The Association Between Self-reported Sleep Quality and Self-care in Adults With Heart Failure: A Cross-sectional Study : Journal of Cardiovascular Nursing

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The Association Between Self-reported Sleep Quality and Self-care in Adults With Heart Failure

A Cross-sectional Study

Spedale, Valentina PhD, MSN, RN; Fabrizi, Diletta PhD, MSc, RN; Rebora, Paola PhD; Luciani, Michela PhD, RN; Alvaro, Rosaria MSN, RN, FAAN, FESC; Vellone, Ercole PhD, RN, FAAN, FESC; Riegel, Barbara PhD, RN, FAAN, FAHA; Ausili, Davide PhD, MSN, RN

Author Information

Valentina Spedale, PhD, MSN, RN Nurse Educator Undergraduate Nursing Degree, Department of Medicine and Surgery, University of Milano - Bicocca_ ASST Monza, Ospedale S.Gerardo, Monza, Italy.

Diletta Fabrizi, PhD, MSc, RN PhD Student, Department of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.

Paola Rebora, PhD Associate Professor of Medical Statistics, Department of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.

Michela Luciani, PhD, RN Postdoctoral Fellow in Nursing, Department of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.

Rosaria Alvaro, MSN, RN, FAAN, FESC Professor of Nursing, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.

Ercole Vellone, PhD, RN, FAAN, FESC Associate Professor of Nursing, Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.

Barbara Riegel, PhD, RN, FAAN, FAHA Edith Clemmer Steinbright Professor of Gerontology, University of Pennsylvania School of Nursing, Philadelphia.

Davide Ausili, PhD, MSN, RN Associate Professor of Nursing Science, Department of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.

The MOTIVATE-HF was funded by the Center of Excellence for Nursing Scholarship, Rome, Italy, which is a no-profit organization.

The authors have no conflicts of interest to disclose.

Correspondence Valentina Spedale, PhD, MSN, RN, Department of Medicine and Surgery, University of Milano - Bicocca_ ASST Monza, Ospedale S. Gerardo, via Pergolesi, 33 - 20900 Monza, Italy ([email protected]).

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.jcnjournal.com).

The Journal of Cardiovascular Nursing 38(3):p E98-E109, 5/6 2023. | DOI: 10.1097/JCN.0000000000000929

Abstract

Heart failure (HF) is highly prevalent worldwide, with high mortality, morbidity, and cost of care.1,2 Despite decades of attention to this condition, the prevalence of HF remains approximately 1% to 2% of the adult population in developed countries.2 Specifically, the prevalence in the United States is approximately 2.5%,3 and in Europe, it is approximately 2%,4 rising to 10% or greater among people aged 70 years.2 Patients with HF experience numerous symptoms that affect their quality of life,3 including dyspnea, fatigue, poor exercise tolerance, swelling,5 difficulty sleeping, and daytime sleepiness.2 Up to 70% of people with HF develop sleep-related disorders, such as insomnia and sleep apnea.6 Factors that interfere the most with sleep are nocturia, cardiac symptoms such as nocturnal dyspnea, coughing and palpitations, HF itself, and the demands of daily activities.7 Anxiety and nocturnal rumination are also common.8 Other factors associated with sleep-related disorders in HF include medications with sleepiness or insomnia as an adverse effect and depression.9 All of these factors and sleep-related disorders strongly affect sleep quality.10

Sleep quality is a simple term for a complex phenomenon that is difficult to define and measure objectively.11 The term is used without consensus and sometimes is used to reflect total sleep time, sleep onset latency, degree of sleep fragmentation, total wake time, sleep efficiency, and sometimes sleep-disrupting events such as spontaneous arousals or apneic events.12 Patients with HF experience many of these issues, and thus, they often reported poor sleep quality.13 Poor sleep quality contributes to excessive daytime sleepiness, described as the propensity to sleep during the day with difficulty maintaining the desired level of wakefulness.14 Poor sleep quality and daytime sleepiness in patients with HF are associated with mood disturbances,15 poor quality of life,16 motor impairment,10 nonspecific physical weakness,10 reduced productivity,17 and cognitive inefficiency.18 It has also been argued that people who sleep poorly may be unable to perform adequate self-care.19 In fact, poor sleep may reduce cognitive functions such as memory, attention, executive function, and psychomotor speed, skills needed to perform adequate self-care.20

