Abstract
Caregivers play an important role in contributing to heart failure (HF) patients’ self-care but no prior studies have examined the caregivers’ contributions to HF patients’ self-care and no prior studies have examined potential determinants of the caregivers’ contribution to HF patients’ self-care.
The purpose of this study was to describe the caregivers’ contribution to HF patients’ self-care and identify its determinants.
The study design involved a secondary analysis of cross-sectional data. Caregivers’ contributions were measured with the Caregiver’s Contribution to Self-care of HF Index (CC-SCHFI) which measures the caregiver’s contribution to self-care maintenance and management and caregiver confidence in contributing to HF patient’s self-care. Potential determinants were measured using a socio-demographic questionnaire completed by caregivers and patients, and patient clinical data was obtained from the medical record.
Data from 515 caregiver/patient dyads were analyzed. Most (55.5%) patients were male (mean age 75.6 years) and most (52.4%) caregivers were female (mean age, 56.6 years). The caregivers’ contribution to patients’ self-care maintenance was low in weight monitoring and physical activity but higher in checking ankles, advising on low-salt foods and taking medicines. The caregivers’ contribution to patients’ self-care management was low in symptom recognition. When symptoms were recognized, caregivers advised patients to reduce fluids and salt and call the provider but rarely advised to take an extra diuretic. Caregiver confidence in the ability to contribute to patient self-care explained a significant amount of variance in the caregiver’s contribution.
These findings suggest that caregivers in this sample did not contribute meaningfully to HF self-care. Providers should educate both HF patients and caregivers. Interventions that improve caregiver confidence have the potential to successfully increase the caregivers’ contribution to patients’ self-care.
Introduction
Heart failure (HF) is a common syndrome in developed countries with prevalence rates between 0.4–2.0% in the adult population.1 In Europe, where this study was conducted, there are over 15 million people affected by HF and in the US there are over five million people with HF.1,2 There is an expected increase in the number of the HF patients in the near future because of the aging of the population. HF is a chronic disease characterized by poor quality of life3,4 and high hospitalization rates.5 Prior studies have found that adherence to self-care recommendations (e.g. taking medications as prescribed, weighing every day, following a low-salt diet, exercising regularly) may improve patients’ outcomes.6,7 While self-care is an important component of HF treatment,8 patients struggle to perform adequate self-care.9,10 Mobilizing informal caregivers may be one way to help patients perform self-care.
Informal caregiving is the act of providing tangible and emotional support for a loved one who is ill or disabled. Caregivers play an important, but often overlooked role in HF patients’ self-care.11,12 The caregiver’s contribution to patient’s self-care has been defined as the provision of time, effort, and support on behalf of another person who is performing HF self-care.13 The actual contributions to self-care by caregivers occur across a spectrum, from making recommendations to the patient on their performance of self-care to actually providing that care when the patient is unable to care for him/herself.13,14 For example, the caregiver may administer medications or prepare low-salt food when the patient is unable to do so.13
There have been no prior studies of differences in spouse and adult children caregivers of persons with HF. There was a recent study of Alzheimer’s disease patients that compared burden in spouses and adult children caring for these patients. Adult children caregivers experienced higher burden than spouse caregivers despite spending less time in the caregiving role.15 These results suggest that confidence in the caregiver role may differ between the two groups.
Even though no specific theories have as yet been developed related to caregivers’ contributions to HF patients’ self-care, in the recently developed Caregiver Contribution to Self-Care of Heart Failure Index (CC-SCHFI),13 two dimensions of caregivers’ contribution to HF patients’ self-care were proposed. These dimensions reflect the patient measure of self-care on which the scale was based, the SCHFI:16,17 (a) caregiver contribution to self-care maintenance, which includes monitoring the patient’s symptoms (e.g. helping the patient to weigh himself/herself daily), and adhering to the treatment regimen (e.g. reminding the patient to take medicine); and (b) caregiver contribution to self-care management, which includes recognizing the patient’s signs and symptoms of a HF exacerbation (e.g. ankle edema), implementing actions aimed at reducing fluid overload (e.g. reducing salt in the diet, recommending fluid restriction), and evaluating the response to the implemented treatment.
