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 (Mage  = 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.

Effects of a 20 minutes delay in school start time on bed and wake up times, daytime tiredness, behavioral persistence, and positive attitude towards life in adolescents.

OBJECTIVES: Preliminary evidence suggests that delaying school start times is an effective tool for improving adolescent sleep duration. Our study assessed whether a policy driven 20-minute delay in school start times led to an increase in adolescents' weekday bed and wake up times. METHOD: Data collected via school satisfaction surveys concerned 663 students (45.2% females, Mean age: 14.91 years, SD = 0.58 years) in three lower-track secondary schools in Switzerland. Of all the students, 249 experienced a policy-driven 20-minutes school start time change (SSTc), from 7.40 am to 8.00 am between the eighth and ninth grade, while 414 students did not (Comparison Group/CG). Students filled out the survey twice, at the end of their eighth and ninth grades, respectively, and reported their weekday bed and wake up times, daytime tiredness, behavioural persistence, and positive attitude towards life. RESULTS: Generalized estimating equations models of bed and wake up times showed that there was a significant delay in both the bed and wake up times of the students in the SSTc group. Multilevel analyses revealed that students in the SSTc group did not significantly differ from CG students in daytime tiredness, behavioural persistence, and positive attitude towards life. CONCLUSIONS: Findings suggest that not only wake up times but also bed times may shift later when school start times are delayed. The 20 minutes delay in school start times may have been too slight to have an impact on daytime tiredness, behavioral persistence and positive attitude towards life.

A pilot cluster-randomised study to increase sleep duration by decreasing electronic media use at night and caffeine consumption in adolescents.

OBJECTIVE: Bedtime electronic media use and caffeine consumption are risk factors for insufficient sleep and poor sleep quality during adolescence, which are in turn risk factors for mental wellbeing. Our study tested the effectiveness of a brief school-based psychoeducative intervention to primarily increase sleep duration, by decreasing bedtime electronic media use and caffeine consumption. Secondary outcomes included improving sleep quality and difficulties, daytime tiredness, and mental wellbeing. METHOD: A pilot cluster-randomised controlled study was conducted involving a 25-min psychoeducative school-based intervention combined with parent information. 352 adolescents from seven schools participated (Intervention Group/IG = 192 students vs. Control Group/CG = 160 students; age: Mean = 15.09 years; SD = 1.65 years; Females = 163). The intervention included information on the importance of sleep and good sleep hygiene habits, particularly emphasizing behavioural rules of avoiding electronic media use at night and evening-time caffeine consumption. A leaflet containing the rules was also sent to parents of IG participants. Baseline and post-intervention sessions were held approximately four weeks apart. RESULTS: Multilevel analyses revealed a significant but modest decrease in electronic media use for participants in the IG versus CG, but showed no effect on caffeine consumption or sleep duration. Moreover, the intervention did not impact any secondary outcome. CONCLUSIONS: Findings indicate the potential effectiveness of a short and easily administrable intervention to decrease electronic media use at night, which may be incorporated into school curricula and standardised for wider use in primary prevention. However, no further benefits of the intervention were found.