Figure - uploaded by Liese Exelmans
Content may be subject to copyright.
Proposed timeline
Source publication
This study argues that going to bed may not be synonymous with going to sleep and that this fragmentation of bedtime results in a two-step sleep displacement. We separated bedtime (i.e. going to bed) from shuteye time (i.e. attempting to go to sleep once in bed) and assessed the prevalence of electronic media use in both time slots. A convenience s...
Similar publications
This study examined sleep concerns among direct-care workers in long-term care and their perceived need for a sleep intervention. Thirty-five participants reported their sleep concerns and willingness to participate in a sleep intervention with preferred delivery forms/content. Multiple sleep characteristics were assessed via ecological momentary a...
Citations
... Bedtime was identified from the video footage as when the participant went to bed for the night and got underneath the bed covers. Shuteye time was identified as when the participant was in bed, had stopped all interactions (including any screen time and conversations with parents) and was attempting to go to sleep [21]. If video footage for bedtime or shuteye times was absent, subjective daily diary entries (n = 14 nights) or a questionnaire assessing 'usual' bedtime and shuteye times (n = 2) was used. ...
Background
Although evening screen time is thought to impair subsequent sleep, current measures are limited to questionnaires which seem unlikely to accurately assess screen time in youth. Given the ubiquitous nature of digital devices, improving measurement of screen time is required before related health effects can be appropriately determined. The aim of this study was to objectively quantify screen time before sleep using video camera footage.
Methods
This repeated-measures observational study in healthy adolescents (11–14 years) from Dunedin, New Zealand measured screen time on four evenings over one week in the home environment from March-December 2021. Wearable and stationary PatrolEyes video cameras captured screen time from two hours before bedtime until sleep and manually coded for device type (phone, tablet, laptop computer, desktop computer, handheld gaming console, gaming console, television and other) and screen activity (watching, listening, reading, educational/creative, browsing, communication, social media, video gaming, multitasking) using a reliable coding schedule (κ ≥ 0.8). Descriptive findings are reported.
Findings
Among the 83 participants (mean 12.3 [SD 1.0] years, 42% female, 52% New Zealand European, 37% Māori [indigenous]), 82 used screens in the two hours before bed on 308 of 344 (90%) nights for a mean of 54.4 min (SD 25.5). Televisions (median 37 min, 56% of nights), phones (19 min, 64% nights), and multitasking using multiple devices (19 min, 48% nights) were most commonly used (> 75% of adolescents). Once in bed but before trying to sleep, 58% of adolescents engaged in screen time for 17 (26.3) minutes on 36% of nights. The most common screen activities were watching (32.5%), social media (26.5%) and communication (20.5%). Even after attempting sleep, 32.5% of participants used screens for 8.0 min (median) on 16% of nights, mostly listening on phones.
Conclusions
Objective video cameras offer detailed insight into evening screen habits, capturing frequency, content, and duration. Youth frequently engage with screens before bed and throughout the night on a range of activities, despite recommendations to restrict screen time prior to sleep.
Trial registration
Australian New Zealand Clinical Trials Registry (anzctr.org.au), AACTRN12621000193875, Registered 23 February 2021, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380926&isReview=true.
... . . (Exelmans & Van den Bulck, 2017), (Cajochen, 2007), (Cain & Gradisar, 2010) . (Bernier et al., 2010;Merín et al., 2024). ...
Objectives: This study explored whether sleep problems in young children mediate the relationship between smart media overdependence and cool (inhibition, working memory, and shifting) and hot (delay of gratification) executive functions.Methods: Participants were 207 children, aged 3–5 years and their mothers. Cool executive functions such as inhibition, working memory, and shifting were assessed using the day-night, eight-box, and dimensional change card sort tasks, respectively. Hot executive function was evaluated using the delay of gratification task. Pearson’s correlation analysis was conducted to examine the associations between variables. A structural equation model was tested to confirm the mediating role of sleep problems in the relationship between smart media overdependence and executive function using AMOS 27.0. The significance of the indirect effect was evaluated using bootstrapping. Children’s age and household income were included as control variables in the analyses.Results: The results indicated that young children’s sleep problems had a fully mediating effect on the relationship between smart media overdependence and executive function, after accounting for the children's age and household income. The influence of smart media overdependence on executive function mediated by sleep problems was domain-specific. Specifically, smart media overdependence indirectly affected shifting, but not inhibition, working memory, or delay of gratification through sleep problems.Conclusion: To reduce the negative impact of smart media overdependence on executive functions, particularly regarding shifting ability, it is necessary to not only prevent smart media overdependence, but also to emphasize the importance of sleep and implement targeted interventions to promote optimal sleep quality.
