Screens and sleep: why the last scroll of the day steals your rest

Introduction: How the last scroll can delay and fragment rest

The last scroll highlights several processes that can shift bedtime, maintain active attention, and reduce available rest time. In adults, daily screen use in the hour before sleep is associated with a 33% higher prevalence of poor sleep quality and 7.64 minutes less sleep on weekdays compared to no screen use (Zhong et al., 2025) . In adolescents, the relationship depends on the timing: use after bedtime is linked to worse sleep quality, while daytime or immediate pre-bedtime use did not show this association in an intensive 21-day follow-up (Siebers et al., 2024) . Therefore, the question is not only how much screen time is used, but what activity is performed, what time it ends, and whether it replaces the effective onset of sleep. The evidence combines plausible physiological mechanisms with observational associations and experimental results that do not always coincide.

Light, activation and memory: the mechanisms that connect the screen with sleep

Nighttime light exposure and circadian rhythm shift

The short-wavelength light emitted by some devices can suppress nighttime melatonin secretion and delay circadian readiness for sleep. In an experiment with adolescents and young adults, 90 minutes of reading on a phone without a blue light filter reduced melatonin immediately after exposure; adolescents recovered these levels within the next 50 minutes, while adults still showed a reduction at bedtime (Höhn et al., 2024) . A laboratory study with twelve adults observed that three hours of blue light maintained melatonin suppression, while red light allowed for greater recovery after two and three hours (Sánchez-Cano et al., 2025) . These results support a biological mechanism, but they do not establish that all screens produce the same disruption: intensity, duration, distance, content, and individual sensitivity all modify the effective exposure.

Emotional, cognitive, and physiological activation during evening use

Interactive activities , such as playing games, chatting, or repeatedly switching between apps, demand continuous responses and can prolong wakefulness. In young people aged 11 to 14.9 years, interactive use before bed was associated with a sleep onset approximately ten minutes later for every additional ten minutes, and interactive use in bed was associated with nine fewer minutes of sleep for every ten minutes (Brosnan et al., 2024) . In emerging adults, emotional investment and frequency of social media use were associated with poorer sleep quality and more insomnia symptoms through negative social comparison and pre-sleep cognitive activation (Kinsella & Chin, 2024) . Physiological activation, however, does not explain all cases: in an objective record of adolescents, heart rate was lower during screen use than during other activities, and associations with sleep were small except for latency linked to a higher heart rate (Meredith-Jones et al., 2026) .

Consequences for memory consolidation and sleep quality

Sleep can be affected without altering all of its neurophysiological processes. In an experiment involving reading on a phone or in a printed book, blue light reduced melatonin and decreased N3 sleep in adults during the first quarter of the night, but did not modify declarative memory consolidation or the coupling between sleep spindles and slow oscillations (Höhn et al., 2024) . Another experiment, with twenty adolescents who used social media for 45 minutes before bed, found no differences in objective sleep quality, subjective arousal, or memory consolidation under two reading conditions (Sennock et al., 2024) . This divergence suggests that an immediate circadian response does not necessarily equate to measurable memory impairment. The issue thus shifts from identifying a single cause to distinguishing between light, content, duration, timing, and lost opportunity for sleep.

Counting minutes isn’t enough: schedule, content, and use after bedtime are also important.

Differences between daytime use, before bedtime, and after turning off the light

Temporality separates exposures that are often grouped under the label of screen time. In adolescents, a study with daily follow-up and recording of 745,706 activities found no effects of daytime or pre-bedtime use on sleep quality, but did find a negative association when the phone was used after bedtime (Siebers et al., 2024) . In an objective cohort of young adults, screen time during the two hours before bedtime was not associated with most sleep health measures that night, while in-bed use was associated with shorter total sleep duration (Brosnan et al., 2024) . This difference may reflect that the pre-bedtime period still allows sleep to begin at the expected time, while in-bed use directly competes with that onset.