Caregiver self-efficacy in contributing to the patient’s self-care (e.g. confidence in the ability to keep the patient free of HF symptoms) is included in the CC-SCHFI as it is in the original scale. This process mirrors the patient-oriented situation-specific theory of HF self-care18 in proposing that caregiver task-specific confidence, or self-efficacy, contributes to patient self-care. Confidence reflects, not a domain of self-care per se, but rather a factor influencing the caregiver’s contribution to patient self-care. Self-efficacy, as defined by Bandura, is the confidence in one’s ability to achieve a desired result.19 Self-efficacy is modifiable with intervention and prior clinical trials with caregivers have shown that education can improve caregivers’ self-efficacy and consequently caregiver and patient outcomes.20–22
Several reviews of the HF caregiving experience have been published,14,23–25 suggesting an expanding or maturing science from which to conduct further meta-analyses, meta-syntheses, or psychometric work. One particular systematic review was conducted examining what is currently known about caregiver contributions to HF patients’ self-care.14 This review used the theory of self-care in chronic illness26 to classify research studies and then identified caregiver support as instrumental to the patient’s HF self-care in the domains of maintenance (e.g. exercise, medication adherence), monitoring (e.g. blood pressure monitoring, regular weighing) and management (e.g. taking an extra diuretic). However, one limitation of these prior studies was the lack of a valid and reliable instrument specifically developed to measure the caregivers’ contribution to HF patients’ self-care. Therefore, no prior studies have been able to examine potential determinants of the caregivers’ contribution to patient self-care. We do know from prior studies of HF patients that socio-demographic characteristics and clinical variables are likely determinants of self-care.27,28 In addition, no prior studies have examined caregiver self-efficacy as a determinant of the caregivers’ contribution to HF patient self-care. Helping HF patients to perform self-care can be challenging for caregivers.29,30 But, if their contributions are influenced by their self-efficacy, interventions aimed at improving caregiver self-efficacy may improve their contributions to patients’ self-care and thus patients’ self-care. As a valid, reliable and disease-specific instrument measuring the caregiver’s contribution to HF patient’s self-care now exists, the aims of this study were to (a) describe the caregivers’ contribution to HF patients’ self-care, (b) identify if patient and caregiver socio-demographic characteristics and patient clinical characteristics are determinants of the caregivers’ contribution to patient self-care, and (c) identify if caregiver self-efficacy increases the amount of explained variance in the caregivers’ contribution to self-care beyond the patient and caregiver socio-demographic characteristics and patient clinical characteristics. Based on prior studies of patients,18,31,32 we hypothesize that caregiver self-efficacy would explain more of the variance in caregivers’ contribution to self-care maintenance and management than that explained by socio-demographic and clinical characteristics alone.
Methods
Design
This was a secondary analysis of data collected in a cross-sectional study.
Sample, setting and procedure
Participants in this study were the primary caregivers of HF patients enrolled in a multisite study conducted in 28 Italian provinces. These provinces are located in the North, Centre and South of Italy. Inclusion criteria specified caregivers of patients with a diagnosis of HF confirmed using the diagnostic criteria of the European Society of Cardiology in 200833 and reconfirmed in 2012;2 and caregivers identified as such by patients at least 18 years of age who had been stable over the prior three months. Caregivers and patients were recruited during routine visits at a cardiovascular ambulatory care center.
Ethical consideration
Before data collection began, the study was approved by the Ethical Committees of each center where patients and caregivers were enrolled. Both patients and caregivers were fully informed by nurse research assistants about the study aims. Informed consent was obtained before data were collected.
Measures
CC-SCHFI
The CC-SCHFI13 is composed of three scales measuring three different dimensions: (a) the caregiver contribution to self-care maintenance scale, which has 10 items; (b) the caregiver contribution to self-care management scale, with six items, and (c) the caregiver confidence in contributing to self-care scale, with six items. Each item uses a four-point response format. Scores on each scale are mathematically standardized to range from 0–100 for ease of interpretation. Higher scores indicate better self-care. The caregiver’s contribution to self-care management scale, as with the SCHFI v.6.2, is administered only when the patient has experienced HF symptoms in the last month. CC-SCHFI validity was established in a sample of 291 Italian HF caregivers with confirmative factor analysis which showed supportive fit indices (comparative fit indices ranging from 0.96–0.99; root mean square error of approximation ranging from 0.03–0.04). CC-SCHFI validity was also tested for contrasting group validity. The CC-SCHFI was able to discriminate between caregivers able to contribute to patients’ self-care versus those who were not (p<0.05). CC-SCHFI reliability was tested with factor score determinacy coefficient and test-retest; all coefficients were >0.70.
Caregiver socio-demographic characteristics
A self-report survey was used to collect information on gender, age, education, marital status, employment, relationship to the patient, cohabitation or living arrangements in relation to the patient. Caregiving hours per day was measured as a continuous variable; caregivers were asked to specify the numbers of hours they spent in caregiving each day.
Patient socio-demographic and clinical characteristics
Patients’ socio-demographic data included gender, age, marital status, and employment. Clinical variables collected from the medical record included New York Heart Association (NYHA) functional class, ejection fraction, and time since diagnosis measured in months. Illnesses were assessed using the Charlson Comorbidity Index (CCI)34 which has established validity for predicting mortality, complications, health care resources use, length of hospital stay, discharge dispositions and cost. In 2011 the CCI was updated to a new version with 12 items,35 each of one has a possible score of 1, 2, 3 or 6 with higher score indicating higher risk for mortality. A total score can be obtained, which ranges from 0–24. In this study all patients had at least a score of 2 (the score given to HF).
The Mini Mental State Examination (MMSE)36 was used to measure global cognition. The MMSE includes 19 items which assess the following areas: orientation to time and place, registration of three words, attention and calculation, recall of three words, language, and visual construction. The MMSE has been widely used in HF patients.37,38 Scores range from 0–30 with higher scores indicating better cognition. Cronbach’s alpha of the MMSE was 0.85 in this study.
Data analysis
Descriptive statistics (frequencies, mean, standard deviation (SD)) were used to describe caregiver and patient socio-demographic characteristics and patient clinical characteristics and to describe both the items and the computed scale dimensions of the CC-SCHFI. Pearson’s correlation was used to identify which caregiver socio-demographic variables and which patient socio-demographic and clinical variables were correlated with the three CC-SCHFI dimensions (caregiver contribution to self-care maintenance and management and caregiver self-efficacy). Since self-care maintenance and management are theoretically distinct,13 two hierarchical regression models were tested. We did this in order to examine the additive role of caregiver confidence in explaining caregiver contributions to self-care maintenance (dependent variable of the first regression) and management (dependent variable of the second regression) above and beyond caregiver socio-demographic variables and patient socio-demographic and clinical variables. Specifically, the caregiver and patient variables chosen for testing that were significantly correlated with caregiver contribution to self-care maintenance and management were entered as independent variables in the first step of each hierarchical regression model. Then caregiver confidence in their abilities to contribute to patient self-care was entered as an independent variable in the second step of the hierarchical regression. To test the hypothesis that caregiver’s contribution would add significant variance over and above socio-demographic and clinical variables, we considered change in R2 and the beta coefficients. Multicollinearity between the predictor variables entered into the models was assessed with the variance inflation factor (VIF) and tolerance: A VIF >4 and a tolerance <0.20 are indicative of multicollinearity.39 Statistical significance was set at p<0.05. All data were analyzed with SPSS version 20.