... That is, loneliness can have an impact on individual behavior (mobile phone addiction) through an individual's cognition (rumination) and affect (negative affect). Immersion theory also proposes (Csikszentmihalyi, 1990) that mobile phone addicted individuals are more likely to be immersed in the mobile phone experience, which affects the individual's sense of time and self-consciousness, leading to late bedtimes and shorter sleep duration, which negatively affects sleep quality (Exelmans & Van den Bulck, 2017). ...
... That is, rumination consists of responses such as constantly trying to figure out why one is overusing the Internet, reading articles about it, or talking to friends about overusing the Internet, thereby exhibiting excessive mobile phone use, which in turn interferes with sleep quality. As described by the sleep displacement hypothesis, mobile phone use, as a typical leisure activity with unstructured temporal characteristics, delays bedtime and affects sleep quality (Exelmans & Van den Bulck, 2017;Liu et al., 2017). Therefore, in order to improve students' sleep problems, schools not only need to guide students to change irrational cognitions, but also guide them to use smartphones rationally. ...
... Secondly, they can use catharsis and humorous methods to regulate self-bad emotions caused by ruminant thinking. Finally, college students should gradually reduce sleep problems (Exelmans & Van den Bulck, 2017;Liu et al., 2017). In addition, many individuals may unknowingly utilize inappropriate sleep habits to reduce sleep disruption. ...
This study aimed to investigate the relationship between loneliness and sleep quality and its intrinsic mediating mechanism. The UCLA Loneliness Scale, Ruminative Responses Scale, Mobile Phone Addiction Index Scale, as well as the Depression-Anxiety-Stress Scale and Self-Rating Scale of Sleep were used to investigate 1145 college students. Results showed that: (1) Loneliness, rumination, negative affect, mobile phone addiction and sleep quality were all significantly and positively correlated with each other; (2) Five mediating pathways existed for the effect of loneliness on sleep quality: the separate mediation of negative affect; the partial mediation of rumination and negative affect, rumination and mobile phone addiction, negative affect and mobile phone addiction; the chain mediation of rumination, negative affect, and mobile phone addiction, with a total mediating effect value of 0.22, accounting for 73.33% of the total effect (direct effect of 0.08); (3) The mediating effect of loneliness on sleep quality exhibits cross-gender consistency. In conclusion, loneliness has a significant predictive effect on sleep quality, which is manifested through the mediating effects of negative affect, rumination, and mobile phone addiction, with negative affect alone mediating the greatest effect, and the study provides a new intervention perspective for improving sleep quality.
... Although various mechanisms have been suggested to explain the relationship between media use and sleep, two major competing explanations are 1) the sleep displacement hypothesis and 2) the media recovery hypothesis. The sleep displacement hypothesis predicts that bedtime media pushes back sleep onset and thus time that would have been spent sleeping is instead spent using media (Exelmans & Van den Bulck, 2017). Not only is sleep displacement due to media associated with less total sleep time, but also with worse sleep quality (Custers & Van den Bulck, 2012). ...
... Not only is sleep displacement due to media associated with less total sleep time, but also with worse sleep quality (Custers & Van den Bulck, 2012). That said, many adults and adolescents turn to media before bed as a sleep aid (Eggermont & Van den Bulck, 2006;Exelmans & Van den Bulck, 2017), as media may serve as a low-effort, relaxing activity that can help users recover from workday stress and strain (Reinecke & Rieger, 2020). Recovery is the process of replenishing and rebalancing stressed systems so that individuals may return to normal functioning, and recovery experiences are those which provide psychological detachment from work, relaxation, mastery, and affect-regulation (Sonnentag et al., 2017). ...
... The authors suggested that this was due to time shifting -that is, media use was related to later sleep onset, but also later wake times (see also Custers & Van den Bulck, 2012;Van den Bulck, 2004). Exelmans and Van den Bulck (2017) have suggested that sleep displacement may be a two-step process, with media use shifting bedtimes later (bedtime displacement) as well as time to fall asleep (shuteye latency). Thus, we broadly consider "sleep displacement processes," based on previous research in this area, as a cascade of decisions from media use, to bedtime delay, to sleep disruption. ...
... Consistent with our hypothesis, sleep quality mediated the relationship between IGD and daily cognitive failures. This finding can be explained by the displacement of sleep hypothesis (Exelmans & Van den Bulck, 2017). This theory postulated that playing games during nighttime reduces sleep duration. ...
