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International Journal of Nursing Practice 2016; 22: 179–188
RESEARCH PAPER
Quality of life, social support and cognitive impairment in heart failure patients without diagnosed dementia Robyn Gallagher RN BA (Psych) MN PhD Professor of Nursing, Sydney Nursing School and Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
Anne Sullivan RN BA Admin Nurse Coronary Care Cert Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Royal North Shore Hospital, Sydney, New South Wales, Australia
Rhonda Burke RN BSN MN Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Manly and Mona Vale Hospitals, Sydney, New South Wales, Australia
Susan Hales RN BN Cert CT Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Ryde Hospital, Sydney, New South Wales, Australia
Precilla Sharpe RN Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Hornsby Hospital, Sydney, New South Wales, Australia
Geoffrey Tofler MBBS Cardiologist, Professor of Medicine, Management of Cardiac Function (MACARF), Royal North Shore Hospital, Sydney, New South Wales, Australia
Accepted for publication February 2015 Gallagher R, Sullivan A, Burke R, Hales S, Sharpe P, Tofler G. International Journal of Nursing Practice 2016; 22: 179–188 Quality of life, social support and cognitive impairment in heart failure patients without diagnosed dementia Improving health-related quality of life (HRQL) is an important goal for heart failure (HF) patients, and understanding the factors that influence HRQL is essential to this process. We investigated the influence of social support and cognitive impairment on HRQL in community dwelling HF patients (n = 104) without diagnosed dementia. Patients were aged mean 80.93 years (SD 11.01) and were classified as New York Heart Association Class 1/II (45%) or III/IV (53%). Age, social support and cognition had important independent effects. Younger people had the most negative effects of HF in all areas of HRQL: emotional (B = −0.32), physical (B = −0.44) and overall (B = −1). Well-supported patients (general
Correspondence: Robyn Gallagher, Sydney Nursing School and Charles Perkins Centre, University of Sydney, Sydney, NSW 2006, Australia. E-mail: [email protected] doi:10.1111/ijn.12402
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social support) had the least negative effect from HF on HRQL: emotional domain (B = −4.62) and overall (B = −11.72). Patients with normal cognition had more negative impact of HF on HRQL: physical domain (B = 5.51) and overall HRQL (B = 10.42). A clearer understanding of the relationships between age, social support and cognition and the effect on the impact of HF on HRQL is needed before interventions can be appropriately developed. Key words: age, cognitive impairment, health-related quality of life, heart failure, social support.
INTRODUCTION Patients who have heart failure (HF) experience multiple and progressive symptoms, which can reduce function, increase disability and impair health-related quality of life (HRQL).1 Improving or at least minimizing the impact on HRQL of HF is an important goal for HF patients. Understanding and investigating factors that influence HRQL are essential to this process. Multiple factors have been identified that influence HRQL in this population, including severity of symptoms,2,3 age, gender and comorbidities,3 and psychological distress.4 However, the relationship between other important factors such as cognitive impairment and social support and HRQL has had limited investigation, despite the potential for these factors to be amenable to, or supplemented by, interventions and therefore minimize impact.5–8 Cognitive impairment is prevalent in HF patients, occurring in 25–50% of this population, and is associated with worse patient outcomes, including mortality.9 Impairment associated with HF has a negative effect on several areas, most notably working memory, memory and executive function,10 self-care, and activities of daily living in HF patients.11 HF patients themselves could notice their impairment, and this impairment, even when mild, negatively affects their daily lives.12 However, the influence of cognitive impairment on HRQL is less clear. A recent study of 249 HF patients found when HF severity, age and depressive symptoms were controlled for, the total recall memory component of cognitive function was an independent predictor of HRQL, but the contribution of this cognitive area was minimal.10 Furthermore, no other area of cognitive function had an independent influence on HRQL. Similarly, another study reported that cognitive impairment did not have an independent effect on HRQL when daytime sleepiness was taken into account.13 Counterintuitive results are also reported, with patients who had the most severe cognitive impairment (following cardiac arrest) reporting better HRQL than patients who were less impaired.14 A potential © 2015 John Wiley & Sons Australia, Ltd
explanation for this unexpected result is the role that social support might play in compensating for deficits so that ultimately HRQL is less affected, although this could not be determined in these studies as social support was not included in the analyses. However, when cognitive impairment is present, HF patients’ social support could provide a crucial buffer to help manage medications and treatments and detect worsening symptoms as well as support other aspects of patients’ day-to-day lives.15 Social support is a multidimensional concept incorporating physical and emotional components, the quality of relationships16 and, potentially, the support provided for a specific condition such as HF. Social support is known to influence many important outcomes for HF patients including mortality,17 admission to hospital,18 anxiety and depression,19,20 and self-care.21,22 Recent studies of HF patients indicate that social support was associated with HRQL even after controlling for age, gender, symptom severity23 and depressive symptoms,24 in both the short and longer term.25 However, other studies have failed to show this association,26–28 which might in part be due to the complex nature of social support. HF-specific support has been found to influence HF self-care when all of these aspects and HF patients’ perceptions of their carers’ HF knowledge and expertise are included in the measure.22 Despite the likely run-on effect of HF-specific support on minimizing the impact of HF on HRQL, no study has distinguished between the relative influence of social support and HF-specific social support. This study aimed to determine the levels of cognitive impairment, social support and HF-specific support and the independent influence on the impact of HF on HRQOL in HF patients after controlling for age, disease severity, gender and comorbidity. The study hypotheses were that after controlling for the influence of age, disease severity, gender and comorbidity on HRQL, (i) cognitive impairment would negatively affect HRQL, and (ii) social support and (iii) HF-specific support would positively affect HRQL in HF patients.
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METHODS Design The study used a descriptive correlational design.
fatigue, palpitations, dyspnea or angina with any effort) to Class IV (fatigue, palpitations, dyspnea or angina at rest). Validity and reliability of the NYHA classification system have been reported previously in HF patients.29
Setting and sample Participants included patients registered with the Management of Cardiac Function (MACARF) HF specialist nurse home visit programme. Patients registered with this programme have a diagnosis of HF and are community dwelling. Patients were eligible for the study if they were newly registered on the home visit programme, able to understand and respond to written and spoken English sufficiently for the consent processes, had no diagnosed major cognitive or psychiatric disorder and did not require palliative or end of life care, and had sufficient vision and hearing to undertake the Montreal Cognitive Assessment Tool (MoCA). Sample size was estimated at 103, to detect an effect size of 0.15, with an alpha level of 0.8, seven predictors and P level of 0.05 (www.danielsoper.com).
