OBJECTIVE: The objective of this study was to test a model of individual patient characteristics, covering symptom severity, comorbidity, social support, education, age, socioeconomic status, and gender, derived from Connelly's Model of Self-Care in Chronic Illness as predictors of self-care in heart failure. DESIGN: This was a nonexperimental correlational study. SETTING: The study took place in 6 hospitals in southern California. PATIENTS: The study included 209 patients diagnosed with heart failure by their physicians. The typical study participant was age 73 years, Class III, married, grade-school educated, and earning an income of less than $20,000 per year. The genders were almost equally represented. OUTCOME MEASURE: Self-care was measured by the Evaluating the Change subscale of the Self-Management of Heart Failure Instrument. RESULTS: The model of 7 variables, analyzed by using multiple regression analysis, explained 10.3% of the variance in self-care. Only 2 of the variables were significant predictors of self-care: education (P =.009) and symptom severity (P =.046); 89.7% of the variance remained unexplained. CONCLUSIONS: Persons with higher education and those who are symptomatic may be more likely to engage in self-care than those who are poorly educated or asymptomatic. Further research is needed to confirm these Results and identify other predictors of self-care.
OBJECTIVE: The objective of this study was to test a model of individual patient characteristics, covering symptom severity, comorbidity, social support, education, age, socioeconomic status, and gender, derived from Connelly's Model of Self-Care in Chronic Illness as predictors of self-care in heart failure. DESIGN: This was a nonexperimental correlational study. SETTING: The study took place in 6 hospitals in southern California. PATIENTS: The study included 209 patients diagnosed with heart failure by their physicians. The typical study participant was age 73 years, Class III, married, grade-school educated, and earning an income of less than $20,000 per year. The genders were almost equally represented. OUTCOME MEASURE: Self-care was measured by the Evaluating the Change subscale of the Self-Management of Heart Failure Instrument. RESULTS: The model of 7 variables, analyzed by using multiple regression analysis, explained 10.3% of the variance in self-care. Only 2 of the variables were significant predictors of self-care: education (P =.009) and symptom severity (P =.046); 89.7% of the variance remained unexplained. CONCLUSIONS:Persons with higher education and those who are symptomatic may be more likely to engage in self-care than those who are poorly educated or asymptomatic. Further research is needed to confirm these Results and identify other predictors of self-care.
Authors: R Oosterom-Calo; A J van Ballegooijen; C B Terwee; S J te Velde; I A Brouwer; T Jaarsma; J Brug Journal: Heart Fail Rev Date: 2012-05 Impact factor: 4.214
Authors: Barbara Riegel; Christopher S Lee; Sarah J Ratcliffe; Sabina De Geest; Sheryl Potashnik; Megan Patey; Steven L Sayers; Lee R Goldberg; William S Weintraub Journal: Circ Heart Fail Date: 2012-05-30 Impact factor: 8.790
Authors: Alexander M Clark; John J V McMurray; Caroline E Morrison; David L Murdoch; Simon Capewell; Margaret E Reid Journal: Pharm World Sci Date: 2005-12
Authors: Sarah J Schrauben; Jesse Y Hsu; Sylvia E Rosas; Bernard G Jaar; Xiaoming Zhang; Rajat Deo; Georges Saab; Jing Chen; Swati Lederer; Radhika Kanthety; L Lee Hamm; Ana C Ricardo; James P Lash; Harold I Feldman; Amanda H Anderson Journal: Am J Kidney Dis Date: 2018-03-24 Impact factor: 8.860
Authors: Christopher S Lee; Barbara Riegel; Andrea Driscoll; Jom Suwanno; Debra K Moser; Terry A Lennie; Victoria V Dickson; Jan Cameron; Linda Worrall-Carter Journal: Int J Nurs Stud Date: 2009-05-13 Impact factor: 5.837