Internet gaming disorder (IGD) refers to sustained, uncontrolled online gaming behavior associated with negative consequences. Previous research has revealed that IGD was a risk factor for daily impaired cognitive outcomes. However, the potential underlying mechanisms are not clear. The present study aimed to examine the mediating role of sleep quality and the moderating role of mindfulness in the link between IGD and daily cognitive failures. Data are from 851 university students using self-reported questionnaires. The results indicated that IGD positively predicted daily cognitive failures and sleep quality partially mediated this association. Furthermore, mindfulness did not regulate the direct pathway between IGD and daily cognitive failures. It moderated the mediating effect of sleep quality, specifically, low mindfulness amplified the positive effect of IGD on daily cognitive failures through sleep quality. This study contributes to a better understanding of the negative influence of IGD on cognitive ability and facilitates the development of targeted prevention strategies aimed at reducing sleep problems and cognitive deficits in daily life for university students with IGD.
... In addition, it remains unclear whether two different forms of nighttime smartphone use, that is, smartphone use shortly before bedtime (pre-bedtime use) and after bedtime (post-bedtime use), have comparable effects on adolescents' sleep quality. Although pre-and post-bedtime use may inherently differ in their effects on sleep quality (see Exelmans & Van Den Bulck, 2017), this distinction has often been overlooked in previous research (e.g., Kühnel et al., 2021;So et al., 2021;Tkaczyk et al., 2023). Therefore, the current study differentiates between daytime, pre-bedtime, and post-bedtime usage in investigating the effects of adolescents' smartphone use on their sleep quality. ...
... In addition, the sleep displacement hypothesis postulates that the time spent on the smartphone may directly displace sleep duration (e.g., Cain & Gradisar, 2010). For instance, adolescents' smartphone use after getting into bed may result in longer shuteye latencies, that is, extending the period between bedtime and closing the eyes (Exelmans & Van Den Bulck, 2017), leaving less time for sleep. As sleep duration is an important aspect of one's overall evaluation of sleep (Phillips et al., 2020), it is likely that adolescents' prolonged smartphone use directly after bedtime negatively affects their sleep quality. ...
The smartphone occupies a substantial part of adolescents’ daily life, from the moment they wake up to, for some, well beyond their bedtime. The current study compared the impact of adolescents’ daytime, pre-bedtime, and post-bedtime smartphone use on their sleep quality. In addition, it explored the differential effects of lean-back and lean-forward smartphone apps. We collected data from 155 adolescents across 21 days using smartphone tracking (745,706 app activities) in combination with experience sampling (1,950 sleep quality assessments). We found no significant effects of daytime and pre-bedtime smartphone use on sleep quality, but a negative association of post-bedtime smartphone use with sleep quality (β = −.09). The association between smartphone use and sleep quality varied across app categories: Time spent on lean-forward apps around bedtime, such as social media apps right before (β = −.08) and game apps after bedtime (β = −.23), was associated with lower sleep quality. The use of lean-back apps (i.e., video players) was not associated with sleep quality, neither before nor after bedtime.
... Research has shown that many people use electronic devices while in bed before sleeping. [15][16][17] Device use in bed is associated with periods of motionless wake that wearable devices may be poor at classifying. ...
... al., 2018). Time spent on smartphones and online gaming platforms can have adverse effects on sleep and sleep-aiding behavior (Exelmans & Bulck, 2017). To be able to carry out activities adequately, every individual needs sufficient sleep time, which is defined not just by the sleep time (sleep quantity), but also by the quality of sleep (Killgore,2010). ...
... Smartphones and other portable technological tools that may be carried to bed are a possible cause for both SMA and IGD-related sleep disruptions (Fossum et al., 2014). With portable cell phones and Wi-Fi connection, the internet (including social media) may be an unstructured, non-timebound activity that may absorb time and as a result, can contribute to sleeplessness (Exelmans & Bulck, 2017;Gezgin, 2018). Moreover, delayed bedtimes and late wake hours may contribute to rhythm dissonance and negatively affect academic performance (Chattu et.al., 2018). ...
