Evidence map›Paper›PMID 40224208›Full record

SynthesisIranian journal of medical sciences2025

Effectiveness of Acupuncture and Acupressure for Improving the Sleep Quality of Menopausal Women: A Meta-Analysis.

Leila Eskandari, Afsaneh Keramat, Marzieh Rohani-Rasaf

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Iranian journal of medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Leila EskandariStudent Research Committee, School of Nursing and Midwifery, Shahroud University of Medical Sciences, Shahroud, Iran.
Afsaneh KeramatDepartment of Reproductive Health, School of Nursing and Midwifery, Shahroud University of Medical Sciences, Shahroud, Iran.
Marzieh Rohani-RasafCenter for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Various pharmacological and non-pharmacological treatments are utilized to address sleep disorders. This meta-analysis aimed to evaluate the effects of acupuncture and acupressure on enhancing sleep quality in menopausal women. Methods: A systematic search was conducted using multiple databases, including Scopus, MEDLINE/PubMed, Cochrane CENTRAL, ProQuest, Google Scholar, and Iranian databases (SID, Iranmedex, Magiran) with no date restrictions up to July 2024. Studies published in both Persian and English were included in this meta-analysis. The search utilized keywords such as acupuncture, acupressure, sleep quality, insomnia, menopause, and sleep disorders. A pairwise random-effects meta-analysis was performed to calculate the mean difference (MD) and 95% confidence intervals (95% CIs). Results: The analyses indicated that both acupuncture and acupressure effectively improved sleep quality in menopausal women. Eight trials with 499 participants demonstrated that acupressure significantly enhanced sleep quality (MD=-2.33, 95% CI=-3.27 to -1.38; I Conclusion: The findings revealed that acupressure and acupuncture might improve sleep quality in menopausal women. However, there was a high heterogeneity between studies, and further research is required to confirm the findings of the present study.

Indexed as

AcupressureAcupuncture TherapyMenopauseSleep QualitySleep Wake DisordersFemaleHumansMiddle AgedAcupressureAcupunctureMenopauseMeta-analysisSleep quality

Identifiers

PMID40224208
PMCPMC11992344

What OpenQuestion holds

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LicenceCC BY-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.