A randomized controlled trial of a behavioral intervention for decreasing bedtime procrastination using a wait-list control group in a non-clinical sample of young adults

Postponing sleep after a stressful day: Patterns of stress, bedtime procrastination, and sleep outcomes in a daily diary approach

Sleep problems and stress are common among students and are associated with negative effects on academic performance as well as mental and physical health risks, but studies exploring mediating factors between stress and sleep on a daily basis are scarce. This study aimed to investigate the relationship of daily stress, Bedtime procrastination (BP) (i.e., postponing bedtime without external reasons), and sleep outcomes controlling for trait factors such as self-control. N = 96 students at a German university (M = 22.2 years, SD = 4.0) wore a sleep-tracking wearable (Fitbit Charge HR) for two weeks to assess sleep duration and to calculate the gap between the intended time to go to sleep and the objectively measured time of falling asleep. Stress, intended time to go to sleep, and sleep quality were assessed via daily diaries. Established questionnaires were used to measure trait self-control, trait BP, and smartphone addiction. Multilevel analyses indicated that more stress experienced during the day was associated with more BP (b = 2.32, p = 0.008), shorter sleep duration (b = -3.46, p = 0.003), and lower sleep quality (b = 1.03, p = 0.005) after controlling for several trait factors. The association of daily stress with sleep outcomes (quality and duration) was partly mediated by BP. Our findings indicate that BP might be one factor that contributes to stress-linked decreases in sleep duration and quality. Potential reasons for stress-related later time to fall asleep-like higher physiological arousal or stress-related worries-should be investigated in future studies.

A bidirectional model of sleep and technology use: A theoretical review of How much, for whom, and which mechanisms

The link between technology and sleep is more complex than originally thought. In this updated theoretical review, we propose a new model informed by the growing body of evidence in the area over the past 10 years. The main theoretical change is the addition of bi-directional links between the use of technology and sleep problems. We begin by reviewing the evidence to date for the originally proposed mechanisms of bright light, arousal, nighttime sleep disruptions, and sleep displacement. Then, in support of the new direction of effect (sleep problems preceding technology use), we propose two new mechanisms: technology before sleep might be used as a time filler and/or as an emotional regulation strategy to facilitate the sleep-onset process. Finally, we present potential moderators of the association between technology and sleep, in recognition of protective and vulnerability factors that may mitigate or exacerbate the effects of technology on sleep and vice versa. The goal of this theoretical review is to update the field, guide future public health messages, and to prompt new research into how much technology and sleep affect each other, for whom it may be problematic, and which mechanisms may explain their association.

Development and validation of the Japanese version of the Bedtime Procrastination Scale (BPS-J)

BACKGROUND

The average sleep duration of Japanese people is shorter than that of people from other countries, and bedtime procrastination is suspected to be one of the factors contributing to this issue. This study aimed to develop and validate the Japanese version of the Bedtime Procrastination Scale (BPS-J).

METHODS

The BPS-J was developed through procedures including the translation and back-translation of the scale, cognitive interviews with 100 participants who reported having experiences of being diagnosed with insufficient sleep syndrome (ISS) or receiving treatment for ISS using open-ended online questionnaires, and expert checking. To investigate the scale's validity and reliability, an online survey was conducted with daytime workers aged 20 - 65 years without a history of sleep disorders other than ISS. Half the participants were retested using the same survey after 14 days. Participants' responses to the Brief Self-Control Scale (BSCS), General Procrastination Scale (GPS), and Munich ChronoType Questionnaire (MCTQ), and data on sleep-related variables such as sleep duration on workdays and the days per week of fatigue or sleep loss, sex, and age, were collected.

RESULTS

We analyzed data from 574 participants to assess scale validity. We then analyzed data from 280 participants to determine test-retest reliability. Confirmatory factor analyses revealed that the two-factor model without Item 2 was most suitable for the BPS-J, unlike other language versions. Regardless of the full-item model or the model with Item 2 eliminated, sufficient reliability and significant correlations with the BSCS, GPS, MCTQ, and sleep-related variables such as sleep duration per night on work days, days per week of feeling fatigued, and days per week of sleep loss were observed. Logistic and linear regressions showed that the relationships between the BPS-J, sleep-related variables, and MCTQ were maintained after adjusting for sex and age.

CONCLUSION

The BPS-J had sufficient validity and reliability. Further, eliminating Item 2 from the original version of the BPS strengthened the ability to survey Japanese daytime workers.

Association between impulsivity and cognitive capacity decrease is mediated by smartphone addiction, academic procrastination, bedtime procrastination, sleep insufficiency and daytime fatigue among medical students: a path analysis

BACKGROUND

Medical students are at high risk for sleep disturbance. One possible cause of their sleeping problem is impulsivity. We aim to investigate the possible mediators between medical students' impulsivity and sleep outcomes. Thus, we developed and investigated a model where the predictors were attentional, non-planning, and motor impulsivity subtraits. In the final model, subjective cognitive capacity decrease was the outcome variable. In light of previous findings, academic procrastination, smartphone addiction, and bedtime procrastination were considered important mediators as well as two variables of poor sleep, sleeping insufficiency, and daytime fatigue.

METHODS

Medical students (N = 211; age_M = 22.15 years; age_SD = 3.47 years; 71.6% women) were recruited to complete an online survey comprised of demographics (age, gender), self-administered scales (Abbreviated Impulsiveness Scale, Bedtime Procrastination Scale, Abbreviated Impulsiveness Scale, Academic Procrastination Scale-Short Form) and questions on tiredness, daily fatigue and subjective cognitive capacity decrease. Correlation and path analyses were implemented to examine hypothesized relationships between the variables.

RESULTS

Both attentional impulsivity (β = 0.33, p < .001) and non-planning impulsivity (β = -0.19, p < .01) had a direct relationship with cognitive capacity decrease. Attentional impulsivity was also associated with decreased cognitive capacity with a serial mediation effect via smartphone addiction, academic procrastination, bedtime procrastination, sleep insufficiency and fatigue (estimate = 0.017, p < .01). The indirect link between non-planning impulsivity and cognitive capacity decrease was mediated by academic procrastination, bedtime procrastination, sleep insufficiency and fatigue (estimate = 0.011, p < .01).

CONCLUSIONS

Inability to stay focused and plan tasks effectively (directly and indirectly) predicts poor sleep outcomes. This relationship is mediated by excessive smartphone use, academic procrastination, and bedtime procrastination. Our findings are relevant in light of self-regulatory learning, which is crucial in medical education. This is a recursive cycle of planning, emotion regulation, proper strategy selection and self-monitoring. Future interventions addressing attentional and non-planning impulsivity, problematic smartphone use, academic procrastination, and in turn, bedtime procrastination might make this routine more effective. In the conclusion section, practical implications of the results are discussed.