Behaviors and Cognitions as Mediators of Psychosocial Variables and Rehospitalizations in Patients with Heart Failure: A Structural Equation Modeling Approach
Abstract
Background. Heart failure is a major financial burden to the United States healthcare system, with much of the cost attributable to frequent re-hospitalizations. . Research has shown that psychosocial variables (e.g., depression, anger, social support) are associated with increased risk of re-hospitalizations in patients with heart failure. In a majority African American population, this study used structural equation modeling to determine the structure of Self-Care and Negative Affect, Attitudes, and Social Support, and their relationship to hospitalizations and death in HF patients. Methods. This was a secondary analysis of a dataset consisting 150 heart failure patients recruited from the University of Maryland Medical Center. Participants were administered measures of psychosocial measures (depression, anxiety, stress, anger, hostility, social support, optimism and self efficacy), as measures of self-care (e.g., dietary and medication adherence and physical activity) and a measure of perceived symptom cognitions. Participants were then followed for up to additional 39 months and data on re-hospitalizations and death were collected. Results. This study determined that: (1) a construct of Negative Affect was comprised of hostility, state and trait anxiety, total stress, total depression, and state and trait anger; (2) a construct of Attitudes was comprised of LOT Pessimism, LOT Optimism, KCCQ Self-efficacy subscale, and an ad-hoc measure of self-efficacy; (3) a Social Support construct was comprised of structural (number of people in social network, number of high contact roles, and number of embedded networks) and functional (ISEL total score) support; and (4) the latent construct of Self-Care was comprised of measures of medication and diet adherence, BMI, and smoking status. Results further indicated that Self-Care predicted mortality and perceived symptoms predicted all-cause hospitalizations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 22, 2016
- Accession Number
- AD1064096
Entities
People
- Felicia Keith
Organizations
- Uniformed Services University of the Health Sciences