Sleep patterns among preschool offspring of parents with and without psychopathology: Association with the development of psychopathology in childhood.

BACKGROUND: Disturbed sleep during early childhood predicts social-emotional problems. However, it is not known how various early childhood sleep phenotypes are associated with the development of childhood psychopathology, nor whether these relationships vary as a function of parental psychopathology. We identified sleep phenotypes among preschool youth; examined whether these phenotypes were associated with child and parent factors; and determined if early sleep phenotypes predicted later childhood psychopathology. METHODS: Using data from the Pittsburgh Bipolar Offspring study, parents with bipolar disorder (BD), non-BD psychopathology, and healthy controls reported about themselves and their offspring (n = 218) when their children were ages 2-5. Offspring and parents were interviewed directly approximately every 2 years from ages 6-18. Latent class analysis (LCA) identified latent sleep classes; we compared these classes on offspring demographics, parental sleep variables, and parental diagnoses. Kaplan-Meier survival models estimated hazard of developing any new-onset Axis-I disorders, as well as BD specifically, for each class. RESULTS: The optimal LCA solution featured four sleep classes, which we characterized as (1) good sleep, (2) wake after sleep onset problems, (3) bedtime problems (e.g., trouble falling asleep, resists going to bed), and (4) poor sleep generally. Good sleepers tended to have significantly less parental psychopathology than the other three classes. Risk of developing new-onset Axis-I disorders was highest among the poor sleep class and lowest among the good sleep class. CONCLUSIONS: Preschool sleep phenotypes are an important predictor of the development of psychopathology. Future work is needed to understand the biopsychosocial processes underlying these trajectories.

It's past your bedtime, but does it matter anymore? How longitudinal changes in bedtime rules relate to adolescents' sleep.

This study investigated how changing or maintaining parent-set bedtimes over time relates to adolescents' sleep timing, latency, and duration. Adolescents (n = 2509; Mage = 12.6 [0.5] years; 47% m) self-reported their sleep patterns, and whether they had parent-set bedtimes on two separate occasions in 2019 (T1; 12.6 years) and 2020 (T2; 13.7 years). We identified four groups based on parent-set bedtimes: (1) bedtime rules at both T1 and T2 (46%, n = 1155), (2) no bedtime rules at T1 nor T2 (26%, n = 656), (3) bedtime rules at T1 but not T2 (19%, n = 472), (4) no bedtime rules at T1 but a parent-set bedtime at T2 (9%, n = 226). As expected, the entire sample showed that bedtimes generally became later and sleep duration shorter across adolescence, but the change differed among the groups. Adolescents whose parents introduced bedtime rules at T2 reported earlier bedtimes and longer sleep duration (~20 min) compared with adolescents with no bedtime rules at T2. Importantly, they no longer differed from adolescents who consistently had bedtimes across T1 and T2. There was no significant interaction for sleep latency, which declined at a similar rate for all groups. These results are the first to suggest that maintaining or re-introducing a parent-set bedtime may be possible and beneficial for adolescents' sleep.

The relationship between family cohesion and bedtime procrastination among Chinese college students: the chain mediating effect of coping styles and mobile phone addiction.

BACKGROUND: Bedtime procrastination refers to an individual's inability to go to bed at a predetermined time without external obstacles. Previous researchers have found that the bedtime procrastination is harmful to human physical and mental health, but these research on bedtime procrastination have mostly focused on exploring individual factors, while ignoring the external environmental factors. Therefore, this is the first study to investigate bedtime procrastination from the perspective of family environments. METHODS: The study was conducted using a convenient sampling method and online questionnaires. Family Cohesion Scale, Coping Styles Questionnaire, Mobile Phone Addiction Tendency Scale and Bedtime Procrastination Scale were used to measure sleep and psychological condition of 1,048 college students. RESULTS: Family cohesion negatively predicted bedtime procrastination. Additionally, positive coping style and mobile phone addiction had significant independent mediating effects. Furthermore, positive coping style and mobile phone addiction had chain mediating effects between family cohesion and bedtime procrastination. CONCLUSION: This study revealed the effect of coping styles and mobile phone addiction on the relationship between family cohesion and bedtime procrastination among Chinese college students. These findings explained the mechanisms of bedtime procrastination from the perspective of environment, so as to effectively intervene the bedtime procrastination of college students from the perspective of external environment.

