Relationship between anxiety and depression, dyspnea severity, and pulmonary function in connective tissue disease-associated interstitial lung disease

doi:10.5498/wjp.v15.i12.110916

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 15, Issue 12

This Article

(36)

(45)

(0)

(701)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Psychiatry

ISSN

2220-3206

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Psychiatry. Dec 19, 2025; 15(12): 110916
Published online Dec 19, 2025. doi: 10.5498/wjp.v15.i12.110916

Full Size Figure Download Figure

Figure 3 Forest plot of marginal estimation results of mixed-effect model. FVC: Forced vital capacity; DLCO: Diffusing capacity of the lungs for carbon monoxide; GAD-7: Generalized anxiety disorder-7; PHQ-9: Patient health questionnaire-9.

Citation: Zhu ZJ, Liu KL, Qu HR. Relationship between anxiety and depression, dyspnea severity, and pulmonary function in connective tissue disease-associated interstitial lung disease. World J Psychiatry 2025; 15(12): 110916
URL: https://www.wjgnet.com/2220-3206/full/v15/i12/110916.htm
DOI: https://dx.doi.org/10.5498/wjp.v15.i12.110916

Zhu ZJ, Liu KL, Qu HR. Relationship between anxiety and depression, dyspnea severity, and pulmonary function in connective tissue disease-associated interstitial lung disease. World J Psychiatry 2025; 15(12): 110916 [PMID: 41357912 DOI: 10.5498/wjp.v15.i12.110916]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.