In adults, population-based associations point in the same direction, albeit with moderate magnitudes. Daily screen use in the hour before bedtime was linked to going to bed 9.33 minutes later in morning chronotypes and 15.62 minutes later in evening chronotypes, as well as an approximate reduction of 50 minutes of weekly sleep (Zhong et al., 2025) . In the Geneva cohort, frequent screen use in the 30 minutes before bedtime was associated with going to bed at midnight or later, sleeping less than seven hours, and experiencing excessive daytime sleepiness, even after adjusting for prior sleep, mental health, and health behaviors (Schrempft et al., 2024) . These figures are derived from questionnaires and observational designs, so they describe adjusted associations, not a causal amount of sleep lost per session.

Social media, video games, and other activities: why content matters

Content modifies attentional demands and the ability to stop the activity. In a study of adolescents tracked via smartphones, lean-forward apps, such as social media before bed and games after bed, were associated with poorer sleep quality; lean-back apps, such as video players, did not show this association ( Siebers et al., 2024) . Objective measurements in young people also identified stronger associations for video games and multitasking than for passive use: ten additional minutes of gaming were associated with 17 fewer minutes of total sleep, while nights with multitasking showed 35 fewer minutes than nights without it (Brosnan et al., 2024) . These estimates should not be interpreted as a universal conversion of gaming minutes to sleep minutes, because they come from nighttime analyses and a small sample size.

Social media also introduces emotional processes that are not reflected in a duration measure. Negative social comparison and pre-sleep cognitive activation mediated the relationship between emotional investment or frequency of use and sleep outcomes in emerging adults (Kinsella & Chin, 2024) . In 212,613 adolescents from 40 countries, problematic social media use was associated with difficulty initiating sleep, with odds ratios of 2.20 for girls and 1.88 for boys; heavy use showed weaker associations, at 1.27 and 1.22, respectively (Khan et al., 2024) . The difference between intensity and problematic use suggests that loss of control, preoccupation, and continued use despite negative consequences may be more informative than raw time spent online.

The pattern of problematic use and its association with insomnia and shorter sleep duration

Quantitative reviews have found a consistent, albeit heterogeneous, relationship between digital use and poor sleep. A meta-analysis of 55 articles and 41,716 participants estimated a correlation of 0.28 between overall use and lower sleep quality, and 0.33 between problematic use and more sleep problems; for problematic internet use, the correlation reached 0.51 (Han et al., 2024) . Another meta-analysis of 21 cohort studies, with 548,338 participants, linked each additional hour of daily screen time with three to five minutes less total sleep, a higher risk of short sleep, more insomnia symptoms, and a 13.2-minute delay in bedtime (He et al., 2025) . The review on social media use in young people included 182 studies but found high heterogeneity and small associations for mental health, sleep, and social use (Ahmed et al., 2024) .

contextual dosage model , not a blanket ban on all evening screen time. Exposure after bedtime, interactive content, and problematic patterns show the strongest associations. Passive, limited use that ends before bedtime may have lesser effects, although the evidence does not yet allow for establishing a common safe threshold for everyone.

Who seems most vulnerable: adolescence, emerging adulthood, and adulthood

Teenagers: nighttime exposure, digital habits, and insufficient sleep

Adolescence combines later biological clocks, school demands, and increasing autonomy over devices. At this stage, problematic social media use is associated with sleep-onset difficulties in multiple countries, and the association is stronger than that observed for heavy use without indicators of loss of control (Khan et al., 2024) . Experimental evidence is less consistent: 90 minutes of reading on a phone without a blue light filter reduced melatonin but not sleep-dependent memory (Höhn et al., 2024) , while 45 minutes of social media did not alter objective sleep outcomes in a small experiment (Sennock et al., 2024) . The difference may be due to sample size or the type of task, as the laboratory prevented continued device use after the intervention.

Children and early adolescents: prospective evidence and objective measurements

In early adolescents, device availability at night appears relevant even when each session is not measured. A US cohort of 9,398 participants aged 11 and 12 found that having a television or internet-connected device in the bedroom was prospectively associated with shorter sleep duration one year later (Nagata et al., 2024) . Keeping the phone ringing at night was also associated with more sleep disturbances and shorter subsequent sleep duration, while talking, texting, listening to music, and using social media predicted more difficulty falling and staying asleep (Nagata et al., 2024) . Objective measurement qualifies this relationship: in 79 young people, almost all used screens before bed, but the association with shorter sleep was concentrated with in-bed use, video games, and multitasking (Brosnan et al., 2024) .

