Heart Failure Reviews

, Volume 17, Issue 3, pp 367–385 | Cite as

Determinants of heart failure self-care: a systematic literature review

  • R. Oosterom-Calo
  • A. J. van Ballegooijen
  • C. B. Terwee
  • S. J. te Velde
  • I. A. Brouwer
  • T. Jaarsma
  • J. Brug
Article

Abstract

Self-care is an important aspect of heart failure (HF) management. Information on the determinants of self-care is necessary for the development of self-care promotion interventions. HF self-care includes self-care management, self-care maintenance, sodium, fluid and alcohol intake restriction, physical activity, smoking cessation, monitoring signs and symptoms and keeping follow-up appointments. To assess the evidence regarding presumed determinants of HF self-care and make recommendations for interventions to promote self-care behavior among HF patients, a systematic literature review was conducted. Based on inclusion and exclusion criteria and a quality assessment, twenty-six articles were included. A best evidence synthesis was used. Results showed that the length of time since patients’ diagnosis with HF is positively related to their performance of self-care maintenance. Moreover, it was found that HF patients’ perceived benefits and barriers are related to their restriction of sodium intake, and that patients with type-D personality are less likely to consult medical professionals. There was also evidence for a few non-significant relationships. All other evidence was inconsistent, mainly due to insufficient evidence. Interventions that aim to increase the performance of self-care maintenance can teach newly diagnosed patients the skills that are usually attained with experience acquired as a result of living with HF for a longer time. Perceived benefits and barriers of restricting sodium intake could be targeted in interventions for sodium intake reduction among HF patients. Finally, interventions for the promotion of adequate consulting of medical professionals can specifically target HF patients with a type-D personality.

Keywords

Heart failure Self-care Self-management Determinants Correlates Behavior change 

Introduction

Five million Americans and 15 million Europeans are living with heart failure (HF) [1], and these numbers may be increasing [2]. HF is associated with adverse outcomes, including high mortality rates [1], frequent hospitalizations [3], impaired health status [4] and increased caregiver burden [5]. In Western countries, between 1 and 2% of total annual health care expenditure is related to the care of HF patients. These costs are mainly the result of hospital admissions [6].

Heart failure is usually irreversible, but can be managed with pharmacological and non-pharmacological treatment. The non-pharmacological treatment is targeted at increasing patient self-care (sometimes referred to as self-management). Self-care refers to “performing the daily activities that serve to maintain or restore health and well-being, prevent illness, and manage chronic illness” [7, 8]. Self-care is sometimes conceptually divided into self-care maintenance, that is, the behaviors that aim to maintain physiologic stability, and self-care management, that is, the behaviors that are performed as a response to symptoms [9]. Self-care specifically includes a number of behaviors. Heart failure self-care behaviors are recommended in the guidelines of HF treatment published by the European Society of Cardiology (ESC) American College of Cardiology/American Heart Association (ACC/AHA) [10] and Heart Failure Society of America (HFSA) [11], including dietary restrictions (sodium, fluid and alcohol intake restriction), physical activity (PA), monitoring signs and symptoms, consulting medical professionals and smoking cessation.

Patients’ level of engagement in self-care is suboptimal [12], and therefore effective interventions to promote HF self-care through education need to be devised [13]. In order to plan effective interventions, it is imperative to understand which patients (do not) engage in self-care and why this is the case. The current systematic literature aims to identify socio-demographic, psychosocial, health-related, care-related, cognitive and behavioral presumed determinants of HF self-care, assess the evidence and provide recommendations for interventions that promote self-care among HF patients. It should be noted that medication adherence, although sometimes included in the range of HF self-care behaviors, falls outside the scope of the current review.

Method

Search strategy

The following databases were searched (Fig. 1) on terms related to HF, self-care and the specific self-care behaviors: Medline (using PubMed), Embase (using Embase.com), PsycInfo (using CSA Illumina) and Cinhal (using EBSCOhost). The search took place in August 2010. Limits were set for full text but not on dates. In addition, bibliographies of selected articles were searched.
Fig. 1

Process of selection of articles for inclusion

Inclusion and exclusion criteria

Studies were selected for inclusion if:
  1. 1.

    At least 50% of the sample consisted of HF patients.

     
  2. 2.

    One or more presumed determinants of HF self-care and/or a specific self-care behavior(s) were (one of the) main outcomes.

     
  3. 3.

    Quantitative results were reported.

     
  4. 4.

    They were published in English.

     
Studies were excluded if:
  1. 1.

    They were review papers.

     
  2. 2.

