Emotional Freedom Techniques for cancer-related sleep disturbance and associated symptoms: A systematic review and meta-analysis
In brief
EFT lowers cancer patients' sleep disturbance score by three points
A meta-analysis of nine trials with 760 cancer patients found that Emotional Freedom Techniques reduced sleep disturbance by an average of three points on the Pittsburgh Sleep Quality Index, with a six-point drop when delivered in a four-week program. Benefits were clear in breast cancer but not other cancers, and early data suggest possible fatigue and pain relief, warranting larger trials.
- Journal
- Complementary therapies in medicine (Q1)
- Published
- 13 August 2026
- Study design
- Systematic review / meta-analysis of RCTs
- Evidence level
- Level 1, High (CEBM 1a)
- Authors
- Huili Xu, Kim Lam Soh, Putri Binti Yubbu, Kim Geok Soh
- PMID
- 42595020
- DOI
- 10.1016/j.ctim.2026.103421
Why clinicians should know about it
- Picked for Complementary and Alternative Medicine (top studies of the week, 16 August 2026): Systematic review, RCTs of EFT for cancer symptoms
Abstract
BACKGROUND: Cancer patients frequently experience a debilitating and interconnected symptom cluster comprising pain, fatigue, and sleep disturbance (P-F-S), which negatively impacts their quality of life and treatment outcomes. Emotional Freedom Techniques (EFT), a mind-body intervention combining cognitive exposure with acupoint stimulation, has shown potential for addressing psychological distress, yet its effectiveness on this specific physiological symptom cluster remains underexplored. OBJECTIVES: This systematic review and meta-analysis aimed to evaluate the efficacy of EFT in alleviating cancer-related sleep disturbance, with narrative syntheses for its effects on pain and fatigue. METHODS: We searched eight databases, including the Cochrane Library, Embase, PubMed, Web of Science, CBM, WeiPu, CNKI, and WanFang from their inception to February 2026. Randomised controlled trials (RCTs) assessing EFT in adult cancer patients, with sleep disturbance as the primary outcome, were included. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment using the Cochrane tool. A random-effects model meta-analysis was performed for sleep disturbance, with subgroup analyses. Narrative syntheses were conducted for pain and fatigue due to insufficient or heterogeneously measured data. RESULTS: Nine RCTs involving 760 patients were included. Six studies using the Pittsburgh Sleep Quality Index (PSQI) were included in the quantitative synthesis. EFT significantly reduced sleep disturbance (MD = -3.00, 95% CI: -4.39 to -1.61, P < 0.01) with high heterogeneity (I² = 97%). Subgroup analyses revealed stronger effects in the 4‑week duration subgroup (MD = -6.50, 95% CI: -7.29 to -5.71, P < 0.01), single sessions ≥30minutes (MD = -3.23, 95% CI: -4.88 to -1.57, P < 0.01), and intervention frequency ≥7 sessions/week (MD = -3.71, 95% CI: -6.24 to -1.18, P < 0.01); EFT alone and combined interventions were equally effective; benefits were significant in breast cancer patients (MD = -2.62, 95% CI: -3.82 to -1.43, P < 0.01) but not in other cancers. Narrative synthesis supported that EFT may relieve fatigue and pain. Sensitivity analysis confirmed robustness, and no publication bias was detected. CONCLUSION: EFT demonstrated beneficial effects on sleep disturbance among cancer patients; however, the statistically significant quantitative evidence was primarily observed in breast cancer populations. The optimal intervention characteristics, including 4-week protocols, single sessions ≥30minutes, and higher frequency, require further confirmation in diverse cancer populations. Narrative evidence suggests that EFT may also provide potential benefits for fatigue and pain. EFT may represent a promising complementary intervention for managing the pain-fatigue-sleep disturbance symptom cluster in cancer patients; however, further high-quality randomized controlled trials are warranted to strengthen the current evidence.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.