The impact of media use on sleep has been one of the subjects often investigated in epidemiological and experimental sleep studies. Initially, TV viewing was the main target of the media [1], followed by video games [2] and the Internet [3]. Today, with the widespread use of electronic media devices like smartphones and tablets, we can access media networks anywhere and at any time.

Lee et al. [4] conducted a study to examine the effects of OTT (over-the-top media service) on sleep patterns in Korean samples using data from the years before the pandemic (2018 and 2019), which was collected and made available by a Korean institute. The researchers employed the RFNN (Random Forest Nearest Neighbor) technique to match control and treatment groups. The control group consisted of individuals who did not use OTT during 2018 and 2019, while their treatment group comprised those who started watching OTT in 2019. The RFNN technique revealed well-matched samples, and the study found that the total OTT watching time did not reduce sleep duration or delay bedtime. However, when specifically analyzing the effects of ‘late night’ OTT watching (10:00 pm to 2:00 am) on sleep patterns, they observed a reduction in total sleep time by approximately 18–20 min and a delay in bedtime by approximately 18 min. Furthermore, upon investigating the effects of ‘late night’ watching on sleep patterns in different age groups, they found these effects to be more pronounced in the young generation, i.e., teenagers and those in their 20s.

The results suggested that a ‘late night’ watching lifestyle had negative effects on sleep health, mirroring findings from studies investigating the effects of more traditional media such as television [5], video games [2], and the internet [3]. This indicates that the impact of media use on sleep is consistent across different types of media. The RFNN technique utilized in this study proved to be useful for comparing the two independent samples with several confounding variables. The method excels in interpreting results without being influenced by the effects of confounding variables.

In the discussion section, the researchers noted that had they used weekend data, the impact of media would be more evident, given that bedtime and rise time on weekends are typically delayed and vary widely among individuals. Previous research by Taylor et al. [6] has shown that a delayed lifestyle during the weekend can affect the beginning days of the following week. Therefore, future studies should seek to clarify the impact of media use on weekends.

Numerous studies, including the one by Lee et al. [4], have pointed out that the impacts of media use on sleep health are more pronounced in young individuals [2, 5, 7]. However, some other studies have suggested no such age effect [4, 8]. Thus, investigating whether the impact of media use on sleep patterns is more prominent in young individuals should be the next subject of investigation.