PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Card Fail. Author manuscript; available in PMC 2010 August 1.
Published in final edited form as:
PMCID: PMC2745342
NIHMSID: NIHMS137911

Heart Failure Self-care in Developed and Developing Countries

Barbara Riegel, DNSc, RN, FAAN, FAHA, Professor, Andrea Driscoll, PhD, RN, Senior Research Fellow, Jom Suwanno, PhD, RN, Assistant Professor, Debra Moser, DNSc, RN, FAAN, FAHA, Professor, Gill Endowed Chair, Terry A. Lennie, PhD, RN, Associate Professor, Misook L. Chung, PhD, RN, Assistant Professor, Jia-Rong Wu, PhD, RN, Post-Doctoral Fellow, Victoria Vaughan Dickson, PhD, RN, Assistant Professor, Beverly Carlson, MS, RN, Lecturer, and Jan Cameron, MSN, RN, PhD Student

Abstract

Background

Heart failure (HF) self-care is poor in developed countries like the United States, but little is known about self-care in developing countries.

Methods

2,082 adults from two developed (United States and Australia) and two developing countries (Thailand and Mexico) were studied in a descriptive, comparative study. Self-care was measured using the Self-Care of HF Index (SCHFI), which provided scores on self-care maintenance, management, and confidence. Data were analyzed using regression analysis after demographic (age, gender, education), clinical (functional status, experience with the diagnosis, comorbid conditions), and setting of enrollment (hospital or clinic) differences were controlled.

Results

When adequate self-care was defined as a standardized score ≥70%, self-care was inadequate in most scales in most groups. Self-care maintenance was highest in the Australian sample and lowest in the Thai sample (p<.001). Self-care management was highest in the U.S. sample and lowest in the Thai sample (p<.001). Self-care confidence was highest in the Mexican sample and lowest in the Thai sample (p<.001). Determinants differed for the three types of self-care (e.g., experience with HF was associated only with self-care maintenance).

Conclusion

Interventions aimed at improving self-care are greatly needed in both the developed and the developing countries studied.

Keywords: Self-management, treatment adherence, Hispanic, minority groups

Heart failure (HF) is the most common and expensive chronic illness among older people in developed countries. In the United States alone, the prevalence of HF is 5,700,000, with one in eight deaths attributable to HF (1). Australia also is caring for a large number of cases, with HF accounting for 2.0% of all deaths in 2002 (2). In developing countries, the epidemiology of HF is becoming increasingly similar to that of industrialized nations. Once communicable diseases and malnutrition are controlled, population aging, hypertension and ischemic heart disease contribute to a rising prevalence of HF (2-5). For example, in Thailand, heart disease is the primary cause of death and 70% of all cardiac deaths in Thailand in 2003 were attributed to HF (6). The prevalence of HF in Latin American countries is currently undocumented although the increase in publications on HF from these countries suggests a rising prevalence of HF (7).

Several studies have demonstrated that poor self-care is associated with admission to the hospital with worsening HF (8-12). Self-care refers to the naturalistic decision-making process that patients use in the choice of behaviors that maintain physiologic stability—symptom monitoring and treatment adherence—and the response to symptoms when they occur (13). Self-care is poor in U.S. and European samples (14-16), but little is known about the adequacy of self-care in developing countries. Exploring HF self-care in developed and developing countries can improve the planning of public health initiatives in countries with increasingly diverse populations. Therefore, the purpose of this study was to describe and compare self-care in two developed - U.S. and Australia - and two developing countries - Thailand and Mexico.

Methods

This study was a descriptive, comparative study of 2,082 adults with chronic HF. The samples had been recruited for other studies between 2002 and 2007. Self-care was measured in each group using the Self-Care of HF Index (SCHFI), a 15 item measure of self-care maintenance, management, and confidence described below (17). All participants had a diagnosis of chronic HF confirmed using objective criteria and all resided in a private residence where self-care was a reasonable expectation. Subtle differences in inclusion and exclusion criteria are shown in Table 1. All studies had been approved by the local institutional review board overseeing research. Each study conformed to the principles outlined in the Declaration of Helsinki and all participants provided informed consent.