Results
Caregivers’ socio-demographic characteristics
A total of 515 caregiver and patient dyads participated in the study. Table 1 presents the caregiver socio-demographic characteristics. Caregivers were relatively young (mean age 56.6 years, SD=14.9) reflecting the large number of adult offspring caregivers. Caregivers were approximately equally distributed between female (52.4%) and male. The level of education was equally distributed, as well, between caregivers with less than a high school education (48%) and others with at least high school education (52%). Most caregivers were married (72.8%) and employed (56.5%). Spouses and children represented more than the 85% of the sample. Among spouses and children there were no statistically significant differences in gender (p=0.82), but spouses were older (79.2 vs 50.0 years, p<0.001) and less educated (p<0.001) than children. Less than half (37.7%) of the caregivers lived with the patient and the mean number of hours of caregiving provided per day was 7.5 (SD=7.2). When we excluded those caregivers who said that they provided caregiving 24 h per day (13.5% of the sample), the mean and SD was 5.39 and 3.93 h respectively.
Caregivers’ socio-demographic characteristics (n=515)
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 245 (47.6) |
| Female | 270 (52.4) |
| Age, mean (SD) | 56.6 (14.9) |
| Education | |
| Elementary | 80 (15.6) |
| Middle school | 167 (32.4) |
| Professional school | 70 (13.6) |
| High school | 146 (28.3) |
| University degree | 52 (10.1) |
| Marital status | |
| Married | 375 (72.8) |
| Single | 74 (14.4) |
| Widowed | 24 (4.6) |
| Divorced | 42 (8.2) |
| Profession | |
| Employed | 291 (56.5) |
| Unemployed | 224 (43.5) |
| Relationship with patient | |
| Spouse | 173 (33.6) |
| Child | 271 (52.6) |
| Friend | 14 (2.7) |
| Nephew/niece | 23 (4.5) |
| Brother/sister | 11 (2.1) |
| Other relative | 23 (4.5) |
| Caregiver living with patient | 194 (37.7) |
| Hours of caregiving per day, mean (SD) | 7.5 (7.2) |
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 245 (47.6) |
| Female | 270 (52.4) |
| Age, mean (SD) | 56.6 (14.9) |
| Education | |
| Elementary | 80 (15.6) |
| Middle school | 167 (32.4) |
| Professional school | 70 (13.6) |
| High school | 146 (28.3) |
| University degree | 52 (10.1) |
| Marital status | |
| Married | 375 (72.8) |
| Single | 74 (14.4) |
| Widowed | 24 (4.6) |
| Divorced | 42 (8.2) |
| Profession | |
| Employed | 291 (56.5) |
| Unemployed | 224 (43.5) |
| Relationship with patient | |
| Spouse | 173 (33.6) |
| Child | 271 (52.6) |
| Friend | 14 (2.7) |
| Nephew/niece | 23 (4.5) |
| Brother/sister | 11 (2.1) |
| Other relative | 23 (4.5) |
| Caregiver living with patient | 194 (37.7) |
| Hours of caregiving per day, mean (SD) | 7.5 (7.2) |
SD: standard deviation.
Caregivers’ socio-demographic characteristics (n=515)
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 245 (47.6) |
| Female | 270 (52.4) |
| Age, mean (SD) | 56.6 (14.9) |
| Education | |
| Elementary | 80 (15.6) |
| Middle school | 167 (32.4) |
| Professional school | 70 (13.6) |
| High school | 146 (28.3) |
| University degree | 52 (10.1) |
| Marital status | |
| Married | 375 (72.8) |
| Single | 74 (14.4) |
| Widowed | 24 (4.6) |
| Divorced | 42 (8.2) |
| Profession | |
| Employed | 291 (56.5) |
| Unemployed | 224 (43.5) |
| Relationship with patient | |
| Spouse | 173 (33.6) |
| Child | 271 (52.6) |
| Friend | 14 (2.7) |
| Nephew/niece | 23 (4.5) |
| Brother/sister | 11 (2.1) |
| Other relative | 23 (4.5) |
| Caregiver living with patient | 194 (37.7) |
| Hours of caregiving per day, mean (SD) | 7.5 (7.2) |
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 245 (47.6) |
| Female | 270 (52.4) |
| Age, mean (SD) | 56.6 (14.9) |
| Education | |
| Elementary | 80 (15.6) |
| Middle school | 167 (32.4) |
| Professional school | 70 (13.6) |
| High school | 146 (28.3) |
| University degree | 52 (10.1) |
| Marital status | |
| Married | 375 (72.8) |
| Single | 74 (14.4) |
| Widowed | 24 (4.6) |
| Divorced | 42 (8.2) |
| Profession | |
| Employed | 291 (56.5) |
| Unemployed | 224 (43.5) |
| Relationship with patient | |
| Spouse | 173 (33.6) |
| Child | 271 (52.6) |
| Friend | 14 (2.7) |
| Nephew/niece | 23 (4.5) |
| Brother/sister | 11 (2.1) |
| Other relative | 23 (4.5) |
| Caregiver living with patient | 194 (37.7) |
| Hours of caregiving per day, mean (SD) | 7.5 (7.2) |
SD: standard deviation.