Data collection Clinical and sociodemographic data were extracted from both the medical records and asked of the patients themselves. This data included the participants’ age, gender, marital and employment status, education level, whether the person lived alone or with other people, New York Heart Association (NYHA) functional class and comorbid conditions.
HRQL HRQL specific to HF was measured using the Minnesota Living with Heart Failure Questionnaire.29 This questionnaire contains 21 items addressing various aspects of the impact of HF on patients being able to live their lives the way they wanted to in the last month. There are three subscales, emotional (five items), physical (nine items) and general (seven items), and participants respond to the questions using a 5-point scale, from no impact (0 points) to very much impact (5 points). Scores are achieved for the subscales and the total scale by summing the points, for a potential score of 0 (no impact) to 105 (very much impact). The validity of this scale has been established in HF patients.25 In the current study, the instrument showed high internal consistency reliability (Cronbach’s α = 0.91).
HF severity The severity of HF symptoms was measured using the NYHA classification system. Scores range from Class I (no
Comorbidity The presence of comorbid conditions was measured using the Charlson Comorbidity Index, which includes 12 conditions weighted for severity at 1, 3 or 6 points. A higher score represents more and/or more severe comorbid conditions. Scores on the Charlson Comorbidity Index are predictive of mortality within 12 months.30
Cognitive function Cognitive impairment was assessed using the MoCA, a brief screening tool specifically designed to detect mild cognitive impairment.31 It is made up of subscales that are designed to assess visuospatial abilities, language, memory, executive functioning, attention, concentration and working memory, and orientation. Scores were graded for each task for a potential total score of 30. When education level was < 12 years, an additional mark was added to the final score. Patients who scored > 22 were considered to have no impairment of cognition (or normal cognition), and patients scoring ≤ 22 were considered to have impaired cognition.12 In previous studies,31,32 the MoCA has reported good internal consistency (Cronbach’s α = 0.81–0.84) and in a more recent study at Cronbach’s α of 0.77.
Social support Perceived social support was measured by the Medical Outcomes Study (MOS) Social Support Survey.33 The tool has 19 items, which are grouped as subscales related to emotional/informational support (nine items), tangible support (four items), affectionate support (three items), positive social interaction (three items) and one further item on social interaction. Participants respond to each item using a 5-point scale ranging from 0 (none of the time) to 5 (all of the time) indicating how often the specific type of support was provided to them whenever they needed it. The mean of each subscale was calculated as well as the sum of all scores, which was then converted to a percentage. Internal consistency reliability was high (Cronbach’s = 0.95) indicating a redundancy of items, and comparable to a recent study by Robitaille et al.34 which also reported a high internal consistency © 2015 John Wiley & Sons Australia, Ltd
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(Cronbach’s α = 0.90–0.97); however, this issue was not considered to outweigh the other benefits of the MOS for the current study.
HF-specific social support Social support specific to HF was determined by a six-item questionnaire adapted from the COACH study.22,35 This questionnaire was developed to identify the HF patients’ main supporter and the quality of social support for HF that the patient perceives this person provides them. The participant identifies the person who provides them the most support; if participants are not able to identify someone, the questions that follow cannot be answered. The questionnaire includes five items which measure the patient’s perception of the adequacy of their carer’s HF knowledge and attention to their HF symptoms (yes = 2/ no = 0 answer), provision of practical and emotional support (no/low = 0 or moderate/high = 2 answer), and the quality of their relationship (0–10 scale). For the final question, participants who had scores of 9 or less were scored 0 (indicating that patients perceived the relationship between themselves and their carer to be low), whereas a perfect score of 10 was given a score of 2 (indicating that the patient perceived the quality of the relationship with their carer to be high). All scores were then totalled; scores of 10 indicated that patients perceived a high level of support overall from their carers. The scale has been reported to have internal consistency reliability (Cronbach’s α = 0.96),22 whereas in the current study reliability was lower (Cronbach’s α = 0.62).
Procedure Patients were screened for eligibility by the MACARF home visit programme during hospital admission, and eligible patients were approached and informed of the study. Once consent was obtained, sociodemographic and clinical information was collected from the medical record, and the survey was administered during the first routine home visit by the MACARF nurses. All study nurses participated in a training workshop for administering the MoCA and practice interviews to ensure a standardized approach to data collection was used.
were used to describe the sample characteristics, levels of social support, prevalence of cognitive impairment and the impact of HF on HRQL. Correlations and Pearson’s r were used to assess relationships between continuous predictor variables and HRQL. Linear regression analyses were used to determine the independent predictors of HRQL emotional and physical domains and overall HRQL. Variables entered into the analyses included age, gender, HF severity, comorbidity, social support, HF-specific support and cognitive status score. As the scores for social support, HF-specific support and cognitive status were not normally distributed, these scores were dichotomized on the median (for social support) or predetermined thresholds outlined above (HF-specific support and cognitive status) for the regression analyses. Missing data were treated pair-wise resulting in a final sample size of 99 for these analyses. The critical level was set at P < .05.
RESULTS Patients in the sample were aged an average 80.65 years (SD 11.52), with approximately half the participants being male (54%) and living alone (52%) as detailed in Table 1. Severity of HF symptoms were classified as NYHA Class I/II (45%) or III/IV (52%). The mean cognitive status score for the sample was 24.64 (SD 3.38), and cognitive impairment was present in 22% (score < 22 on MoCA) as illustrated in Table 2. Scores on cognitive status were poorest for the subdomains of visual processing and delayed recall relative to the potential top score for that subdomain. The overall mean social support score for the sample was 78.83 (SD 21.64), with affectionate support having the highest mean score of all the support subscales. Of those patients who had carers (98%), the majority (70%) reported a high level of HF-specific support; the lowest proportion of HF-specific support was for having a high-quality relationship with the carer (72%). The HRQL score for the emotional domain was a mean 7.33 (SD 6.98) from a potential range of 0–25, indicating a low impact of HF, and for the physical domain 25.31 (SD 10.18), indicating a moderate impact of HF on HRQL (potential range 0–80). Overall, HF resulted in HRQL that was moderately poor at mean score of 42.4 (SD 21.92) from a potential range of 0–105.