Table 1
Details of the Parent Studies from which Data were obtained for this Analysis

Sampling

A team of collaborating HF investigators gathered six samples of HF patients from the United States (2 samples), Australia (2 samples), Thailand, and Mexico. All available subjects were used in the analysis except for three Hispanic patients enrolled in the U.S. sample who were deleted from the database to avoid confounding the comparison with the Mexican sample.

United States

Two samples of adults with HF were enrolled from four states in the eastern United States. In the first sample, 131 patients were enrolled from either an out-patient HF clinic (71%) or during an acute hospitalization in Pennsylvania. These patients were pre-screened by staff, so the number screened is not available, but of those eligible and referred, 85% were enrolled. In the second sample, 322 patients were enrolled from out-patient settings in Kentucky, Indiana, and Georgia; 65.5% of those eligible to participate agreed to do so.

Australia

Two samples of HF patients were enrolled from Australia. The first sample of 1045 patients was recruited from HF disease management programs across the continent of Australia. Forty-nine of the 65 programs existing in 2006 and 2007 participated in the study (74% program participation rate). Each of these out-patient programs enrolled a consecutive sample of at least 20 patients; 66.1% of eligible patients agreed to participate. This was the only sample that had received an intervention (i.e., disease management) before self-care was measured. The second sample of 50 consecutive patients was drawn from HF patients hospitalized in Melbourne, Australia between June and December 2005. In this sample, 52% of eligible patients agreed to participate.

Thailand

A consecutive sample of 400 Thai HF patients was enrolled from four tertiary care hospitals and two smaller community hospitals randomly selected from 12 hospitals in southern Thailand; 91% were enrolled while hospitalized. In this sample, 98.5% of eligible patients agreed to participate. In Thailand, most persons invited to participate in research conducted by students seeking a higher academic degree agree to participate.

Mexico

A consecutive sample of 134 self-identified Hispanics of Mexican decent was enrolled during a hospitalization at two participating community hospitals in Southern California close to the United States-Mexico border (18). Although these patients were technically living in the U.S., few had acculturated, defined as the extent to which they had adapted to the U.S. culture (19). Acculturation was measured using the 5-item Short Acculturation Scale for Hispanics (20), with possible scores ranging from 5 to 25; lower scores indicate less acculturation. Over half (52%) of the patients in the sample were completely unacculturated (score = 5). The average score was low (X = 8.2 ± 5.4) and only eight (6%) had a score of 25 indicating full acculturation into U.S. society. Most (55%) completed all data collection in Spanish. There were no significant differences in age, gender, or self-care scores between those acculturated and those not acculturated, so the full sample of 134 was retained for analysis. Although these patients used the U.S. health care system, no disease management programs were available in the area at the time this study was conducted. Most were treated in free neighborhood clinics or by Hispanic providers; many routinely returned to Mexico for care that was not urgent.

Measurement

Sociodemographic variables were measured using investigator-designed surveys. Clinical information was obtained primarily from medical record review. Comorbid illnesses were measured using the Charlson Comorbidity Index (21). Scores can range from 0 to 34 but every study participant had a score of at least 1 because all had HF. Responses are summed, weighted, and indexed into one of three categories (low, moderate, or high) according to the published method. Validity was demonstrated by the instrument authors when comorbidity category predicted mortality, complications, health care resource use, length of hospital stay, discharge disposition, cost.

In each study, HF self-care was quantified using the Self-Care of HF Index (SCHFI) (17). Except for the Australian sample obtained from disease management programs, only baseline data obtained before the receipt of any planned intervention were used in this analysis. The 15 item SCHFI uses a 4-point Likert scale to gather information used to form three scales: self-care maintenance, management, and confidence. Maintenance and management are the essential elements of self-care; confidence is thought to be a mediator or moderator of the relationship between self-care and outcomes (13). For this reason, the three scale scores are calculated separately.

Self-care maintenance items assess treatment adherence behaviors and self-monitoring performed to prevent an acute exacerbation of HF (e.g., daily weighing). Self-care management items assess ability to recognize symptoms when they occur, evaluate symptoms, make decisions about treatments (e.g., take an extra diuretic for weight gain), and evaluate the effectiveness of the treatments implemented. Items measuring self-care confidence address the patient’s perceived ability to engage in each phase of self-care (e.g., recognize symptoms). Scores on each of the scales are standardized to 100; higher scores reflect better self-care. In this study, the internal consistency of the SCHFI scales were .61 (maintenance), .67 (management), and .88 (confidence). The SCHFI has been shown previously to be valid and sensitive to subtle behavioral changes in a variety of HF samples (22-24).