Patients’ socio-demographic and clinical characteristics
Table 2 presents patients’ socio-demographic and clinical characteristics. Patients were predominately older (mean age 75.6 years, SD=10.7) and male (55.5%). The level of education was low with 75.2% of patients having less than a high school education. Most patients were unemployed (88.7%) and married (55.7%). All NYHA classes were represented in the sample but most patients (72.6%) were in NYHA class II and III. The mean score on the CCI was three indicating a relatively low level of comorbidity, while the mean of score on the MMSE was 23, which denotes mild cognitive impairment.
Patients’ socio-demographic and clinical characteristics (n=515)
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 286 (55.5) |
| Female | 229 (44.5) |
| Age (mean, SD) | 75.6 (10.7) |
| Education | |
| Elementary | 270 (52.5) |
| Middle school | 117 (22.7) |
| Professional school | 45 (8.7) |
| High school | 65 (12.6) |
| University degree | 18 (3.5) |
| Marital status | |
| Married | 287 (55.7) |
| Single | 17 (3.3) |
| Widowed | 183 (35.5) |
| Divorced | 28 (5.4) |
| Profession | |
| Employed | 58 (11.3) |
| Unemployed | 457 (88.7) |
| New York Heart Association class | |
| I | 94 (18.2) |
| II | 192 (37.3) |
| III | 182 (35.3) |
| IV | 47 (9.2) |
| Ejection fraction (mean, SD) | 44.1 (10.7) |
| Time since diagnosis (months) (median, interquartile range) | 45.5 (24–72) |
| CCI (mean, SD) | 3.05 (1.3) |
| MMSE (mean, SD) | 23.4 (6.7) |
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 286 (55.5) |
| Female | 229 (44.5) |
| Age (mean, SD) | 75.6 (10.7) |
| Education | |
| Elementary | 270 (52.5) |
| Middle school | 117 (22.7) |
| Professional school | 45 (8.7) |
| High school | 65 (12.6) |
| University degree | 18 (3.5) |
| Marital status | |
| Married | 287 (55.7) |
| Single | 17 (3.3) |
| Widowed | 183 (35.5) |
| Divorced | 28 (5.4) |
| Profession | |
| Employed | 58 (11.3) |
| Unemployed | 457 (88.7) |
| New York Heart Association class | |
| I | 94 (18.2) |
| II | 192 (37.3) |
| III | 182 (35.3) |
| IV | 47 (9.2) |
| Ejection fraction (mean, SD) | 44.1 (10.7) |
| Time since diagnosis (months) (median, interquartile range) | 45.5 (24–72) |
| CCI (mean, SD) | 3.05 (1.3) |
| MMSE (mean, SD) | 23.4 (6.7) |
CCI: Charlson Comorbidity Index; MMSE: Mini Mental State Examination; SD: standard deviation.
Patients’ socio-demographic and clinical characteristics (n=515)
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 286 (55.5) |
| Female | 229 (44.5) |
| Age (mean, SD) | 75.6 (10.7) |
| Education | |
| Elementary | 270 (52.5) |
| Middle school | 117 (22.7) |
| Professional school | 45 (8.7) |
| High school | 65 (12.6) |
| University degree | 18 (3.5) |
| Marital status | |
| Married | 287 (55.7) |
| Single | 17 (3.3) |
| Widowed | 183 (35.5) |
| Divorced | 28 (5.4) |
| Profession | |
| Employed | 58 (11.3) |
| Unemployed | 457 (88.7) |
| New York Heart Association class | |
| I | 94 (18.2) |
| II | 192 (37.3) |
| III | 182 (35.3) |
| IV | 47 (9.2) |
| Ejection fraction (mean, SD) | 44.1 (10.7) |
| Time since diagnosis (months) (median, interquartile range) | 45.5 (24–72) |
| CCI (mean, SD) | 3.05 (1.3) |
| MMSE (mean, SD) | 23.4 (6.7) |
| Variables | n (%) |
|---|---|
| Gender | |
| Male | 286 (55.5) |
| Female | 229 (44.5) |
| Age (mean, SD) | 75.6 (10.7) |
| Education | |
| Elementary | 270 (52.5) |
| Middle school | 117 (22.7) |
| Professional school | 45 (8.7) |
| High school | 65 (12.6) |
| University degree | 18 (3.5) |
| Marital status | |
| Married | 287 (55.7) |
| Single | 17 (3.3) |
| Widowed | 183 (35.5) |
| Divorced | 28 (5.4) |
| Profession | |
| Employed | 58 (11.3) |
| Unemployed | 457 (88.7) |
| New York Heart Association class | |
| I | 94 (18.2) |
| II | 192 (37.3) |
| III | 182 (35.3) |
| IV | 47 (9.2) |
| Ejection fraction (mean, SD) | 44.1 (10.7) |
| Time since diagnosis (months) (median, interquartile range) | 45.5 (24–72) |
| CCI (mean, SD) | 3.05 (1.3) |
| MMSE (mean, SD) | 23.4 (6.7) |
CCI: Charlson Comorbidity Index; MMSE: Mini Mental State Examination; SD: standard deviation.