Data analysis
Correlations
Data were analysed using the ibm spss v. 22 (IBM Global New York, New York, USA). Frequencies and descriptive statistics including means, medians and standard deviations
Table 3 illustrates associations between age, cognitive status, HF-specific support, social support and the impact of HF on HRQL overall and subdomains. Age was slightly
© 2015 John Wiley & Sons Australia, Ltd
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Table 1 Sample socio-demographic characteristics (n = 103) Characteristic
Number
%
Male
56
54
Education level < 12 years Year 12 only University/TAFE Employed/seeking employment Primary language: English Married/de facto Living alone
53 20 27 8 97 48 54
51 19 26 8 94 47 52
Carer Spouse Daughter Son Multiple family members Friend, neighbour or other No one (self)
35 27 8 24 5 2
34 26 8 24 5 2
46 54 4.83
45 52 1.40
New York Heart Association Class I/II III/IV Charlson Comorbidity Index, mean, standard deviation
related to increased cognitive impairment and low to moderately correlated with reduced impact of HF on HRQL. Increased cognitive impairment was correlated with less HF-specific support and less impact of HF on HRQL. Increased social support was highly correlated with increased HF-specific support. HF severity (NYHA) was not associated with either type of support (data not shown).
Predictors of HRQL The independent predictors of the impact of HF on HRQL and the emotional and physical domains of HRQL were determined using linear regression analyses. The three models developed explained 22% of physical HRQL, 25% of emotional HRQL and 27% of overall HRQL (Table 4). Age independently predicted both emotional and physical domains as well as the overall impact of HF on HRQL so that younger people had more negative affects from HF on HRQL than older people. Social support independently predicted the emotional domain and overall HRQL so that patients with a high level of social support reported less
negative effect of HF on HRQL. Cognitive status predicted both the physical domain and overall HRQL so that patients who were not cognitively impaired were more negatively affected from HF in HRQL in comparison with patients who did have an impairment.
DISCUSSION In this sample of older HF patients who did not have a dementia diagnosis and were living at home following a recent hospital admission, the impact of HF resulted in HRQL that was moderate–poor, and the most negative impact was experienced by patients who were younger, had less social support and less cognitive impairment. The potential buffering effect of older age and general social support on the impact of HF on HRQL is consistent with previous reports.3–5,22,24,26 However, this study helps distinguish the effects of different types of support and the potential interaction with cognitive impairment. The influence of cognitive status on the impact of HF on HRQL might be complex and requires further exploration. Cognitive impairment is common in HF patients and often goes undetected.8 One in five of the current study sample screened positive for cognitive impairments despite the lack of a related diagnosis. Without this screening, it is likely that impairment in cognition would not have been detected. It is not clear why the presence of cognitive impairment was a predictor of less negative impact of HF on HRQL, given that patients with better cognition would be expected to manage self-care more ably and therefore experience less negative effects from HF on HRQL. One other study also had this apparently counterintuitive finding; however, the sample in that study had also experienced a traumatic event in cardiac arrest.14 Other explanations are possible including that cognitive impairment might reduce insight. The current study provides an indication that HF-specific support might offset the effects of decreased cognition as evidenced by the association between poorer cognition and higher HF-specific support; however, this connection might not ultimately decrease the impact of HF on HRQL. Supporting changes in cognitive status is important in HF patients, whose cognitive status might change over time and with illness exacerbations.35 For partners/ families of HF patients, this implies the need for regular, unintrusive monitoring of cognitive status and accommodating changes in multiple areas of life. These efforts might be HF specific, for example, through support for medication adherence and detection of symptom changes, © 2015 John Wiley & Sons Australia, Ltd
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Table 2 Cognition, social support and HRQL characteristics (n = 103) Cognitive status
Mean
Visual processing Naming Attention Language Abstraction Delayed recall Total Cognitive Status Score (potential range 0–30)
3.63 2.66 5.41 2.49 1.77 2.30 24.64
Emotional/informational support Tangible support Affectionate support Positive social support Overall Score (Potential range 16–100)
SD
Range
Median
1.24 0.64 1.12 0.75 0.53 1.54 3.38
0–5 0–3 1–6 0–3 0–2 0–5 12–30
4 3 6 3 2 2 25
4.07 4.17 4.47 4.05 78.83
0.98 1.11 0.92 1.07 21.64
1–5 1–5 1–5 1–5 16–100
4.5 4.8 5 4 85.53
HF-specific support
Number
%
Adequate HF knowledge Pays attention to HF symptoms Provides adequate practical support Provides adequate emotional support High-quality relationship with carer High level of support (Full points)
92 94 97 98 73 71
90 92 95 96 72 70
Impact of HF on HRQL
Mean
SD
Range
Median
Emotional (potential range 0–25) Physical (potential range 0–80) Total (potential range 0–115)
7.33 25.31 42.40
6.98 10.18 21.92
(0–25) (0–45) (0–83)
5 26 39
Social support
N/A N/A N/A N/A N/A N/A
HF, heart failure; HRQL, health-related quality of life; N/A, not applicable.
or more generally through bill paying and diary reminders. However, the role of partners and family in supporting HF patients who have cognitive impairment needs further investigation as no influence on the impact of HF on HRQL was found in the current study, and given the complexity of the issues, it would benefit from in-depth qualitative investigation. In fact, cognition might be a side issue compared with the more important role of social support. The effects of social support are likely to be multifactorial and complex, and it is important to distinguish and understand the effects of different types of support. In this study, participants perceived that they were well sup© 2015 John Wiley & Sons Australia, Ltd
ported as they reported high levels of social support and support for HF from their family/friends. However, our study results indicate that it might be general social support and not HF-specific support that lessens the negative impact of HF on HRQL. Although the positive effects of general social support were expected, the lack of influence of HF-specific support on the impact of HF on HRQL was unexpected. A previous study identified an association between HF-specific support and several aspects of self-care,22 so it was anticipated that this support would also influence HF-specific HRQL. There are multiple potential explanations for the apparent lack of influence of high levels of HF-specific
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Table 3 Correlation matrix of predictor variables: age, cognition, social and HF-specific support, and impact of HF on HRQL Characteristic
Support
Age Cognition Social HF specific Emotional Physical
Support Impact of HF on HRQL
Impact of HF on HRQL
Cognition
Social
HF specific
Emotional
Physical
Total
−0.21* — — — — —
−0.09 −0.09 — — — —
0.10 −0.21* .69** — — —
−0.27** 0.05 −0.18 −0.08 — —
−0.33** 0.23* −0.16 −0.13 0.62** —
−0.39** 0.16 −0.19 −0.14 0.89** 0.87**
* P = < 0.05; ** P = < 0.01. HF, heart failure; HRQL, health-related quality of life. Table 4 Predictors of influence of HF on HRQL (n = 99) Predictors
Emotional HRQL B†
Age Not cognitively impaired High social support High HF-specific support Male gender NYHA Comorbidities Constant Model statistics †
SE‡
Physical HRQL r§
P
−0.32 0.06 −0.30 < 0.01 2.39 1.56 0.14 0.12 −4.62 1.55 −0.26 < 0.01 1.48 1.63 0.09 0.39 −1.17 1.35 −0.05 0.38 −1.8 1.19 −0.14 0.18 0.38 0.51 0.09 0.45 36.92 F = 4.15, P = < 0.01, r2 = 0.25
B†
SE‡
Overall HRQL r§
B†
P
−0.44 0.09 −0.34 < 0.01 5.51 2.22 0.23 0.01 −3.17 2.21 −0.15 0.16 −0.1 2.33 0.05 0.97 −3.32 1.92 −0.14 0.08 0.07 1.70 −0.03 0.97 0.36 0.73 0.20 0.62 58.54 F = 3.55, P = < 0.01, r2 = 0.22
SE‡
r§
P
−1.0 0.19 −0.41 < 0.01 10.42 4.60 0.21 0.03 −11.72 4.58 −0.25 0.01 0.57 4.82 0.06 0.91 −5.4 3.97 −0.10 0.18 −3.09 3.52 −0.08 0.44 0.86 1.52 0.16 0.58 32.12 F = 4.68, P < 0.01, r2 = 0.27
Unstandardized Beta. ‡ Standard Error. § Partial correlation. HF, heart failure; HRQL, health-related quality of life.