    Evaluations of interventions were their main purpose.

     
  3. 3.

    The only self-care behavior they reported is medication adherence.

     

Article selection

First, two authors (ROC and AJB) scanned titles and abstracts separately and selected articles for inclusion independently, based on the inclusion and exclusion criteria. They discussed differences and reached consensus. If not enough information was included in the title or abstract, then the study was taken to the next stage in the review process. In the next stage, full-text articles were scanned by the same two authors independently. They made selections for inclusion and discussed their selections. If there was lack of consensus, a third author specialized in research methodology was consulted (CT). If there was disagreement about clinical aspects, a fourth author was consulted (TJ).

Quality assessment

To analyze the quality of the included studies, a quality checklist (Table 3, Appendix) was developed based on quality items described in a review of tools for quality assessment [14] and based on a review on the quality of prognostic studies in systematic reviews [15]. Two authors (ROC and AJB) independently assessed the quality of each study and compared their scores on each item in the checklist. A third author was contacted (CBT) in case of disagreement. After reaching consensus, average scores were calculated per article. On each item in the quality checklist, articles could score between 1 and 3 points. Therefore, studies could potentially score between 17 and 51 points. Studies that received an average score of ≥2.5 were regarded as good-quality studies, those that received a score of <2.5 were regarded as fair quality and those that received an average score of <2 were regarded as poor-quality studies.

Extraction of data

The study characteristics (author, year, outcome variable(s), sample characteristics, presumed determinants and measurement instruments) and results (statistics reported in the article) of the included studies were extracted by two authors (ROC and AJB) independently. Differences were discussed and consensus was reached. In case of disagreement, a third author was contacted (CT). Continuous rather than categorical statistics were extracted from articles when both were reported. In case more articles reported on the same study sample, associations presented in both articles were only extracted once. In case an article reported on a subsample of a study population included in another article, only results from the full study population were reported. However, all articles chosen for inclusion are presented in the results table (Table 2) regardless of whether we report their results in the text.

Rating the levels of scientific evidence

A best evidence synthesis [16, 17] was applied in order to synthesize the results of the studies, while taking the number of studies, the methodological quality of the studies and the consistency of the results into account. This rating system (Table 1) was based on levels of evidence as described by review groups from the Cochrane Collaboration [15]. Results were considered consistent when at least 75% of the studies demonstrated results in the same direction, according to statistical significance of P < 0.05 [16, 17]. We describe in the text only results on relationships that were found in more than one study. However, all the results from included studies can be found in the results table (Table 2).
Table 1

Best evidence synthesis rating system used to combine the results of the studies

Level of evidence

Consistent findings in multiple (≥2) high quality studies

Strong evidence

Consistent findings in one high quality study and at least one fair quality study or consistent findings in multiple fair quality studies

Moderate evidence

Only one study available or inconsistent findings in multiple studies (≥2)

Inconsistent evidence

Table 2

Overview of the authors, study characteristics, presumed determinants and summary statistics for all studies included in the systematic literature review

Author, year, place of research

Description of the sample (measurement instrument)

Presumed determinants investigated

Summary statistics

(1) Gallagher (2010), Australia [18]

N = 63; mean age 78; 57% male. Hospitalized for HF, had a hospital admission in the previous 4 weeks and/or newly enrolled in the hospital-based HF support program. (Partners in Health Scale and questionnaire about five key HF symptoms developed for the study)

 

Self-management

Symptom monitoring

    

Comorbid conditions

β = −2.64, P = .028

NS

    

Sense of coherence

β = −0.24, P = 0.002

NS

    

High baseline self-management scores

β = 0.65, P < 0.001

NS

    

Gender

NS

OR 9.18 CI 2.15, 39.3

    

Education

NS

NS

    

Symptom severity

NS

NS

    

Self efficacy for self-management

NS

NS

    

Age

NS

NS

    

Number of comorbid illnesses

NS

NS

    

Sense of coherence

NS

NS

    

(2) Pelle (2010), the Netherlands [19]

N = 313; mean age 66; 71% male. From a cardiology outpatient unit. (Minnesota Living with HF Questionnaire and European Heart Failure Self-care Behavior Scale (EHFScBS))

 

Inadequate consultation behavior

     

Male sex

NS

     

Age

NS

     

Having no partner

NS

     

Low education

NS

     

LVEF

NS

     

NYHA class

NS

     

Ischemic etiology

NS

     

Type-D personality

OR 1.80 CI (1.03, 3.16)

     

Time since diagnosis

OR 1.07 (CI 1.01, 1.14)