Caregiver contribution to self-care maintenance and management
Figure 1 illustrates the caregiver’s contribution to self-care maintenance which had a total score of 55.9 (SD 17.9; range 0–100). The descriptive analysis of individual items on the caregiver’s contribution to self-care maintenance scale showed that more than half of the caregivers never/rarely or only sometimes recommended that the patient check his/her weight (54.9%) or perform physical activity (60.6%) or exercise (64.8%). However, more than 60% of caregivers reported recommending that the patient check his/her ankles and eat a low-salt diet. More than 70% of caregivers recommended that the patient take medicines, try not to get sick, and keep doctor or nurse appointments (Figure 1). More than half of caregivers (56.1%) used a system to remind patients to take their medicines.
Percentages of responses per each Likert point to caregiver contribution to self-care maintenance scale. Numbers in bars are percentages of responses per each Likert point
Of the total sample, only 255 caregivers (or 50%) reported that the patient had HF symptoms in the preceding month, allowing for administration of The Caregiver’s Contribution to Self-Care Management scale (caregiver actions taken to relieve HF symptoms) (Figure 2). The mean score on this scale was 58.4 (SD=18.19, range 5–100). More than a half of these caregivers (54.2%) were unable to recognize the signs and symptoms of a HF exacerbation quickly or very quickly. Once recognized, most caregivers recommended that patients reduce the salt in their diet (66.7%), drink fewer fluids (54.9%) or call their providers (76.5%). Few caregivers (47.8%) recommended that patients take an extra diuretic. Most (69%) caregivers felt sure of their ability to judge whether the remedy they recommended most recently was effective.
Percentages of responses per each Likert point to caregiver contribution to self-care management scale. Numbers in bars are percentages of responses per each Likert point
Caregiver confidence in contributing to self-care
Figure 3 illustrates caregiver confidence in contributing to patient self-care. Mean caregiver score on the self-care confidence scale was 56.9 (SD 19.3, range 11.1–100). Caregivers were most confident in their ability to follow treatment advice (80.6%), evaluate the importance of symptoms (61.4%) and evaluate if a remedy suggested to relieve symptoms worked (50.9%). They were less confident in their ability to prevent HF symptoms (58.8%) and do something to relieve symptoms when they occurred (53.8%). There were no statistically significant differences in confidence between spouse and adult children caregivers (mean scores 53.94, SD 19.18 vs. 57.03, SD 19.94 respectively, p=0.19).
Percentages of responses per each Likert point to caregiver confidence in contributing to self-care. HF: heart failure. Numbers in bars are percentages of responses per each Likert point
Variables correlated with caregiver’s contribution to self-care maintenance and management
As shown in Table 3, variables significantly correlated with better caregiver’s contribution to self-care maintenance were caregiver female gender, being married to the HF patient, better NYHA functional class, longer time since diagnosis, and higher caregiver confidence. Variables significantly correlated with caregiver’s contribution to self-care management were younger caregiver age, fewer caregiving hours, female patient gender, single marital status of the patient, and higher caregiver confidence.
Correlations with caregiver contribution to self-care (CC-SC) maintenance and CC-SC management
| CC-SC maintenance | CC-SC management | |
|---|---|---|
| Caregiver gender (0=male; 1=female) | 0.10a | 0.01 |
| Caregiver age (from 20–88 years) | 0.0 | −0.16a |
| Caregiver education (from 1=elementary to 5=university degree) | −0.06 | −0.04 |
| Caregiver marital status (0=without partner; 1= with partner) | 0.10a | 0.011 |
| Caregiver job (0=unemployed; 1=employed) | −0.02 | −0.03 |
| Do you live with patient? (0=no; 1=yes) | 0.02 | 0.04 |
| How many hours do you care for the patient in a day? (from 1–24 h) | −0.01 | −0.21b |
| Patient gender (0=male; 1=female) | 0.03 | 0.12a |
| Patient age (from 29–96 years) | −0.05 | −0.05 |
| Patient’s marital status (0=without partner; 1= with partner) | 0.04 | −0.16b |
| Patient’s job (0=unemployed; 1=employed) | −0.02 | 0.04 |
| NYHA class (from 1–4) | 0.10a | −0.09 |
| EF (from 20–90) | 0.01 | 0.08 |
| Time since diagnosis (months) (from 1–240) | 0.12b | −0.01 |
| CCI (from 2–11) | 0.09 | −0.08 |
| MMSE (from 10–30) | −0.02 | 0.01 |
| Caregiver confidence (from 0–100) | 0.42b | 0.59b |
| CC-SC maintenance (from 0–100) | − | 0.44b |
| CC-SC maintenance | CC-SC management | |
|---|---|---|
| Caregiver gender (0=male; 1=female) | 0.10a | 0.01 |
| Caregiver age (from 20–88 years) | 0.0 | −0.16a |
| Caregiver education (from 1=elementary to 5=university degree) | −0.06 | −0.04 |
| Caregiver marital status (0=without partner; 1= with partner) | 0.10a | 0.011 |
| Caregiver job (0=unemployed; 1=employed) | −0.02 | −0.03 |
| Do you live with patient? (0=no; 1=yes) | 0.02 | 0.04 |
| How many hours do you care for the patient in a day? (from 1–24 h) | −0.01 | −0.21b |
| Patient gender (0=male; 1=female) | 0.03 | 0.12a |
| Patient age (from 29–96 years) | −0.05 | −0.05 |
| Patient’s marital status (0=without partner; 1= with partner) | 0.04 | −0.16b |
| Patient’s job (0=unemployed; 1=employed) | −0.02 | 0.04 |
| NYHA class (from 1–4) | 0.10a | −0.09 |
| EF (from 20–90) | 0.01 | 0.08 |
| Time since diagnosis (months) (from 1–240) | 0.12b | −0.01 |
| CCI (from 2–11) | 0.09 | −0.08 |
| MMSE (from 10–30) | −0.02 | 0.01 |
| Caregiver confidence (from 0–100) | 0.42b | 0.59b |
| CC-SC maintenance (from 0–100) | − | 0.44b |
CCI: Charlson Comorbidity Index; EF: ejection fraction; MMSE: Mini Mental State Examination; NYHA: New York Heart Association. Note: Numbers being presented are correlation coefficients; all comparisons were against the variable coded 0. ap<0.05; bp<0.01.