support. One possible explanation is that the impact of HF on HRQL is a self-rated measure, where people rate the reality of their lives against their expectations of life for their life stage and circumstances.16 Although this means that those with preserved cognition could be more aware and distressed by the limitations arising from HF and younger patients, who also had poorer HRQL in the study, and might find the reality of the lives with HF a stark contrast to their unaffected peers, other influential factors are present. However, our results also suggest that those without cognitive impairment do not receive more social support than those who are impaired, whereas they receive more HF failure-specific support, which does not reduce the impact of HF on HRQL and is therefore less useful to them in this respect. It was also interesting to
note that HF severity was not related to the level of support, when it was expected that support would increase with severity. On the other hand, assessments were conducted early after discharge from their first HF admission at the initial home visit so patients might have been unable to realistically gauge the level of HF-specific support they received. It is also possible that the apparent differences in influence on the impact of HF on HRQL of social support and HF-specific support are an artefact of the use of measures with different levels of variability. The social support measure had 19 items, whereas the HF-specific support measure had five, although scores from both measures were ultimately dichotomized for the regression analyses reducing the likelihood of this effect. Finally, family members were almost always present at © 2015 John Wiley & Sons Australia, Ltd
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interviews which might have promoted more positive ratings by patients. Regardless of these considerations, the goal of improving HRQL or at least reducing the negative impact of HF on HRQL is important for HF patients, and fostering social support might help, and therefore, promotion of social support is included in international guidelines for HF self-care.36 The patients in the current study perceived a high level of support so it is not completely clear in what area support can be promoted or what effect this promotion would achieve. Indeed, interventions addressing this area have had limited success. A recent review found that most current models of chronic illness care inadequately addressed the roles and influences of family in patient self-care, even though family members are well suited to provide effective support, and family support is associated with improved outcomes.37 More in-depth understanding is required of different types of social support and patient and family members’ perceptions of the roles they play. Strategies are required which directly address family member roles in HF illness management and seek to give family members the tools and skills they need to carry out these roles, including support for failing cognition.
Limitations
The variance explained in all models was < 30% so other unmeasured variables, such as symptom perception and depressive symptoms, might be equally or more important in understanding differences in the impact of HF on HRQL.26 Results of the study might not be representative of HF patients in general as the sample only includes patients eligible for home support. Furthermore, the measure of HF-specific support requires further development to determine the accuracy of the relative contribution of the subcomponents, including the quality of the relationship with the carer. The current study was crosssectional only so influences noted might be bidirectional.
CONCLUSIONS AND IMPLICATIONS FOR PRACTICE The impact of HF on HRQL in HF patients living at home is moderate and indicates a population likely to need support in addition to that being provided by family and friends. Screening for social support deficits and cognitive impairment might be an important component of HF patient care and should be included in routine practice. Strategies are required to garner social support, particularly for younger people and those with intact cognition. © 2015 John Wiley & Sons Australia, Ltd
The influence of cognitive status on the impact of HF on HRQL and the interaction with support provided by family members needs further investigation, particularly across time. Available caregivers need to be supported in their efforts.
ACKNOWLEDGEMENTS The authors acknowledge Patrick Gallagher for manuscript preparation and editorial assistance. The NSW Health Nursing and Midwifery Office Innovations Scholarship supported this study.
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22 Gallagher R, Luttik ML, Jaarsma T. Social support and self-care in heart failure. The Journal of Cardiovascular Nursing 2011; 26: 439–445. 23 Årestedt K, Saveman BJ, Johansson P, Blomqvist K. Social support and its association with health-related quality of life among older patients with chronic heart failure. European Journal of Cardiovascular Nursing: Journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology 2013; 12: 69–77. 24 Chung ML, Moser DK, Lennie TA, Frazier SK. Perceived social support predicted quality of life in patients with heart failure, but the effect is mediated by depressive symptoms. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation 2013; 22: 1555–1563. 25 White-Williams C, Grady KL, Myers S et al. The relationships among satisfaction with social support, quality of life, and survival 5 to 10 years after heart transplantation. The Journal of Cardiovascular Nursing 2013; 28: 407–416. 26 Heo S, Moser DK, Riegel B, Hall LA, Christman N. Testing a published model of health-related quality of life in heart failure. Journal of Cardiac Failure 2005; 11: 372–379. 27 Westlake C, Dracup K, Creaser J et al. Correlates of healthrelated quality of life in patients with heart failure. Heart and Lung: The Journal of Critical Care 2002; 31: 85–93. 28 Luttik ML, Jaarsma T, Moser D, Sanderman R, Van Veldhuisen D. The importance and impact of social support on outcomes in patients with heart failure: An overview of the literature. The Journal of Cardiovascular Nursing 2005; 20: 162–169. 29 Rector TS, Tschumperlin LK, Kubo SH et al. Use of the living with heart failure questionnaire to ascertain patients’ perspectives on improvement in quality of life versus risk of drug-induced death. Journal of Cardiac Failure 1995; 1: 201– 206. 30 Charlson ME, Pompei P, Ales KL. A new method of classifying prognostic comorbidity in longitudinal studies development and validation. Journal of Chronic Diseases 1987; 40: 373–383. 31 Nasreddine ZS, Phillips NA, Bédirian V et al. The Montreal cognitive assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society 2005; 3: 695–699. 32 Lee JY, Dong Woo Lee DW, Cho SJ et al. Brief screening for mild cognitive impairment in elderly outpatient clinic: Validation of the Korean version of the Montreal Cognitive Assessment. Journal of Geriatric Psychiatry and Neurology 2008; 21: 104–110. 33 Sherbourne CD, Stewart AL. The MOS social support survey. Social Science and Medicine 1991; 32: 705–714. 34 Robitaille A, Orpana H, McIntosh CN. Psychometric properties, factorial structure, and measurement invariance of
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the English and French versions of the Medical Outcomes Study social support scale. Health Reports 2011; 22: 33–40. 35 Riegel B, Moser DK, Anker SD et al. State of the science: Promoting self-care in persons with heart failure: A scientific statement from the American Heart Association. Circulation 2009; 120: 1141–1163. 36 Jaarsma T, Van Der Wal MH, Hogenhuis J et al. Design and methodology of the COACH study: A multicenter
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randomised Coordinating study evaluating Outcomes of Advising and Counselling in Heart failure. European Journal of Heart Failure: Journal of the Working Group on Heart Failure of the European Society of Cardiology 2004; 6: 227– 233. 37 Rosland AM, Piette JD. Emerging models for mobilizing family support for chronic disease management: A structured review. Chronic Illness 2010; 6: 7–21.