     

(3) van der Wal (2006), the Netherlands [20]

N = 50; mean age 72; 60% male. Hospitalized for HF and participating in the Coordinating Study Evaluating Outcomes of Advising and Counselling in HF (Revised HF Compliance Questionnaire (HFCQ))

 

Compliance

Sodium restriction

Fluid restriction

Exercise

Daily weighing

 

Benefits diet

OR 1.08 CI (1.01, 1.16)

OR 1.19 CI (1.11, 1.28)

    

Benefits medication

NS

  

OR 1.78 CI (1.18, 2.69)

  

Lower educational level

OR 2.23 CI (1.19, 4.17)

 

OR 2.67 CI (1.44, 4.93)

   

Barriers diet

 

OR 0.41 CI (0.23, 0.76)

    

Knowledge

  

OR 3.15 CI (1.50, 6.59)

 

OR 5.67 CI (2.87, 11.19)

 

Depressive symptoms

   

OR 0.53 CI (0.35, 0.78)

  

(4) Park (2008), USA [21]

N = 163; mean age 65; 95% male. Have been hospitalized in the past year (Cincinnati Medical Center). (Compliance measure developed by Sherborne et al., 1992)

 

HF specific behaviors

HF-related diet

Substance use

   

Religious commitment

β = 0.249, P < 0.05

NS

NS

   

Baseline level of Adherence

β = 0.179, P < 0.05

NS

    

Religious spiritual support

NS

NS

NS

   

Positive religious coping

 

NS

NS

   

Negative religious coping

NS

NS

β = −0.201, P < 0.05

   

(5) Sayers (2008) USA [22]

N = 74; mean age 63; 96% male. From the cardiology clinic of the Philadelphia Veteran Affairs Medical Center and a university affiliated cardiology practice. (Self-Care HF Index (SCHFI))

 

Self-care maintenance

HF-related diet

    

Emotional support

NS

β = 0.39, P = 0.05

    

Instrumental support

NS

NS

    

Family involvement

NS

NS

    

(6) Schweitzer (2007), Australia [23]

N = 115; mean age of 64; 71% male. Receiving treatment through an Australian hospital for diagnosed HF patients. (SCHFI and HFCQ)

 

Alcohol restriction

Sodium restriction

Fluid restriction

PA

Smoking cessation

Daily weighing

Self efficacy

β = 0.51, P < .001

β = 0.42, P < 0.001

β = 0.25, P < .05

β = −0.41, P < .001

β = 0.39, P < .001

β = 0.38, P < .001

Anxiety

β = 0.27, P < .05

NS

NS

NS

β = 0.26, P < .05

NS

Age

NS

NS

NS

NS

β = −0.29, P < 0.05,

NS

Gender

NS

NS

NS

NS

NS

NS

NYHA

NS

NS

NS

β = −0.23, P < 0.05

NS

NS

LVEF

NS

NS

NS

NS

NS

β = −0.27, P < 0.01

Depression

NS

NS

NS

NS

NS

NS

(7) van der Wal (2007), the Netherlands [24]

N = 954; mean age 71; 62% male. Baseline data from the COACH (Coordinating study evaluating Outcomes of Advising and Counselling in Heart Failure). (Revised HFCQ)

 

Sodium restriction

Daily weighing

    

Barriers

OR 0.91, CI (0.87, 0.95)

OR 0.91, CI (0.88, 0.95)

    

Benefits

OR 1.17, CI (1.11, 1.23)

     

(8) Cameron (2010), Australia [25]

N = 93; mean age 70; 71% male. Referred to hospital case-manager in 2 metropolitan health networks in Victoria. (SCHFI)

 

Self-care maintenance

     

Experience

β = 0.31, P = <0.01

     

Age

NS

     

Gender

NS

     

Cognitive impairment

NS

     

Depression

NS

     

Living with support

NS

     

Comorbidity

NS

     

NYHA class

NS

     

<12 years of education

NS

     

(9) Holzapfel (2009), Germany [26]

N = 287; mean age 63; 74% male. From 3 outpatient departments. (German version of EHFScBS)

 

Self-care behavior

     

Age

β = 0.34, P = < 0.001

     

Minor depression

β = −0.19, P = 0.001

     

LVEF

β = −0.19, P = 0.001

     

Multimorbidity

β = −0.14, P = 0.001

     

Family status

β = −0.14, P = 0.02

     

(10) Rockwell (2001), USA [27]

N = 209; mean age 73; 51% male. Admitted to 1 of 6 hospitals in Southern California. (Self-Management of HF Instrument)