In preschool children, a review of 13 studies linked excessive screen time to shorter and poorer sleep quality, and connected impaired sleep to behavioral and cognitive problems (Merín et al., 2024) . The review also suggests that sleep may mediate or modify these associations, although the evidence does not prove a single direction. The National Sleep Foundation’s consensus statement concludes that, overall, screens impair the sleep health of children and adolescents, that pre-sleep content matters, and that behavioral strategies can mitigate the effects (Hartstein et al., 2024) .

Adults: population associations, mediating factors, and individual variability

In adults, the relationship persists beyond adolescence, but varies according to chronotype and mental health. In 122,058 participants, daily use before bed was associated with less sleep on both weekdays and weekends, and the associations were stronger among those with an evening chronotype (Zhong et al., 2025) . In 4,188 adults from the Specchio cohort, frequent use within the 30 minutes prior to bedtime was associated with late bedtime, short sleep, and daytime sleepiness after accounting for mental health and prior sleep (Schrempft et al., 2024) . Mental health modified the association with sleep quality and insomnia, as the link was detectable among individuals with better mental health in that analysis (Schrempft et al., 2024) .

Emerging adulthood adds specific social mechanisms. Emotional investment in social media, rather than mere duration, was associated with negative social comparison and cognitive activation before sleep (Kinsella & Chin, 2024) . These individual differences prevent translating the evidence into a one-size-fits-all rule. The risk appears to increase when evening chronotype, emotionally absorbing use, nighttime notifications, and a fixed wake-up time are combined.

How solid is the evidence: convergences, disagreements, and methodological limitations

This is what the reviews, cohort studies, and consensus statement all agree on.

Systematic reviews, cohort studies, and consensus statements converge on an association between digital use and less favorable sleep, especially when problematic use, interactive content, or in-bed exposure are involved (Han et al., 2024; Hartstein et al., 2024; He et al., 2025) . Consistency is greater for delayed bedtime, shorter sleep duration, and insomnia symptoms than for specific changes in sleep architecture. Prospective cohort studies support some temporal precedence, such as the association between nighttime behaviors at 11–12 years of age and sleep one year later (Nagata et al., 2024) . Even so, objective studies of specific nights show that the time before bedtime may not alter most parameters, thus limiting blanket recommendations against all screens (Brosnan et al., 2024) .

The two-way relationship: technology affects sleep, but poor sleep also drives nighttime use

The bidirectional nature of screen use offers some explanation for the heterogeneity. While screen time can displace sleep through light, stimulation, interruptions, and the substitution of rest time, sleep difficulties can also lead to phone use for entertainment, distraction, or emotional regulation (Bauducco et al., 2024) . A person who is awake may initiate a nighttime screen session because they need to fill the time or reduce the discomfort associated with not falling asleep (Bauducco et al., 2024) . Consequently, an association between screen time and insomnia does not prove that screens are the cause in all cases. The review on social media and mental health also notes that the scarcity of longitudinal studies limits the determination of the causal direction (Ahmed et al., 2024) .

From questionnaire to objective record: problems of causality, measurement and generalization

Questionnaires capture habitual habits and allow for the study of large samples, but they can confound recall, sleep perception, and actual use. In contrast, cameras, accelerometers, and app logs describe specific nights, although they typically involve small samples and short periods (Brosnan et al., 2024; Siebers et al., 2024) . Experiments control for timing and content, but they can prevent participants from continuing to use the device, a condition distinct from everyday life (Sennock et al., 2024) . Limitations to generalizability also remain: the experimental light study included only adolescent and young adult males (Höhn et al., 2024) , and adult population studies relied primarily on self-reporting (Zhong et al., 2025) . The strongest evidence describes risk patterns, but it has not yet defined a universal causal dose.

From the blue filter to the usage cutoff: which strategies seem reasonable and what remains unresolved

Reduce exposure, change schedules, and protect your slow-down routine.