Sleep behaviors predicted sleep disturbances among Chinese health science students: a cross-sectional study.

PURPOSE: Healthy sleep is essential for individuals' physiological and psychological health. Health science students experience a high prevalence of sleep disturbances which may be due to maladaptive behaviors. This study aimed to examine the associations of sleep behaviors including sleep hygiene and bedtime procrastination with the associations of sleep disturbances (e.g., poor sleep quality, insomnia, and short sleep). METHODS: This cross-sectional study included health science students from a medical university in Shanghai, China. Sleep disturbances included poor sleep quality, insomnia, and short sleep. They were measured by the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and one question "How many hours of sleep did you usually get during the past week?", respectively. Sleep behaviors included sleep hygiene and bedtime procrastination measured by the Sleep Hygiene Index (SHI) and Bedtime Procrastination Scale (BPS), respectively. Logistic regression was performed while controlling for potential confounders. RESULTS: A total of 464 health science students participated. Poorer overall sleep hygiene and more bedtime procrastination were independently associated with higher odds of poor sleep quality (OR=1.065, 95% CI 1.028-1.103; OR=1.040, 95% CI 1.006-1.075, respectively) and insomnia (OR=1.059, 95% CI 1.018-1.101; OR=1.093, 95% CI 1.049-1.139, respectively). More bedtime procrastination was associated with higher odds of short sleep (OR=1.148, 95% CI 1.093-1.206). Commonly reported specific sleep behaviors, such as "Going to bed later than intended", "Doing other things than sleep at bedtime", and "Easily stopping what I am doing at bedtime", were also related to higher odds of sleep disturbances. CONCLUSIONS: Sleep hygiene and bedtime procrastination were strong predictors of sleep disturbances. Tailored interventions targeting specific sleep behaviors are warranted to clarify their effect on sleep disturbances.

Bedtime procrastination related to loneliness among Chinese university students during post-pandemic period: a moderated chain mediation model.

BACKGROUND: This study examined the relationship between loneliness and bedtime procrastination among Chinese university students, the mediating effects of COVID-19 risk perception and self-regulatory fatigue, and connectedness to nature's protective role, post pandemic. METHODS: We recruited 855 students to complete the Loneliness, Perceived Risk of COVID-19 Pandemic, Self-Regulatory Fatigue, Bedtime Procrastination, and Connectedness to Nature Scales. Data for descriptive statistics, correlation analysis, and moderated chain mediation effects were analyzed using SPSS 24.0 and process 3.5 macros. RESULTS: Loneliness positively correlated with bedtime procrastination, COVID-19 risk perception mediated the impact of loneliness on bedtime procrastination, self-regulatory fatigue mediated the effect of loneliness on bedtime procrastination, and COVID-19 risk perception and self-regulatory fatigue mediated the effect between loneliness and bedtime procrastination. Furthermore, connectedness to nature mediated the impact of COVID-19 risk perception on self-regulatory fatigue. CONCLUSIONS: The results indicate the effects and potential mechanisms of loneliness on bedtime procrastination after the relaxation of the pandemic prevention and control policy in China from the perspective of self-regulatory resources and provide insights into improving university students' sleep routine and mental health post pandemic.

Sleep patterns are associated with cardiometabolic risk factors in nine-year-old Swedish children.

