The Impact of Behavioral and Psychosocial Protective Factors on Health Outcomes in Heart Failure Patients: A Structural Equation Model Analysis
Abstract
Objective: Heart failure (HF) rates have continued to increase, despite decreases in the incidence of heart disease. In addition to health consequences of HF, it contributes a staggering financial cost to the individual, caregiver, and the broader health care. One significant component of the total cost and burden is frequent hospitalizations. HF research has suggested the importance of behavioral and psychological risk factors, but there has also been increased examination of protective factors that may reduce the progression of HF and improve overall prognosis. This study aims to determine if psychosocial or behavioral protective factors predict improved long-term health status and decreased hospitalizations in HF patients. The present study used a Structural Equation Model (SEM) approach to examine the impact of protective factors on outcomes in HF patients. Method and Results: This study is based on previously collected data from the Behavioral Triggers of Heart Failure (BETRHEART) study. One hundred and fifty participants were administered self-report measures on psychosocial (e.g., positive affect, optimism, self-efficacy, social support, coping styles), and behavioral variables (e.g., medication adherence, sleep quality, physical activity, adherence to a healthy diet), at the baseline assessment and up to a total of 39 months. The Kansas City Cardiomyopathy Questionnaire (KCCQ) was also administered at the baseline and subsequent follow-up assessments to evaluate HF symptoms and health status. Data on hospitalizations were collected over the entire 39-month study period. SEM was conducted to determine whether the two theoretical factors Psychosocial Protective Factor and Behavioral Protective Factor predict hospitalizations and KCCQ health status at a 9-month and up to a 39-month follow-up. Results of a confirmatory factor analysis indicated some of the items/measures had low factor loadings and were removed based on model fit statistics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 10, 2019
- Accession Number
- AD1182694
Entities
People
- Julia A. Garza
Organizations
- Uniformed Services University of the Health Sciences