DOI: 10.1097/md.0000000000034595 ISSN:

A new theory to promote self-management of symptom clusters and healthcare quality in patients with decompensated cirrhosis

Zhen Liu, Ling Luo, Yunzhi Zhang, Rong Chen, Anlin Liu
  • General Medicine

Patients with decompensated cirrhosis, a symptomatic phase of cirrhosis, commonly experience multiple symptoms concurrently, referred to as symptom clusters. Effective self-management of symptoms is known to improve outcomes in various chronic diseases. However, a theory for self-management of symptom clusters in decompensated cirrhosis is lacking. In this study, we applied grounded theory research methodology to construct a new theory of self-management of symptom clusters in these patients. This qualitative study prospectively enrolled 20 patients with decompensated cirrhosis within 1 week after hospital admission. Data related to patients’ experiences, needs, perspectives, and abilities related to their symptoms were collected via a semi-structured, in-depth interview and analyzed with Nvivo version 20 software. Grounded theory methodology with 3 coding steps (open, axial, and selective coding) was applied to generate a theory of self-management of symptom clusters. From the step-by-step coding process, 2 core categories or major themes were identified: patients’ experiences with symptoms and coping with symptoms. The first major theme included symptom clustering, multidimensionality, recurrence, and specificity, while the second consisted of endogenous motivation, endogenous resistance, and external support needs. A new theory of self-management of symptom clusters was then constructed and delineated to enhance self-management among patients with decompensated cirrhosis. Using patient experience data, we developed a new theory of self-management of symptom clusters in patients with decompensated cirrhosis. Use of this theory has the potential to promote patient self-management and guide healthcare providers in planning optimal treatments and implementing timely interventions, ultimately improving in patient outcomes.

More from our Archive