The aim of the study was to examine the associations between Internet Gaming Disorder, Fear of Missing Out, and Sleep Quality among adolescents and emerging adults. A cross-sectional study was conducted among 67 individuals from Delhi NCR region (females=37 (62%) and males=30(45%). The data were collected via the convenience sampling method through social media platforms. The data obtained were analysed with the SPSS version 22 software package. The descriptive statistics for the sample under study shows a significance of internet gaming disorder, with an overall average score of 30.8657 (SD=12.22875), moderate risk of Fear of Missing Out, with an overall average score of 33.1791 (SD=10.979) and moderate levels of sleep difficulties with an average score of 11.5821 (SD=4.37676). Results show that male adolescents (15-19 years) tend to have higher levels of Internet Gaming Disorder and Fear of Missing Out as compared to emerging adults (20-24 years) and their female counterparts. Sleep Quality found to be slightly worse among male adolescents (15-19 years). Internet Gaming Disorder is found to be significantly correlated with Fear of Missing Out (ρ = 0.626) at 0.01 % level of significance and moderately correlated with Sleep Quality (ρ= 0.288) at 0.05% level of significance. Also, Fear of Missing Out is found to be significantly correlated with Sleep Quality (ρ= 0.384) at 0.01% level of significance. The p values for Internet gaming Disorder(p=0.208) and Fear of Missing Out(p=0.105) found to be more than 0.05 and hence they are not the predictors of Sleep Quality. The findings from the present study suggest that due care should be taken to address online gaming behaviours and social media usage. The more a person fears being left out, the more they may indulge in online gaming and other digital activities to compensate, which will disrupt their sleep rhythms and lead to poorer sleep habits. Moreover, lifestyle, familial, and social variables, mental health, and digital usage can all contribute to poorer sleep habits and sleep disruptions.
... Previous studies have demonstrated that PMPU is a significant predictor of poor sleep quality [11,18]. Excessive mobile phone use not only results in bedtime procrastination, but also leads to hyperarousal, which can impede falling asleep and reduce sleep quality [18][19][20]. For instance, a longitudinal study suggested that students with prolonged PMPU may experience a disturbed circadian rhythm, resulting in poor sleep quality [21]. ...
Background
With the widespread adoption of smartphones, there has been a notable increase in problematic mobile phone use (PMPU), particularly prevalent among college students. Research suggests that apart from being associated with various problematic behaviors, this excessive mobile phone use might also have an impact on individual personality traits, such as time management disposition (TMD), which plays a significant role in individual motivation and psychological well-being. While previous literature has identified a negative relationship between PMPU and TMD, few studies have delved into the underlying mediating mechanism. Thus, the main aim of this study was to examine the chain mediating effect of sleep quality and cognitive flexibility on the relationship between PMPU and TMD.
Methods
A total of 921 Chinese college students completed the questionnaire. We collected basic information about the participants and assessed their PMPU, TMD, sleep quality, and cognitive flexibility using the Problematic Mobile Phone Use Scale-10, Adolescence Time Management Disposition Inventory, Pittsburgh Sleep Quality Index scale and Cognitive Flexibility Inventory.
Results
The results indicated a significant correlation among all the variables. Moreover, we noted that both sleep quality and cognitive flexibility fully mediated the association between PMPU and TMD. Additionally, a chain mediating effect involving sleep quality and flexibility in this relationship was also identified.
Conclusion
We found that sleep quality and cognitive flexibility had a series of multiple mediating effects in the pathway from PMPU to TMD, and both significantly mediated TMD. These findings indicated that impaired cognitive function and sleep quality may contribute to time management difficulties resulting from PMPU, suggesting that problematic behaviors like PMPU can impact one’s personality traits. Therefore, interventions should be enhanced to mitigate the adverse effects of PMPU.
... The mechanisms with which ST interferes with sleep have been mainly studied in the adult population. The three major hypotheses are: (i) screen light directly suppresses melatonin levels [59], (ii) DM causes mental arousal [60], and (iii) ST displaces sleep time [61]. ...
Nowadays, children and adolescents are exposed to digital media (DM) from an early age. Therefore, specific guidelines have been published by the World Health Organization, whose aim is to limit daily screen time (ST) viewing. However, during the COVID-19 pandemic, a rise in DM use, and consequently ST viewing, was observed. More and more aspects of modern life are thought to be affected by excessive ST viewing. Accordingly, the aim of this review is to document the health effects of excessive ST viewing on children and adolescents. A narrative review was performed in searchable databases. In total, 43 original articles were considered. Excessive ST viewing was correlated with increased risk for obesity and other cardiometabolic risk factors, mental health, unhealthy dietary habits and eating disorders, and problems in development and child–parent relationships. Sleep, physical activity, eyesight, headaches, and the musculoskeletal system were negatively affected as well. However, the effect of ST was weighted by the type of media used and the way types of media were used. Other confounding factors were reported. There is evidence to suggest a negative correlation between excessive ST and youth health exists. Nevertheless, more research is needed if this correlation is to be established.