AIM: Sleep duration and bedtime may play a role in children's cardiometabolic health, but research is lacking. This study examined associations between sleep patterns and cardiometabolic risk factors in Swedish nine-year-olds. METHODS: This cross-sectional study used data from three studies, where identical outcome measures were conducted in 411 nine-year-olds, 51% boys, between 2016 and 2020. Sleep was assessed with wrist-worn accelerometers and sleep journals. Children were grouped based on meeting the sleep guidelines of 9-11 h and going to bed early or late based on the median bedtime. Analysis of covariance was used to examine associations between sleep patterns and cardiometabolic risk factors. RESULTS: Meeting sleep guidelines and going to bed early were associated with lower metabolic syndrome score (-0.15 vs. 0.42, p = 0.029), insulin resistance (0.30 vs. 0.60, p = 0.025) and insulin levels (6.80 vs. 8.87 mIU/L, p = 0.034), compared with their peers who did not meet the guidelines and went to bed later. When adjusting for total sleep time, analyses still showed associations with the metabolic syndrome score (-0.19 vs. 0.50, p = 0.011). CONCLUSION: The findings indicate that good sleep patterns could help mediate positive overall cardiometabolic health in children.

Late bedtime combined with more screen time before bed increases the risk of obesity and lowers diet quality in Spanish children.

This cross-sectional study aimed to investigate whether the combination of bedtime and screen time (ST) before bed were associated with obesity and diet quality in toddlers and school-aged children. Parents reported children's bedtimes and ST before bed (0 min, 1-30 min, >30 min). We then defined bed + screen time behavior using bedtime median cut-offs (early [EB] or late [LB]) and ST responses, resulting in four groups: EB-0'ST, EB ≤ 30'ST/LB-0'ST, EB > 30'ST/LB ≤ 30'ST, and LB > 30'ST. For all participants (n = 1133; 5.4 ± 2.7 years, 49.7% girls, 51.9% school-aged) we evaluated body mass index (BMI), diet quality, sleep-related variables, physical activity, and health-related quality of life (HRQoL). Outcome variables were compared across bed + screen time behavior groups, stratified by age group (toddlers and school-aged children) using general linear models for continuous variables, as well as chi-squared tests or logistic regressions for categorical variables. Additionally, we calculated linear p-trends. Analyses were adjusted for sociodemographic variables, BMI, and physical activity (unless the variable was tested). The results showed that toddlers and school-aged children in the LB ≥ 30'ST group were more likely to have overweight/obesity (OR: 3.42 [95%CI:1.41,8.26] and OR: 2.53 [95%CI:1.10,5.03], respectively) than those in the EB-0'ST group. Additionally, toddlers and school-aged children in the EB > 30'ST/LB ≤ 30'ST and LB > 30'ST groups showed significantly lower adherence to the Mediterranean diet compared to the other groups (p < 0.001). Regarding sleep-related outcomes, we observed that the combination of LB and more ST was associated with poorer sleep quality and shorter sleep duration in toddlers and school-aged children (p < 0.001). These findings emphasize the importance of promoting earlier bedtimes and limiting ST before bed as part of obesity prevention strategies for children. Furthermore, such intervention could benefit the quality of children's diet and overall lifestyle.

Impact of Social Media Addiction and Internet Gaming Disorder on Sleep Quality: Serial Mediation Analyses.

Poor sleep quality is a concerning and prevalent consequence of social media addiction (SMA) and internet gaming disorder (IGD). Due to the lack of research examining how SMA and IGD lead to poor sleep quality, the current study aimed to understand the relationship between SMA and sleep quality, as well as that between IGD and sleep quality, through impulse control and bedtime procrastination. The study tested the hypotheses that higher levels of SMA and IGD would predict lower levels of impulse control, which would then predict higher levels of bedtime procrastination, leading to poorer sleep quality. A serial mediation analysis was performed with a sample of 221 participants (63.3% females, 34.4% males, and 2.3% prefer not to say) aged 18 to 53 years (M = 23.64, SD = 5.72). Participants completed questionnaires that assessed for social media addiction, internet gaming disorder, impulse control factor, bedtime procrastination, and sleep quality. There was a full serial mediation of impulse control and bedtime procrastination in the relationship between SMA and sleep quality, as well as that between IGD and sleep quality, providing support for the hypotheses. The findings provide the knowledge needed to develop and implement strategies that target impulse control issues and reduce bedtime procrastination to improve sleep quality.

