Association between quality of sleep and screen time during the COVID-19 outbreak among adolescents in the United Arab Emirates.

The COVID-19 pandemic had a major impact on people of all ages. Adolescents' exposure to online learning is linked to excessive screen time on digital devices, which leads to poor sleep quality. This study aimed to investigate the association between screen time on different electronic devices and sleep quality among adolescents in the United Arab Emirates. This study was based on a self-reported questionnaire, which was administered online to school-aged adolescents (aged 12-19 years). The multicomponent questionnaire collected information on sociodemographic characteristics, sleep quality using the Pittsburgh Sleep Quality Index (PSQI), and screen time (minutes) on TV, TV-connected devices, laptops, smartphones, and tablets on weekdays, weeknight, and weekends using the Screen Time Questionnaire (STQ). Univariate and multivariate analyses were used to identify factors correlated with poor sleep quality. A total of 1720 adolescents were recruited from private and public schools (mean age 14.6 ± 1.97 years). The mean PSQI score was 8.09 ± 3.37, and 74.3% of participants reported poor sleep (cutoff score >5). Mean scores were highest for the sleep latency (1.85 ± 0.97) and sleep disturbance (1.56 ± 0.62) domains. The highest STQ score was observed for smartphones, with a median screen time of 420 min on weekdays and 300 min on weekends. Screen time related to smartphones on weekends (p = 0.003) and increased screen time in bed (p < 0.001) were significantly associated with poor sleep. Our results confirmed the correlation between sleep and screen time in adolescents. The results may inform educational polices that target screen time and sleep among adolescents during and after the COVID-19 pandemic.

Digital Screen Time and Pediatric Sleep: Evidence from a Preregistered Cohort Study.

OBJECTIVES: To determine the extent to which time spent with digital devices predicts meaningful variability in pediatric sleep. STUDY DESIGN: Following a preregistered analysis plan, data from a sample of American children (n = 50 212) derived from the 2016 National Survey of Children's Health were analyzed. Models adjusted for child-, caregiver-, household-, and community-level covariates to estimate the potential effects of digital screen use. RESULTS: Each hour devoted to digital screens was associated with 3-8 fewer minutes of nightly sleep and significantly lower levels of sleep consistency. Furthermore, those children who complied with 2010 and 2016 American Academy of Pediatrics guidance on screen time limits reported between 20 and 26 more minutes, respectively, of nightly sleep. However, links between digital screen time and pediatric sleep outcomes were modest, accounting for less than 1.9% of observed variability in sleep outcomes. CONCLUSIONS: Digital screen time, on its own, has little practical effect on pediatric sleep. Contextual factors surrounding screen time exert a more pronounced influence on pediatric sleep compared to screen time itself. These findings provide an empirically robust template for those investigating the digital displacement hypothesis as well as informing policy-making.

Digital screens in community pharmacy for public health messaging; a mixed-methods study.

OBJECTIVES: An independent evaluation was undertaken to investigate the perceived impact of installing digital screens in a group of community pharmacies as an approach to provide public health messaging. METHODS: Community pharmacy staff were interviewed prior to screen installation to investigate experience and perceptions of conventional public health campaigns using written materials. Staff were interviewed after the digital screen installation to investigate their opinions of the installation and its impact on public health delivery in the pharmacy. Patients and public representatives were recruited to visit the pharmacies and asked to complete a survey about what they observed and thought about the public health messaging. Interviews were transcribed verbatim and thematically analysed. Surveys consisted of open, closed, and rating questions. The results of which were descriptively analysed. KEY FINDINGS: Community pharmacy staff found paper-based campaigns work-intensive and created paper wastage. The digital screen installation was received positively by pharmacy staff and patient, and public representatives found them eye-catching and engaging. Staff were unable to report any conversations with members of the public triggered by the screens, but the patient and public volunteers were able to recall some of the health messages. CONCLUSIONS: Digital messaging is common practice and digital screens are already in use in areas where patients and the public have conventionally been in attendance, e.g. GP surgeries. Digital screens in community pharmacy for public health messaging could be considered an inevitable progression for public health messaging given concerns about wastage and up-to-date information. The impact, however, on triggering healthier choices and lifestyles requires further investigation.

Digital Screen Time and the Risk of Female Breast Cancer: A Retrospective Matched Case-Control Study.