Self-care is defined as “a naturalistic decision-making process involving the choice of behaviors that influence actions that maintain physiologic stability, facilitate the perception of symptoms, and direct the management of those symptoms.”21(p226) The theoretical framework used to define the concept of self-care is the Situation-Specific Theory of Heart Failure Self-Care, which originally22 included 2 dimensions: self-care maintenance and self-care management. In the updated version21 of the theory, a new dimension reflecting the process of symptom perception—a specific form of self-care monitoring—was added. Self-care maintenance is defined as those behaviors used by patients to maintain physical and emotional stability. Symptom perception involves detecting physical sensations and interpreting their meaning.21 Symptom perception is the link between self-care maintenance and self-care management. Self-care management includes actions that patients perform in response to signs and symptoms detected.21 These 3 dimensions are influenced by self-care confidence, defined as “the confidence that one has in the ability to perform a specific action and to persist in performing that action despite barriers.”23(p201) Self-care confidence is task specific, reflecting both confidence and persistence despite obstacles, and thus reflects self-efficacy.23

Adequate self-care maintenance and self-care management improved health-related quality of life in adults with HF.24 Furthermore, in a study by Lee et al,25 patients who were more engaged in self-care management (patients who reported a self-care management score greater than the sample mean) had less than half the risk of all-cause mortality, hospitalization, or emergency room admission compared with patients who were less engaged in self-care management (patients who reported a self-care management score less than the sample mean). However, an international study26 that explored important HF self-care behaviors, such as medication adherence, exercise, weight monitoring, annual flu vaccine, and sodium restriction, showed that self-care behaviors are suboptimal in patients with HF and need to be improved worldwide. Self-care is dynamic and requires complex knowledge and skills as problem solving and decision making.23

Poor sleep quality may impact problem solving and decision making by impairing active cognitive processes such as planning, coping, and problem solving.27 In individuals with poor sleep quality, these deficits may manifest, particularly in behaviors that require creative solutions to problems that are complex or lack sufficient information. The energy required to analyze unfamiliar health challenges or to sustain an extended chain of logical thought may be particularly reduced in individuals with poor sleep quality.27 Thus, poor sleep quality may influence the motivation and ability of people with HF to engage in self-care maintenance and self-care management behaviors.27 In addition, in patients with poor sleep quality, compared with those with good sleep quality, more visits to the emergency department and more hospitalizations occurred, with an increased risk of death.19

Results of previous studies have shown an association in adults with HF between sleep quality or excessive daytime sleepiness and self-care behaviors such as medication adherence, daily monitoring of weight and ankle swelling, daily physical activity, monitoring of salt and fluid intake, trying to avoid getting sick, and keeping doctor or nurse appointments.28–33 However, as reported by a recent systematic review,34 the number of studies describing the association between sleep and self-care is limited. Not all the studies included in the review34 found a significant association between sleep and self-care. Furthermore, measures used were heterogeneous. In fact, authors of some studies assessed daytime sleepiness, whereas others assessed sleep quality; authors of some studies assessed a single self-care behavior such as medication adherence, whereas others assessed self-care as a decision-making process.34 Thus, there is a lack of solid evidence to conclude that sleep quality is associated with HF self-care.34 In addition, no authors of known studies evaluated the association of individual sleep quality components (ie, subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction) with self-care maintenance, self-care management, and self-care confidence. Evaluating the association of individual sleep components might be important because not all sleep components may influence self-care in the same way. Knowing the association between global quality of sleep, individual sleep quality components, and self-care maintenance, self-care management, and self-care confidence in patients with HF can improve the clinical evaluation of those factors representing a risk for self-care. Furthermore, having this information could facilitate the ability of health professionals to tailor effective interventions to improve HF self-care.

To address the 2 previously mentioned gaps, the aims of this study were (1) to evaluate the association between global sleep quality and self-care maintenance, self-care management, and self-care confidence in adults with HF and (2) to evaluate the association between specific sleep quality components (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction) and self-care maintenance, self-care management, and self-care confidence in adults with HF.

Methods

Study Design

This cross-sectional study was a secondary analysis of baseline data from the “motivational interviewing to improve self-care in heart failure patients” (MOTIVATE-HF) study, a 3-arm randomized controlled trial conducted on a sample of 510 patients with HF and their caregivers.35 In this study, only patients' data were considered for the analysis.

Study methods were described previously35 and are briefly summarized here. The primary aim of the parent study35 was to evaluate the effect of motivational interviewing in improving self-care maintenance in patients with HF. The results of the primary end point have been previously reported.31

Sample: Recruitment, Eligibility Assessment, and Size

In the parent study, adults with HF were recruited from hospitals, outpatients, and community settings across Italy between June 2014 and October 2018. Patients with HF were assessed for study eligibility based on the following inclusion and exclusion criteria: (1) a confirmed diagnosis of HF according to international guidelines2; (2) New York Heart Association functional classes II to IV (mild to severe symptoms); (3) a score of 0, 1, or 2 in at least 2 items of the self-care maintenance or self-care management scales of the Self-Care of Heart Failure Index (SCHFI v6.2)36; (4) willingness to participate. Exclusion criteria were (1) severe cognitive impairment evaluated with a score of 0 to 4 on the 6-item screener,37 (2) acute coronary syndrome event during the previous 3 months, (3) living in a residential setting (eg, nursing home) where self-care is not typically performed, and (4) unwillingness of the caregiver to participate in the study. Data from all patients who provided self-reported sleep quality at enrollment (n = 498, 98%) were used in this study.

