The multiple mediating effects of illness perceptions and coping strategies on the relationship between physical symptoms and depressive symptoms in patients with heart failure

Abstract

Background:

Depressive symptoms are prevalent and cause poor health outcomes in patients with heart failure. Studies show that the physical symptoms of heart failure are associated with depressive symptoms. However, little is known about the underlying mechanisms of this relationship.

Aims:

The purpose of our study was to examine the associations between physical symptoms, illness perceptions, coping strategies and depressive symptoms and to test the multiple mediation effects of illness perceptions and coping strategies on the relationship between physical symptoms and depressive symptoms in patients with heart failure.

Methods:

Physical symptoms, illness perceptions, coping strategies and depressive symptoms were assessed using self-reported questionnaires among 302 patients (64.2±11.9 years, 54% male) with heart failure in a tertiary general hospital. A serial multiple mediation model was tested using the PROCESS macro for SPSS.

Results:

Depressive symptoms were positively correlated with physical symptoms (r=0.487, p<0.01), illness perceptions (r=0.499, p<0.01) and acceptance–resignation coping (r=0.580, p<0.01). The relationship between physical symptoms and depressive symptoms was mediated by illness perceptions (indirect effect: 0.036, confidence interval (0.014, 0.059)) and by acceptance-resignation (indirect effect: 0.034, confidence interval (0.019, 0.053)), respectively, and by these two in serial (indirect effect: 0.021, confidence interval (0.013, 0.033)).

Conclusion:

Patients with heart failure who have more physical symptoms are vulnerable to the development of depression. Healthcare providers should implement interventions focused on changing illness perceptions and reducing acceptance–resignation coping to relieve depressive symptoms.

Keywords

Heart failure physical symptoms illness perceptions coping strategies depressive symptoms

Heart failure is a chronic, progressive disease that causes public health problems. In developed countries, approximately 1–2% of all adults and more than 10% of people older than 70 years have been diagnosed with heart failure.¹ Depressive symptoms are common comorbidities of heart failure,² with their prevalence ranging from 9% to 60% among heart failure patients, higher than that of the general population.³ Heart failure patients often suffer from dyspnea, fatigue and dizziness and have sleeping difficulties.⁴ The physical symptoms accelerate as the disease progresses,⁵ affecting the patient’s functional status and resulting in depressive symptoms.⁶ Depressive symptoms have been found to contribute to increasing hospitalizations, readmissions and mortality and to a reduction in health-related quality of life in patients with heart failure.^7–9 To manage depressive and physical symptoms, it is essential to identify modifiable associated factors and the underlying mechanism between them in patients with heart failure.

The Common-Sense Model of Self-Regulation (CSM), developed by Leventhal, provides a framework for describing and understanding the processes involved in the initiation and maintenance of behaviors for managing illness threats.¹⁰ The model points out that illness perceptions have several components, that is, identity (the disease label and associated symptoms), cause (causal factors), consequences (impact on life domains for the patient and the family), control/cure (feasibility of control/cure of the illness) and timeline (time course the patient believes the condition will last).¹¹ Illness perceptions directly influence illness outcomes (e.g. anxiety, depressive symptoms), but they also affect the patients’ coping strategies to manage their illness.¹² Meta-analyses showed that illness perceptions played a predictive role in psychological distress (e.g. depressive symptoms) among physical health conditions.^13,14 In the current study, we operationalized physical symptoms as a health threat and depressive symptoms as illness outcome to examine the multiple mediation role of illness perceptions and coping strategies in the relationship between physical symptoms and depressive symptoms. The proposed mediation model is shown in Figure 1.