Staying up late increases cardiovascular disease risk in women with polycystic ovary syndrome.

STUDY QUESTION: What is the association between late bedtime, night sleep duration, and lifetime cardiovascular disease (CVD) risk in women with polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: Both late bedtime (≥1:00) and short sleep duration (<7 h/night) were independently associated with a high-lifetime CVD risk among women with PCOS. WHAT IS KNOWN ALREADY: Previous studies indicated that sleep disturbances, including altered sleep duration and staying up late (SUL), occurred more frequently among women with PCOS compared to women without PCOS. Studies have shown that both PCOS and sleep disturbances are associated with deterioration in cardiometabolic health in the longer term. However, there are limited data regarding the possible association between sleep disturbances and CVD risk among reproductive-aged women with PCOS. STUDY DESIGN, SIZE, DURATION: From the original 393 women identified at our center, a total of 213 women with PCOS aged 18-40 years were enrolled in a cross-sectional study between March 2020 and July 2022. PARTICIPANTS/MATERIALS, SETTING, METHODS: Bedtime and night sleep duration were obtained from a standardized self-administered questionnaire. The prediction for atherosclerotic CVD risk in the China risk model was applied to estimate the lifetime CVD risk in the PCOS population. Restricted cubic spline regression was applied to explore the non-linear association between sleep duration and lifetime CVD risk in a series of models. Multivariable logistic regression analyses were performed to determine the association between bedtime, night sleep duration, and lifetime CVD risk. MAIN RESULTS AND THE ROLE OF CHANCE: In our study, we found that the proportion of SUL was 94.25% and the mean (±SD) of night sleep duration was 7.5 ± 1.1 h in women with PCOS. Restricted cubic spline regression analysis showed a U-shaped relation between sleep duration and lifetime CVD risk. After adjusting for occasional drinking, fasting insulin, triglyceride, low-density lipoprotein cholesterol, and testosterone in multivariable logistic analyses, compared with going to bed at 23-24 o'clock, those who went to bed after 1 o'clock were independently associated with high-lifetime CVD risk [odds ratio (OR) = 3.87, 95% CI: 1.56-9.62]; compared with optimal sleep duration (7-8 h/night), short sleep (<7 h/night) was also independently associated with high-lifetime CVD risk (OR = 2.46, 95% CI: 1.01-5.97). LIMITATIONS, REASONS FOR CAUTION: Inferring causality is limited owing to the cross-sectional design. All sleep variables data were obtained from a standardized self-administered questionnaire rather than measurements using objective approaches. Even after adjusting for potential confounders, we still cannot completely rule out the possibility of residual confounding from unmeasured factors such as socioeconomic status. Future studies with larger sample sizes are needed to further explore the relation between long sleep duration and lifetime CVD risk. Although these findings are not generalizable to non-SUL PCOS populations, they could be used for guiding multidimensional treatment. Lastly, there is no non-PCOS group in the current cross-sectional study, which limits the interpretation of the findings from the PCOS group. WIDER IMPLICATIONS OF THE FINDINGS: This is the first study to report that both late bedtime (≥1:00) and short sleep duration (<7 h/night) were independently associated with a high-lifetime CVD risk among reproductive-aged women with PCOS, in a sample of Chinese adults. Predicting cardiovascular risk and examining the association between sleep disturbances and predicted CVD risk among women with PCOS help to highlight the need for early interventions on sleep to improve their cardiovascular outcomes. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the Natural Science Foundation of Fujian Province (No. 2020J011242), the Fujian provincial health technology project (No. 2022CXB016), the Joint Research Projects of Health and Education Commission of Fujian Province (No. 2019-WJ-39), and the Medical and Health project of Xiamen Science & Technology Bureau (No. 3502Z20214ZD1001). The authors declare that they have no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Variation in sleep profiles in children with ADHD and associated clinical characteristics.