Background: As the use of electronic devices such as mobile phones, tablets, and computers continues to rise globally, concerns have been raised about their potential impact on human health. Exposure to high energy visible (HEV) blue light, emitted from digital screens, particularly the so-called artificial light at night (ALAN), has been associated with adverse health effects, ranging from disruption of circadian rhythms to cancer. Breast cancer incidence rates are also increasing worldwide. Objective: This study aimed at finding a correlation between breast cancer and exposure to blue light from mobile phone. Material and Methods: In this retrospective matched case-control study, we aimed to investigate whether exposure to blue light from mobile phone screens is associated with an increased risk of female breast cancer. We interviewed 301 breast cancer patients (cases) and 294 controls using a standard questionnaire and performed multivariate analysis, chi-square, and Fisher's exact tests for data analysis. Results: Although heavy users in the case group of our study had a statistically significant higher mean 10-year cumulative exposure to digital screens compared to the control group (7089±14985 vs 4052±12515 hours, respectively, P=0.038), our study did not find a strong relationship between exposure to HEV and development of breast cancer. Conclusion: Our findings suggest that heavy exposure to HEV blue light emitted from mobile phone screens at night might constitute a risk factor for promoting the development of breast cancer, but further large-scale cohort studies are warranted.

The impact of blue light and digital screens on the skin.

INTRODUCTION: The skin is frequently subjected to a variety of environmental trauma and stress. It is unavoidably subjected to blue light due to the increased use of electronic equipment, including indoor lighting and digital gadgets like smartphones and laptops, which have a range of detrimental effects. The method of action and numerous harmful consequences of blue light on the skin are the main subjects of this review. MATERIALS AND METHODS: A literature search has been performed using PubMed, GoogleScholar and EmBase databases and an updated review on the topic has been presented. RESULTS: Numerous studies have shown that being exposed to blue light accelerates the aging process and produces cutaneous hyperpigmentation. It also modifies the circadian rhythm. The two main molecules that mediate cellular responses to blue light are nitric oxide (NO) and reactive oxygen species. However, the precise process is still not fully known. CONCLUSION: These negative consequences may eventually cause more general skin damage, which may hasten the aging process. At times, skin protection may be crucial for protection against blue light.

The Effect of Online Education on Healthy Eyes of Saudi Teachers in the COVID-19 Pandemic: A Local Study.

Background Digital eye strain (DES) or computer vision syndrome (CVS) manifests as eye fatigue caused by prolonged exposure to screens and exaggerated by some attitudes. Online education plays a crucial role in helping schools, instructors, and universities ensure the continuity of the education process during the COVID-19 pandemic. There is a lack of attention given to the effects of online teaching on teachers' eyes health during the pandemic and is nearly nonexistent. Hence, we aim to evaluate this among teachers in the Eastern Province of Saudi Arabia. Methodology A cross-sectional electronic self-administered questionnaire was distributed through social media applications among teachers in the eastern province of Saudi Arabia. The survey contained three main parts: biographical data, educational status, and eye health scale before and during the pandemic. All statistical analysis was done using IBM SPSS version 22 (IBM Corp., Armonk, NY). Results A total sample of 301 teachers was identified with ages ranging from 22 to 60 years, the majority were female (75.4%). Twenty-four point nine percent (24.9%) of the sample have a chronic disease, and 17.3% had previous LASIK surgery. Twenty-four point nine percent (24.9%) spent two to five hours teaching before the pandemic versus 60.8% with online education during the pandemic spent two to five hours daily. Fifty-two point eight percent (52.8%) of the teachers kept the distance between them and the digital screen at less than 50 cm. Eighty-one point four percent (81.4%) of teachers reported severe to moderate effects of online teaching using a computer/tablet/phone on their eye health. Fifty-two point two percent (52.2%) reported headache. Conclusion There is an obvious negative effect reflected by subjects' symptomatology and complaints in their eyes. This should prompt health authorities to provide better teaching equipment and accessibility to essential eye care to teachers.

Machine Learning Models for Predicting Breast Cancer Risk in Women Exposed to Blue Light from Digital Screens.