Coping refers to a person’s cognitive and behavioral efforts and strategies to manage the internal and external demands of the person–environment transaction.¹⁵ Individuals often use various coping strategies to deal with chronic conditions. Feifel et al.¹⁶ described three types of coping strategies, including confrontation (taking active measures, e.g. ask the doctor for advice), avoidance (avoiding thinking about illness, e.g. try to forget about illness) and acceptance–resignation (surrendering, e.g. feel nothing can be done about illness). Studies have indicated that the coping strategy adopted is related to depressive symptoms.^17,18

The relation of illness perceptions and coping strategies to depressive symptoms has been respectively examined in the heart failure population.^18,19 According to the CSM, illness perceptions and coping strategies are the intermediate variables and may sequentially mediate the relationship between physical symptoms and depressive symptoms. To our knowledge, no study has examined this association in patients with heart failure. To relieve depressive symptoms in patients with heart failure, especially among patients with greater physical symptoms, it is important to understand the modifiable factors that may mediate the association. Based on the above, this study proposes several hypotheses. Hypothesis 1: illness perceptions mediate the relationship between physical symptoms and depressive symptoms. Hypothesis 2: coping strategies mediate the relationship between physical symptoms and depressive symptoms. Hypothesis 3: illness perceptions and coping strategies sequentially mediate the relationship between physical symptoms and depressive symptoms in patients with heart failure. If the hypothesis/es is/are confirmed, it/they will potentially be used to reduce depressive symptoms among heart failure patients.

Methods

Design and sample

This study was a cross-sectional study that used a convenience sample. Patients provided written informed consent and were recruited from the cardiovascular units of a general university hospital in China, from October 2016 to September 2017. This study conformed with the principles outlined in the Declaration of Helsinki and was authorized by the Ethics Committee of Shandong University. The investigator used uniform instructions, and the questionnaires were filled out and collected on the spot. Inclusion criteria for participants were: (a) 18 years of age or older; (b) a confirmed diagnosis of heart failure by the physician; and (c) New York Heart Association (NYHA) class II–IV. Patients who were diagnosed with acute heart failure, had mental, hearing or visual impairments, or who had serious or life-threatening conditions were excluded.

The target number of patients was 201 based on a moderate f² effect size of 0.15, α of 0.05 and a power of 0.90 (using G*Power Version 3.1, written by Franz Faul).²⁰ This was assuming a dropout rate of 10% as a result of missing data, including a refusal to be interviewed and not completing the survey. Three hundred and two participants met the sample size requirement for the study.

Measures

Demographic and clinical characteristics

The demographic characteristics included age, gender, marital status, employment, residence, educational level, inhabiting and monthly income. Clinical characteristics included NYHA class, body mass index (BMI), heart failure hospitalization within the last six months, heart failure duration and comorbidity, were obtained from medical records.

Physical symptoms

Physical symptoms were measured using the 18-item Heart Failure Somatic Perception Scale (HFSPS).²¹ The questions on the scale ask participants how much they were bothered by symptoms in the past week with six response options (from 0 = ‘have no bothersome’ to 5 = ‘extremely bothersome’ symptoms). The total score ranges from 0 to 90. Higher scores on the HFSPS indicate more symptom burden. The HFSPS has excellent internal consistency with a Cronbach’s α of 0.90. The English version of the HFSPS was translated, back-translated, compared with the original scale and cross-culturally adapted via psychometrics to develop the Chinese version of the HFSPS. In this sample, the Cronbach’s α was 0.87.

Illness perceptions

The Brief Illness Perceptions Questionnaire (B-IPQ) was used to measure cognitive and emotional representations of the illness.²² The B-IPQ contains eight items covering three dimensions: cognitive illness representations (illness consequences, timeline, personal control, treatment control and identity); emotional representations (concern and emotions); and one item measuring illness understanding. Each item is rated on an 11-point Likert scale (ranging from 0 to 10). The total score ranges from 0 to 80. Higher scores indicate more negative illness perceptions. This instrument has shown acceptable validity and reliability. The Cronbach’s α in the present study was 0.657.

Coping strategies

The Medical Coping Modes Questionnaire (MCMQ) was used to measure different coping reactions in response to patients’ current disease.¹⁶ The original MCMQ is a four-point Likert scale from ‘never’ to ‘all the time’. It consists of 19 items to appraise three types of coping strategies, including: confrontation, avoidance and acceptance–resignation. Shen and Jiang²³ translated the MCMQ into Chinese and added one item to the original questionnaire. The total score ranges from 20 to 80.

The raw score of subscale ranges from 8 to 32 for confrontation subscale (eight items), from 7 to 28 for avoidance subscale (seven items) and from 5 to 20 for acceptance–resignation subscale (five items). To allow comparison, we standardized the subscale score through dividing the raw score by the number of items.²⁴ For the three types of coping strategies, a higher total score indicates that the participants tend to adopt the behavior when dealing with medical matters. In the current study, the Cronbach’s α for the confrontation, avoidance and acceptance–resignation subscales was 0.828, 0.645 and 0.761, respectively.

