The influence of sleep on subjective well-being: An experience sampling study

Previous research has associated sleep with subjective well-being (SWB), but less is known about the underlying within-person processes. In the current study, we investigated how self-reported and actigraphy-measured sleep parameters (sleep onset latency, sleep duration, sleep satisfaction, social jetlag, and sleep efficiency) influence SWB (positive affect [PA], negative affect [NA], and life satisfaction [LS]) at the within- and between-person levels. Multilevel analyses of data from 109 university students who completed a 2-week experience sampling study revealed that higher within-person sleep satisfaction was a significant predictor of all three components of next day's SWB (ps < .005). Higher between-person sleep satisfaction was also related to higher levels of PA and LS (ps < .005), whereas shorter self-reported between-person sleep onset latency was associated with higher PA and LS, and lower NA (ps < .05). However, longer actigraphy-measured within-person sleep onset latency was associated with higher next day's LS (p = .028). When including within- and between-person sleep parameters into the same models predicting SWB, only within- and between-person sleep satisfaction remained a significant predictor of all components of SWB. Additionally, we found an effect of higher self-reported within-person sleep onset latency on PA and of shorter self-reported within-person sleep duration on LS (ps < .05). Our results indicate that the evaluative component of sleep-sleep satisfaction-is most consistently linked with SWB. Thus, sleep interventions that are successful in not only altering sleep patterns but also enhancing sleep satisfaction may stand a better chance at improving students' SWB. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Intraindividual Variability and Temporal Stability of Mid-Sleep on Free and Workdays

People differ in their sleep timings that are often referred to as a chronotype and can be operationalized as mid-sleep (midpoint between sleep onset and wake-up). The aims of the present studies were to examine intraindividual variability and longer-term temporal stability of mid-sleep on free and workdays, while also considering the effect of age. We used data from a 2-week experience sampling study of British university students (Study 1) and from a panel study of Estonian adults who filled in the Munich Chronotype Questionnaire twice up to 5 years apart (Study 2). Results of Study 1 showed that roughly 50% of the variance in daily mid-sleep scores across the 14-day period was attributed to intraindividual variability as indicated by the intraclass correlation coefficient. However, when the effect of free versus workdays was considered, the intraindividual variability in daily mid-sleep across 2 weeks was 0.71 the size of the interindividual variability. In Study 2, mid-sleep on free and workdays showed good levels of temporal stability-the retest correlations of mid-sleep on free and workdays were 0.66 and 0.58 when measured twice over a period of 0-1 to 5 years. The retest stability of mid-sleep scores on both free and workdays sharply increased from young adulthood and reached their peak when participants were in late 40 to early 50 years of age, indicating that age influences the stability of mid-sleep. Future long-term longitudinal studies are necessary to explore how age-related life circumstances and other possible factors may influence the intraindividual variability and temporal stability of mid-sleep.

Bedtime social media use, sleep, and affective wellbeing in young adults: an experience sampling study

BACKGROUND

Findings from primarily cross-sectional studies have linked more extensive social media use to poorer sleep and affective wellbeing among adolescents and young adults. This study examined bedtime social media use, sleep, and affective wellbeing, using an experience sampling methodology with the aim of establishing a day-to-day temporal link between the variables. The study hypothesized a positive association between increased bedtime social media use and lower affective wellbeing the following day, mediated by poorer sleep.

METHODS

Using a smartphone application, 101 undergraduate students (M_age  = 19.70 years, SD = 1.09 years), completed daily questionnaires assessing the previous night's bedtime social media use and sleep duration and satisfaction (one measurement per day, questionnaire sent at 08:00), and momentary affective wellbeing (five measurements per day, at randomly varying times between 08:00 and 22:00 on weekdays and 10:00 and 22:00 on weekends), for 14 consecutive days. Objective assessments of total sleep time and sleep efficiency were obtained via wrist-worn actigraphs. By means of separate multilevel models, it was tested whether increased bedtime social media use predicted poorer sleep the same night, whether poorer sleep was predictive of positive and negative affect the following day, and whether sleep mediated the relationship between social media use and affective wellbeing.

RESULTS

Increased bedtime social media use was not associated with poorer sleep the same night. Apart from subjective sleep satisfaction, no other sleep variable (i.e., subjective sleep duration, objective total sleep time and objective sleep efficiency) predicted positive or negative affect the following day.

CONCLUSIONS

This study found that bedtime social media use is not detrimental to the sleep and affective wellbeing of healthy young adults. However, it is possible that bedtime social media use may be harmful to the sleep of vulnerable individuals.