Measurements

The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate global sleep quality and individual components of sleep quality. The PSQI contains 19 self-rated questions, which generate an overall score and 7 component scores11: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction during the previous month.11 Subjective sleep quality assesses the quality of sleep perceived by the person.38 Sleep latency measures the time taken to fall asleep after lights out.38 Sleep duration reports the total amount of sleep obtained during the nocturnal sleep episode.39 Habitual sleep efficiency is the ratio of total sleep time to time in bed (at least 85% of the total time).40 Sleep disturbance measures how many times and why one has awakened after the onset of sleep.41 Use of sleep medications evaluates whether and how often the person takes drug/s to fall asleep or stay asleep.42 Finally, daytime dysfunction assesses how often the person has problems staying awake while driving, eating, or engaging in social activities, and how much of a problem it is for the person to keep up the enthusiasm to do things.41 Each item of the PSQI has a range of 0 to 3 points: a score of 0 indicates no difficulty, and a score of 3 indicates severe difficulty. The 7 component scores (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction) are combined into 1 global score, with a range of 0 to 21 points (0, no difficulty; 21, severe difficulty); a score greater than 5 indicates poor self-reported sleep quality.11

To assess self-care in patients with HF, we used the SCHFI v6.2.36 This version of the instrument is based on the original Situation-Specific Theory of Heart Failure Self-care.22 It consists of 3 different self-report scales, namely, self-care maintenance, self-care management, and self-care confidence, each of which is used individually providing a specific score. It is a 22-item instrument used to assess self-care in patients with HF. Items use a 4-point Likert scale. Self-care maintenance items (10) assess daily monitoring and treatment adherence behaviors (eg, monitoring weight and taking medications as prescribed). Self-care management items (6) assess symptom perception, the choice of the treatments used by the patient, and the ability to evaluate the effectiveness of the treatments implemented. Items measuring self-care confidence (6) address self-efficacy or the patient's perceived confidence in the ability to perform self-care. The raw scores obtained in the individual scales are standardized 0 to 100. Higher scores reflect better self-care. A score of 70 points or greater for each standardized SCHFI v6.2 scale defines adequate self-care.36

In addition to the primary measures of sleep and self-care, sociodemographic and clinical characteristics were collected from the medical records: gender, age, nationality, marital status, school education, occupation, financial status, tobacco use, drinking habits, HF etiology, New York Heart Association class, oxygen therapy, and body mass index. Furthermore, anxiety and depression were measured by the Hospital Anxiety and Depression Scale,43 somatic perception was measured by the Heart Failure Somatic Perception Scale v.3,44 and cognition was measured by the Montreal Cognitive Assessment.45

Statistical Analysis

Sociodemographic and clinical data were described with frequencies and percentages when variables were categorical and with medians and quartiles when they were continuous. For descriptive purposes, we split the sample using the median of the PSQI total score, because the vast majority of the scores exceeded the 5-point cutoff score. We compared sociodemographic and clinical data using χ2 test or Mann-Whitney U test, as appropriate.

To assess the association between global sleep quality and self-care maintenance, management, and confidence, after checking the assumption of linearity, multivariable linear regression models were performed adjusting for gender, age, New York Heart Association class, comorbidity, anxiety and depression, somatic perception, and cognition.

To assess the association between the specific components of sleep quality and self-care, a 2 stage-process was performed. First, raw associations were estimated between each of the 7 components of self-reported sleep quality and self-care maintenance, management, and confidence (Supplemental Digital Content 1, Table 1, https://links.lww.com/JCN/A165). Second, sleep components that were significantly associated with at least 1 self-care dimension were tested, after checking the assumption of linearity, in a multivariable linear regression model adjusting for gender, age, New York Heart Association class, comorbidity index, anxiety, depression, somatic perception, and cognition. A complete case analysis was performed because of the low percentage (<5%) of missing data.

Ethical Approval and Informed Consent

The randomized controlled trial complied with the Declaration of Helsinki, was approved by the institutional review board of the University of Rome “Tor Vergata” (approval number: 121/13), and was registered at ClinicalTrials.gov (identifier: NCT02894502).

In the parent study, informed consent was obtained from all individual participants included in the study.

