Do blue light filter applications improve sleep outcomes? A study of smartphone users' sleep quality in an observational setting.

Exposure to blue light at bedtime, suppresses melatonin secretion, postponing the sleep onset and interrupting the sleep process. Some smartphone manufacturers have introduced night-mode functions, which have been claimed to aid in improving sleep quality. In this study, we evaluate the impact of blue light filter application on decreasing blue light emissions and improving sleep quality. Participants in this study recorded the pattern of using their mobile phones through a questionnaire. In order to evaluate sleep quality, we used a PSQI questionnaire. Blue light filters were used by 9.7% of respondents, 9.7% occasionally, and 80% never. The mean score of PSQI was more than 5 in 54.10% of the participants and less than 5 in 45.90%. ANOVA test was performed to assess the relationship between using blue light filter applications and sleep quality (p-value = 0.925). The findings of this study indicate a connection between the use of blue light filter apps and habitual sleep efficiency in the 31-40 age group. However, our results align only to some extent with prior research, as we did not observe sustained positive effects on all parameters of sleep quality from the long-term use of blue light filtering apps. Several studies have found that blue light exposure can suppress melatonin secretion, exacerbating sleep problems. Some studies have reported that physical blue light filters, such as lenses, can affect melatonin secretion and improve sleep quality. However, the impact of blue light filtering applications remains unclear and debatable.

Using smartphones before bedtime and being exposed to its blue light can make it harder to fall asleep and disrupt your sleep. Some smartphone makers have introduced a night mode feature claiming it can help improve your sleep. In this study, we wanted to find out if using these blue light filters on smartphones really makes a difference. We asked people how often they used blue light filters on their phones and also had them fill out a questionnaire about their sleep quality. Only about 10% of people said they used blue light filters regularly, another 10% used them occasionally, and the majority, around 80%, never used them. When we looked at the results, more than half of the participants had sleep scores higher than 5, indicating they might have sleep problems. Less than half had sleep scores lower than 5, suggesting better sleep quality. We used some statistical tests to see if using blue light filters had any link to sleep quality, and the results showed that there was only a connection between the use of blue light filter apps and habitual sleep efficiency in the 31­40 age group. Our findings matched what other studies have found before, that using blue light filters on smartphones may not significantly help improve sleep. So, while it might be a good idea to limit smartphone use before bed, using a blue light filter app may not be the magic solution for better sleep.

Mobile Cellular Data and Wi-Fi Use Are Not Associated with Adverse Health Effects.

Background: Smartphone users frequently connect to the Internet via mobile data or Wi-Fi. Over the past two decades, the worldwide percentage of people who connect to the Internet using their mobile phones has increased drastically. Objective: This study aimed to evaluate the potential link between mobile cellular data/ and Wi-Fi use and adverse health effects. Material and Methods: This cross-sectional study was conducted on 2,796 employees (52% female and 48% male) of Shiraz University of Medical Sciences (SUMS), Shiraz, Iran. The sociodemographic data (e.g., gender, age, nationality, and education level) were collected for all the participants. They were also requested to provide information about their smartphone use including the characteristics of the connection to the Internet using their smartphones (mobile data and Wi-Fi). In addition, the participants' history of diabetes, hypertension, cardiac ischemia, myocardial infarction, renal failure, fatty liver, hepatitis, chronic lung disease, thyroid disease, kidney stone, gall bladder stone, rheumatoid disease, epilepsy, and chronic headache was recorded through face-to-face interviews. Results: 94% of people participating in this study reported using mobile/Wi-Fi internet. The mean (±SD) Internet usage per day was 117.85±122.70 minutes including 76±98 minutes of mobile data and 42±81 minutes of Wi-Fi use. Conclusion: Our findings showed no link between mobile phone Internet usage and the risk of the above-mentioned health problems. As in 2021, the global average daily time spent on the Internet using mobile phones was 155 minutes, the participants' lower use time could explain the failure to show any detrimental effects. Considering the study limitations, further large-scale studies are warranted.