S0033291717002070jlp 876..877 Correspondence Psychological Medicine, 48 (2018). doi:10.1017/S0033291717002070 First published online 3 August 2017 Letter to the Editor Is poor sleep, and loneliness linked by increased use of technology? Using data from a UK nationally-representative cohort, Matthews and colleagues found that young adults who report feeling lonely were also likely to report poor sleep (Matthews et al. 2017). The researchers were able to attribute the findings to individual experiences of loneliness and account for shared environmental exposures and genetic factors between the twins by examining differences in loneli- ness and sleep between monozygotic twins. In a second key finding, it was reported that exposure to victimisation moderated the association between lone- liness and sleep quality. Whilst the effects found were modest, they appeared robust, even if no casual effect could be determined; however, they did find a dose– response relationship between reduced sleep and increased level of victimisation. It is already known that that the link between lone- liness and sleep is not accounted for by: depression; BMI; or other health-related behaviours (Cacioppo et al. 2002; Hawkley et al. 2010). Furthermore, not all children who were lonely suffered from poor sleep, so draws debate to the potential moderating factors. The researchers established that individuals exposed to victimisation experienced greater loneliness and poor sleep, and this was exacerbated by severe victim- isation. Whilst this study controlled for many confoun- ders and moderators one of the few individual widespread exposures not able to be controlled for in this study was the use of screen-based technology (herein defined as device use). There is already an argument that the effect of loneliness is associated with both increased device use, and poorer sleep, as bored children turn to their device for companionship (Carter et al. 2016; Lleras & Panova, 2016; Ndasauka et al. 2016). Health consequence may follow in the extreme cases, as highlighted by Henry David Thoreau who wrote that the problems that arise when people become ‘tools of their tools’ and today many children are addicted to their device (Thoreau, 1864). The consequence of heavy usage has already been linked to loneliness (Cacioppo et al. 2002) as well as a multitude of poorer health outcomes, including loss of sleep, and poorer physical and mental health (Gradisar et al. 2013; Owens & Committee a ASWG, 2014). It has been reported that greater loneli- ness traits have been reported in those children with the greatest intensity of device usage (Ndasauka et al. 2016). Recent evidence has pointed to device use (or merely access) being linked to poorer sleep quantity, and quality, even when the device are not being used, but were present in the bedroom. It has been argued that evening device use led to cognitive engagement, linked with poorer sleep (Carter et al. 2016), and a possible cause of the loneli- ness (Cacioppo et al. 2002; Carter et al. 2016). Examples of engagement may be wide ranging from: peer engagement in social media; anticipation; fear of missing out; or in extreme cases cyber bullying; or vic- timisation, as highlighted by Matthews et al. (2017). Whilst the overriding net effect of technology on our lives is positive, it is not without consequence (Lleras & Panova, 2016; Ndasauka et al. 2016). There is limited guidance on media device use by the American Academy of Pediatrics (Chassiakos et al. 2016; Hill et al. 2016), but it needs development and translation into practical implementation for parents and schools. Since harmful use of technology by children would be seen by teachers, as the first to notice the signs and symptoms of daytime sleepiness, or withdrawal due to loneliness or victimisation. I conclude, there is need to differentiate between our devices, and our relationships, that education on the short-term consequences of device is warranted. We need to recognise chronic sleep deprivation sooner, and explore the cause, if for no other reason to rule out screen-based addiction and victimisation. Acknowledgement We acknowledge the support of The National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. References Cacioppo JT, Hawkley LC, Berntson GG, Ernst JM, Gibbs AC, Stickgold R, Hobson J (2002). Do lonely days invade the nights? Potential social modulation of sleep efficiency. Psychological Science 13, 384–387. Carter B, Ree P, Hale L, Bhattacharjee D, Paradkar MS (2016). 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Journal of Clinical Sleep Medicine: JCSM: Official Publication of the American Academy of Sleep Medicine 9, 1291–1299. Hawkley LC, Preacher KJ, Cacioppo JT (2010). Loneliness impairs daytime functioning but not sleep duration. Health Psychology 29, 124–129. Hill D, Ameenuddin N, Chassiakos YR, Cross C, Radesky J, Hutchinson J, Boyd R, Mendelson R, Moreno MA, Smith J, Swanson WS, Council on Communications and Media (2016). Media and young minds. Pediatrics 138, e20162591. doi: 10.1542/peds.2016-2591. Lleras A, Panova T (2016). Avoidance or boredom: negative mental health outcomes associated with the use of information and communication technologies depend on users motives. Computers in Human Behavior 58, 249–258. Matthews T, Danese A, Gregory AM, Caspi A, Moffitt TE, Arseneault L (2017). Sleeping with one eye open: loneliness and sleep quality in young adults. Psychological Medicine. doi: 10.1017/S0033291717000629. Ndasauka Y, Hou J, Wang Y, Yang L, Yang Z, Ye Z, Hao Y, Fallgatter A, Kong Y, Zhang Z (2016). Excessive use of Twitter among college students in the UK: validation of the microblog excessive Use Scale and relationship to social interaction and loneliness. Computers in Human Behavior 55, 963–971. Owens J, Committee a ASWG (2014). Insufficient sleep in adolescents and young adults: an update on causes and consequences. Pediatrics 134, e921–e931. Thoreau HD (1864). Walden. In Walden or Life in the Woods and ‘on the Duty of Civil Disobedience’, pp. 1–264. New American Library: New York, NY. Originally published 1854. p. 29. B. CA R T ER 1,2* 1Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, De Crespigny Park, London, UK 2Cochrane Skin Group, School of Medicine, Nottingham University, Nottingham, Nottinghamshire, UK *Address for correspondence: Dr B. Carter, Ph.D., Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, De Crespigny Park, London SE5 8AF, UK; Cochrane Skin Group, School of Medicine, Nottingham University, Nottingham, Nottinghamshire, UK. (Email: ben.carter@kcl.ac.uk) Correspondence 877 https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0033291717002070 Downloaded from https://www.cambridge.org/core. Carnegie Mellon University, on 06 Apr 2021 at 00:59:57, subject to the Cambridge Core terms of use, available at mailto:ben.carter@kcl.ac.uk https://www.cambridge.org/core/terms https://doi.org/10.1017/S0033291717002070 https://www.cambridge.org/core