BACKGROUND: Sleep difficulties are common in children with attention-deficit/hyperactivity disorder (ADHD). However, sleep problems are multifaceted and little is known about the variation in sleep difficulties across children with ADHD. We examined the profiles of sleep difficulties in children with ADHD and associated clinical factors (e.g. co-occurring mental health conditions, stimulant use and parent mental health). METHODS: Data from two harmonised studies of children with ADHD (total: N = 392, ages 5-13 years) were used. Parents completed measures of children's sleep, co-occurring mental health conditions and their own mental health. Both parents and teachers completed measures of child ADHD symptoms and emotional and conduct symptoms. Latent profile analysis was used to identify sleep profiles, and multinomial logistic regression assessed clinical correlates of the groups. RESULTS: Five sleep profiles were identified: (a) insomnia/delayed sleep phase (36%), (b) generalised sleep difficulties at sleep onset and overnight (25%), (c) high anxious/bedtime resistance difficulties (11%), (d) overnight sleep difficulties including obstructive sleep apnoea and parasomnias (5%) and (e) no sleep difficulties (22%). Compared with the group without sleep difficulties, the generalised, anxious/bedtime resistance and insomnia/delayed sleep phase sleep had greater parent-reported emotional and conduct symptoms, co-occurring anxiety and increased parent mental health difficulties. The generalised and anxious/bedtime resistance groups also had greater parent-reported ADHD symptoms, with the anxious/bedtime resistance sleep group also having more frequent co-occurring depression and teacher-reported emotional symptoms. CONCLUSIONS: The sleep difficulties experienced by children with ADHD are varied. Supports to help children with ADHD need to consider the particular profiles of sleep difficulties experienced and broader clinical characteristics. Tailored intervention approaches are likely needed (including a need to address parent mental health).

The night before night shift: Chronotype impacts total sleep and rapid eye movement sleep during a strategically delayed sleep.

Transition to night shift may be improved by strategically delaying the main sleep preceding a first night shift. However, the effects of delayed timing on sleep may differ between chronotypes. Therefore, the study aim was to compare the impacts of chronotype on sleep quality and architecture during a normally timed sleep opportunity and a delayed sleep opportunity. Seventy-two (36 female, 36 male) healthy adults participated in a laboratory study. Participants were provided with a normally timed sleep opportunity (23:00-08:00) and a delayed sleep opportunity (03:00-12:00) over two consecutive nights in a sleep laboratory. Sleep was monitored by polysomnography (PSG), and chronotype was determined from dim light melatonin onset (DLMO). A tertile split of DLMO defined early (20:24 ± 0:42 h), intermediate (21:31 ± 0:12 h), and late chronotype (22:56 ± 0:54 h) categories. Although there was no main effect of chronotype on any sleep measure, early chronotypes obtained less total sleep with delayed sleep than with normally timed sleep (p = 0.044). Intermediate and late chronotypes obtained more rapid eye movement (REM) sleep with delayed sleep than with normally timed sleep (p = 0.013, p = 0.012 respectively). Wake was more elevated for all chronotypes in the later hours of the delayed sleep opportunity than at the start of the sleep opportunity. Strategically delaying the main sleep preceding a first night shift appears to benefit intermediate and late chronotypes (i.e., more REM sleep), but not early chronotypes (i.e., less total sleep). Circadian processes appear to elevate wakefulness for all chronotypes in the later stages of a delayed sleep opportunity.

Delayed bedtime on non-school days associates with higher weight and waist circumference in children: Cross-sectional and longitudinal analyses with Mendelian randomisation.