Results

Of the 510 patients who were enrolled and randomized in the MOTIVATE-HF study, 498 had complete PSQI and SCHFI v6.2 scores. Most patients were male (58.0%, n = 289), 65 years or older (75.5%, n = 376), and married (61.4%, n = 306); had a low level of formal education (elementary or middle school: 67.5%, n = 336); and were retired (76.4%, n = 379). The most frequent etiology of HF was ischemic (33.8%, n = 165), and most of the sample was in New York Heart Association class II (61.7%, n = 305). Almost 20% of patients received oxygen therapy (17.8%, n = 87). Most patients (53.0%, n = 211) had a body mass index of 30 or higher. Sociodemographic and clinical characteristics of the overall sample and by sleep quality score as measured by the PSQI are shown in Table 1.

TABLE 1 - Sociodemographic and Clinical Characteristics of the Overall Sample and by Sleep Quality Score as Measured by the Pittsburgh Sleep Quality Index (N = 498)
Variable Total PSQI Total ≤ 12 a PSQI Total > 12 P
n 498 273 225
Gender
 Female 209 (42.0%) 93 (34.1%) 116 (51.6%) <.001
Age, median [first to third quartile] 75 [65–82] 71 [62–80] 78 [69–83] <.001
Nationality
 Italian 494 (99.2%) 271 (99.3%) 223 (99.1%) .396
Marital status
 Unmarried 23 (4.6%) 15 (5.5%) 8 (3.6%) <.001
 Married 306 (61.4%) 191 (70.0%) 115 (51.1%)
 Divorced/separated 20 (4.0%) 7 (2.6%) 13 (5.8%)
 Widowed 149 (29.9%) 60 (22.0%) 89 (39.6%)
School education
 Elementary 205 (41.2%) 103 (37.7%) 102 (45.3%) .365
 Middle school 131 (26.3%) 74 (27.1%) 57 (25.3%)
 Professional school 35 (7.0%) 18 (6.6%) 17 (7.6%)
 High school 92 (18.5%) 56 (20.5%) 36 (16.0%)
 Degree 35 (7.0%) 22 (8.1%) 13 (5.8%)
Occupation
 Worker 10 (2.0%) 4 (1.5%) 6 (2.7%) .026
 Employee 33 (6.7%) 24 (8.8%) 9 (4.0%)
 Freelance 22 (4.4%) 17 (6.2%) 5 (2.2%)
 Retired 379 (76.4%) 201 (73.6%) 178 (79.1%)
 Other 52 (10.5%) 27 (9.9%) 25 (11.1%)
Financial status
 Not enough income 22 (4.4%) 11 (4.0%) 11 (4.9%) .026
 Just enough income 399 (80.1%) 209 (76.6%) 190 (84.4%)
 More than enough income 77 (15.5%) 53 (19.4%) 24 (10.7%)
Smoking habit
 Yes 56 (11.2%) 32 (11.07%) 24 (10.07%) .819
Drinking habit
 Yes 85 (17.1%) 55 (20.1%) 30 (13.3%) .0590
Heart failure etiology
 Ischemic 165 (33.8%) 92 (33.7%) 73 (32.4%) .368
 Nonischemic 118 (24.2%) 57 (20.9%) 61 (27.1%)
 Idiopathic 130 (26.6%) 79 (28.9%) 51 (22.7%)
 Other 75 (15.4%) 39 (14.3%) 36 (16.0%)
NYHA class
 II 305 (61.7%) 200 (73.5%) 105 (47.3%) <.001
 III 159 (32.2%) 63 (23.2%) 96 (43.2%)
 IV 30 (6.1%) 9 (3.3%) 21 (9.5%)
Oxygen therapy
 Yes 87 (17.8%) 35 (12.8%) 52 (23.1%) .003
BMI, median [first to third quartile] 27.1 [22.4–30.5] 27.14 [24.57–31.00] 27.10 [24.22–30.28] .469
Months from heart failure diagnosis, median [first to third quartile] 36 [18–84] 36 [16–74] 42.5 [24–87] .065
No. medications, median [first to third quartile] 6 [4–8] 6 [4–8] 7 [5–9] .044
Charlson Comorbidity Index, median [first to third quartile] 2 [2–4] 2 [1–3] 3 [2–4] <.001
Hospital Anxiety and Depression Scale (HADS), median [first to third quartile] 8 [4–11] 6 [3–9] 10 [6–12] <.001
HADS, median [first to third quartile] 8 [5–11] 7 [3–9] 10 [7–12] <.001
Heart Failure Somatic Perception Scale, median [first to third quartile] 26.00 [15.00–40.75] 20.00 [10.00–33.00] 35.00 [22.00–46.00] <.001
Montreal Cognitive Assessment, median [first to third quartile] 25.00 [20.00–28.00] 26.00 [22.00–28.00] 24.00 [17.00–26.75] <.001
Self-care maintenance (SCHFI v6.2), median [first to third quartile] 46.66 [36.66–56.66] 46.66 [40.00–56.66] 43.33 [33.33–53.33] .030
Self-care managementb (SCHFI v6.2), median [first to third quartile] 40.00 [30.00–50.00] 40.00 [30.00–50.00] 35.00 [25.00–50.00] .187
Self-care confidence (SCHFI v6.2), median [first to third quartile] 50.04 [33.36–66.72] 55.60 [38.92–66.72] 44.48 [33.36–61.16] .003
The number of missing data was as follows: 2 for age, 2 for occupation, 10 for heart failure etiology, 4 for NYHA class, 9 for oxygen therapy, 100 for BMI, 9 for months from heart failure diagnosis, 8 for the number of medications, 149 for self-care management, 1 for self-care confidence, and 7 for cognitive assessment.
Abbreviations: BMI, body mass index; NYHA, New York Heart Association; PSQI, Pittsburgh Sleep Quality Index; SCHFI, Self-Care of Heart Failure Index.
aThe sample was divided into 2 groups according to the PSQI global score, considering its median value in our data (12) as the cutoff score.
bThese results were obtained from a sample of 349 participants (149 missing). The answer to the self-care management questions was required only for those patients who had symptoms related to heart failure (trouble breathing and ankle swelling) in the last month.

