BACKGROUND: Pharmacological options remain the primary approach for chronic pain management; however, alternative multimodal interventions are necessary. Light therapy, which can modulate circadian (24-h) rhythms, has been increasingly explored as a potential treatment for chronic pain; yet, its efficacy and underlying mechanisms remain unclear. This systematic review summarises evidence on photoreceptor-mediated light therapy for chronic pain in clinical and preclinical studies. METHODS: Four databases (Ovid MEDLINE, EMBASE, PsycINFO, and Web of Science) were searched for studies published up to August 29, 2025. Eligible studies evaluated the effects of light therapy on chronic pain outcomes; risk of bias was assessed using the Cochrane tool for clinical populations and the SYRCLE tool for animal models. Studies involving light acting directly on the site of injury or skin were excluded. Outcomes related to pain were synthesised descriptively due to heterogeneity in study designs and interventions. This review was registered with the PROSPERO database (CRD42023429231). FINDINGS: Of 7757 studies screened, 18 studies were included (11 clinical and 7 preclinical). Overall, light therapy was associated with improvements in pain-related outcomes. However, the findings were inconsistent, particularly when dim-light (low intensity illumination) conditions were used as controls. Evidence was limited by methodological heterogeneity, unclear risk of bias in most preclinical studies, and incomplete assessment of circadian rhythms. INTERPRETATION: Light therapy may represent a promising non-pharmacological intervention for chronic pain. Current evidence is insufficient to draw firm conclusions regarding efficacy or underlying circadian mechanisms. Further well-designed studies incorporating circadian assessments and individual pain profiles are needed. FUNDING: This work was supported by the Canadian Institutes of Health Research (PJT-497592 and MYG-191676).
Building similarity graph...
Analyzing shared references across papers
Loading...
Doriana Taccardi
Hailey G M Gowdy
Emily V Sharp
Queen's University
University Health Network
Centre Hospitalier de l’Université de Montréal
Building similarity graph...
Analyzing shared references across papers
Loading...
Taccardi et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69f5951171405d493affffca — DOI: https://doi.org/10.1016/j.ebiom.2026.106251