Background and objectives:
     
     Disorders of gut-brain interaction are highly prevalent and burdensome conditions for both patients and healthcare systems. Given the limited effectiveness of pharmacotherapy in treating disorders of gut-brain interaction, non-pharmacological interventions are increasingly used; however, the value for money of non-pharmacological treatments is uncertain. This is the first review to assess the economic evaluation evidence of non-pharmacological interventions for disorders of gut-brain interaction.
   

Methods:
     
     A scoping review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. Reporting adhered to ISPOR's good practices for systematic reviews with cost and cost-effectiveness outcomes. Comprehensive searches were performed on 24 October, 2023, and an updated search was run on 18 May, 2024 in PubMed/MEDLINE, Embase, Web of Science, Scopus and the International HTA database, with two reviewers screening studies in parallel. The novel Criteria for Health Economic Quality Evaluation (CHEQUE) framework was used to assess methodological and reporting quality. Reporting quality was further assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022.
   

Results:
     
     Fifteen studies were included. Most studies examined treatments for irritable bowel syndrome. Cognitive behavioural therapy, dietary interventions and sacral neuromodulation were cost effective. Acupuncture and physiotherapy were not. CHEQUE assessment showed 12 studies met at least 70% of the methodological criteria, and 14 studies achieved 70% or more for reporting quality.
   

Conclusions:
     
     This review highlights gaps in the current evidence base, particularly in the robustness and generalisability of results due to methodological inconsistencies. Future research should incorporate longer follow-ups, comprehensive cost assessments, subgroup analyses, equity considerations and clearer justifications for modelling assumptions.