 

Self-care

     

Education level

β = 0.228, P = 0.009

     

Severity of symptoms

β = 0.182, P = 0.046

     

Gender

NS

     

Socioeconomic status

NS

     

Age

NS

     

Social support

NS

     

Comorbidity

NS

     

Spirituality

NS

     

(11) Sneed (2003), USA [28]

N = 178; mean age 56; 62% male. Enrolled in the heart failure clinic and in the clinical trials of the Medical University of South Carolina. (A questionnaire measuring self-care behavior)

 

Sodium restriction

Fluid restriction

Exercise

Daily weighing

  

Sodium restriction stage of change

P < .001

     

Fluid restriction stage of change

P < .001

     

Fluid restriction stage of change

 

P < .001

    

Exercise stage of change

  

P < 0.001

P < 0.001

  

Losing weight stage of change

  

NS

P < 0.001

  

Knowledge

   

NS

  

(12) Black (2006), USA [29]

N = 95; mean age 72; 63% male. From outpatient (HFCQ)

 

Compliance

     

Spirituality

NS

     

Purpose and meaning in life

NS

     

Inner resources

NS

     

Unifying interconnectedness

NS

     

Transcendence

NS

     

Age

NS

     

Gender

NS

     

(13) Cameron (2010), Australia [30]

N = 143; mean age 72; 73% male. Referred to case manager from 2 health networks in Victoria. Have recently been hospitalized. (SCHFI)

 

Self-care maintenance

Self-care management

    

Experience

β = 0.29, P = 0.00

β = 0.20, P = 0.02

    

Age

β = 0.19, P = 0.03

NS

    

Depression

β = −0.17, P = 0.04

NS

    

Gender

NS

β = −0.19, P = 0.02

    

NYHA Class

NS

β = 0.25, P = 0.00

    

Comorbidity

NS

β = −0.24, P = 0.01

    

Living with support

NS

NS

    

<11 years of education

NS

NS

    

Employment

NS

NS

    

Cognitive impairment

NS

NS

    

Renal impairment

NS

NS

    

(14) Cameron (2009), Australia [31]

N = 50; mean age 73; 76% male. Referred to CHF health network in Victoria. Have been recently hospitalized. (SCHFI)

 

Self-care maintenance

Self-care management

    

Age

β = 0.51, P < 0.01

NS

    

Gender (male)

NS

β = −0.33, P = 0.02

    

Cognitive function

NS

NS

    

Depression

NS

β = 0.32, P = 0.04

    

Living with social support

NS

NS

    

Self-care self confidence

NS

NS

    

Comorbidity

β = 0.34, P = 0.02

β = 0.33, P = 0.03

    

(15) Schiffer (2007), the Netherlands [32]

N = 178; mean age 67; 79% male. Outpatients from a teaching hospital in Tilburg, pharmacologically stable for a month. (EHFScBS)

 

Self-management

Lack of consultation behavior

    

Type-D personality

NS

OR 2.67 CI (1.19, 6.00)

    

Age

NS

NS

    

Sex

NS

NS

    

Having no partner

NS

NS

    

Lower educational level

NS

NS

    

NYHA class III and IV

NS

NS

    

LVEF

NS

NS

    

Ischaemic etiology

NS

NS

    

Time since diagnosis

NS

NS

    

Using diuretics

NS

NS

    

Using ACEi’s

NS

NS

    

(16) Schnell-Hoehn (2009), Canada [33]

N = 65; mean age 59; 77% male. Ambulatory care patients treated in an outpatient clinic. (SCHFI)

 

Self-care maintenance

Self-care management

Self-care

   

Psychological status

r = 0.269, P = 0.030

NS

NS

   

Self-confidence

r = 0.449, P = 0.0002

NS

β = 0.600, P = 0.004

   

Race

P = 0.048

NS

NS

   

Diagnosis age

NS

NS

NS

   

NYHA Classification

NS

NS

NS

   

Physical limitations

NS

NS

NS

   

Social limitations

NS

NS

NS

   

Ejection fraction

NS

NS

NS

   

Hospital admissions

NS

NS

P = 0.019

   

Ejection fraction

  

NS

   

Marital status

  

NS

   

Residency

  

NS

   

Living situation

  

NS

   

Education

  

NS

   

Occupational status

  

NS

   

Family income

  

NS

   

Social support

  

NS

   

(17) Sebern (2009), USA [34]

N = 75; mean age 71; 22% male. From an outpatient cardiology clinic affiliated with a Midwestern university (SCHFI)

