ArticlePloS one2023
The audio features of sleep music: Universal and subgroup characteristics.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 26 citations in OpenAlex.
- Trial
- Self-Chosen Music as a Contributor to Music-Induced Analgesia Across Diverse Socio-Cultural Backgrounds: A Crossover Randomised Controlled Trial.European journal of pain (London, England) · 2025Trial
- Music and Sleep Hygiene Interventions for Pregnancy-Related Insomnia: An Online Randomized Controlled Trial.Journal of midwifery & women's healthTrial
- Relaxation music for stress alleviation: Exploring relationships of audio features and listener profiles.Musicae scientiae : the journal of the European Society for the Cognitive Sciences of Music · 2026Article
- Individual differences in the effects of musical familiarity and musical features on brain activity during relaxation.Cognitive, affective & behavioral neuroscience · 2026Article
- Article
- The art of sleep: examining sleep strategies in the general population with a focus on the use of music for sleep.Journal of sleep research · 2025Article
- Elements of music that work to improve sleep, a narrative review.Frontiers in sleep · 2025Review
- Article
- Predicting danceability and song ratings using deep learning and auditory features.PeerJ. Computer science · 2025Article
- Universality, domain-specificity, and development of psychological responses to music.Nature reviews psychology · 2023Article
- Music that is used while studying and music that is used for sleep share similar musical features, genres and subgroups.Scientific reports · 2023Article
- Diurnal fluctuations in musical preference.Royal Society open science · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Throughout history, lullabies have been used to help children sleep, and today, with the increasing accessibility of recorded music, many people report listening to music as a tool to improve sleep. Nevertheless, we know very little about this common human habit. In this study, we elucidated the characteristics of music associated with sleep by extracting audio features from a large number of tracks (N = 225,626) retrieved from sleep playlists at the global streaming platform Spotify. Compared to music in general, we found that sleep music was softer and slower; it was more often instrumental (i.e. without lyrics) and played on acoustic instruments. Yet, a large amount of variation was present in sleep music, which clustered into six distinct subgroups. Strikingly, three of the subgroups included popular tracks that were faster, louder, and more energetic than average sleep music. The findings reveal previously unknown aspects of the audio features of sleep music and highlight the individual variation in the choice of music used for sleep. By using digital traces, we were able to determine the universal and subgroup characteristics of sleep music in a unique, global dataset, advancing our understanding of how humans use music to regulate their behaviour in everyday life.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.