Translation

The SCHFI was translated into both Thai and Spanish for the studies used in this analysis. The Thai process of translation and back-translation was guided by the methods of Brislin (25). Decentering and back translation techniques were used to ensure culturally equivalent versions in the Thai language. Decentering refers to a process by which material in an original language (English), when translated, is changed so that there is a smooth, natural-sounding version in another language (Thai). A back translation technique was employed to ensure accuracy in the translation. The SCHFI was translated into Thai by a native Thai speaker and back translated into English by two bilingual translators fluent in both languages. Items with apparent discrepancies between the two language versions were modified until both the researcher and the translators mutually agreed that the final back translation conveyed the same meaning as the original. Two rounds of back translation were conducted. The modified Thai version of the SCHFI was judged by a panel of experts to be clinically and culturally valid.

A similar rigorous process was used in the translation of the SCHFI into Spanish. The SCHFI was translated into Spanish and back translated into English by two fluently bilingual translators. Items with discrepancies between the two language versions were modified and back translated again until the translators mutually agreed that the back translation conveyed the same meaning as the original SCHFI. Then the Spanish version of the SCHFI was judged by a panel of experts to be clinically and culturally valid.

Analysis

Raw data from each site were integrated into a single database. Scores were computed for each of the three SCHFI scales—self-care maintenance, management, confidence. Self-care management scores were computed only for persons who were symptomatic in the prior month, as specified in the instrument scoring instructions. Correlations between the mean self-care scores (maintenance, management, and confidence) were computed for each of the four countries.

Adequacy of self-care was defined as a standardized score of ≥ 70 on each scale, based on prior research (24, 26). The proportion of the sample in each group scoring within the adequate range on each of the self-care scales was compared using Pearson Chi-square analysis. Then binary logistic regression analysis with an enter method was used to identify the determinants of self-care maintenance, management, and confidence.

Factors anticipated to influence self-care were entered in the first step and country was entered in a separate, second step. The factors anticipated to influence self-care were age (27), gender (27), education (28), functional status measured using New York Heart Association (NYHA) class (28), comorbid illness severity (27), and experience with the HF diagnosis (29). Less than or equal to two months was used as the cut-point for experience, based on prior results showing that even without intervention, patients develop some competence in HF self-care within the first two months after diagnosis (29). In addition, the setting of enrollment (hospital vs. clinic) differed among the participants and the sites so this characteristic was adjusted as well. Some factors shown previously to be associated with poor self-care - worse cognition, more sleepiness, higher depression, and poorer family functioning (24) - were not measured consistently in all the studies so these factors could not be adjusted in analyses. Simple comparisons were performed using the last category as the reference group.

Results

The samples representing the four countries differed in their demographic and clinical profiles (Table 2). The U.S. sample was the youngest. The samples from the developing countries were more likely to be female than those from the developed countries. Education was lower in the developing countries. The sample from the U.S. had a higher level of comorbid illness than the samples from the other countries.

Table 2
Demographic and Clinical Characteristics of the Combined Samples from the Four Countries

Correlations between Mean Self-Care Scores by Country

In the full sample, self-care maintenance, management and confidence were significantly but only moderately correlated. When separate analyses were done using each individual country alone, in the U.S. sample the correlations were similar to that of the full sample, but in the Mexican and Australian samples, the correlations were lower. Correlations among the three scales were highest in the Thai sample (Table 3).

Table 3
Mean Scale Scores Separated by Country, with Scale Correlations

Adequacy of Self-Care

When the proportion of participants adequate in self-care was compared across the four countries, adequate self-care maintenance was significantly more common in those from Australia than any of the other countries (Figure 1) (p<.001). Self-care management was inadequate in most of the samples but it was adequate most commonly in the U.S. sample and least commonly in the Thai sample (52.5% vs. 5%); the difference among the countries was statistically significant (p<.001). Adequate self-care confidence was most common in the Mexican sample and least common in the Thai sample (65.6% vs. 17.5%, p<.001).