Background: Nowadays, there is a growing global concern over rapidly increasing screen time (smartphones, tablets, and computers). An accumulating body of evidence indicates that prolonged exposure to short-wavelength visible light (blue component) emitted from digital screens may cause cancer. The application of machine learning (ML) methods has significantly improved the accuracy of predictions in fields such as cancer susceptibility, recurrence, and survival. Objective: To develop an ML model for predicting the risk of breast cancer in women via several parameters related to exposure to ionizing and non-ionizing radiation. Material and Methods: In this analytical study, three ML models Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron Neural Network (MLPNN) were used to analyze data collected from 603 cases, including 309 breast cancer cases and 294 gender and age-matched controls. Standard face-to-face interviews were performed using a standard questionnaire for data collection. Results: The examined models RF, SVM, and MLPNN performed well for correctly classifying cases with breast cancer and the healthy ones (mean sensitivity> 97.2%, mean specificity >96.4%, and average accuracy >97.1%). Conclusion: Machine learning models can be used to effectively predict the risk of breast cancer via the history of exposure to ionizing and non-ionizing radiation (including blue light and screen time issues) parameters. The performance of the developed methods is encouraging; nevertheless, further investigation is required to confirm that machine learning techniques can diagnose breast cancer with relatively high accuracies automatically.

Digital screen use for a road safety campaign message was not associated with road safety awareness of passers-by: A quasi-experimental study.

INTRODUCTION: Recent evidence suggests fatality risks for cyclists may be increasing in Britain. Understanding how to increase levels of cycling while keeping risk low is paramount. Educating drivers about cyclists may help with road safety, and mass-media messaging is a possible avenue, potentially utilizing digital displays screens in public areas. However, no studies have examined the use of these screens for road safety campaigns. METHODS: A quasi-experiment was conducted to examine if digital screens may be effective to raise awareness of a campaign message and encourage recall of car drivers. A digital campaign image was selected that encouraged car drivers and cyclists to 'look out for each other,' and stated than 80% of cyclists owned a driving license. Views and knowledge on driver priorities around cyclists were examined before (control) and after campaign exposure (intervention), and tested using regression modelling. RESULTS: 364 people were interviewed over five days. Those interviewed on intervention days were more likely to rank 'Look out for cyclists' as being more important compared to those interviewed on control days (OR 1.20), but this was not statistically significant (p = 0.355). Those who said they had seen the image did not rank 'Look out for cyclists' higher than those who said they had not seen it (p = 0.778). The disparity between reported and displayed percentage of cyclists with a driving license did not differ between intervention and control days, but was 8% higher amongst those who claimed to have seen the image (p = 0.026). CONCLUSIONS: We did not find strong evidence that use of an image on digital screens increased public awareness or recall of a casualty reduction campaign message. Work is needed to investigate the effects of longer-term exposure to road safety images. Practical Applications: Short-term use of digital signage is not recommended for raising awareness of road safety campaigns.

Women with hereditary breast cancer predispositions should avoid using their smartphones, tablets, and laptops at night.

Breast cancer is the most common malignancy among women, both in the developed and developing countries. Women with mutations in the BRCA1 and BRCA2 genes have an increased risk of breast and ovarian cancers. Recent studies show that short-wavelength visible light disturb the secretion of melatonin and causes circadian rhythm disruption. We have previously studied the health effects of exposure to different levels of radiofrequency electromagnetic fields (RF-EMFs) such as mobile phones, mobile base stations, mobile phone jammers, laptop computers, and radars. Moreover, over the past several years, we investigated the health effects of exposure to the short wavelength visible light in the blue region emitted from digital screens. The reduction of melatonin secretion after exposure to blue light emitted from smartphone's screen has been reported to be associated with the negative impact of smartphone use at night on sleep. We have shown that both the blue light and RF-EMFs generated by mobile phones are linked to the disruption of the circadian rhythm in people who use their phones at night. Therefore, if women with hereditary breast cancer predispositions use their smartphones, tablets and laptops at night, disrupted circadian rhythms (suppression of melatonin caused by exposure to blue light emitted from the digital screens), amplifies the risk of breast cancer. It can be concluded that women who carry mutated BRCA1 or BRCA2, or women with family history of breast cancer should avoid using their smartphones, tablets and laptops at night. Using sunglasses with amber lenses, or smartphone applications which decrease the users' exposure to blue light before sleep, at least to some extent, can decrease the risk of circadian rhythm disruption and breast cancer.