STACEY, Adam and SANCHEZ, Dario (2026). Outcome Measures for Dysfunctional Breathing: A Scoping Review of Use, Validation, and Research Gap. Respiratory Medicine: 108883. [Article]
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Sanchez-OutcomeMeasuresForDysfunctional(AM).pdf - Accepted Version
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Abstract
Introduction
Dysfunctional Breathing (DB) is a complex, multifactorial condition affecting respiratory function and quality of life. Its definition remains inconsistent, creating challenges in diagnosis and clinical management. The tools used to assess and monitor DB are heterogeneous, often lack validation, and are applied inconsistently, limiting comparability between studies and clinical decision-making.Aims
This scoping review aims to systematically map the outcome measures used to assess dysfunctional breathing and identify gaps in their application and validation.Methods
A comprehensive search including both peer-reviewed and grey literature was conducted across relevant databases. Screening and data extraction followed Joanna Briggs Institute (JBI) guidelines.Results
Of 239 records identified, 69 studies met inclusion criteria. Twenty-two distinct outcome measures (OMs) were reported, assessing biomechanical (n = 10), biochemical (n = 6), and psychophysiological (n = 4) features of DB and two evaluated more than one dimension. The Nijmegen Questionnaire (NQ) was the most frequently used OM (n = 41). Only 12 studies formally evaluated psychometric properties of the OMs. Populations ranged from paediatric to adult, with fifty-six studies employing multiple OMs rather than a single tool.Conclusion
Outcome measures used to assess dysfunctional breathing are highly heterogeneous, poorly standardised, and rarely fully validated, particularly in populations with comorbidities. No single tool captures all dimensions of the condition, and reliance on multiple measures highlights uncertainty in its definition and assessment rather than true diagnostic precision. Establishing a standardised suite of validated outcome measures, aligned with clearly defined domains of DB, is essential to improve assessment accuracy, clinical utility, and research comparability.More Information
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