Evidence map›Paper›PMID 41873031›Full record

SynthesisPsycho-oncology2026

Efficacy of Mindfulness-Based Interventions for Reducing Cancer-Related Fatigue: A Systematic Review and Meta-Analysis.

Jihyun Lee, Myoungsuk Kim

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Psycho-oncology, 2026. 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

2 authors.

Jihyun LeeCollege of Nursing, Kangwon National University, Chuncheon-si, Gangwon-do, Republic of Korea.
Myoungsuk KimCollege of Nursing, Kangwon National University, Chuncheon-si, Gangwon-do, Republic of Korea.ORCID https://orcid.org/0000-0002-1495-5153

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer-related fatigue (CRF) is a common and distressing symptom among patients with cancer. Although mindfulness-based interventions (MBIs) are increasingly applied for CRF management, evidence regarding their efficacy remains inconsistent.

aimsThis systematic review and meta-analysis aimed to evaluate the efficacy of MBIs in reducing CRF.

methodsPubMed, EMBASE, Web of Science, Cochrane, and CINAHL were comprehensively searched from database inception to August 31, 2025, for randomized controlled trials (RCTs) involving patients with cancer who received MBIs. The primary outcome of interest was fatigue. The risk of bias was assessed using the Cochrane risk-of-bias 2.0 tool. A meta-analysis was performed using a random-effects model, and standardized mean differences (SMDs) with 95% confidence intervals (CI) were calculated. Subgroup analyses, meta-regressions, publication bias assessments, and sensitivity analyses were also performed.

resultsA total of 29 RCTs involving 3178 participants were included. Compared with control interventions, MBIs were associated with significantly lower fatigue levels (SMD = -0.89; 95% CI: -1.23 to -0.55, p < 0.001). However, substantial heterogeneity was observed (I

conclusionsThis study demonstrates that MBIs are an efficacious approach for significantly reducing fatigue among patients with cancer, supporting the role and broader application of nonpharmacological strategies in managing CRF. However, substantial between-study heterogeneity, moderate certainty of evidence, and indications of publication bias warrant cautious interpretation of the pooled estimates.

Indexed as

FatigueMindfulnessNeoplasmsHumansRandomized Controlled Trials as TopicTreatment Outcomecancerfatiguemeta‐analysismindfulness‐based intervention

Identifiers

PMID41873031
PMCPMC13009704

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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.