The strategy with the best practical support is to remove the device from the bed , silence notifications, and end interactive activities before the intended bedtime. A prospective cohort study of early adolescents linked active ringtones and the presence of devices in the bedroom with worse subsequent outcomes (Nagata et al., 2024) . Objective evidence also suggests that restricting use in bed may be more realistic and targeted than banning all screens for the two hours prior to bedtime (Brosnan et al., 2024) . In adults, limiting screen use for 30 to 60 minutes before bedtime seems reasonable to reduce sleep delays, although available studies do not establish a trial that determines the optimal duration (Höhn et al., 2024; Schrempft et al., 2024) . The routine should favor low-demand activities with a recognizable end, rather than relying solely on willpower against an app designed to prolong attention.

Blue light filters and night mode: a partial solution with limited evidence

Blue light filters can reduce some light exposure, but they don’t eliminate cognitive activation or sleep-wake cycle disruption. In an experimental study with adolescents and young adults, reading on a phone without a filter resulted in melatonin attenuation, while using a filter did not appear to be a sufficient solution for all sleep outcomes (Höhn et al., 2024) . An observational study of phone users found no consistent association between filtering apps and overall sleep quality, and described uncertain results for habitual sleep efficiency (Rabiei et al., 2024) . Therefore, night mode may be a complementary measure, not a license to continue browsing in bed.

Research gaps on dosage, individual differences, and physiological activation

Gaps remain regarding cumulative dose, chronotype response, session content, and the independent contribution of light and arousal. Recent physiological recordings suggest that nighttime use does not always increase heart rate and that the time difference may explain more than just intense bodily arousal (Meredith-Jones et al., 2026) . Representative cohorts with long-term follow-up, simultaneous objective measurement of screen time and sleep, and trials that reduce specific behaviors, such as notifications, video games in bed, or problematic use, are needed. It is also unclear whether interventions are equally effective in adolescents, emerging adults, and individuals with pre-existing insomnia.

Conclusion: to recover the last stretch of the night without simplifying science

The final scroll can disrupt sleep in several ways: nightlight, interactive activity, cognitive activation, notifications, and shifting bedtime. The association is more consistent when use continues after turning off the light, occurs in bed, or follows a problematic pattern (Han et al., 2024; Siebers et al., 2024) . The evidence does not justify treating all screens or all content as equivalent, because some objective and experimental studies find no or limited effects in the pre-sleep period (Brosnan et al., 2024; Sennock et al., 2024) . A proportionate recommendation is to protect the final stretch of the night, remove the phone from the bed, and prioritize timing and content over an isolated count of minutes. A blue light filter can complement this decision, but it does not replace cutting back on use or resolve the two-way relationship between insomnia and technology.