 

Self-care maintenance

     

Shared care: decision making

r = 0.65, P = 0.000

     

Shared care: communication

NS

     

Shared care: reciprocity

NS

     

(18) Thomas (2007), USA [35]

N = 97; mean age 62; 62% male. From 2 clinics: One was located in a rural/ suburban area and one in a large urban inner-city area. (EHFScBS )

 

Adherence

     

Threat to self concept

r = −0.35, P < 0.01

     

Threat to body sensation

r = −0.27, P < 0.01

     

Threat to body image

r = −0.38, P < 0.01

     

Threat to self consistency

r = −0.33, P < 0.01

     

Threat to self ideal

r = −0.24, P < 0.05

     

Challenge to self concept

r = 0.36, P < 0.01

     

Challenge to body sensation

r = 0.28, P < 0.01

     

Body image

r = 0.29, P < 0.01

     

Self consistency

r = 0.21, P < 0.05

     

Self ideal

r = 0.26, P < 0.05

     

Moral-ethical-spiritual self

r = 0.33, P < 0.01

     

(19) Evangelista (2001), USA [36]

N = 82; mean age 54; 38% male. From an outpatient clinic in Los Angeles. (HFCQ)

 

Compliance

HF-related diet

Physical activity

Smoking cessation

Alcohol intake restriction

Keeping medical appointments

Education

r² = 0.038, P = 0.046

NS

NS

NS

NS

NS

Mental health

r² = 0.120, P = 0.005

Adjusted r² = 0.057, P = 0.018

r² = 0.209, P = 0.000

NS

NS

NS

Physical health

r² = 0.172, P = 0.017

NS

r² = 0.240, P = 0.042

NS

NS

NS

Neuroticism

NS

NS

r² = 0.272, P = 0.039

NS

NS

Adjusted r² = 0.176, P = 0.002

Age

NS

NS

NS

NS

NS

NS

Race

NS

NS

NS

NS

NS

NS

Health satisfaction

NS

NS

NS

NS

NS

NS

Martial status

   

Adjusted r² = 0.204, P = 0.000

NS

Adjusted r² = 0.076, P = 0.007

(20) Chriss (2004), USA [37]

N = 66; mean age 71; 44% male. From a HF intervention program in 2 hospitals in Southern California. (SCHFI)

 

Self-care maintenance

     

Baseline self-care maintenance scores

β = 0.551, P < .001

     

Comorbid illnesses

β = −0.246, P = .01

     

Age

NS

     

Education

NS

     

Social support satisfaction

NS

     

Functional status

NS

     

NYHA class

NS

     

(21) Dickson (2008), USA [38]

N = 41; mean age of 49; 63% male. From 2 outpatient settings affiliated with a large urban medical centre. (SCHFI)

 

Self-care maintenance

Self-care management

    

Cognition

r = −0.33, P = 0.03

     

Physical functioning

 

r = −0.43, P = 0.02

    

(22) Joekes (2007), the Netherlands [39]

N cardiac patients = 82: 41 HF patients; mean age of 61; 76% of the patients were male. From four general hospitals in the Netherlands. (self- constructed scale tailored for the disease)

 

Self-management

     

Self efficacy

β = 0.057, P < 0.05

     

Overprotection of partner

NS

     

Type of illness

NS

     

Gender

NS

     

Chest panic

NS

     

(23) Carlson (2001), USA [40]

N = 139; mean age 69; 53% were male. From six hospitals in California and Ohio (N = 114) recruited at the time of hospitalization for HF (N = 25) from an HF clinic. (Self management of HF (SMHF))

 

Self-care

     

Newness of diagnosis

NS

     

(24) Lee (2009), USA Australia, Thailand [41]

N = 2082; mean age from all countries was 67; 63% male. USA: 2 groups of patients: Hispanic patients enrolled during hospitalization at two community hospitals and other patients enrolled in outpatient clinics or during hospitalization. Australia: 2 samples from five states in Australia with at least one hospital admission. Thailand: From tertiary care settings and secondary care settings in Southern Thailand. (SCHFI)

 

Self-care maintenance

     

Age

β = 0.174, P < 0.01

     

Education: high school or higher

β = 8.905, P = <0.001

     

HF ≤ 2 months

β = −1.904, P = <0.01

     

NYHA class

β = −3.805, P < 0.001

     

Diastolic HF

β = −3.92, P < 0.001

     

Country

β = 2.278, P < 0.05

     

Married

NS

     

Co-morbid category

NS

     

