Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 May 13;25(1):233.
doi: 10.1186/s12890-025-03699-6.

Influencing mechanisms of kinesiophobia in middle-aged and elderly patients with chronic obstructive pulmonary disease: a cross-sectional study

Yaru Wang  1 , Xiaofang Zou  2 , Chen Xiong  1 , Xiaoqiao Xie  1 , Guilian He  3
Affiliations

Influencing mechanisms of kinesiophobia in middle-aged and elderly patients with chronic obstructive pulmonary disease: a cross-sectional study

Yaru Wang et al. BMC Pulm Med. .

Abstract

Background: The aim of this study is to explore the mechanism of the role of kinesiophobia in patients with chronic obstructive pulmonary disease (COPD), to construct a structural equation model of the factors influencing kinesiophobia in patients with COPD, and to provide a theoretical basis for the development of targeted intervention strategies.

Methods: The cross-sectional design was conducted from December 2023 to July 2024, and middle-aged and elderly patients with COPD from a tertiary hospital in Guangzhou, China, were selected using convenience sampling. A general demographic information questionnaire, Breathlessness Beliefs Questionnaire scale (BBQ), modified Medical Research Council Dyspnea Scale (mMRC), Fatigue Scale (FS-14), Hospital Anxiety and Depression Scale (HADS), Self-Efficacy for Exercise (SEE), and Social Support Rating Scale (SSRS) were used for data collection. Spearman correlation analysis and structural equation modeling (SEM) were used for data analysis.

Results: A total of 278 COPD patients were included. Correlation analysis showed that dyspnoea (r = 0.689, p < 0.01), fatigue (r = 0.731, p < 0.01) and anxiety (r = 0.678, p < 0.01) were significantly positively correlated with kinesiophobia, whereas social support (r=-0.518, p < 0.01) and exercise self-efficacy (r=-0.740, p < 0.01) were significantly negatively correlated with kinesiophobia. SEM analyses revealed six significant pathways of action: dyspnoea, exercise self-efficacy was a direct predictor of kinesiophobia. Fatigue, and social support were indirect predictors of kinesiophobia. Anxiety was a direct and indirect predictor of kinesiophobia.

Conclusions: Dyspnoea, fatigue, anxiety, social support and exercise self-efficacy are important predictors of kinesiophobia in COPD patients. Clinical interventions should focus on the synergistic effects of these five types of variables to establish a multidimensional and comprehensive management programme.

Trial registration: The protocol was reviewed by the Ethics Committee of the Third Affiliated Hospital of Guangzhou Medical University (Ethics Code: LCYJ-2023-055).

Keywords: Chronic obstructive pulmonary disease; Dyspnoea; Exercise self-efficacy; Influencing mechanisms; Kinesiophobia.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study strictly adhered to the relevant provisions of the Declaration of Helsinki and was approved by the the Ethics Committee of the Third Affiliated Hospital of Guangzhou Medical University (Ethics Code: LCYJ-2023-055). All participants were given informed consent and had the right to withdraw from the study at any time. Their names and other confidential information were protected. No harm was caused to the participants during the study. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Structural equation model of kinesiophobia in COPD patients
See this image and copyright information in PMC

References

    1. MacLeod M, Papi A, Contoli M, et al. Chronic obstructive pulmonary disease exacerbation fundamentals: diagnosis, treatment, prevention and disease impact[J]. Respirology. 2021;26(6):532–51. - PubMed
    1. Adeloye D, Song P, Zhu Y, et al. Global, regional, and National prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019. A systematic review and modelling analysis[J]. Lancet Respir Med. 2022;10(5):447–58. - PMC - PubMed
    1. Xing Z, Yang T, Shi S, et al. Combined effect of Ozone and household air pollution on COPD in people aged less than 50 years old[J]. Thorax. 2023;79(1):35–42. - PMC - PubMed
    1. Wang C, Xu J, Yang L, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China pulmonary health [CPH] study): a National cross-sectional study[J]. Lancet. 2018;391(10131):1706–17. - PubMed
    1. Müller A, Wouters EF, Koul P, et al. Association between lung function and dyspnoea and its variation in the multinational burden of obstructive lung disease (BOLD) study[J]. Pulmonology. 2025;31(1):2416815. - PubMed