The PSQI global score was almost entirely (98.8%, n = 492) higher than the 5-point cutoff score11 (median, 12; first-third quartile, 10–15), indicating poor self-reported sleep quality. For this reason, the suggested value was not useful in our sample, so we used the median value in analyses. The percentage of women (P < .001), older (P < .001) and widowed or divorced/separated (P < .001) patients was higher in those with higher PSQI global scores (>12), or poorer sleep quality, than in the group with a PSQI global score of 12 or lower. In those with poorer sleep quality, compared with those with lower PSQI global score, the percentage of subjects with higher New York Heart Association class (P < .001) and oxygen therapy (P = .003) was higher. Patients with a PSQI global score greater than 12 had a higher comorbidity index (P < .001), were more often anxious (P < .001) and depressed (P < .001), reported a higher symptom burden (P < .001), and had worse cognition (P < .001) than patients with lower PSQI global scores. Self-care maintenance and self-care management were inadequate in almost the entire sample (95.0%, n = 470, and 93.4%, n = 326, respectively). Self-care confidence was inadequate in most patients (79.9%, n = 397). Self-care maintenance behaviors with the lowest scores were physical activity, use of salt in the diet, and weight measurement. The poorest self-care management behaviors were recognizing HF symptoms, reducing salt and fluid intake, and taking extra diuretic medications. The lowest self-care confidence score was for being free of or relieving HF symptoms and evaluating the effectiveness of a remedy. The scores of individual items are shown in Supplemental Digital Content 2, Table 2, https://links.lww.com/JCN/A166. Patients with PSQI greater than 12 also had lower self-care maintenance (P = .030) and self-care confidence (P = .003) scores than patients with PSQI of 12 or lower.

Global sleep quality and self-care maintenance, management, and confidence scales were not associated with the multivariable regression models (Table 2). The raw associations between each sleep quality component and self-care maintenance, management, and confidence are shown in Supplemental Digital Content 1, Table 1, https://links.lww.com/JCN/A165. Figures 1 to 3 show by boxplots the distribution of self-care maintenance, self-care management, and self-care confidence by different levels of sleep latency, habitual sleep efficiency, use of sleep medication, and daytime dysfunction, which were the sleep quality components significantly associated with at least 1 self-care dimension.