International Journal of Nursing Practice 2016; 22: 179–188
RESEARCH PAPER
Quality of life, social support and cognitive impairment in heart failure patients without diagnosed dementia Robyn Gallagher RN BA (Psych) MN PhD Professor of Nursing, Sydney Nursing School and Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
Anne Sullivan RN BA Admin Nurse Coronary Care Cert Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Royal North Shore Hospital, Sydney, New South Wales, Australia
Rhonda Burke RN BSN MN Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Manly and Mona Vale Hospitals, Sydney, New South Wales, Australia
Susan Hales RN BN Cert CT Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Ryde Hospital, Sydney, New South Wales, Australia
Precilla Sharpe RN Clinical Nurse Specialist Heart Failure, Management of Cardiac Function (MACARF), Hornsby Hospital, Sydney, New South Wales, Australia
Geoffrey Tofler MBBS Cardiologist, Professor of Medicine, Management of Cardiac Function (MACARF), Royal North Shore Hospital, Sydney, New South Wales, Australia
Accepted for publication February 2015 Gallagher R, Sullivan A, Burke R, Hales S, Sharpe P, Tofler G. International Journal of Nursing Practice 2016; 22: 179–188 Quality of life, social support and cognitive impairment in heart failure patients without diagnosed dementia Improving health-related quality of life (HRQL) is an important goal for heart failure (HF) patients, and understanding the factors that influence HRQL is essential to this process. We investigated the influence of social support and cognitive impairment on HRQL in community dwelling HF patients (n = 104) without diagnosed dementia. Patients were aged mean 80.93 years (SD 11.01) and were classified as New York Heart Association Class 1/II (45%) or III/IV (53%). Age, social support and cognition had important independent effects. Younger people had the most negative effects of HF in all areas of HRQL: emotional (B = −0.32), physical (B = −0.44) and overall (B = −1). Well-supported patients (general
Correspondence: Robyn Gallagher, Sydney Nursing School and Charles Perkins Centre, University of Sydney, Sydney, NSW 2006, Australia. E-mail: [email protected] doi:10.1111/ijn.12402
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social support) had the least negative effect from HF on HRQL: emotional domain (B = −4.62) and overall (B = −11.72). Patients with normal cognition had more negative impact of HF on HRQL: physical domain (B = 5.51) and overall HRQL (B = 10.42). A clearer understanding of the relationships between age, social support and cognition and the effect on the impact of HF on HRQL is needed before interventions can be appropriately developed. Key words: age, cognitive impairment, health-related quality of life, heart failure, social support.
INTRODUCTION Patients who have heart failure (HF) experience multiple and progressive symptoms, which can reduce function, increase disability and impair health-related quality of life (HRQL).1 Improving or at least minimizing the impact on HRQL of HF is an important goal for HF patients. Understanding and investigating factors that influence HRQL are essential to this process. Multiple factors have been identified that influence HRQL in this population, including severity of symptoms,2,3 age, gender and comorbidities,3 and psychological distress.4 However, the relationship between other important factors such as cognitive impairment and social support and HRQL has had limited investigation, despite the potential for these factors to be amenable to, or supplemented by, interventions and therefore minimize impact.5–8 Cognitive impairment is prevalent in HF patients, occurring in 25–50% of this population, and is associated with worse patient outcomes, including mortality.9 Impairment associated with HF has a negative effect on several areas, most notably working memory, memory and executive function,10 self-care, and activities of daily living in HF patients.11 HF patients themselves could notice their impairment, and this impairment, even when mild, negatively affects their daily lives.12 However, the influence of cognitive impairment on HRQL is less clear. A recent study of 249 HF patients found when HF severity, age and depressive symptoms were controlled for, the total recall memory component of cognitive function was an independent predictor of HRQL, but the contribution of this cognitive area was minimal.10 Furthermore, no other area of cognitive function had an independent influence on HRQL. Similarly, another study reported that cognitive impairment did not have an independent effect on HRQL when daytime sleepiness was taken into account.13 Counterintuitive results are also reported, with patients who had the most severe cognitive impairment (following cardiac arrest) reporting better HRQL than patients who were less impaired.14 A potential © 2015 John Wiley & Sons Australia, Ltd
explanation for this unexpected result is the role that social support might play in compensating for deficits so that ultimately HRQL is less affected, although this could not be determined in these studies as social support was not included in the analyses. However, when cognitive impairment is present, HF patients’ social support could provide a crucial buffer to help manage medications and treatments and detect worsening symptoms as well as support other aspects of patients’ day-to-day lives.15 Social support is a multidimensional concept incorporating physical and emotional components, the quality of relationships16 and, potentially, the support provided for a specific condition such as HF. Social support is known to influence many important outcomes for HF patients including mortality,17 admission to hospital,18 anxiety and depression,19,20 and self-care.21,22 Recent studies of HF patients indicate that social support was associated with HRQL even after controlling for age, gender, symptom severity23 and depressive symptoms,24 in both the short and longer term.25 However, other studies have failed to show this association,26–28 which might in part be due to the complex nature of social support. HF-specific support has been found to influence HF self-care when all of these aspects and HF patients’ perceptions of their carers’ HF knowledge and expertise are included in the measure.22 Despite the likely run-on effect of HF-specific support on minimizing the impact of HF on HRQL, no study has distinguished between the relative influence of social support and HF-specific social support. This study aimed to determine the levels of cognitive impairment, social support and HF-specific support and the independent influence on the impact of HF on HRQOL in HF patients after controlling for age, disease severity, gender and comorbidity. The study hypotheses were that after controlling for the influence of age, disease severity, gender and comorbidity on HRQL, (i) cognitive impairment would negatively affect HRQL, and (ii) social support and (iii) HF-specific support would positively affect HRQL in HF patients.
