Topic Revised March 21, 2019 Oral Presentation

Topic Revised March 21 2019oral Presentati

Compare and analyze the impact of electronic media devices on sleep quality based on various research studies, including their effects on sleep duration, interruptions, and psychological factors; also explore conflicting findings and suggest areas for further research.

Paper For Above instruction

In the contemporary era, electronic media devices such as smartphones, tablets, and computers have become ubiquitous, influencing various aspects of daily life, including sleep patterns. The relationship between media device usage and sleep quality has garnered significant research attention, primarily due to concerns over the adverse effects of screen time on restorative sleep. This paper critically examines the existing scientific literature to evaluate the claims about how electronic media devices impact sleep quality, considering diverse research methodologies, findings, and interpretations.

Research findings indicate that high usage of electronic media devices correlates with poorer sleep quality, shorter sleep duration, and increased sleep disturbances among adolescent and young adult populations. For instance, King et al. (2014) conducted a study involving 1,287 adolescents aged 12 to 18 and found that frequent media use was associated with increased sleep problems. The study suggests that media use, especially during evening hours, can interfere with the natural sleep cycle, potentially delaying sleep onset and reducing total sleep time. Similarly, Bruni et al. (2015) reported that adolescents using devices past 9 p.m. experienced diminished sleep quality, emphasizing the impact of late-night screen time on sleep continuity and efficiency.

Further empirical evidence supports these findings. Dube et al. (2017) examined whether media use before sleep influences sleep patterns in children and found that entertainment and communication devices disrupt sleep by causing interruptions and delaying sleep onset. These interruptions can be linked to notifications, calls, or the physical act of engaging with devices, which fragment sleep cycles, leading to non-restorative sleep. Moreover, the blue light emitted from screens suppresses melatonin production, an essential hormone for sleep regulation, exacerbating sleep difficulties (Harvard Health Publishing, 2020).

Contrasting these perspectives, some studies have yielded inconclusive or even contradictory findings. Hysing et al. (2015) reported no significant correlation between media use and sleep quality among adolescents, challenging the generalized assumption of media-induced sleep disruption. Similarly, Dunican et al. (2017) simulated device removal in elite athletes during camp settings and observed no immediate positive effects on sleep patterns, suggesting that factors other than device use might mediate sleep quality. These studies highlight the complexity of sleep behavior and suggest that media use might not be a sole determinant but rather one of multiple contributing factors.

Analyzing the divergence in findings reveals that methodological approaches, sample populations, and measurement tools differ markedly across studies. Some rely on self-reported sleep and media usage, which can introduce bias, while others utilize objective measures such as actigraphy or polysomnography to assess sleep parameters. Additionally, the role of confounding variables such as stress, anxiety, family environment, and baseline sleep habits complicates the attribution of sleep problems solely to device use (Levenson et al., 2017). It is plausible that pre-existing psychological distress or familial factors influence both media consumption and sleep quality, confounding causal interpretations.

From a theoretical standpoint, the 'displacement hypothesis' posits that time spent on media displaces sleep hours, especially when devices are used late at night. Conversely, the 'arousal hypothesis' suggests that engaging with stimulating content, or the physiological arousal resulting from notifications, contributes to sleep difficulties. Both mechanisms are plausible, yet empirical evidence indicates that the effect might vary based on individual differences and contextual factors. For example, some adolescents may experience minimal impact due to resilience or late-night media use being less interfering with their sleep schedules (Levenson et al., 2017).

The ethical considerations surrounding media use and sleep health point towards the need for responsible technology habits. Education about screen time management, especially before bedtime, and promoting 'digital curfews' can serve as practical interventions. Furthermore, technological solutions such as night mode filters, blue light emission reduction, and scheduled device disablement during bedtime are designed to mitigate potential adverse effects, but their efficacy varies across studies.

In conclusion, while a majority of research supports the view that electronic media device usage negatively impacts sleep quality, the evidence is not unequivocal. Divergent findings underscore the necessity for rigorous, controlled longitudinal studies employing objective measurement techniques and accounting for confounding variables. Future research should explore causal pathways, individual differences, and effective intervention strategies, underscoring a nuanced understanding of the media-sleep relationship. A multifaceted approach involving behavioral education, technological aids, and policy recommendations would be most effective in addressing sleep health in an increasingly digital world.

References

  • Bruni, O., Sette, S., Fontanesi, L., Baiocco, R., Laghi, F., & Baumgartner, E. (2015). Technology use and sleep quality in preadolescence and adolescence. Journal of Clinical Sleep Medicine, 11(12).
  • Dube, N., Khan, K., Loehr, S., Chu, Y., & Veugelers, P. (2017). The use of entertainment and communication technologies before sleep could affect sleep and weight status: a population-based study among children. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 97.
  • Dunican, I. C., Martin, D. T., Halson, S. L., Reale, R. J., Dawson, B. T., Caldwell, J. A., & Eastwood, P. R. (2017). The effects of the removal of electronic devices for 48 hours on sleep in elite judo athletes. The Journal of Strength & Conditioning Research, 31(10).
  • Harvard Health Publishing. (2020). Blue light has a dark side. Harvard Medical School. https://www.health.harvard.edu/blog/blue-light-has-a-dark-side-2019122318351
  • Hysing, M., Pallesen, S., Stormark, K. M., Jakobsen, R., Lundervold, A. J., & Sivertsen, B. (2015). Sleep and use of electronic devices in adolescence: results from a large population-based study. BMJ Open, 5(1), e006748.
  • King, D. L., Delfabbro, P. H., Zwaans, T., & Kaptsis, D. (2014). Sleep interference effects of pathological electronic media use during adolescence. International Journal of Mental Health and Addiction, 12(1), 21-35.
  • Levenson, J. C., Shensa, A., Sidani, J. E., Colditz, J. B., & Primack, B. A. (2017). The association between social media use and sleep disturbance among young adults. Preventive Medicine, 95, 124-128.
  • National Sleep Foundation. (2019). How electronics affect sleep. https://www.sleepfoundation.org/articles/how-electronics-affect-sleep
  • Schmidt, M. E., Greendale, G., & Chou, C. P. (2018). Electronic media use and sleep in adolescents. Sleep Medicine Clinics, 13(3), 369-377.
  • Vallor, S. (2016). Technology and sleep: A review of the behavioral and physiological evidence. Philosophy & Technology, 29(3), 401-417.

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