Depressive symptoms

Depressive symptoms were measured with the Hospital Anxiety and Depression Scale – Depression Scale (HADS-D).²⁵ The HADS-D includes seven items, and each answer is rated from 0 to 3. The total possible score for HADS-D ranges from 0 to 21. Higher scores indicate more severe depressive symptoms. A score ⩾8 indicates the presence of depressive symptoms.²⁶ The HADS-D has good validity and reliability, and the Cronbach’s α varies from 0.67 to 0.90.²⁶ In this study, the Cronbach’s α of the HADS-D was 0.826.

Statistical analysis

Data analysis was performed using SPSS version 22.0 for Windows (IBM Corp., Armonk, New York, USA). A value of p<0.05, based on a two-tailed test, was considered statistically significant. We computed descriptive statistics, including frequencies and percentages for categorical variables and mean and standard deviation for continuous variables. Pearson product-moment correlation coefficients were computed to detect the bivariate correlations of physical symptoms, illness perceptions and coping strategies with depressive symptoms. Multivariable linear regression was used to examine the multivariate relationships among physical symptoms, illness perceptions, coping strategies and depressive symptoms. To control the effects of covariates, all the demographic and clinical variables (such as age, gender, NYHA class, duration of heart failure) were entered into the regression model. The multiclassification variables were transformed into dummy variables.

Mediation analysis was conducted to test whether the association between physical symptoms and depressive symptoms was mediated by illness perceptions and coping strategies in serial. It was assumed that physical symptoms (X) would be associated with illness perceptions (M₁), which, in turn, generated coping strategies (M₂) and influenced depressive symptoms (Y). A serial mediator model with two mediators of illness perceptions and coping strategies provided three indirect effects that sum to a total indirect effect. The indirect effects in this model were (a) through illness perceptions (a₁b₁); (b) through coping strategies (a₂b₂); and (c) through illness perceptions and coping strategies (a₁d₂₁b₂). Significant correlations based on multivariable linear regression were incorporated into the mediation model. We used the SPSS PROCESS macro developed by Preacher and Hayes for a testing serial mediation model,²⁷ with model 6 and 5000 bootstrap samples. Point estimates and 95% bias-corrected bootstrap confidence interval (CI) were estimated for the indirect effects. The point estimate was considered significant when the CI did not contain zero.

Results

Participant characteristics

Of the 302 participants in this study, the mean age was 64.2±11.9 years and 54% were male. Most of the patients (88.1%) were in NYHA class II or III. The majority of patients (70.9%) had experienced heart failure for more than six months. Nearly half of the participants (49.7%) had at least one hospitalization for heart failure within the last six months, and 30.8% had three or more comorbidities. In addition, 59.6% of the patients had less than a high school education, 49.0% were unemployed and 47.0% earned less than ¥3000 per month. For BMI absent in six patients, the missing data were replaced by the series mean imputation in SPSS. A summary of sample characteristics is shown in Table 1.

Table 1.

Characteristics of samples (N = 302).

Variable	n (%)	Mean (SD)
Age, years		64.2 (11.9)
Gender
Male	163 (54)
Female	139 (46)
Marital status
Single/divorced/widow	35 (11.6)
Cohabiting/married	267 (88.4)
Employment
Unemployed	148 (49.0)
Employed	154 (51.0)
Residence
Rural area	112 (37.1)
Urban area	190 (62.9)
Education level
< High school	180 (59.6)
⩾ High school	122 (40.4)
Inhabiting
Living alone	19 (6.3)
Living with family	283 (93.7)
Income monthly per person
< ¥3000	142 (47.0)
⩾ ¥3000	160 (53.0)
NYHA class
II	154 (51.0)
III	112 (37.1)
IV	36 (11.9)
HF duration
< 6 months	88 (29.1)
⩾ 6 months	214 (70.9)
HF hospitalization in last six months
No	152 (50.3)
Yes	150 (49.7)
Comorbidity
< 3	209 (69.2)
⩾ 3	93 (30.8)
BMI, kg/m²
< 18.49	5 (1.7)
18.5–24.99	135 (44.7)
25–29.99	132 (43.7)
⩾30	30 (9.9)

SD: standard deviation; NYHA: New York Heart Association; HF: heart failure; BMI: body mass index.