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METHODS Design The study used a descriptive correlational design.
fatigue, palpitations, dyspnea or angina with any effort) to Class IV (fatigue, palpitations, dyspnea or angina at rest). Validity and reliability of the NYHA classification system have been reported previously in HF patients.29
Setting and sample Participants included patients registered with the Management of Cardiac Function (MACARF) HF specialist nurse home visit programme. Patients registered with this programme have a diagnosis of HF and are community dwelling. Patients were eligible for the study if they were newly registered on the home visit programme, able to understand and respond to written and spoken English sufficiently for the consent processes, had no diagnosed major cognitive or psychiatric disorder and did not require palliative or end of life care, and had sufficient vision and hearing to undertake the Montreal Cognitive Assessment Tool (MoCA). Sample size was estimated at 103, to detect an effect size of 0.15, with an alpha level of 0.8, seven predictors and P level of 0.05 (www.danielsoper.com).
Data collection Clinical and sociodemographic data were extracted from both the medical records and asked of the patients themselves. This data included the participants’ age, gender, marital and employment status, education level, whether the person lived alone or with other people, New York Heart Association (NYHA) functional class and comorbid conditions.
HRQL HRQL specific to HF was measured using the Minnesota Living with Heart Failure Questionnaire.29 This questionnaire contains 21 items addressing various aspects of the impact of HF on patients being able to live their lives the way they wanted to in the last month. There are three subscales, emotional (five items), physical (nine items) and general (seven items), and participants respond to the questions using a 5-point scale, from no impact (0 points) to very much impact (5 points). Scores are achieved for the subscales and the total scale by summing the points, for a potential score of 0 (no impact) to 105 (very much impact). The validity of this scale has been established in HF patients.25 In the current study, the instrument showed high internal consistency reliability (Cronbach’s α = 0.91).
HF severity The severity of HF symptoms was measured using the NYHA classification system. Scores range from Class I (no
Comorbidity The presence of comorbid conditions was measured using the Charlson Comorbidity Index, which includes 12 conditions weighted for severity at 1, 3 or 6 points. A higher score represents more and/or more severe comorbid conditions. Scores on the Charlson Comorbidity Index are predictive of mortality within 12 months.30
Cognitive function Cognitive impairment was assessed using the MoCA, a brief screening tool specifically designed to detect mild cognitive impairment.31 It is made up of subscales that are designed to assess visuospatial abilities, language, memory, executive functioning, attention, concentration and working memory, and orientation. Scores were graded for each task for a potential total score of 30. When education level was < 12 years, an additional mark was added to the final score. Patients who scored > 22 were considered to have no impairment of cognition (or normal cognition), and patients scoring ≤ 22 were considered to have impaired cognition.12 In previous studies,31,32 the MoCA has reported good internal consistency (Cronbach’s α = 0.81–0.84) and in a more recent study at Cronbach’s α of 0.77.
Social support Perceived social support was measured by the Medical Outcomes Study (MOS) Social Support Survey.33 The tool has 19 items, which are grouped as subscales related to emotional/informational support (nine items), tangible support (four items), affectionate support (three items), positive social interaction (three items) and one further item on social interaction. Participants respond to each item using a 5-point scale ranging from 0 (none of the time) to 5 (all of the time) indicating how often the specific type of support was provided to them whenever they needed it. The mean of each subscale was calculated as well as the sum of all scores, which was then converted to a percentage. Internal consistency reliability was high (Cronbach’s = 0.95) indicating a redundancy of items, and comparable to a recent study by Robitaille et al.34 which also reported a high internal consistency © 2015 John Wiley & Sons Australia, Ltd
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(Cronbach’s α = 0.90–0.97); however, this issue was not considered to outweigh the other benefits of the MOS for the current study.
HF-specific social support Social support specific to HF was determined by a six-item questionnaire adapted from the COACH study.22,35 This questionnaire was developed to identify the HF patients’ main supporter and the quality of social support for HF that the patient perceives this person provides them. The participant identifies the person who provides them the most support; if participants are not able to identify someone, the questions that follow cannot be answered. The questionnaire includes five items which measure the patient’s perception of the adequacy of their carer’s HF knowledge and attention to their HF symptoms (yes = 2/ no = 0 answer), provision of practical and emotional support (no/low = 0 or moderate/high = 2 answer), and the quality of their relationship (0–10 scale). For the final question, participants who had scores of 9 or less were scored 0 (indicating that patients perceived the relationship between themselves and their carer to be low), whereas a perfect score of 10 was given a score of 2 (indicating that the patient perceived the quality of the relationship with their carer to be high). All scores were then totalled; scores of 10 indicated that patients perceived a high level of support overall from their carers. The scale has been reported to have internal consistency reliability (Cronbach’s α = 0.96),22 whereas in the current study reliability was lower (Cronbach’s α = 0.62).
Procedure Patients were screened for eligibility by the MACARF home visit programme during hospital admission, and eligible patients were approached and informed of the study. Once consent was obtained, sociodemographic and clinical information was collected from the medical record, and the survey was administered during the first routine home visit by the MACARF nurses. All study nurses participated in a training workshop for administering the MoCA and practice interviews to ensure a standardized approach to data collection was used.
were used to describe the sample characteristics, levels of social support, prevalence of cognitive impairment and the impact of HF on HRQL. Correlations and Pearson’s r were used to assess relationships between continuous predictor variables and HRQL. Linear regression analyses were used to determine the independent predictors of HRQL emotional and physical domains and overall HRQL. Variables entered into the analyses included age, gender, HF severity, comorbidity, social support, HF-specific support and cognitive status score. As the scores for social support, HF-specific support and cognitive status were not normally distributed, these scores were dichotomized on the median (for social support) or predetermined thresholds outlined above (HF-specific support and cognitive status) for the regression analyses. Missing data were treated pair-wise resulting in a final sample size of 99 for these analyses. The critical level was set at P < .05.
