Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Stroke often leads to functional impairment in patients and carries a risk of recurrence. Therefore, it is crucial for post-stroke patients to proactively pursue self-management behaviors that foster functional recovery and prevent recurrent strokes, such as keeping a balanced diet or exercising. The implementation of self-management behaviors requires the combined influence of internal and external factors, which have not been fully explored. This study aimed to investigate the level of self-management behaviors in post-stroke patients and to explore the impact of chronic illness resources, fear of recurrence, hope, and health locus of control on these behaviors.
Methods: A cross-sectional study was conducted among 262 post-stroke patients from a tertiary hospital in Sichuan, China. The scores of the Self-management Behavior Scale for Post-stroke patients, the Chronic Illness Resource Scale, the Fear of Recurrence Inventory Short Form, the Herth Hope Index, and the Multidimensional Health Locus of Control were collected. Multiple linear regression was ultimately used to determine the predictors of self-management behaviors.
Results: The mean score of the Self-management Behavior Scale for Post-stroke patients was 92.23 ± 14.61, with the item mean score of 3.55 ± 0.56. Approximately 56.2% of the variation in self-management behaviors in post-stroke patients could be explained by educational level (β = 0.222, < 0.001), rehabilitation training (β = 0.444, < 0.001), physician/health care team resources (β = 0.139, = 0.007), family and friends resources (β = 0.160, = 0.003), personal resources (β = 0.182, = 0.002), fear of recurrence (β = -0.145, = 0.001), internal locus of control (β = 0.181, < 0.001), and chance health locus of control (β = -0.141, = 0.004).
Conclusion: The self-management of post-stroke patients was moderate, with emotional management and utilization of resources being the weaknesses. Patients' coping abilities, the establishment of a positive psychological locus of control, and the development of a realistic yet constructive recurrence risk perception were beneficial for their self-management. In addition, professional rehabilitation treatment and enhanced support from chronic illness resources such as medical staff and family and friends were also important.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12130028 | PMC |
http://dx.doi.org/10.3389/fmed.2025.1598945 | DOI Listing |