JOURNAL ARTICLE

Contributions of patient-generated mental and emotional health status to diaphragm function in young males with low back pain.

  • Published In: Journal of Back & Musculoskeletal Rehabilitation, 2026, v. 39, n. 3. P. 930 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Iwakura, Hirokazu; Terada, Masafumi; Shimozawa, Yuka; Shinohara, Yasushi; Isaka, Tadao 3 of 3

Abstract

This article focuses on the relationship between diaphragm function and psychological health in young males with low back pain (LBP). Using ultrasonography in a standing position, the study found that participants with LBP exhibited significantly reduced contractility in both hemidiaphragms compared to healthy controls. Notably, poorer psychological health, measured by the mental component summary of the Short Form-36 (SF-36), was associated with diminished right hemidiaphragm contractility, while social life dysfunction and pain-related disorders partially explained variance in left hemidiaphragm contractility. These findings suggest that diaphragm dysfunction in LBP may be linked to psychological factors, highlighting the potential value of integrating diaphragm assessment with psychosocial evaluation in clinical management. The study's limitations include its focus on young males, mild pain severity, and cross-sectional design, indicating a need for further research in more diverse populations and longitudinal settings.

Additional Information

  • Source:Journal of Back & Musculoskeletal Rehabilitation. 2026/05, Vol. 39, Issue 3, p930
  • Document Type:Article
  • Subject Area:Anatomy and Physiology
  • Publication Date:2026
  • ISSN:1053-8127
  • DOI:10.1177/10538127251406955
  • Accession Number:193250144
  • Copyright Statement:Copyright of Journal of Back & Musculoskeletal Rehabilitation is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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