HF etiology

NS

     

(25) Riegel (2009), Australia, USA, Thailand and Mexico [42]

N = 2082; mean age; male %: Australia 70; 33%, U.S. 60; 34%, Thailand 65; 48%, Mexico 72; 54%. Patients from these countries were from inpatient and outpatient settings. Two samples from USA, two from Australia, one from Thailand and one from Mexico.(SCHFI)

 

Self-care management

Self-care maintenance

    

Country: US–Thailand

OR 11.10 (5.66, 21.78)

OR 1.85 CI (1.12, 3.04), P < 0.05

    

Country: Australia–Thailand

OR 5.54 (2.83, 10.85), P < .001

OR 6.05 CI (3.73, 9.80), P < 0.001

    

Country: Mexico-Thailand

OR 12.75 (7.02, 23.15), P < .001

NS

    

Education less than high school- education more than high school

NS

OR 0.67 CI (0.51, 0.88), P < 0.01

    

Experienced with HF–Newly diagnosed

NS

OR 1.63 CI (1.24, 2.12), P < .001

    

Functional class NYHA class I–IV

NS

OR 1.99 CI (1.33, 2.98), P  < 0.01

    

II–IV

NS

OR 1.75 CI (1.2, 2.46), P < 0.01

    

III–IV

NS

OR 1.62 CI (1.15, 2.29), P < 0.01

    

Setting where enrolled

NS

NS

    

Age: younger-older

OR 0.98 (0.97, 0.99), P < 0.01

NS

    

Gender

NS

NS

    

Few comorbidities- Many comorbidities

OR 0.68 (0.50, 0.93), P < 0.05

NS

    

(26) Ni (1999), USA [43]

N = 113; mean age 51; 74% male. From a HF outcomes research project at an academic medical centre. (A questionnaire measuring self-care)

 

Self-care

     

Marital status

β = 1.30, P = 0.03

     

Specialty of referring physician (cardiologist vs. non-cardiologist)

β = 1.32, P = 0.05

     

Patients’ self-confidence to maintain health status

β = 0.50, P = 0.05

     

Hospitalization during the past year

NS

     

Self-care knowledge

NS

     

NS = Non-significant, LVEF = Left ventricular ejection fraction, NYHA = New York Heart Association

* Only the results that have been reported in the articles are presented in the table

* Articles 1–11 are good quality articles; 12–16 are fair quality article

Behavioral outcomes

We include all results on the following outcomes: general HF self-care scores (composite scores including different self-care behaviors rather than focusing on a specific self-care behavior), self-care management (composite scores including different behaviors related to management of symptoms), self-care maintenance (composite scores including behaviors related to maintaining long-term physiologic stability), HF dietary behaviors, PA, monitoring signs and symptoms, consulting medical professionals and smoking cessation.

Results

Twenty-six articles were included in the review. Eleven of the articles were rated as good quality, fifteen as fair quality (the articles are numbered according to quality score in Tables 2 and 4; studies numbered 1–11 are rated as good quality [18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28], and those numbered 12–26 are rated as fair quality [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]). Four articles were excluded due to a low quality score [44, 45, 46, 47].

Various HF self-care behavioral outcomes were reported in the literature. Results (Table 2) on HF self-care (composite) scores were reported in thirteen articles. Although some studies used the term “self-care” [26, 27, 33, 40, 43], other studies used other terms, including “self-management” [18, 32, 39], “adherence” [35], “compliance” [20, 29, 36] and “self-care specific behaviours” [21]. In addition, eight articles reported results on self-care management [22, 25, 30, 31, 33, 38, 41, 42] and ten on self-care maintenance [22, 25, 30, 31, 33, 34, 37, 38, 41, 42].

The following specific HF self-care behavioral outcomes were reported: HF-related dietary behaviors [21, 22, 36] and in particular sodium [20, 23, 28], fluid [20, 23, 28] and alcohol intake restriction [23, 36]; PA [20, 23, 28, 36]; monitoring signs and symptoms [18] and in particular daily weighing [20, 23, 24, 28]; consulting medical professionals [19, 32, 36]; and smoking cessation [23, 36]. One article measured substance use, including both alcohol intake restriction and smoking cessation [21].

Evidence was found for relationships between a number of determinants and self-care maintenance, sodium intake restriction, consulting medical professionals and smoking cessation. First, the results demonstrate that the longer ago patients were diagnosed, the more they engaged in self-care maintenance (moderate evidence). However, gender and cognition level were found unrelated to self-care maintenance (moderate evidence).