Figure 1
Comparison of Self-Care Adequacy across Developed and Developing Countries

Determinants of Self-Care

When age, gender, education, functional status, comorbid illness severity, experience with HF, and setting of enrollment (hospital vs. clinic) were entered into the logistic regression equation first, they explained 25.8% of the variance in self-care maintenance. When country was entered in a separate step, it added an additional 5.2% variance in self-care maintenance. Significant determinants of self-care maintenance were higher education, experience with the diagnosis, lower or better NYHA class, and country. Setting where enrolled, age, gender, and comorbidity were not significant determinant of self-care maintenance (Table 5).

Table 5
Logistic Regression Analysis Indentifying Determinants of Self-Care Maintenance, Management, and Confidence Adequacy after Accounting for the Influence of Covariates

The model of seven covariates explained 10.3% of the variance in self-care management. When country was entered in the second step, country added 7.8% of the variance in self-care management. Significant determinants of self-care management were younger age, more comorbid illnesses, and country. Gender, education, experience with the illness, setting where enrolled, and functional status were not significant determinants of self-care management.

The model of seven covariates explained only 8.4% of the variance in self-care confidence. When country was entered in the next step, an additional 6.7% of the variance in self-care confidence was explained. Significant determinants of self-care confidence were relatively younger age, less comorbid illness, higher education, and lower or better NYHA class, and country. Gender, experience with HF, and setting where enrolled were not significant determinants of self-care confidence.

Discussion

The results of this study demonstrate poor self-care in chronic HF patients in all four countries, with few notable distinctions. Self-care maintenance was adequate most commonly in the Australian sample. This finding may be explained by the fact that most of the Australian sample was obtained based on their participation in a HF disease management program (30). However, a determinant of self-care maintenance that differed in the Australian sample was functional status. Better functional status was a significant determinant of self-care maintenance and the Australian sample had the lowest proportion of NYHA class III and IV participants.

Adequate self-care management was significantly more common in the U.S. sample compared to the others. Two determinant of self-care management that differed in the U.S. sample were age and comorbid illness. The U.S. sample was the youngest, on average, yet they had the highest proportion of severe comorbid illness. These factors may explain the higher self-care management scores in the U.S. sample.

Adequate self-care confidence was more common in the Mexican sample than the other samples. The confidence scale is the only scale of the SCHFI that demonstrates some social desirability. That is, some of the items in this scale stimulate people to respond in the manner they think others want them to respond. So, we suspect that social desirability may have something to do with the high confidence scores in the Mexican sample. But, regardless of the reason for it, confidence is an important factor that influences the relationship between self-care and clinical outcomes (13). In a secondary analysis of the data from the Mexican sample included in this article, Lee and colleagues (31) demonstrated that when self-care confidence was assessed as a moderator of the relationship between self-care management and acute care costs, higher self-care management was associated with lower direct inpatient costs. This finding illustrates the importance of identifying ways to build self-care confidence in HF patients. Disease management is one way to build confidence in self-care ability (32). Another factor associated with self-care confidence is functional status, which is amenable to influence. For example, when HF patients adhere to a low sodium diet, they retain less fluid, which improves functional status (33). Helping patients see the relationship between their self-care and their functional abilities may build confidence in self-care.

Self-care in the Thai sample was poor in every category of HF self-care. The reason for low self-care in the Thai population is probably that community awareness and understanding of HF is low in Thailand. A decade ago, HF was not widely recognized as a major cause of death in Thailand (6) so knowledge about how to care for oneself or a family member with HF is not widely known. Self-care is a cultural norm in Thailand (34), though, so once knowledge about how to care for this chronic illness is disseminated we expect self-care to increase.

The determinants of self-care maintenance, management, and confidence differed among the countries in an interesting fashion. Younger aged patients were more likely to have adequate self-care management and confidence in this study. It may be that those patients who are relatively younger are used to making decisions about their health care while older patients expect decisions to be made by the provider. Another interpretation is that older patients struggle relatively more with symptom recognition because of age-related changes in interoception (35).