TABLE 2 - Association Between Sleep Quality (Pittsburgh Sleep Quality Index) and Self-care Maintenance, Management, and Confidence (Self-Care of Heart Failure Index v6.2) by Multivariable Regression Models
Variable Self-care Maintenance Self-care Management Self-care Confidence
b
(95% CI)		 P b
(95% CI)		 P b
(95% CI)		 P
(Intercept) 26.434
(13.604–39.265)		 <.001 40.427
(21.040–59.813)		 <0.001 42.176
(23.279–61.072)		 <.001
PSQI total score 0.256
(−0.158 to 0.669)		 .2252 0.331
(−0.265 to 0.926)		 0.2757 0.364
(−0.245 to 0.973)		 .2412
Gender: male
(ref = female)		 −1.356
(−4.116 to 1.405)		 .3351 −0.437
(−4.390 to 3.516)		 0.8280 1.214
(−2.863 to 5.291)		 .5588
Age 0.232
(0.113–0.352)		 .0002 −0.051
(−0.236 to 0.134)		 0.5886 0.056
(−0.121 to 0.232)		 .5361
NYHA class 3
(ref = 2)		 1.369
(−1.793 to 4.530)		 .3955 0.492
(−3.850 to 4.834)		 0.8239 0.358
(−4.299 to 5.014)		 .8801
NYHA class 4
(ref = 2)		 9.150
(3.173–15.127)		 .0028 8.045
(0.181–15.910)		 0.0450 1.782
(−7.020 to 10.584)		 .6909
Charlson Comorbidity Index 0.623
(−0.050 to 1.295)		 .0694 −0.771
(−1.715 to 0.173)		 0.1089 0.297
(−0.694 to 1.288)		 .5559
Hospital Anxiety and Depression Scale (HADS) −0.616
(−1.044 to −0.188)		 .0048 0.347
(−0.270 to 0.963)		 0.2697 −0.094
(−0.724 to 0.536)		 .7692
HADS −0.386
(−0.822 to 0.050)		 .0829 −0.950
(−1.596 to −0.304)		 0.0041 −0.626
(−1.268 to 0.017)		 .0563
Heart Failure Somatic Perception Scale −0.126
(−0.227 to −0.025)		 .0150 0.070
(−0.081 to 0.222)		 0.3605 −0.180
(−0.329 to 0.030)		 .0185
Montreal Cognitive Assessment 0.359
(0.134–0.583)		 .0018 0.158
(−0.149 to 0.466)		 0.3117 0.391
(0.060–0.721)		 .0206
Multiple R2: self-care maintenance, 0.1492; self-care management, 0.0568; self-care confidence, 0.068.
Abbreviations: b, parameter estimate; CI, confidence interval; NYHA, New York Heart Association; PSQI, Pittsburgh Sleep Quality Index; ref, reference category.

F1
FIGURE 1:
Self-care maintenance by sleep quality components. Vertical lines represent the ranges of observation. The boxes denote the interquartile ranges, where the lower horizontal line is the first quartile, the central horizontal line is the median, and the upper horizontal line is the third quartile. The gray line highlights the cutoff point of 70, identifying the self-care maintenance score as adequate or inadequate. Dots report the individual values of self-care maintenance by sleep quality components.
F2
FIGURE 2:
Self-care management by sleep quality components. Vertical lines represent the ranges of observation. The boxes denote the interquartile ranges, where the lower horizontal line is the first quartile, the central horizontal line is the median, and the upper horizontal line is the third quartile. The gray line highlights the cutoff point of 70, identifying the self-care management score as adequate or inadequate. Dots report the individual values of self-care management by sleep quality components.
F3
FIGURE 3:
Self-care confidence by sleep quality components. Vertical lines represent the ranges of observation. The boxes denote the interquartile ranges, where the lower horizontal line is the first quartile, the central horizontal line is the median, and the upper horizontal line is the third quartile. The gray line highlights the cutoff point of 70, identifying the self-care confidence score as adequate or inadequate. Dots report the individual values of self-care confidence by sleep quality components.

In the multivariable regression models (Table 3), people who had a habitual sleep efficiency of 75% to 84% showed lower self-care maintenance compared with people who had a habitual sleep efficiency of 85% or greater (b = −3.95; 95% confidence interval [CI], −7.54 to −0.36; P = .03). However, there were no differences between groups of sleep efficiency less than 75% versus greater than 85%, and self-maintenance scores tended to be lower in the sleep efficiency group less than 75% compared with greater than 85%. Patients who took sleep medications once or twice a week reported lower self-care maintenance compared with patients who took sleep medications less than once a week (b = −6.07; 95% CI, −9.88 to −2.25; P = .001). No differences in self-care maintenance were found in patients who took sleep medications 3 or more times a week compared with patients who took sleep medications less than once a week. Patients with a frequency of daytime dysfunction less than once a week had lower self-care management compared with patients who had a frequency of daytime dysfunction of 3 or more times a week (b = 6.34; 95% CI, 0.78–11.91; P = .03). Patients who took sleep medications less than once a week showed lower self-care confidence than patients who took sleep medications 3 or more times a week (b = 6.43; 95% CI, 1.07–11.80; P = .02).