Second, we found that perceived benefits and barriers are related to adhering to a low-sodium diet [20, 24] (strong evidence). In the reviewed studies, perceived benefits and barriers were measured with the Beliefs about Dietary Compliance subscale from the Heart Failure Belief Scale. This includes items such as “eating a low salt diet will keep me healthy” and “eating a low salt diet makes it hard to go to restaurants” [24].

Third, type-D personality was found to be related to consulting medical professionals (which was operationalized differently in the different studies. Specifically, the results demonstrate a relationship between not consulting medical professionals and having a type-D personality (moderate evidence). However, other potential determinants found in the literature were found unrelated to consulting medical professionals. These are age [19, 32, 36], sex [19, 32], educational level, LVEF and NYHA (moderate evidence) [19, 32].

For most HF self-care behaviors, most potential determinants were investigated in single studies only. These include self-care (composite scores) (although age [18, 26, 27, 29, 32, 33, 36], gender [18, 26, 27, 29, 39] (strong evidence) and time since diagnosis [32, 39] (moderate evidence) were found to be unrelated to self-care); HF dietary behavior [21, 22, 36]; fluid intake restriction [20, 23, 28]; alcohol restriction [21, 23, 36] (although it was found that patients’ age was unrelated to their alcohol intake restriction [22, 36] (moderate evidence)), PA [20, 23, 28, 36] (although age was found unrelated to PA level [23, 36] (moderate evidence)), monitoring signs and symptoms [18, 20, 23, 24, 28] and smoking cessation [23, 36]. Therefore, for these behaviors no consistent evidence for relationships with potential determinants was found.

Discussion

The current work is the first to systematically review presumed determinants of HF self-care employing a quality analysis and a best evidence synthesis. As such, it is the most comprehensive summary of findings on this topic. By reviewing the evidence from the 26 articles available to date of at least fair quality about HF self-care, (including self-care maintenance, self-care management and the specific HF self-care behaviors), we cover potential determinants for the full range of behaviors that HF patients need to perform to adequately care for themselves.

The available research indicated that being diagnosed with HF for a longer time is related to self-care maintenance. Self-care maintenance relates to the long-term performance of self-care behaviors to maintain physiologic stability. Experience with self-care behaviors may be a facilitating factor to maintaining these behaviors over the long term, since these behaviors may be learned and practiced through time. This result is in line with the components of naturalistic decision-making framework, which specifies experience (as measured in the studies identified in the current review as time since diagnosis) as one of the core influences when making decisions, including those about self-care [9]. Since experience was found to be related to self-care maintenance, it may be advisable that interventions facilitate patients’ gaining of experience in a shorter time-span, by teaching skills and providing the support needed to practice them.

The available evidence also indicated that patients’ beliefs about sodium are related to their level of sodium intake. Specifically, it appears that the more benefits patients perceive, the more likely they are to restrict their sodium intake and the more barriers they perceive, the less likely they are to do so. This finding is in line with important health behavior theories, such as social cognitive theory [48] and the health belief model [49], that place emphasis on the importance of cognitions related to a health behavior in predicting the likelihood of performing that behavior. In particular, evidence exists for effects of various cognitive variables (e.g., awareness of one’s behavior) on healthy dietary behaviors, including sodium, saturated fat and energy intake levels, among others [50].

In both of the articles from which these results were extracted [20, 24], adherence to the sodium intake recommendations was measured with the Revised HF Compliance Questionnaire (HFCQ). Perceived benefits and barriers were measured with the HF Belief Scale. Future studies may consider replicating the findings using objective measures of sodium intake, to establish whether objective measures also yield the same results.

It is advisable that interventions that aim to promote sodium intake do so by targeting patients’ specific perceived benefits and barriers. HFSA recommends that patient education on HF self-care should start by assessing each patient’s barriers for self-care [51] and then education can be provided for each patient’s identified perceived benefits and barriers [52]. This may include providing patients with strategies to overcome the barriers they perceive and reinforcing the benefits they perceive. In the current review, we only found evidence for the effects of barriers on sodium restriction and therefore it is unclear whether barriers need to be assessed for all self-care behaviors or only sodium restriction. More research on barriers to self-care is needed to establish this.

A further finding is that patients with a type-D personality appear to be less likely to consult medical professionals. People with a type-D personality have high levels of negative affectivity and social inhibition [53]. It is possible that these personality dimensions lead HF patients to be less willing to consult medical professionals, but further research should empirically clarify why this is the case.