Higher education was associated with better self-care maintenance and confidence scores. This finding substantiates that of Rockwell et al. (28) who, using an early version of the same measure of self-care maintenance, also found that higher education was associated with better HF self-care. It may be that formal education makes it easier for patients to understand the rationale behind self-care. The finding that experience with the diagnoses was associated with better self-care maintenance is consistent with that of Francque-Frontiero et al. (36) who, using an early version of the same measure of self-care maintenance, also noted that those diagnosed more than two months prior had better self-care even without provider intervention. So, some learning occurs with early experience with the diagnosis.

We found that more comorbid illnesses was associated with better self-care management but not with self-care maintenance, as Chriss et al. (27) had found using an early version of the same measure of self-care maintenance. It may be that as HF patients become more ill, attending to self-care becomes more salient to them. It was interesting, though, that low comorbidity, not high, was a determinant of self-care confidence. It may be that when other illnesses do not confuse the picture, patients are more confident that they can use self-care to manage their HF.

Functional status measured using the NYHA classes was associated with both self-care maintenance and confidence; better functional status was associated with better self-care. Those with better functional status may have energy to devote to self-care. They may also believe that because they are less symptomatic they must be managing their HF well. These results differ from those of Rockwell et al. (28) who found that patients with worse NYHA scores were more likely to engage in self-care than those who were asymptomatic.

Limitations of this study include the secondary analytic approach. The data sets used in this study were all collected for other primary studies and integrated for the current analysis. The data were not uniformly sampled, although most were consecutive samples and one was both consecutive and random. These differences may have influenced the results. Because of differences in the data collected, possible confounding variables were unavailable for use as covariates in the analysis. Type of HF was unavailable in a large proportion of the Thai sample because echocardiography is not routinely performed in Thailand. However, the etiology of most cases of HF was ischemic, so the HF type can be assumed to be primarily systolic. Another limitation was the demographic, clinical, and treatment differences among the groups. Differences among the groups required statistical adjustment that may not have adequately controlled existing differences. Another limitation was that no Aborigines were enrolled in the Australian samples. They were not excluded on purpose, but most of the participants were obtained from the coastal areas. At the time these studies were conducted, there were no HF programs in Central Australia, top of Western Australia, or in Central Queensland (36), the areas of Australia most densely populated with Aborigines. As there were no programs in these areas it naturally restricted the number of the indigenous population recruited into the Australian cohort.

In summary, we found significant differences in self-care in the four countries we sampled, but self-care was not adequate in the majority of any of the samples studied. The attention given to translating the measure of self-care into the languages used by the two groups that were not native English speakers—Thai and Spanish—suggests that these differences reflect true differences in self-care rather than a lack of cultural sensitivity of the measure. These results illustrate an important opportunity for improvement in the care provided to HF patients worldwide. Future research is needed to identify ways to improve self-care maintenance, management, and confidence in both developed and developing countries.

Table 4
Correlation Matrix Displaying the Relationship between Self-Care Scores in the Four Groups

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Barbara Riegel, University of Pennsylvania School of Nursing, Philadelphia, PA.

Andrea Driscoll, Monash University, Dept of Epidemiology and Preventive Medicine, Melbourne, Australia.

Jom Suwanno, Walailak University School of Nursing, Thailand.

Debra Moser, University of Kentucky, College of Nursing, Lexington, KY.

Terry A. Lennie, University of Kentucky, College of Nursing, Lexington, KY.

Misook L. Chung, University of Kentucky, College of Nursing, Lexington, KY.

Jia-Rong Wu, University of Kentucky, College of Nursing, Lexington, KY.

Victoria Vaughan Dickson, New York University, College of Nursing, New York, NY.

Beverly Carlson, School of Nursing, San Diego State University, San Diego, CA.

Jan Cameron, School of Nursing and Midwifery, Australian Catholic University, Fitzroy, Victoria, Australia.