Correlations with caregiver contribution to self-care (CC-SC) maintenance and CC-SC management
| CC-SC maintenance | CC-SC management | |
|---|---|---|
| Caregiver gender (0=male; 1=female) | 0.10a | 0.01 |
| Caregiver age (from 20–88 years) | 0.0 | −0.16a |
| Caregiver education (from 1=elementary to 5=university degree) | −0.06 | −0.04 |
| Caregiver marital status (0=without partner; 1= with partner) | 0.10a | 0.011 |
| Caregiver job (0=unemployed; 1=employed) | −0.02 | −0.03 |
| Do you live with patient? (0=no; 1=yes) | 0.02 | 0.04 |
| How many hours do you care for the patient in a day? (from 1–24 h) | −0.01 | −0.21b |
| Patient gender (0=male; 1=female) | 0.03 | 0.12a |
| Patient age (from 29–96 years) | −0.05 | −0.05 |
| Patient’s marital status (0=without partner; 1= with partner) | 0.04 | −0.16b |
| Patient’s job (0=unemployed; 1=employed) | −0.02 | 0.04 |
| NYHA class (from 1–4) | 0.10a | −0.09 |
| EF (from 20–90) | 0.01 | 0.08 |
| Time since diagnosis (months) (from 1–240) | 0.12b | −0.01 |
| CCI (from 2–11) | 0.09 | −0.08 |
| MMSE (from 10–30) | −0.02 | 0.01 |
| Caregiver confidence (from 0–100) | 0.42b | 0.59b |
| CC-SC maintenance (from 0–100) | − | 0.44b |
| CC-SC maintenance | CC-SC management | |
|---|---|---|
| Caregiver gender (0=male; 1=female) | 0.10a | 0.01 |
| Caregiver age (from 20–88 years) | 0.0 | −0.16a |
| Caregiver education (from 1=elementary to 5=university degree) | −0.06 | −0.04 |
| Caregiver marital status (0=without partner; 1= with partner) | 0.10a | 0.011 |
| Caregiver job (0=unemployed; 1=employed) | −0.02 | −0.03 |
| Do you live with patient? (0=no; 1=yes) | 0.02 | 0.04 |
| How many hours do you care for the patient in a day? (from 1–24 h) | −0.01 | −0.21b |
| Patient gender (0=male; 1=female) | 0.03 | 0.12a |
| Patient age (from 29–96 years) | −0.05 | −0.05 |
| Patient’s marital status (0=without partner; 1= with partner) | 0.04 | −0.16b |
| Patient’s job (0=unemployed; 1=employed) | −0.02 | 0.04 |
| NYHA class (from 1–4) | 0.10a | −0.09 |
| EF (from 20–90) | 0.01 | 0.08 |
| Time since diagnosis (months) (from 1–240) | 0.12b | −0.01 |
| CCI (from 2–11) | 0.09 | −0.08 |
| MMSE (from 10–30) | −0.02 | 0.01 |
| Caregiver confidence (from 0–100) | 0.42b | 0.59b |
| CC-SC maintenance (from 0–100) | − | 0.44b |
CCI: Charlson Comorbidity Index; EF: ejection fraction; MMSE: Mini Mental State Examination; NYHA: New York Heart Association. Note: Numbers being presented are correlation coefficients; all comparisons were against the variable coded 0. ap<0.05; bp<0.01.
The role of caregiver confidence in explaining caregiver’s contribution to self-care maintenance and management
Collinearity analysis showed a VIF for all tested models ≤1.2 and a tolerance ≥0.84, indicating no collinearity. Results of the two hierarchical regression analyses suggested that caregiver confidence significantly affected caregiver’s contribution to both self-care maintenance and to self-care management. This contribution was above that associated with the caregivers’ socio-demographic variables and the patients’ socio-demographic and clinical variables (Table 4). For caregiver’s contribution to self-care maintenance, in Model 1, the only significant predictor was time since diagnosis, which explained only 0.02% of the variance (F=2.606, p=0.035). Adding caregiver confidence, the model (Model 2) improved the explained variance in caregiver contribution to self-care maintenance to 16% (F=15.567, p=0.000). In Model 2 the only two variables that explained caregiver’s contribution to self-care maintenance were patient’s time since diagnosis and caregiver confidence.