TABLE 3 - Association Between Sleep Latency, Habitual Sleep Efficiency, Use of Sleeping Medication, and Daytime Dysfunction (Pittsburgh Sleep Quality Index) and Self-care Maintenance, Management, and Confidence (Self-Care of Heart Failure Index v6.2) by Multivariable Regression Models
Variable a Self-care Maintenance Self-care Management Self-care Confidence
b
(95% CI)		 P Multiple R 2 b
(95% CI)		 P Multiple R 2 b
(95% CI)		 P Multiple R 2
2. Sleep latency
(ref = 1, 16–30 min)		 31–60 min (2) −2.371
(−5.394 to 0.652)		 .1239 0.1514 −1.294
(−5.913 to 3.325)		 .5819 0.0544 −1.043
(−5.486 to 3.400)		 .6447 0.0759
>60 min (3) −0.351
(−3.707 to 3.006)		 .8375 −0.395
(−5.189 to 4.400)		 .8714 4.424
(−0.510 to 9.358)		 .0787
4. Habitual sleep efficiency
(ref = 0, >85%)		 75%–84% (1) −3.948
(−7.538 to −0.357)		 .0312 0.1578 −2.599
(−7.977 to 2.780)		 .3426 0.0597 −2.310
(−7.646 to 3.026)		 .3954 0.0684
65%–74% (2) −2.291
(−6.756 to 2.174)		 .3139 0.511
(−5.848 to 6.870)		 .8746 −2.006
(−8.616 to 4.603)		 .5511
<65% (3) −0.052
(−3.264 to 3.160)		 .9748 0.999
(−3.933 to 5.931)		 .6906 0.262
(−4.492 to 5.017)		 .9137
6. Use of sleeping medication
(ref = 1, less than once a week)		 Once or twice a week (2) −6.067
(−9.881 to −2.253)		 .0019 0.1727 2.459
(−2.849 to 7.768)		 .3628 0.0589 −1.505
(−7.168 to 4.159)		 .6019 0.0793
3 or more times a week (3) 2.577
(−1.036 to 6.189)		 .1617 3.326
(−1.866 to 8.519)		 .2085 6.434
(1.070–11.798)		 .0188
7. Daytime dysfunction
(ref = 1, less than once a week)		 Once or twice a week (2) 0.718
(−2.546 to 3.981)		 .6659 0.1496 3.493
(−1.403 to 8.390)		 .1615 0.0675 4.322
(−0.479 to 9.124)		 .0776 0.0726
3 or more times a week (3) 2.480
(−1.449 to 6.409)		 .2154 6.343
(0.776–11.911)		 .0257 4.365
(−1.449 to 10.179)		 .1408
The estimated association between each of the sleep components and self-care maintenance, self-care management, self-care confidence was adjusted by inserting in each linear model the following covariates: gender, age, New York Heart Association class, comorbidity index, anxiety, depression, somatic perception, and cognition.
Abbreviations: b, parameter estimate; CI, confidence interval; ref, reference category.
aThe sleep components included in these models were those that were significantly associated with at least 1 self-care dimension in the raw associations (Supplemental Digital Content 1, Table 1, https://links.lww.com/JCN/A165).

Discussion

In this study, we evaluated the association between global sleep quality and each sleep quality component with self-care maintenance, self-care management, and self-care confidence in adults with HF. We found that overall sleep quality was not significantly associated with any self-care scale. However, when we examined the 7 specific components of sleep quality, we found some significant associations. People who had a habitual sleep efficiency of 75% to 84% showed lower self-care maintenance than people who had a habitual sleep efficiency of 85% or greater. Patients who took sleep medications once or twice a week reported lower self-care maintenance compared with patients who took sleep medications less than once a week. Patients with a frequency of daytime dysfunction less than once a week had lower self-care management than patients who had a frequency of daytime dysfunction of 3 or more times a week. Patients who took sleep medications less than once a week showed lower self-care confidence compared with patients who took sleep medications 3 or more times a week. To the best of our knowledge, this is the first known study to consider the associations between specific sleep quality components and self-care in the population with HF.

Similar to other studies,19,46–48 we found that poor sleep quality is common in people with HF. Furthermore, in our sample, lower self-care maintenance and self-confidence scores were observed in patients who scored PSQI greater 12 compared with patients who scored PSQI less than 12, supporting previous results.33,49 However, in multivariable regression models, global sleep quality was not associated with self-care maintenance and self-care confidence. This could be because of other independent variables as anxiety, depression, or New York Heart Association class. Alternatively, perhaps using a global sleep quality score is not the best approach to study the relationship between sleep and self-care. This is because the global PSQI score is the sum of the scores obtained in each of the 7 components of sleep quality and using a global score could hide the influences of individual sleep components on self-care. Furthermore, not all sleep components may influence self-care in the same way, and some may have more influence than others; for example, habitual sleep efficiency may have more influence on self-care than sleep latency.

Habitual sleep efficiency is defined as the ratio between actual sleep time and time spent in bed.40 Habitual sleep efficacy of 75% to 84%, compared with habitual sleep efficacy greater than 85%, was associated with lower self-care maintenance. Previous studies50,51 demonstrated that, in chronically ill populations, poor sleep efficiency may reduce cognitive function (eg, memory, attention, executive function, and psychomotor speed).20 This result is consistent with studies in the general population52–54 demonstrating that sleep disturbances impair cognition and performance. Cognition is known to be an antecedent of self-care in patients with HF,55 and authors of previous studies56 observed significant associations between cognitive dysfunction and poor self-care maintenance. On the basis of these findings,20,50,51 we argue that poor habitual sleep efficiency could affect self-care maintenance via its effect on cognition. A mediation analysis of longitudinal data would be needed to confirm this hypothesis. Accounting for moderators, such as mood disorders and daytime sleepiness, would also be needed.20,34