RESULTS Patients in the sample were aged an average 80.65 years (SD 11.52), with approximately half the participants being male (54%) and living alone (52%) as detailed in Table 1. Severity of HF symptoms were classified as NYHA Class I/II (45%) or III/IV (52%). The mean cognitive status score for the sample was 24.64 (SD 3.38), and cognitive impairment was present in 22% (score < 22 on MoCA) as illustrated in Table 2. Scores on cognitive status were poorest for the subdomains of visual processing and delayed recall relative to the potential top score for that subdomain. The overall mean social support score for the sample was 78.83 (SD 21.64), with affectionate support having the highest mean score of all the support subscales. Of those patients who had carers (98%), the majority (70%) reported a high level of HF-specific support; the lowest proportion of HF-specific support was for having a high-quality relationship with the carer (72%). The HRQL score for the emotional domain was a mean 7.33 (SD 6.98) from a potential range of 0–25, indicating a low impact of HF, and for the physical domain 25.31 (SD 10.18), indicating a moderate impact of HF on HRQL (potential range 0–80). Overall, HF resulted in HRQL that was moderately poor at mean score of 42.4 (SD 21.92) from a potential range of 0–105.
Data analysis
Correlations
Data were analysed using the ibm spss v. 22 (IBM Global New York, New York, USA). Frequencies and descriptive statistics including means, medians and standard deviations
Table 3 illustrates associations between age, cognitive status, HF-specific support, social support and the impact of HF on HRQL overall and subdomains. Age was slightly
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Table 1 Sample socio-demographic characteristics (n = 103) Characteristic
Number
%
Male
56
54
Education level < 12 years Year 12 only University/TAFE Employed/seeking employment Primary language: English Married/de facto Living alone
53 20 27 8 97 48 54
51 19 26 8 94 47 52
Carer Spouse Daughter Son Multiple family members Friend, neighbour or other No one (self)
35 27 8 24 5 2
34 26 8 24 5 2
46 54 4.83
45 52 1.40
New York Heart Association Class I/II III/IV Charlson Comorbidity Index, mean, standard deviation
related to increased cognitive impairment and low to moderately correlated with reduced impact of HF on HRQL. Increased cognitive impairment was correlated with less HF-specific support and less impact of HF on HRQL. Increased social support was highly correlated with increased HF-specific support. HF severity (NYHA) was not associated with either type of support (data not shown).
Predictors of HRQL The independent predictors of the impact of HF on HRQL and the emotional and physical domains of HRQL were determined using linear regression analyses. The three models developed explained 22% of physical HRQL, 25% of emotional HRQL and 27% of overall HRQL (Table 4). Age independently predicted both emotional and physical domains as well as the overall impact of HF on HRQL so that younger people had more negative affects from HF on HRQL than older people. Social support independently predicted the emotional domain and overall HRQL so that patients with a high level of social support reported less
negative effect of HF on HRQL. Cognitive status predicted both the physical domain and overall HRQL so that patients who were not cognitively impaired were more negatively affected from HF in HRQL in comparison with patients who did have an impairment.
DISCUSSION In this sample of older HF patients who did not have a dementia diagnosis and were living at home following a recent hospital admission, the impact of HF resulted in HRQL that was moderate–poor, and the most negative impact was experienced by patients who were younger, had less social support and less cognitive impairment. The potential buffering effect of older age and general social support on the impact of HF on HRQL is consistent with previous reports.3–5,22,24,26 However, this study helps distinguish the effects of different types of support and the potential interaction with cognitive impairment. The influence of cognitive status on the impact of HF on HRQL might be complex and requires further exploration. Cognitive impairment is common in HF patients and often goes undetected.8 One in five of the current study sample screened positive for cognitive impairments despite the lack of a related diagnosis. Without this screening, it is likely that impairment in cognition would not have been detected. It is not clear why the presence of cognitive impairment was a predictor of less negative impact of HF on HRQL, given that patients with better cognition would be expected to manage self-care more ably and therefore experience less negative effects from HF on HRQL. One other study also had this apparently counterintuitive finding; however, the sample in that study had also experienced a traumatic event in cardiac arrest.14 Other explanations are possible including that cognitive impairment might reduce insight. The current study provides an indication that HF-specific support might offset the effects of decreased cognition as evidenced by the association between poorer cognition and higher HF-specific support; however, this connection might not ultimately decrease the impact of HF on HRQL. Supporting changes in cognitive status is important in HF patients, whose cognitive status might change over time and with illness exacerbations.35 For partners/ families of HF patients, this implies the need for regular, unintrusive monitoring of cognitive status and accommodating changes in multiple areas of life. These efforts might be HF specific, for example, through support for medication adherence and detection of symptom changes, © 2015 John Wiley & Sons Australia, Ltd
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Table 2 Cognition, social support and HRQL characteristics (n = 103) Cognitive status
Mean
Visual processing Naming Attention Language Abstraction Delayed recall Total Cognitive Status Score (potential range 0–30)
3.63 2.66 5.41 2.49 1.77 2.30 24.64
Emotional/informational support Tangible support Affectionate support Positive social support Overall Score (Potential range 16–100)
SD
Range
Median
1.24 0.64 1.12 0.75 0.53 1.54 3.38
0–5 0–3 1–6 0–3 0–2 0–5 12–30
4 3 6 3 2 2 25
4.07 4.17 4.47 4.05 78.83
0.98 1.11 0.92 1.07 21.64
1–5 1–5 1–5 1–5 16–100
4.5 4.8 5 4 85.53
HF-specific support
Number
%
Adequate HF knowledge Pays attention to HF symptoms Provides adequate practical support Provides adequate emotional support High-quality relationship with carer High level of support (Full points)
92 94 97 98 73 71
90 92 95 96 72 70
Impact of HF on HRQL
Mean
SD
Range
Median
Emotional (potential range 0–25) Physical (potential range 0–80) Total (potential range 0–115)
7.33 25.31 42.40
6.98 10.18 21.92
(0–25) (0–45) (0–83)
5 26 39
Social support
N/A N/A N/A N/A N/A N/A
HF, heart failure; HRQL, health-related quality of life; N/A, not applicable.