The role of caregiver confidence in explaining self-care maintenance and management
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| Standardized β | p | Standardized β | p | |
| Dependent variable: caregiver contribution to self-care maintenance | ||||
| Caregiver gender (0=male; 1=female) | 0.000 | 0.998 | −0.008 | 0.860 |
| Caregiver marital status (0=without partner; 1=with partner) | 0.019 | 0.698 | 0.021 | 0.641 |
| NYHA class | 0.055 | 0.296 | 0.045 | 0.357 |
| Month of illness | 0.125 | 0.018 | 0.097 | 0.049 |
| Caregiver confidence | 0.370 | <0.001 | ||
| R2 | 0.025 | 0.160 | ||
| Adjusted R2 | 0.015 | 0.150 | ||
| F | 2.606 | 0.035 | 15.567 | <0.001 |
| Dependent variable: caregiver contribution to self-care management | ||||
| Caregiver age | −0.065 | 0.344 | −0.013 | 0.825 |
| Caregiving hours | −0.147 | 0.024 | −0.079 | 0.152 |
| Patient gender (0=male; 1=female) | −0.050 | 0.444 | −0.052 | 0.341 |
| Patient’s marital status (0=without partner; 1=with partner) | −0.115 | 0.099 | −0.051 | 0.386 |
| Caregiver confidence | 0.543 | <0.001 | ||
| R2 | 0.065 | 0.342 | ||
| Adjusted R2 | 0.050 | 0.329 | ||
| F | 4.489 | 0.002 | 97.882 | <0.001 |
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| Standardized β | p | Standardized β | p | |
| Dependent variable: caregiver contribution to self-care maintenance | ||||
| Caregiver gender (0=male; 1=female) | 0.000 | 0.998 | −0.008 | 0.860 |
| Caregiver marital status (0=without partner; 1=with partner) | 0.019 | 0.698 | 0.021 | 0.641 |
| NYHA class | 0.055 | 0.296 | 0.045 | 0.357 |
| Month of illness | 0.125 | 0.018 | 0.097 | 0.049 |
| Caregiver confidence | 0.370 | <0.001 | ||
| R2 | 0.025 | 0.160 | ||
| Adjusted R2 | 0.015 | 0.150 | ||
| F | 2.606 | 0.035 | 15.567 | <0.001 |
| Dependent variable: caregiver contribution to self-care management | ||||
| Caregiver age | −0.065 | 0.344 | −0.013 | 0.825 |
| Caregiving hours | −0.147 | 0.024 | −0.079 | 0.152 |
| Patient gender (0=male; 1=female) | −0.050 | 0.444 | −0.052 | 0.341 |
| Patient’s marital status (0=without partner; 1=with partner) | −0.115 | 0.099 | −0.051 | 0.386 |
| Caregiver confidence | 0.543 | <0.001 | ||
| R2 | 0.065 | 0.342 | ||
| Adjusted R2 | 0.050 | 0.329 | ||
| F | 4.489 | 0.002 | 97.882 | <0.001 |
NYHA: New York Heart Association.
Note. All comparison were against the variable coded 0.
The role of caregiver confidence in explaining self-care maintenance and management
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| Standardized β | p | Standardized β | p | |
| Dependent variable: caregiver contribution to self-care maintenance | ||||
| Caregiver gender (0=male; 1=female) | 0.000 | 0.998 | −0.008 | 0.860 |
| Caregiver marital status (0=without partner; 1=with partner) | 0.019 | 0.698 | 0.021 | 0.641 |
| NYHA class | 0.055 | 0.296 | 0.045 | 0.357 |
| Month of illness | 0.125 | 0.018 | 0.097 | 0.049 |
| Caregiver confidence | 0.370 | <0.001 | ||
| R2 | 0.025 | 0.160 | ||
| Adjusted R2 | 0.015 | 0.150 | ||
| F | 2.606 | 0.035 | 15.567 | <0.001 |
| Dependent variable: caregiver contribution to self-care management | ||||
| Caregiver age | −0.065 | 0.344 | −0.013 | 0.825 |
| Caregiving hours | −0.147 | 0.024 | −0.079 | 0.152 |
| Patient gender (0=male; 1=female) | −0.050 | 0.444 | −0.052 | 0.341 |
| Patient’s marital status (0=without partner; 1=with partner) | −0.115 | 0.099 | −0.051 | 0.386 |
| Caregiver confidence | 0.543 | <0.001 | ||
| R2 | 0.065 | 0.342 | ||
| Adjusted R2 | 0.050 | 0.329 | ||
| F | 4.489 | 0.002 | 97.882 | <0.001 |
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| Standardized β | p | Standardized β | p | |
| Dependent variable: caregiver contribution to self-care maintenance | ||||
| Caregiver gender (0=male; 1=female) | 0.000 | 0.998 | −0.008 | 0.860 |
| Caregiver marital status (0=without partner; 1=with partner) | 0.019 | 0.698 | 0.021 | 0.641 |
| NYHA class | 0.055 | 0.296 | 0.045 | 0.357 |
| Month of illness | 0.125 | 0.018 | 0.097 | 0.049 |
| Caregiver confidence | 0.370 | <0.001 | ||
| R2 | 0.025 | 0.160 | ||
| Adjusted R2 | 0.015 | 0.150 | ||
| F | 2.606 | 0.035 | 15.567 | <0.001 |
| Dependent variable: caregiver contribution to self-care management | ||||
| Caregiver age | −0.065 | 0.344 | −0.013 | 0.825 |
| Caregiving hours | −0.147 | 0.024 | −0.079 | 0.152 |
| Patient gender (0=male; 1=female) | −0.050 | 0.444 | −0.052 | 0.341 |
| Patient’s marital status (0=without partner; 1=with partner) | −0.115 | 0.099 | −0.051 | 0.386 |
| Caregiver confidence | 0.543 | <0.001 | ||
| R2 | 0.065 | 0.342 | ||
| Adjusted R2 | 0.050 | 0.329 | ||
| F | 4.489 | 0.002 | 97.882 | <0.001 |
NYHA: New York Heart Association.