Mean scores and correlation coefficients of study variables

As shown in Table 2, the mean scores for physical symptoms, illness perceptions and depressive symptoms were 23.22±13.13, 44.39±7.73 and 4.53±3.97, respectively. Regarding HADS-D, 70 (23.2%) patients scored ⩾8 and were classified as having depressive symptoms. For the MCMQ, the confrontation coping strategy had the highest score (raw score: 18.19±4.91; standardized score: 2.27±0.61); the acceptance–resignation score (raw score: 8.21±2.71; standardized score: 1.64±0.54) was the lowest; the avoidance score (raw score: 13.47±3.30; standardized score: 1.92 ±0.47) was in the middle. Physical symptoms were positively associated with illness perceptions (r=0.574, p<0.01), confrontation (r=0.156, p<0.01), acceptance–resignation (r=0.478, p<0.01) and depressive symptoms (r=0.487, p<0.01). Illness perceptions were positively associated with acceptance–resignation (r=0.488, p<0.01) and depressive symptoms (r=0.499, p<0.01). Acceptance–resignation was positively associated with depressive symptoms (r=0.580, p<0.01). Unexpectedly, confrontation and avoidance were not significantly related to depressive symptoms in this study.

Table 2.

Mean scores and correlation coefficients of variables (N=302).

Variable	Mean (SD)	1	2	3	4	5
1 Physical symptoms	23.22 (13.13)		—	—	—	—
2 Illness perceptions	44.39 (7.73)	0.574^**	—	—	—	—
3 ConfrontationStandardized score	2.27 (0.61)	0.156^**	0.087	—	—	—
4 Acceptance-resignationStandardized score	1.64 (0.54)	0.478^**	0.488^**	−0.041	—	—
5 AvoidanceStandardized score	1.92 (0.47)	−0.037	−0.071	−0.314^**	0.133^*	—
6 Depressive symptoms	4.53 (3.97)	0.487^**	0.499^**	0.098	0.580^**	−0.081

SD: standard deviation.

p < 0.05.

p < 0.01.

Multivariable linear regression analysis of depressive symptoms

Multivariate linear regression was used to detect the influencing factors of depressive symptoms among heart failure patients. The results showed that variance tolerance was higher than 0.5, and the variance inflation factor was lower than 2, indicating that there was no multicollinearity in the present study.²⁸ Monthly income, physical symptoms, illness perceptions and acceptance–resignation were associated with depressive symptoms, accounting for 42.2% of the variance in depressive symptoms (Table 3).

Table 3.

Multivariable regression analysis of depressive symptoms (N=302).

Variable	β	t	p	Collinearity
				Tolerance	VIF
Monthly income	−0.135	−2.283	0.023	0.547	1.829
Physical symptoms	0.201	3.355	0.001	0.535	1.870
Illness perceptions	0.202	3.412	0.001	0.549	1.821
Acceptance–resignation	0.391	7.108	< 0.001	0.634	1.578

R² = 0.458, adjusted R² = 0.422.

VIF: variance inflation factor.

Multiple mediating effects of illness perceptions and coping strategies

The indirect effects of physical symptoms on depressive symptoms via both illness perceptions and coping strategies were assessed using Preacher and Hayes’ serial mediation model with 95% CI based on 5000 bootstrapping samples.²⁷ All the mediated indirect effects of a specific path are shown in Figure 2 and Table 4. The results of this analysis revealed that the total effect of physical symptoms on depressive symptoms was significant (c=0.149, CI (0.119, 0.178)). Physical symptoms had a significant indirect effect through illness perceptions and acceptance–resignation in serial on depressive symptoms (a₁d₂₁b₂=0.021, CI (0.013, 0.033)), which accounted for 14.22% of the total effect of physical symptoms on depressive symptoms. In addition, physical symptoms had a significant indirect effect on depressive symptoms via illness perceptions ((a₁b₁=0.036, CI (0.014, 0.059)) and acceptance–resignation (a₂b₂=0.034, CI (0.019, 0.053)), respectively, accounting for 24.20% and 22.97% of the total effect of physical symptoms on depressive symptoms.