References

1. Lloyd-Jones D, Adams R, Carnethon M, et al. Heart Disease and Stroke Statistics--2009 Update. A Report From the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2008
2. Clark RA, McLennan S, Dawson A, et al. Uncovering a hidden epidemic: a study of the current burden of heart failure in Australia. Heart Lung Circ. 2004;13:266–73. [PubMed]
3. Mendez GF, Cowie MR. The epidemiological features of heart failure in developing countries: a review of the literature. Int J Cardiol. 2001;80:213–9. [PubMed]
4. Yip GW, Ho PP, Woo KS, Sanderson JE. Comparison of frequencies of left ventricular systolic and diastolic heart failure in Chinese living in Hong Kong. Am J Cardiol. 1999;84:563–7. [PubMed]
5. Najafi F, Dobson AJ, Jamrozik K. Recent changes in heart failure hospitalisations in Australia. Eur J Heart Fail. 2007;9:228–33. [PubMed]
6. Heart Association of Thailand Cardiovascular epidemiology in Thailand. [cited 2003 December 12]; Available from: http://www.thaiheart.org/epidemiology/first.htm.
7. World Heart Failure Society . Prevalence, incidence, aetiology and management of heart failure in Latin America. Sticares Foundation; The Netherlands: 2006. [updated 2006; cited 2008 December 7]; Available from: http://www.worldheartfailure.org/index.php?item=83.
8. Vinson JM, Rich MW, Sperry JC, et al. Early readmission of elderly patients with congestive heart failure. J Am Geriatr Soc. 1990;38:1290–5. [PubMed]
9. Opasich C, Rapezzi C, Lucci D, et al. Precipitating factors and decision-making processes of short-term worsening heart failure despite “optimal” treatment (from the IN-CHF Registry) Am J Cardiol. 2001;15(88):382–7. [PubMed]
10. Bennett S, Huster G, Baker S, et al. Characterization of the precipitants of hospitalization for heart failure decompensation. Amer J Crit Care. 1998;7:168–74. [PubMed]
11. Tsuyuki RT, McKelvie RS, Arnold JM, et al. Acute precipitants of congestive heart failure exacerbations. Arch Intern Med. 2001;161:2337–42. [PubMed]
12. Ghali JK, Kadakia S, Cooper R, Ferlinz J. Precipitating factors leading to decompensation of heart failure. Traits among urban blacks. Arch Intern Med. 1988;148:2013–6. [PubMed]
13. Riegel B, Dickson V. A Situation-Specific Theory of Heart Failure Self-Care. J Cardiovasc Nurs. 2008;23:190–6. [PubMed]
14. Artinian NT, Magnan M, Sloan M, Lange MP. Self-care behaviors among patients with heart failure. Heart Lung. 2002;31:161–72. [PubMed]
15. Carlson B, Riegel B, Moser DK. Self-care abilities of patients with heart failure. Heart Lung. 2001;30:351–9. [PubMed]
16. Jaarsma T, Abu Saad HH, Dracup K, Halfens R. Self-care behaviour of patients with heart failure. Scandinavian Journal of Caring Sciences. 2000;14:112–9. [PubMed]
17. Riegel B, Carlson B, Moser DK, et al. Psychometric testing of the self-care of heart failure index. J Card Fail. 2004;10:350–60. [PubMed]
18. Riegel B, Carlson B, Glaser D, Romero T. Randomized controlled trial of telephone case management in Hispanics of Mexican origin with heart failure. J Card Fail. 2006;12:211–9. [PubMed]
19. Park-Taylor J, Ng V, Ventura AB, et al. What it means to be and feel like a “true” American: perceptions and experiences of second-generation Americans. Cultur Divers Ethnic Minor Psychol. 2008;14:128–37. [PubMed]
20. Marin G, Sabogal F, Marin B, et al. Development of a short acculturation scale for Hispanics. Hisp J Behav Sci. 1987;9:183–205.
21. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40:373–83. [PubMed]
22. Riegel B, Carlson B. Is individual peer support a promising intervention for persons with heart failure? J Cardiovasc Nurs. 2004;19:174–83. [PubMed]
23. Riegel B, Dickson VV, Hoke L, et al. A motivational counseling approach to improving heart failure self-care: mechanisms of effectiveness. J Cardiovasc Nurs. 2006;21:232–41. [PubMed]
24. Riegel B, Vaughan Dickson V, Goldberg LR, Deatrick JA. Factors associated with the development of expertise in heart failure self-care. Nurs Res. 2007;56:235–43. [PubMed]