Sleep duration has been linked with obesity in population-based studies. Less is known about bedtimes and, especially, if discrepancy between bedtimes on school and non-school days associate with adiposity in children. The associations of self-reported bedtimes with the body mass index z-score (BMIz) and waist-to-height ratio (WtHr) were examined among children with a mean (SD) age of 11.2 (0.85) years in cross-sectional (n = 10,245) and longitudinal (n = 5085) study settings. The causal relationship of whether BMIz contributes to bedtimes, was further examined in a subset of 1064 participants by exploiting Mendelian randomisation (MR). After adjusting for sleep duration and other confounders, every 0.5 h later bedtime on non-school nights and a delay in bedtime in non-school nights compared with school nights associated with 0.048 (95% CI 0.027; 0.069) and 0.08 (95% CI 0.056; 0.105) higher BMIz as well as 0.001 (95% CI 0; 0.002) and 0.004 (95% CI 0.003; 0.005) with higher WtHr, respectively. Moreover, every 0.5-h delay in bedtime in non-school nights compared with school nights associated with 0.001 (95% CI 0; 0.002) greater increase in WtHr in the 2.5 years follow-up. Thus, a 2-h delay in bedtime at the age of 11 years corresponds with a 0.6 cm increase in waist circumference. The MR analysis did not indicate an opposite causal relationship: higher BMIz was not causing delayed bedtimes. Later bedtime on non-school days and discrepancy in bedtimes associated with increased BMIz and WtHr, while longitudinally these predicted higher WtHr, independently of sleep duration. Promoting early bedtimes, especially on weekends, should be considered in obesity prevention among school-aged children.

Longitudinal course and outcome of social jetlag in adolescents: A 1-year follow-up study of the adolescent sleep health epidemiological cohorts.

The discrepancy in sleep timing between weekdays and weekends - social jetlag (SJL) - is known to negatively affect student quality of life (QOL). However, the association between social jetlag and physical/mental QOL among adolescents and the precise effect of social jetlag on depressive symptoms and daytime sleepiness remains unknown. This study investigated the longitudinal course, risk factors, and effects of social jetlag, a circadian misalignment, in a school-based cohort. The participants were 427 students (13.3 ± 0.6 years, 45.2% girls) from five junior high schools. We performed a baseline survey in 2019 and a 1-year follow-up survey in 2020. Depressive symptoms, QOL, and daytime sleepiness were assessed using the Birleson Depression Self-Rating Scale for Children, Paediatric Quality of Life Inventory, and Paediatric Daytime Sleepiness Scale. In the baseline survey, 49.6% of the students reported SJL ≥1 h, and 17.1% reported SJL ≥2 h. Among them, 37.2% and 6.8% reported persistent SJL at follow-up, respectively. New incidences of SJL ≥1 h were associated with older age, non-attainment of menarche or voice changes, and longer duration of smartphone use, whereas its persistence was associated with a later chronotype. Persistence of SJL ≥1 h and ≥2 h predicted depressive symptoms and daytime sleepiness at follow-up, whereas new incidences of SJL ≥2 h predicted lower QOL. In conclusion, social jetlag has a persistent course, and daytime functioning can deteriorate as social jetlag becomes chronic. Our findings suggest the need for intensive interventions for social jetlag among adolescents.

Development and validation of the while-in-bed-smartphone-use-induced sleep procrastination scale (WSPS) in Chinese undergraduates with/without problematic smartphone use.

