest that these effects are mitigated in older adults. Yet, much less is known whether day-to-day variations of sleep have similar consequences in the context of everyday life. This project uses an intensive longitudinal design to investigate the occurrence of day-today variations in sleep and their impact on mood and performance in everyday life and to examine whether effects differ between young and older adults. We aim to include 160 young (18–30  years) and 160 older adults (55–75  years) to complete a 21-day experience sampling method (ESM) protocol. During the ESM period, participants are asked to fill in (i) a brief morning questionnaire, (ii) 8 short daytime questionnaires addressing momentary well-being, sleepiness, stress, and mind wandering, followed by a 1  min cognitive task and (iii) a brief evening questionnaire, all delivered via a mobile phone application. Sleep will be measured using self-reports (daily questions) and objectively with wrist actigraphy. The impact of adult age on mean levels and intraindividual variability of sleep will be analyzed using mixed-effects location scale models. The impact of sleep on daily cognitive performance will be analyzed using multilevel linear mixed models. The relationship of sleep to mean values and variability of positive and negative affect in young and older adults will be analyzed using mixed-effects location scale modeling. The overarching purpose of the project is improving the current knowledge on the occurrence of day-to-day variations in sleep and their relationship to performance as well as positive and negative affect in young and older adults. [ABSTRACT FROM AUTHOR]

This study explores the prevalence of attributed causes of disturbed sleep and the association between stress‐disturbed sleep and age, sex, and sleep duration on weekdays as well as weekends in a representative sample. A nationally representative sample (n = 1,128, response rate 72.8%), stratified for sex and age, completed a computer‐assisted phone survey that included questions about sleep disturbances and attributed causes. Stress was the main attributed cause of sleep disturbance (35.1%), most frequently attributed by younger women (χ2 = 26.5, p < 0.001). Prevalence of stress‐disturbed sleep was higher with lower age (B = −0.05, odds ratio (OR) = 0.94, CI = 0.91, 0.98). There was a trend, however, toward a significant interaction between age and sex, with women in the older age‐groups more frequently reporting stress‐disturbed sleep than older men (B = −0.02, OR = 1.022, CI = 1.003, 1.042). Weekday sleep duration decreased with increased stress‐disturbed sleep, with an inverse relationship on weekends except for those reporting stress‐disturbed sleep more than 5 days per week (F = 10.5, p < 0.001), who also had the shortest weekend sleep duration. Sleep disturbances were commonly attributed to stress, and more strongly so in women younger than 46 years. Stress‐disturbed sleep during weekdays seems to be potentially compensated for with extended sleep on weekends, except for those with continuous stress‐disturbed sleep. [ABSTRACT FROM AUTHOR]

Summary: Accelerometers placed on the thigh provide accurate measures of daily physical activity types, postures and sedentary behaviours, over 24 h and across consecutive days. However, the ability to estimate sleep duration or quality from thigh‐worn accelerometers is uncertain and has not been evaluated in comparison with the 'gold‐standard' measurement of sleep polysomnography. This study aimed to develop an algorithm for sleep estimation using the raw data from a thigh‐worn accelerometer and to evaluate it in comparison with polysomnography. The algorithm was developed and optimised on a dataset consisting of 23 single‐night polysomnography recordings, collected in a laboratory, from 15 asymptomatic adults. This optimised algorithm was then applied to a separate evaluation dataset, in which, 71 adult males (mean [SD] age 57 [11] years, height 181 [6] cm, weight 82 [13] kg) wore ambulatory polysomnography equipment and a thigh‐worn accelerometer, simultaneously, whilst sleeping at home. Compared with polysomnography, the algorithm had a sensitivity of 0.84 and a specificity of 0.55 when estimating sleep periods. Sleep intervals were underestimated by 21 min (130 min, Limits of Agreement Range [LoAR]). Total sleep time was underestimated by 32 min (233 min LoAR). Our results evaluate the performance of a new algorithm for estimating sleep and outline the limitations. Based on these results, we conclude that a single device can provide estimates of the sleep interval and total sleep time with sufficient accuracy for the measurement of daily physical activity, sedentary behaviour, and sleep, on a group level in free‐living settings. [ABSTRACT FROM AUTHOR]