Evidence map›Paper›PMID 41425167›Full record

ReviewFrontiers in sleep2025

Elements of music that work to improve sleep, a narrative review.

Ethan Y Pan, Wei Wang

Abstract readReview
In one paragraph

Review in Frontiers in sleep, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ethan Y PanDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States.
Wei WangBay Area Sleep Medicine, San Jose, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep health is essential for overall wellbeing; however, millions of people worldwide experience poor sleep quality due to insomnia, stress, or lifestyle-related disturbances. Pharmacological and behavioral treatments, while effective, remain limited by side effects, accessibility barriers, or patient adherence. In contrast, music is an accessible, low-cost, and non-invasive intervention that is increasingly used by individuals to improve sleep. This narrative review synthesizes findings from randomized controlled trials and meta-analyses to identify the musical elements and delivery methods that are most effective in enhancing sleep quality. Across studies, listening to music consistently reduced sleep-onset latency, improved sleep efficiency, and increased total sleep time. Music that was slow in tempo (60-80 bpm), soft and smooth in melodies, instrumental, and simple in structure, often classical or new age, was most effective. Cultural familiarity, nature sounds, and religious music also demonstrated benefits in specific contexts. Innovative approaches, such as brain-wave music and binaural beats, show promise but require further validation. Optimal dosing included 30-45 min of daily listening before bedtime at comfortable volume levels. Despite strong evidence of short-term benefits, gaps remain in our understanding of the long-term effects, mechanisms of action, and impacts on youth populations. Future research should explore how personalized music interventions and artificial intelligence-generated compositions may advance sleep health. Overall, this review highlights the elements at work that make music a safe, scalable, and culturally adaptable adjunct to traditional sleep therapies.

Indexed as

binaural beatsbrain wave musicinsomniamusic characteristicsmusic dosingrandomized controlled trialssleep healthsleep quality

Identifiers

PMID41425167
PMCPMC12713922

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.