Evidence map›Paper›PMID 40049603›Full record

SynthesisNursing & health sciences2025

Effectiveness of Acupressure on Sleep Quality Among Inpatients: A Systematic Review and Meta-Analysis.

Weihong Ling, Chenxi Yang, Mu-Hsing Ho, Jung Jae Lee

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Nursing & health sciences, 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

4 authors.

Weihong LingSchool of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Chenxi YangSchool of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0009-0007-0410-587X
Mu-Hsing HoSchool of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Jung Jae LeeSchool of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0001-9704-2116

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep quality in adult inpatients is frequently and severely disturbed by various factors such as noise, pain, and unfamiliar surroundings, which can impair disease recovery. Acupressure is widely used to improve sleep quality in hospitalized patients, but its overall effectiveness is unclear. This meta-analysis aims to analyze the efficacy of acupressure therapy on sleep quality and sleep parameters in adult inpatients. Eight electronic databases were searched for randomized controlled trials published before April 2024. Two researchers independently screened, assessed, and extracted data from the included studies. A total of 41 studies involving 3680 subjects were included. The meta-analysis showed a significant difference between the acupressure and control groups in sleep quality (SMD = -1.58, 95% CI [-1.85, -1.31]), total sleep time (SMD = 1.12, 95% CI [0.40, 1.83]), sleep efficiency (SMD = 0.90, 95% CI [0.29, 1.52]), sleep onset latency (SMD = -0.73, 95% CI [-1.14, -0.33]), and wake after sleep onset (SMD = -1.32, 95% CI [-2.55, -0.09]). The meta-regression results suggested that the number of sessions daily and the duration of each session were significant factors influencing heterogeneity. Acupressure is an effective intervention to improve sleep quality and sleep parameters in inpatients.

Indexed as

AcupressureInpatientsSleep QualityAdultHumansRandomized Controlled Trials as Topicacupressureadultsinpatientsmeta‐analysissleep qualitysystematic review

Identifiers

PMID40049603
PMCPMC11884929

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.