25. Brislin RW. Translation and content analysis of oral and written materials: Methodology. In: Triandis HC, Berry JW, editors. Handbook of cross-cultural psychology. Allyn & Bacon; Boston: 1980. pp. 389–444.
26. Dickson VV, Deatrick JA, Riegel B. A typology of heart failure self-care management in non-elders. Eur J Cardiovasc Nurs. 2008;7:171–81. [PubMed]
27. Chriss PM, Sheposh J, Carlson B, Riegel B. Predictors of successful heart failure self-care maintenance in the first three months after hospitalization. Heart Lung. 2004;33:345–53. [PubMed]
28. Rockwell JM, Riegel B. Predictors of self-care in persons with heart failure. Heart Lung. 2001;30:18–25. [PubMed]
29. Francque-Frontiero L, Riegel B, Bennett J, et al. Self-care of persons with heart failure: Does experience make a difference? Clin Excel Nurse Pract. 2002;6:23–30.
30. McAlister FA, Stewart S, Ferrua S, McMurray JJ. Multidisciplinary strategies for the management of heart failure patients at high risk for admission: a systematic review of randomized trials. J Am Coll Cardiol. 2004;44:810–9. [PubMed]
31. Lee CS, Carlson B, Riegel B. Heart failure self-care improves economic outcomes, but only when self-care confidence is high. J Card Fail. 2007;2007(13):S75.
32. Smith B, Forkner E, Krasuski RA, et al. Educational attainment has a limited impact on disease management outcomes in heart failure. Dis Manag. 2006;9:157–66. [PubMed]
33. Alvelos M, Ferreira A, Bettencourt P, et al. The effect of dietary sodium restriction on neurohumoral activity and renal dopaminergic response in patients with heart failure. Eur J Heart Fail. 2004;6:593–9. [PubMed]
34. de Paula K, Lagana’ T, Gonzalez-Ramirez L. Mexican Americans. In: Lipson JG, Dibble SL, Minarik PA, editors. Culture and Nursing Care: A Pocket Guide. UCSF Nursing Press; San Francisco: 1996.
35. Cameron OG. Interoception: the inside story--a model for psychosomatic processes. Psychosom Med. 2001;63:697–710. [PubMed]
36. Clark RA, Driscoll A, Nottage J. Inequitable provision of optimal services for patients with chronic heart failure: a national geo-mapping study. Med J Aust. 2007;186:169–73. t al. [PubMed]
37. Chung ML, Lennie TA, de Jong M, et al. Patients differ in their ability to self-monitor adherence to a low-sodium diet versus medication. J Card Fail. 2008;14:114–20. [PubMed]
38. Chung ML, Moser DK, Lennie TA, et al. Gender differences in adherence to the sodium-restricted diet in patients with heart failure. J Card Fail. 2006;12:628–34. [PMC free article] [PubMed]
39. Lennie TA, Moser DK, Heo S, et al. Factors influencing food intake in patients with heart failure: a comparison with healthy elders. J Cardiovasc Nurs. 2006;21:123–9. [PubMed]
40. Lennie TA, Chung ML, Habash DL, Moser DK. Dietary fat intake and proinflammatory cytokine levels in patients with heart failure. J Card Fail. 2005;11:613–8. [PubMed]
41. Wu JR, Moser DK, Chung ML, Lennie TA. Objectively measured, but not self-reported, medication adherence independently predicts event-free survival in patients with heart failure. J Card Fail. 2008;14:203–10. [PMC free article] [PubMed]
42. Cameron J, Worrall-Carter L, Riegel B, et al. Testing a Model of Patient Characteristics, Psychological Status, and Cognitive Function as Predictors of Self-care in Persons with Chronic Heart Failure. Heart Lung. in press. [PubMed]
43. Driscoll A, Worrall-Carter L, Hare DL, et al. Evidence-based chronic heart failure management programs: myth or reality. Qual Safety Health Care. in press. [PubMed]
44. Suwanno J, Petpichetchian W, Riegel B, Issaramalai S. A model predicting the health status of patients with heart failure. Songkla Med J. 2008;26:239–51.
45. Swedberg K, Cleland J, Dargie H, et al. Guidelines for the diagnosis and treatment of chronic heart failure: executive summary (update 2005): The Task Force for the Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology. Eur Heart J. 2005;26:1115–40. [PubMed]