Note. All comparison were against the variable coded 0.
For the caregiver’s contribution to self-care management, in Model 1, the only significant determinant was caregiving hours. This model explained only the 6% of variance in caregiver contribution to self-care management (F=4.489, p=0.002). When caregiver confidence was added in Model 2, the explained variance of caregiver’s contribution to self-care management improved to 34%. Caregiver confidence was the only significant predictor of caregiver’s contribution to self-care management (F=97.882, p<0.001). Thus, our hypothesis that caregiver self-efficacy explained more of the variance in caregiver’s contribution to self-care maintenance and management beyond that explained by socio-demographic and clinical characteristics was supported.
Discussion
The aim of this study was to describe caregivers’ contributions to HF patients’ self-care and then to identify potential determinants of that care, testing patient and caregiver socio-demographic characteristics, patient clinical characteristics and caregiver self-efficacy. In this sample we found that self-efficacy was the primary determinant of caregivers’ contributions to patients’ self-care maintenance and management. Prior studies carried out in other populations with similar caregiving responsibilities have shown that higher caregiver self-efficacy is associated with better outcomes for both caregivers and patients.40,41 But, to the best of our knowledge, this is the first study that has documented the importance of self-efficacy in caregivers of HF patients.
Although caregivers were not informed contributors, they were supportive of some self-care maintenance activities. Unfortunately, they never or rarely supported some important activities such as daily weighing and exercise. Of particular concern is the finding that over half of the caregivers reported that they did not quickly recognize common signs of a HF exacerbation such as shortness of breath or ankle edema. Once signs were recognized, most recommended reducing salt in the diet and fluid intake or calling the provider over an active intervention such as taking an extra diuretic. These behaviors suggest that knowledge about what self-care maintenance behaviors are most effective is insufficient in many caregivers.
This conclusion is supported by a recent meta-synthesis of 10 qualitative studies,23 where a recurrent theme in the experience of HF caregivers was ‘searching for support’, which also included the need of caregivers to be adequately prepared for the disease. In particular, in four studies included in this meta-synthesis, caregivers complained about knowledge deficits regarding the disease and its management and did not know the importance of behavioral management strategies such as weight monitoring, physical activity, salt and fluid restriction. Of note, these specific needs were reported by caregivers even after 18 months of caregiving. Uncertainty in how to behave with patients has also been reported previously.42 However further studies are needed to understand other factors influencing caregivers’ contributions to patients’ self-care.
Considering self-care management, 54% of our sample of caregivers was unable to recognize symptoms of a HF exacerbation quickly. Quinn and Dunbar43 found poor congruence between caregivers and patients in symptom assessment as well as poor caregiver skills in symptom recognition. Similarly, Janssen et al.44 found that caregivers tend to overestimate symptoms. Our results contribute to this small body of knowledge by reiterating the need for caregivers to learn as much as patients about how to monitor and interpret early symptoms.
Caregivers felt confident in contributing to some self-care activities (treatment adherence, evaluating the importance of symptoms, and evaluating symptom remedies) but felt less confident in their ability to prevent and relieve symptoms. Preventing and relieving patients’ symptoms might be difficult if caregivers lack sufficient knowledge on disease management. Studies carried out in other caregiver populations have shown that knowledge of disease management is a predictor of higher caregiver self-efficacy and better contributions to patient self-care.22,45
This is the first study that has measured the caregiver’s contribution to HF patient’s self-care with a disease-specific instrument. The CC-SCHFI provides a specific measure of the support provided to HF patients by caregivers. Data from this instrument facilitates the identification of areas where caregivers contribute more (e.g. medication regimen) and areas where caregivers contribute less (e.g. symptom recognition). Specific measurements of the caregiver’s contribution to HF patient’s self-care, such as the CC-SCHFI, can be useful to guide future research and tailored interventions for HF caregivers.
This study has several limitations. Even though this was a multicenter study, a convenience sample was enrolled. A further limitation is the cross-sectional design, which allowed only the identification of correlates or determinants of self-care. Future studies should use a longitudinal design in order to identify true predictors of the caregiver’s contribution to self-care maintenance and management. In addition, results from this study should be generalized to other countries with caution as Italian cultural aspects may have influenced how caregivers in this sample took care of their loved ones.
Conclusion
In this study we found that self-efficacy was a unique determinant of caregivers’ contributions to both self-care maintenance and self-care management. According to Bandura’s cognitive theory19 self-efficacy can be improved with performance accomplishment, vicarious experience, verbal persuasion, and emotional arousal. Further studies are needed in order to test the applicability and effectiveness of interventions guided by Bandura’s theory for HF caregivers.
Conflict of interest
None declared.
Funding
This work was funded by the Center of Excellence for Nursing Scholarship, Rome, Italy.
Providers need to strengthen the education given to heart failure caregivers and to understand reasons that prevent them from contributing to heart failure patients’ self-care.
Providers should reinforce the importance of weight monitoring and physical activity with caregivers as well as patients.
Caregiver understanding and implementation of symptom monitoring and diuretic self-titration should be assessed frequently and reinforced as needed.
Improving caregiver self-efficacy may improve their contributions to patients’ self-care and thus patients’ self-care.
Self-efficacy building activities are needed for this vital group.
References
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