or more generally through bill paying and diary reminders. However, the role of partners and family in supporting HF patients who have cognitive impairment needs further investigation as no influence on the impact of HF on HRQL was found in the current study, and given the complexity of the issues, it would benefit from in-depth qualitative investigation. In fact, cognition might be a side issue compared with the more important role of social support. The effects of social support are likely to be multifactorial and complex, and it is important to distinguish and understand the effects of different types of support. In this study, participants perceived that they were well sup© 2015 John Wiley & Sons Australia, Ltd
ported as they reported high levels of social support and support for HF from their family/friends. However, our study results indicate that it might be general social support and not HF-specific support that lessens the negative impact of HF on HRQL. Although the positive effects of general social support were expected, the lack of influence of HF-specific support on the impact of HF on HRQL was unexpected. A previous study identified an association between HF-specific support and several aspects of self-care,22 so it was anticipated that this support would also influence HF-specific HRQL. There are multiple potential explanations for the apparent lack of influence of high levels of HF-specific
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Table 3 Correlation matrix of predictor variables: age, cognition, social and HF-specific support, and impact of HF on HRQL Characteristic
Support
Age Cognition Social HF specific Emotional Physical
Support Impact of HF on HRQL
Impact of HF on HRQL
Cognition
Social
HF specific
Emotional
Physical
Total
−0.21* — — — — —
−0.09 −0.09 — — — —
0.10 −0.21* .69** — — —
−0.27** 0.05 −0.18 −0.08 — —
−0.33** 0.23* −0.16 −0.13 0.62** —
−0.39** 0.16 −0.19 −0.14 0.89** 0.87**
* P = < 0.05; ** P = < 0.01. HF, heart failure; HRQL, health-related quality of life. Table 4 Predictors of influence of HF on HRQL (n = 99) Predictors
Emotional HRQL B†
Age Not cognitively impaired High social support High HF-specific support Male gender NYHA Comorbidities Constant Model statistics †
SE‡
Physical HRQL r§
P
−0.32 0.06 −0.30 < 0.01 2.39 1.56 0.14 0.12 −4.62 1.55 −0.26 < 0.01 1.48 1.63 0.09 0.39 −1.17 1.35 −0.05 0.38 −1.8 1.19 −0.14 0.18 0.38 0.51 0.09 0.45 36.92 F = 4.15, P = < 0.01, r2 = 0.25
B†
SE‡
Overall HRQL r§
B†
P
−0.44 0.09 −0.34 < 0.01 5.51 2.22 0.23 0.01 −3.17 2.21 −0.15 0.16 −0.1 2.33 0.05 0.97 −3.32 1.92 −0.14 0.08 0.07 1.70 −0.03 0.97 0.36 0.73 0.20 0.62 58.54 F = 3.55, P = < 0.01, r2 = 0.22
SE‡
r§
P
−1.0 0.19 −0.41 < 0.01 10.42 4.60 0.21 0.03 −11.72 4.58 −0.25 0.01 0.57 4.82 0.06 0.91 −5.4 3.97 −0.10 0.18 −3.09 3.52 −0.08 0.44 0.86 1.52 0.16 0.58 32.12 F = 4.68, P < 0.01, r2 = 0.27
Unstandardized Beta. ‡ Standard Error. § Partial correlation. HF, heart failure; HRQL, health-related quality of life.
support. One possible explanation is that the impact of HF on HRQL is a self-rated measure, where people rate the reality of their lives against their expectations of life for their life stage and circumstances.16 Although this means that those with preserved cognition could be more aware and distressed by the limitations arising from HF and younger patients, who also had poorer HRQL in the study, and might find the reality of the lives with HF a stark contrast to their unaffected peers, other influential factors are present. However, our results also suggest that those without cognitive impairment do not receive more social support than those who are impaired, whereas they receive more HF failure-specific support, which does not reduce the impact of HF on HRQL and is therefore less useful to them in this respect. It was also interesting to
note that HF severity was not related to the level of support, when it was expected that support would increase with severity. On the other hand, assessments were conducted early after discharge from their first HF admission at the initial home visit so patients might have been unable to realistically gauge the level of HF-specific support they received. It is also possible that the apparent differences in influence on the impact of HF on HRQL of social support and HF-specific support are an artefact of the use of measures with different levels of variability. The social support measure had 19 items, whereas the HF-specific support measure had five, although scores from both measures were ultimately dichotomized for the regression analyses reducing the likelihood of this effect. Finally, family members were almost always present at © 2015 John Wiley & Sons Australia, Ltd
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interviews which might have promoted more positive ratings by patients. Regardless of these considerations, the goal of improving HRQL or at least reducing the negative impact of HF on HRQL is important for HF patients, and fostering social support might help, and therefore, promotion of social support is included in international guidelines for HF self-care.36 The patients in the current study perceived a high level of support so it is not completely clear in what area support can be promoted or what effect this promotion would achieve. Indeed, interventions addressing this area have had limited success. A recent review found that most current models of chronic illness care inadequately addressed the roles and influences of family in patient self-care, even though family members are well suited to provide effective support, and family support is associated with improved outcomes.37 More in-depth understanding is required of different types of social support and patient and family members’ perceptions of the roles they play. Strategies are required which directly address family member roles in HF illness management and seek to give family members the tools and skills they need to carry out these roles, including support for failing cognition.
Limitations
The variance explained in all models was < 30% so other unmeasured variables, such as symptom perception and depressive symptoms, might be equally or more important in understanding differences in the impact of HF on HRQL.26 Results of the study might not be representative of HF patients in general as the sample only includes patients eligible for home support. Furthermore, the measure of HF-specific support requires further development to determine the accuracy of the relative contribution of the subcomponents, including the quality of the relationship with the carer. The current study was crosssectional only so influences noted might be bidirectional.
CONCLUSIONS AND IMPLICATIONS FOR PRACTICE The impact of HF on HRQL in HF patients living at home is moderate and indicates a population likely to need support in addition to that being provided by family and friends. Screening for social support deficits and cognitive impairment might be an important component of HF patient care and should be included in routine practice. Strategies are required to garner social support, particularly for younger people and those with intact cognition. © 2015 John Wiley & Sons Australia, Ltd
The influence of cognitive status on the impact of HF on HRQL and the interaction with support provided by family members needs further investigation, particularly across time. Available caregivers need to be supported in their efforts.
ACKNOWLEDGEMENTS The authors acknowledge Patrick Gallagher for manuscript preparation and editorial assistance. The NSW Health Nursing and Midwifery Office Innovations Scholarship supported this study.
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