Resume: While most people prefer to fall asleep listening to quieter, slower songs, some feel more relaxed when listening to popular, high-energy music.
A new study has identified several typical characteristics of music associated with sleep, such as being quieter and slower than other music.
However, the popular sleep music playlists on Spotify also include faster, louder, and more energetic tracks. Rebecca Jane Scarratt of Aarhus University, Denmark, and her colleagues present these findings in the open access journal PLUS ONE on January 18, 2023.
Many people say that they listen to music to help them fall asleep, which raises the question of whether the music chosen for this purpose shares certain universal characteristics. However, research on the sleep characteristics of music is limited, and previous studies have tended to be relatively small.
To better understand the characteristics of sleep music, Scarratt and her colleagues analyzed 225,626 tracks from 985 playlists on Spotify that are associated with sleep. They used the Spotify API to compare the audio features of dream tracks with the audio features of music in a data set representing music in general.
This analysis showed that sleep music tends to be calmer and slower than other music. It also more frequently lacks lyrics and more frequently features acoustic instruments. Despite these trends, however, the researchers found considerable diversity in the musical characteristics of sleep music, identifying six distinct subcategories.
Three of the subcategories, including background music, align with the typical characteristics identified for sleep music.
However, the music in the other three subcategories was louder and had a higher degree of energy than the average sleep music. These tracks included several popular songs, such as “Dynamite” by the band BTS and “lovely (with Khalid)” by Billie Eilish and Khalid.
The authors speculate that, despite their higher energy, popular songs could potentially help some people relax and sleep through their familiarity. However, more research will be needed to explore this possibility and to identify the various reasons why different people choose different music for sleep.
Overall, this study suggests that there is no “one size fits all” when it comes to the music people choose to sleep with. The findings could help inform the future development of music-based strategies to help people sleep.
The authors add: “In this study, we investigated the characteristics of music used for sleep and found that although sleep music is generally softer, slower, instrumental, and is played more often on acoustic instruments than other Music The music that people use to fall asleep shows great variation that includes music characterized by high energy and tempo.
“The study may inform the clinical use of music and advance our understanding of how music is used to regulate human behavior in everyday life.”
About this music and sleep research news
Author: Hana Abdullah
Contact: Hanna Abdallah – PLOS
Picture: The image is in the public domain.
original research: Open access.
“The Audio Characteristics of Sleep Music: Universal and Subgroup Characteristics” by Kira Vibe Jespersen. PLUS ONE
The audio characteristics of sleep music: universal and subgroup characteristics
Throughout history, lullabies have been used to help children fall asleep and today, with the increasing accessibility of recorded music, many people report listening to music as a sleep-enhancing tool. However, we know very little about this common human habit.
In this study, we elucidate the characteristics of music associated with sleep by extracting audio characteristics from a large number of tracks (N = 225,626) retrieved from sleep playlists on the global streaming platform Spotify. Compared to music in general, we found sleep music softer and slower; it was more often instrumental (i.e. without lyrics) and played on acoustic instruments.
However, there was a large amount of variation in sleep music, which was grouped into six distinct subgroups. Surprisingly, three of the subgroups included popular tracks that were faster, louder, and more energetic than your average sleep music.
The findings reveal previously unknown aspects of the audio characteristics of sleep music and highlight individual variation in the choice of music used for sleep.
Using digital traces, we were able to determine universal and subgroup characteristics of sleep music in a single global dataset, furthering our understanding of how humans use music to regulate their behavior in everyday life.