PURPOSE: Problematic smartphone use (PSU) has become a global public health problem. Excessive while-in-bed smartphone use may result in sleep procrastination and other negative outcomes. The present study aimed to develop and validate a new scale called WSPS to assess while-in-bed-smartphone-use-induced sleep procrastination among undergraduates. METHODS: In total, 910 Chinese undergraduates completed the collection of WSPS, smartphone addiction scale-short version (SAS-SV), bedtime procrastination scale, Pittsburgh sleep quality index, and Zung self-rating depression scale. The whole sample were randomly splited in the exploratory factor analysis (EFA) sample (n = 455) and confirmatory factor analysis (CFA) sample (n = 455). 40 undergraduates with PSU (SAS-SV > 31) and 40 without PSU were asked to keep sleep diary for 2 weeks and complete the WSPS again. RESULTS: EFA and CFA supported a six-item unidimensional structure of the WSPS. The WSPS demonstrated acceptable internal consistency among undergraduates. The WSPS showed good concurrent validity with other relevant variables including PSU, BP, sleep quality, and depression. Scalar invariance of the WSPS between undergraduates with/without PSU was supported, as well as scalar invariance across gender. The WSPS showed good convergent validity with self-report everyday while-in-bed smartphone use duration and good discriminant validity with sleep duration and sleep onset latency recorded by sleep diary. The WSPS also presented good test-retest reliability among undergraduates with/without PSU. CONCLUSION: The WSPS is a reliable and valid measure of while-in-bed-smartphone-use-induced sleep procrastination in undergraduates with/without PSU.

The effect of smartphone addiction on the relationship between psychological stress reaction and bedtime procrastination in young adults during the COVID-19 pandemic.

BACKGROUND: Previous studies on bedtime procrastination mainly focused on the influencing factors of stress and draw less attention on the role of family environment. AIM: This study aimed to explore the effect of psychological stress reaction on bedtime procrastination in young adults, with considering the mediating effect of smartphone addiction, and the moderating effect of family cohesion during the COVID-19 pandemic. METHODS: A sample of 1217 young adults completed psychological stress reaction scale, Smartphone addiction tendency scale for young adults, bedtime procrastination scale and family cohesion scale. A moderated mediation model was conducted to clarify the effect of psychological stress reaction on bad bedtime procrastination in young adults. RESULTS: The findings showed that: (1) The individual level of psychological stress reaction was positively associated with bedtime procrastination; (2) Smartphone addiction mediated the effect of psychological stress reaction on bedtime procrastination; (3) Family cohesion moderated the relationship among psychological stress reaction, smartphone addiction and bedtime procrastination. CONCLUSIONS: This study revealed the effect of smartphone addiction on the relationship between psychological stress reaction and bedtime procrastination during the COVID-19 pandemic, and these findings could provide novel evidence that family cohesion may serve as a protective factor against the negative consequences of smartphone addiction on bad bedtime procrastination.

Mobile phone dependency and sleep quality in college students during COVID-19 outbreak: the mediating role of bedtime procrastination and fear of missing out.

OBJECTIVE: The purpose of this study was to investigate the associations between mobile phone dependency, bedtime procrastination, FoMO, and sleep quality among college students during the COVID-19 outbreak. Specifically, we examined whether bedtime procrastination and FoMO mediate the relationship between mobile phone dependency and sleep quality. METHODS: A total of 881 college students completed an online survey in May 2022 in Shanghai, China. Mobile Phone Involvement Questionnaire, Bedtime Procrastination Scale, Fear of Missing Out Scale and Pittsburgh Sleep Quality Index were used to assess mobile phone dependency, bedtime procrastination, fear of missing out, and sleep quality, respectively. Multiple linear regression and mediation analysis were conducted. RESULTS: The correlation analyses indicated mobile phone dependency was positively associated with fear of missing out, bedtime procrastination, and poor sleep quality among college students. The structural equation modeling analyses revealed that mobile phone dependency had significant indirect effects on sleep quality through bedtime procrastination (indirect effect: 0.030, 95%CI: 0.022-0.041) and fear of missing out (indirect effect: 0.013, 95%CI: 0.003-0.023). CONCLUSION: The findings indicated that bedtime procrastination and fear of missing out are mediators mediating the relationship between mobile phone dependency with sleep quality. Bedtime procrastination and fear of missing out should be considered as potential intervention targets for reducing mobile phone dependency and improving sleep quality in college students.

