Unraveling the Key Factors Behind Patient Decision Delay in Aortic Dissection Patients: A Cross-Sectional Study.
Jiaqi Zhang, Yuelin Song, Shimei Jin, Ruiying Zhang, Lehan Li, Shumei Zhuang
Abstract
Open AccessPurpose: To determine the prevalence of patient decision delay in aortic dissection and identify its associated factors, representing the first application of the Self-Regulatory Model as a guiding theoretical framework. Patients and Methods: A total of 386 patients with aortic dissection were enrolled in this single-center, cross-sectional study. Participants were recruited from the emergency department of a tertiary cardiovascular hospital in China, using a convenience sampling methodology. Data were collected using the Brief Illness Perception Questionnaire, the Perceived Barriers to Healthcare-Seeking Decision Scale, and the Social Support Rating Scale. Logistic regression analysis was performed to identify factors associated with patient decision delay. Results: The prevalence of patient decision delay in this study was 67.88% (95% CI: 63.22% - 72.54%). Logistic regression analysis identified several potential factors associated with this delay, including education level, presence of bystanders at symptom onset, Stanford classification, and pain severity. Symptoms such as back pain, abdominal pain, profuse perspiration, and persistent unrelieved pain were also significant. Furthermore, perceived barriers and illness perception were found to be linked to decision delay. Conclusion: Decision delay is a prevalent issue among aortic dissection patients, necessitating targeted interventions. The study confirms that patient decision delay is driven by clinical factors and, crucially, by modifiable factors within the Self-Regulatory Model, such as negative illness perceptions and heightened perceived barriers. Interventions targeting these cognitive and psychosocial barriers are imperative for improving outcomes.