<abstract xmlns="http://www.w3.org/1999/xhtml">

<sec>
<h3>Objective</h3>
<p>To examine physical activity (PA) of post-percutaneous coronary intervention (PCI) patients and explore the demographic, clinical, and social psychological characteristics associated with PA levels.</p>
</sec>
<sec>
<h3>Methods</h3>
<p>A total of 246 post-PCI patients from the Peking University Third Hospital in Beijing, China, were included in this crosssectional study through convenience sampling. Data were collected from a self-reported questionnaire. PA was categorized into low, moderate, or high levels. The ordinal multinomial logistic regression model was used to estimate the relationship among demographic, medical, and psychosocial characteristics.</p>
</sec>
<sec>
<h3>Results</h3>
<p>The overall prevalence of low, moderate, and high PA was 20%, 70%, and 10%, respectively. For the domain-specific PA patterns, most participants took part in leisure-time PA (84.5%); walking was the most common PA. Increased motivation and selfefficacy, lower monthly income, and unemployment were predictors of high PA.</p>
</sec>
<sec>
<h3>Conclusions</h3>
<p>PA levels in post-PCI patients was not optimal, and leisure-time PA had the highest participation rate. Analyses of influencing factors can provide medical staff and health workers information to focus on high-risk groups and introduce more tailored interventions. Future studies can explore more regions, and ecological models can be introduced to study more influencing factors.</p>
</sec>
</abstract>

Objective
To examine physical activity (PA) of post-percutaneous coronary intervention (PCI) patients and explore the demographic, clinical, and social psychological characteristics associated with PA levels.


Methods
A total of 246 post-PCI patients from the Peking University Third Hospital in Beijing, China, were included in this crosssectional study through convenience sampling. Data were collected from a self-reported questionnaire. PA was categorized into low, moderate, or high levels. The ordinal multinomial logistic regression model was used to estimate the relationship among demographic, medical, and psychosocial characteristics.


Results
The overall prevalence of low, moderate, and high PA was 20%, 70%, and 10%, respectively. For the domain-specific PA patterns, most participants took part in leisure-time PA (84.5%); walking was the most common PA. Increased motivation and selfefficacy, lower monthly income, and unemployment were predictors of high PA.


Conclusions
PA levels in post-PCI patients was not optimal, and leisure-time PA had the highest participation rate. Analyses of influencing factors can provide medical staff and health workers information to focus on high-risk groups and introduce more tailored interventions. Future studies can explore more regions, and ecological models can be introduced to study more influencing factors.

Physical activity levels and predictors in patients following percutaneous coronary intervention: a cross-sectional study

Frontiers of Nursing

This work is licensed under the Creative Commons Attribution 4.0 International License.

Objective
To examine physical activity (PA) of post-percutaneous coronary intervention (PCI) patients and explore the demographic, clinical, and social...

Physical activity levels and predictors in patients following percutaneous coronary intervention: a cross-sectional study

Article Category: Original Article

Published Online: Dec 18, 2023

Page range: 471 - 480

Received: Nov 25, 2022

Accepted: Feb 02, 2023

DOI: https://doi.org/10.2478/fon-2023-0051

Keywords
cardiac rehabilitation, determinant, percutaneous coronary interventions, physical activity, prevalence

© 2023 Xiao-Lin Feng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Physical activity levels and predictors in patients following percutaneous coronary intervention: a cross-sectional study

Article Category: Original Article

Published Online: Dec 18, 2023

Page range: 471 - 480

Received: Nov 25, 2022

Accepted: Feb 02, 2023

DOI: https://doi.org/10.2478/fon-2023-0051

Keywordscardiac rehabilitation, determinant, percutaneous coronary interventions, physical activity, prevalence

© 2023 Xiao-Lin Feng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
cardiac rehabilitation, determinant, percutaneous coronary interventions, physical activity, prevalence