References

• Ahmed, O., Walsh, E., Dawel, A., Alateeq, K., Oyarce, DAE, & Cherbuin, N. (2024). Social media use, mental health and sleep: A systematic review with meta-analyses. Journal of Affective Disorders , 367 , 701–712. https://doi.org/10.1016/j.jad.2024.08.193
• Bauducco, S., Pillion, M., Bartel, K., Reynolds, C.M., Kahn, M., & Gradisar, M. (2024). A bidirectional model of sleep and technology use: A theoretical review of how much, for whom, and which mechanisms. Sleep Medicine Reviews , 76 , 101933. https://doi.org/10.1016/j.smrv.2024.101933
• Brosnan, B.J., Haszard, J.J., Meredith-Jones, K.A., Wickham, S.-R., Galland, B.C., & Taylor, R.W. (2024). Screen use at bedtime and sleep duration and quality among youths. Archives of Pediatrics and Adolescent Medicine , 178 (11), 1147. https://doi.org/10.1001/jamapediatrics.2024.2914
• Han, X., Zhou, E., & Liu, D. (2024). Electronic media use and sleep quality: Updated systematic review and meta-analysis. Journal of Medical Internet Research , 26 , e48356. https://doi.org/10.2196/48356
• Hartstein, LE, Mathew, GM, Reichenberger, D., Rodriguez, I., Allen, N.B., Chang, A., Chaput, J., Christakis, D., Garrison, MM, Gooley, JJ, Koos, JA, Van den Bulck, J., Woods, HC, Zeitzer, JM, Dzierzewski, JM, & Hale, L. (2024). The impact of screen use on sleep health across the lifespan: A national sleep foundation consensus statement. Sleep Health , 10 (4), 373–384. https://doi.org/10.1016/j.sleh.2024.05.001
• He, X., Pan, B., Ma, N., Li, D., Kong, W., Liu, Q., Liu, X., Wang, X., Deng, The association of screen time and the risk of sleep outcomes: a systematic review and meta-analysis. Frontiers in Psychiatry , 16 , 1640263. https://doi.org/10.3389/fpsyt.2025.1640263
• Höhn, C., Hahn, MA, Gruber, G., Pletzer, BA, Cajochen, C., & Hoedlmoser, K. (2024). Effects of evening smartphone use on sleep and declarative memory consolidation in male adolescents and young adults. Brain Communications , 6 (3), fcae173. https://doi.org/10.1093/braincomms/fcae173
• Khan, A., Thomas, G., Karatela, S., Morawska, A., & Werner‐Seidler, A. (2024). Intense and problematic social media use and sleep difficulties of adolescents in 40 countries. Journal of Adolescence , 96 (5), 1116–1125. https://doi.org/10.1002/jad.12321
• Kinsella, J.E., & Chin, B.N. (2024). Mechanisms linking social media use and sleep in emerging adults in the united states. Behavioral Sciences , 14 (9), 794. https://doi.org/10.3390/bs14090794
• Meredith-Jones, K.A., Haszard, J.J., Galland, B.C., Wickham, S.-R., Brosnan, B.J., Russell‐Camp, T., & Taylor, R.W. (2026). Screens, teens, and sleep: Is the impact of nighttime screen use on sleep driven by physiological arousal? Journal of Sleep Research , 35 (4), e70288. https://doi.org/10.1111/jsr.70288
• Merín, L., Toledano-González, A., Fernández‐Aguilar, L., Nieto, M., Del Olmo, N., & Latorre, JM (2024). Evaluation of the association between excessive screen use, sleep patterns and behavioral and cognitive aspects in preschool population. a systematic review. European Child & Adolescent Psychiatry , 33 (12), 4097–4114. https://doi.org/10.1007/s00787-024-02430-w
• Nagata, JM, Cheng, CM, Shim, JE, Kiss, O., Ganson, KT, Testa, AM, He, J., & Baker, FC (2024). Bedtime screen use behaviors and sleep outcomes in early adolescents: A prospective cohort study. Journal of Adolescent Health , 75 (4), 650–655. https://doi.org/10.1016/j.jadohealth.2024.06.006
• Rabiei, M., Masoumi, SJ, Haghani, M., Nematolahi, S., Rabiei, R., & Mortazavi, SMJ (2024). Do blue light filter applications improve sleep outcomes? a study of smartphone users’ sleep quality in an observational setting. Electromagnetic Biology and Medicine , 43 (1–2), 107–116. https://doi.org/10.1080/15368378.2024.2327432
• Sánchez-Cano, AI, Bartolomé, MJL, & Solanas, E. (2025). Comparative effects of red and blue LED light on melatonin levels during three-hour exposure in healthy adults. Life , 15 (5), 715. https://doi.org/10.3390/life15050715
• Schrempft, S., Baysson, H., Chessa, A., Lorthe, E., Zaballa, M.-E., Stringhini, S., Guessous, I., & Nehme, M. (2024). Associations between bedtime media use and sleep outcomes in an adult population-based cohort. Sleep Medicine , 121 , 226–235. https://doi.org/10.1016/j.sleep.2024.06.029
• Sennock, S., Wilkau, KVLU, Günther, A., Brandhorst, I., Zinke, K., Conzelmann, A., Renner, TJ, & Kurz, E. (2024). Investigation of the influence of 45-minute pre-sleep social media use on sleep quality and memory consolidation in adolescents. Sleep Medicine , 124 , 299–307. https://doi.org/10.1016/j.sleep.2024.09.034
• Siebers, T., Beyens, I., Baumgartner, S.E., & Valkenburg, P.M. (2024). Adolescents’ digital nightlife: The comparative effects of day- and nighttime smartphone use on sleep quality. Communication Research , 53 (5), 632–658. https://doi.org/10.1177/00936502241276793
• Zhong, C., Masters, M., Donzella, SM, Diver, WR, & Patel, AV (2025). Electronic screen use and sleep duration and timing in adults. JAMA Network Open , 8 (3), e252493. https://doi.org/10.1001/jamanetworkopen.2025.2493