The Effect of Trait Anxiety on Bedtime Procrastination: the Mediating Role of Self-Control.

BACKGROUND: Bedtime procrastination (BP), a special type of health behavior procrastination, is considered to be a failure of self-control. Notably, self-control may mediate the effect of trait anxiety on general procrastination. However, there is no evidence demonstrating the role of self-control in the relationship between trait anxiety and BP. Moreover, the association between BP and trait anxiety has not yet been thoroughly studied. Therefore, the present study aimed to explore the direct relationship between them as well as the mediating role of self-control in this relationship. METHODS: This cross-sectional survey included 718 college students enrolled in Chinese universities between October 2018 and January 2020. The Chinese versions of the Bedtime Procrastination Scale, the Self-Control Scale, and the Trait Anxiety Inventory were used to evaluate BP, self-control, and trait anxiety, respectively. RESULTS: Multiple linear regression analysis revealed trait anxiety independently predicted BP while controlling for demographic characteristics. Correlation analyses showed that BP was positively correlated with trait anxiety, but negatively related to self-control. Structural equation modeling further revealed a mediating role of self-control in the relationship between trait anxiety and BP. CONCLUSIONS: Trait anxiety is a significant independent predictor of BP and may induce BP directly or indirectly through the effect of self-control. These findings provide a deeper understanding of the relationship between trait anxiety and BP and the underlying mechanism by exploring the mediating effect of self-control. As such, trait anxiety and self-control should be included in prevention and intervention strategies to address BP behavior in college students.

Association between sleep duration, sleep quality, bedtime and myopia: A systematic review and meta-analysis.

BACKGROUND: We performed a systematic review and meta-analysis to investigate the links between different sleep characteristics and risk of myopia. METHODS: PubMed, EMBASE, Web of Science, the Cochrane Library, PsycINFO, Wanfang, and CNKI were searched from inception to August 26, 2022, without any language restriction. Cross-sectional, case-control, or cohort studies that explored the association between sleep duration, sleep quality, bedtime, and myopia were included. NIH quality assessment tools were used to assess the methodological quality of included studies. Random-effect or fixed-effect models were used to pool the associations according to whether there is heterogeneity. RESULTS: A total of 31 studies with 205 907 participants were included in the final analysis (25 studies reporting sleep duration; four studies examining sleep quality and six studies evaluating bedtime). Compared to reference sleep duration, sufficient sleep duration (OR = 0.63, 95% CI = 0.51-0.78) was associated with a lower risk of myopia, and short sleep duration (OR = 1.66, 95% CI = 1.14-2.42) was associated with a higher risk of myopia. In addition, poor sleep quality (OR = 1.24, 95% CI = 1.05-1.47) was associated with a higher risk of myopia while late bedtime (OR = 1.30, 95% CI = 0.96-1.75) was not significantly associated with an increased risk of myopia. CONCLUSIONS: Alteration in sleep duration and sleep quality may influence the risk of myopia. Well-designed cohort studies are needed in future investigations to identify a causal relationship between different sleep characteristics and myopia.

Activities and social contact as antecedents to sleep onset time in U.S. adolescents.

This study evaluated adolescents' evening patterns in activities, social contact, and location to better understand antecedents to adolescents' sleep onset time (SOT). The SOT is important for sleep duration and related health outcomes. Using a nationally representative sample of 15- to 18-year-old adolescents from the American Time Use Survey (N = 10,341; 47% female; 57% white), structural equation modeling demonstrated that late SOTs mediated links between evening activities, social contact, locations, and shorter sleep durations. Passive leisure, time in public locations, and time with friends late in the evenings were associated with later SOTs, whereas homework and active leisure did not. Parents and practitioners can use this information to carefully evaluate evening activities, social contact, and location to support healthy SOTs for adolescents across time.

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; ageM = 22.15 years; ageSD = 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 (ß = 0.33, p < .001) and non-planning impulsivity (ß = -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.