Evidence map›Paper›PMID 40303318›Full record

SynthesisFrontiers in pain research (Lausanne, Switzerland)2025

Assessment of non-pharmacological nursing strategies for pain management in tumor patients: a systematic review and meta-analysis.

Shen Yan, Feng Yan, Pei Liangyu, Xu Fei

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in pain research (Lausanne, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. 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.

Shen YanDepartment of Cancer V, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Feng YanDepartment of Cancer V, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Pei LiangyuDepartment of Cancer V, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xu FeiDepartment of Cancer V, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Summary background: Cancer is a multifactorial disease associated with intense pain and fatigue. Pain is the main discomfort experienced during cancer treatment, particularly as a major side effect of chemotherapy. Objective: This study has aimed to investigate the effectiveness of non-pharmacological nursing strategies, including reflexology, aromatherapy, acupressure, massage therapy and acupuncture, in the management of cancer-associated pain. Moreover, it provides evidence-based recommendations for integrating these interventions into standard pain management protocols. Search methodology: We gathered data from three major online databases; PubMed, the Cochrane Library and Embase. For the analysis, we exclusively targeted randomized controlled trials (RCTs) assessing the effectiveness of non-pharmacological interventions in managing cancer-related pain. No language restrictions were applied, and pain was considered the primary outcome measure. Results: Seventeen RCTs ( Conclusion: This meta-analysis found the significant effectiveness of non-pharmacological nursing strategies, particularly reflexology and massage in reducing cancer-related pain. The findings support their integration into clinical practice, providing evidence-based recommendations for enhancing standard pain management protocols.

Indexed as

acupressureacupuncturearomatherapycancer-related painmassagereflexology

Identifiers

PMID40303318
PMCPMC12037582

What OpenQuestion holds

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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.