Taking sleep medication once or twice a week compared with taking sleep medication less than once a week was associated with a lower self-care maintenance score and a higher self-care confidence score. Previous investigators42 reported that patients with HF took sleeping medication in small doses or only if strictly necessary because they had difficulties in fully functioning during the day after sleep medication use. When the quality of sleep worsens, medications become necessary but lead to residual daytime sedation, poor motor coordination, and cognitive impairment.57 Taking sleep medication could worsen self-care maintenance because of medication adverse effects that might impact cognition, as supported by previous findings.58,59 To better discuss this result, we verified the trend of cognition measured by the Montreal Cognitive Assessment for different levels of use of sleep medication and found that cognition showed the same trend as self-care maintenance for different levels of use of sleep medication. Furthermore, we also examined the relative frequencies of levels of daytime dysfunction for different levels of use of sleep medication, and we found that daytime dysfunction was less common among patients taking sleep medication less often than in patients taking sleep medication more often. These results may support the explanation previously stated about the relationships between sleep medication, cognition, and self-care maintenance. Conversely, patients might feel relieved because they are more able to sleep because of medications, showing improvements in their self-care confidence. However, these mechanisms should be investigated by future studies, and qualitative research could also help clarify this issue.

Finally, patients with a frequency of daytime dysfunction less than once a week had lower self-care management than patients who had a frequency of daytime dysfunction of 3 or more times a week. Frequent examples of daytime dysfunction include daytime sleepiness, fatigue, depressed mood, lack of energy, impaired cognition, memory problems, irritability, psychomotor dysfunction, and decreased alertness and concentration.41 Excessive daytime sleepiness was found to be associated with poor medication adherence, an indicator of self-care maintenance.33 Fatigue, depressed mood, and lack of energy also compromise the performance of self-care.55 Worsening of symptoms motivates and makes patients more willing to perform self-care maintenance and follow the established treatment plan.55,60–63 This may be particularly true for self-care management because, when symptoms increase, patients take actions to find different management strategies to control symptoms. Finally, it should also be considered that self-care and illness management can be studied as dyadic phenomena where patient self-care influences caregiver contribution to self-care, and vice versa.56,64–66 Therefore, future research is needed to investigate how patients and caregivers address poor sleep quality if it occurs, and how poor sleep quality affects behaviors and outcomes of the dyads.

Limitations and Strengths

The design of this study was the main limitation. This was a secondary analysis of existing data, which could lead to the lack of important variables, for example, the presence or absence of sleep apnea. Furthermore, the study was cross-sectional, and generalization should be done with caution. In addition, one of the inclusion criteria of the parent study required a score of 0, 1, or 2 in at least 2 items on the self-care maintenance or self-care management subscales of the SCHFI v6.2, increasing the probability of including only patients with poor self-care. However, having a score of 0, 1, or 2 in at least 2 items of the self-care maintenance or self-care management did not preclude the possibility of getting a score of 70 or greater, which is considered adequate.36 Nevertheless, it is important to consider this when interpreting our results. Furthermore, as this study was conducted on patients with HF, the potential contribution of caregivers to patient self-care was not examined. However, the study was conducted at multiple centers; the sample was large and represented hospitals, outpatients, and community settings. In addition, valid and reliable instruments were used to measure the main study variables. Finally, this is the first known study to consider each individual sleep quality component, informing a deeper understanding of the effect of sleep quality on self-care behaviors.

Conclusions

Poor sleep quality is frequently reported by patients with HF, but evidence of the relationship between sleep quality and self-care needs to be strengthened. In this study, patients had poor sleep quality and poor self-care. Thus, interventions to improve both are needed. We found no association between global sleep quality and self-care, but we did find specific sleep quality components associated with self-care of patients with HF. Habitual sleep efficiency, frequency of taking sleep medications, and daytime dysfunction might play a role in the self-care of people with HF.

Future research on this topic is needed to further test the association between overall sleep quality and its specific components and self-care to make evidence-based clinical recommendations. Authors of studies on sleep and self-care should assess the different components of sleep and the effect of chronic and acute sleep problems on self-care. Longitudinal studies are needed to better understand the directions of these associations. Mediation analysis assessing the effect of sleep quality on self-care via cognition should be performed.

What’s New and Important

  • Overall or global sleep quality was not associated with self-care maintenance, management, and confidence. However, habitual sleep efficiency, sleep medication use, and daytime dysfunction were associated with self-care.
  • Patients with HF report both poor sleep quality and poor self-care. Interventions to improve both sleep quality and self-care are required.

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Keywords:

heart failure; self-care; self-management; sleep deprivation; sleep quality

Supplemental Digital Content

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