All other evidence regarding potential determinants of HF self-care behaviors reviewed was rated as inconsistent, often due to too few studies investigating the same potential determinants and rarely because of conflicting evidence. Many psychological variables were significantly associated with self-care behaviors in single studies. Some examples include relationships between knowledge and monitoring signs and symptoms [20], self efficacy and smoking cessation [23], and stage of change and fluid restriction [28]. Studies aimed to reproduce existing findings on psychological determinants of HF self-care behaviors are thus warranted. Fewer studies have focused on potential social--environmental determinants, although studies were found that investigated the relationship between emotional support and keeping a HF-related diet [22] and marital status and smoking cessation [36], for instance. Previous, non-systematic, literature reviews on HF self-care behavior (e.g., [54]) discuss various factors, including, for instance, socioeconomic factors such as socioeconomic status, health care system-related factors such as communication with providers and condition-related factors such as symptoms experienced. In the current review it is apparent that there is insufficient evidence for these potential determinants and that they need to be further investigated to elucidate their effects.

Most studies on potential determinants of self-care behaviors were not guided or informed by comprehensive behavioral theories. This could be the reason that a variety of potential determinants were investigated in single studies, and that some potential determinants that are included in behavioral theories have not been studied at all. Our review thus shows that there is an eminent need for better designed and theory informed research to provide a more complete overview of determinants of engaging in self-care among HF patients. According to the social-ecological models of health behavior, individual as well as social and other environmental factors are important determinants of health behaviors [55], and future research should focus on such individual as well as environmental correlates and predictors of HF self-care.

The current review focused on the self-care behaviors that are recommended by the guidelines of the ESC, ACC/AHA and HFSA. It should, however, be noted that not all of these behaviors have the same level of evidence. The ESC, for instance, describes a level of evidence of each recommendation and distinguishes between three classes of recommendations, thereby clarifying the extent to which each behavior can improve clinical and patient outcomes. Studies are still being conducted to establish the efficacy of each of the recommended behaviors in influencing outcomes. A recent study [56] demonstrates that out of the various behaviors related to non-pharmacological treatment, PA is the only specific self-care behavior that affects readmission rates. Therefore, not all behaviors have the same effects on outcomes. This must be considered when planning interventions that target patients’ behavior. Unfortunately, the number of studies does not necessarily correspond with the relative importance of the various behaviors in achieving clinical and patient outcomes.

There are a few limitations in the current work. First, due to possible publication bias, whereby studies that have significant results are more likely to get published [57], the findings should be interpreted with caution. Another limitation stems from the fact that results from association and prediction models were synthesized. A presumed determinant from a prediction model is different than the same presumed determinant in an association model because its function in the model is different and therefore (non-) significant results may have a different meaning. Results from univariate and multivariate models were also synthesized, causing a similar potential problem. Moreover, when extracting the results from studies, it was unclear in some cases which variables were tested or included in models. We report and assessed the results that were directly addressed in the articles; however, the results may be confounded by variables that were not taken into account in the current review.

Based on the results of the current review, we can conclude (1) that interventions may facilitate gaining experience with performing self-care maintenance behaviors; (2) that patients’ perceived benefits and barriers should be addressed in interventions that target the promotion of sodium intake restriction; and (3) that since patients with a type-D personality may be specifically prone to not consult medical professionals when needed, interventions can address specifically this subgroup of patients. More systematic, high-quality and behavioral theory-driven research is needed to provide further directions for future HF self-care promotion interventions.

Notes

Acknowledgments

The authors would like to thank Ilse Jansma, MSc., Medical Information Specialist, VU Amsterdam University Library, Medical Library, The Netherlands, for her support in performing the literature search for this review. In addition, the authors would like to thank Dr. Wim Stut for providing comments on the manuscript.

Conflict of interest

None.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • R. Oosterom-Calo
    • 1
    • 2
  • A. J. van Ballegooijen
    • 3
  • C. B. Terwee
    • 2
  • S. J. te Velde
    • 2
  • I. A. Brouwer
    • 3
  • T. Jaarsma
    • 4
  • J. Brug
    • 2
  1. 1.Philips ResearchEindhovenThe Netherlands
  2. 2.EMGO Institute for Health and Care Research and the Department of Epidemiology and BiostatisticsVU University Medical CenterAmsterdamThe Netherlands
  3. 3.EMGO Institute for Health and Care Research and the Department of Health Sciences, Faculty of Earth and Life SciencesVU University AmsterdamAmsterdamThe Netherlands
  4. 4.Department of Social and Welfare StudiesLinköping UniversityLinköpingSweden

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