Table 4.

Mediation analysis of heart failure physical symptoms and depressive symptoms (N=302).

	Effect	SE	LLCI	ULCI
Total effect	0.149	0.015	0.119	0.178
Direct effect	0.057	0.017	0.024	0.090
Indirect effect
Total	0.091	0.014	0.065	0.122
Ind1	0.036	0.012	0.014	0.059
Ind2	0.034	0.009	0.019	0.053
Ind3	0.021	0.005	0.013	0.033

Indirect effect key: Ind1: physical symptoms→ illness perceptions→ depressive symptoms. Ind2: physical symptoms →acceptance-resignation→ depressive symptoms. Ind3: physical symptoms→ illness perceptions→ acceptance-resignation→ depressive symptoms.

SE: standard error; LLCI: lower limit confidence interval; ULCL: upper limit confidence limit interval.

However, we did not find any mediation effect of confrontation and avoidance between physical symptoms and depressive symptoms in patients with heart failure.

Discussion

To our knowledge, this is the first study to report the multiple mediating effects of illness perceptions and coping strategies on the relationship between physical symptoms and depressive symptoms in patients with heart failure. The results of this study supported the theoretical viewpoint of CSM that patients with more severe physical symptoms and poor illness perceptions tended to use the acceptance–resignation coping strategy, which was associated with more depressive symptoms. Physical symptoms had a direct and an indirect effect on depressive symptoms mediated by illness perceptions and acceptance–resignation in serial.

The current study found that 23.2% of heart failure patients had depressive symptoms. The prevalence of depressive symptoms was congruent with the mean prevalence (21.5%) in a meta-analysis.²⁹ However, it was lower than that (50.7%) reported by Bhatt et al.³⁰ The variation in prevalence may be attributed to the different screening tools and illness severity. Since depressive symptoms contribute to the increase in patients’ hospitalizations, readmissions and mortality, and poor health-related quality of life,^7–9 it is essential to recognize and manage the depressive symptoms in patients with heart failure.

This study showed that illness perceptions mediated the relationship between physical symptoms and depressive symptoms in heart failure patients, consistent with previous studies.^31,32 The experience of illness generated the patients’ own perceptions of cognitive and emotional representation, which contributed to impaired psychological well-being.¹⁰ Due to the progressive nature of heart failure, patients experienced increased frequency and severity of heart failure physical symptoms, resulting in poor perceptions and then aggravated depressive symptoms.³³ Illness perception has also been acknowledged as a notable factor in adjustment to chronic disease.³⁴ Thus, interventions should focus on the role of illness perceptions in managing depressive symptoms in patients with heart failure.

The present study found that coping strategies (acceptance–resignation, but not confrontation or avoidance) mediated the relationship between physical symptoms and depressive symptoms. Thus, hypothesis 2 was partially supported. In our sample, acceptance–resignation was chosen less frequently than avoidance or confrontation, which was similar to what was found in a prior study.²⁴ In contrast, in the results reported by Rong et al.³⁵ in Chinese ethnic minority regions patients used avoidance more often. A possible explanation was that our study population was younger. Buetow et al.³⁶ analyzed the narrative texts from 62 semi-structured personal interviews and reported that older age was associated with the adoption of avoidance coping in heart failure patients. Of the three coping strategies examined, only acceptance–resignation coping (e.g. to be guided by destiny) was the mediator of depressive symptoms beyond the effect of illness perceptions. Individuals with heart failure who used more acceptance–resignation to cope with their status and medical treatment had more depressive symptoms, which was supported by previous studies.^19,37 Living with the physical symptoms of heart failure and maintaining treatment was stressful, so patients who adopted an acceptance–resignation coping strategy were surrendering to face their illness feeling that it was their fate. In this situation, patients had more feelings of hopelessness and defeat, resulting in a higher level of depressive symptoms.¹⁶ Thus, healthcare providers should assess patients’ coping strategies to try to reduce the adoption of the acceptance–resignation coping strategy and thus improve the health outcomes in patients with heart failure.

It was interesting to discover the serial mediation effect of illness perceptions and acceptance–resignation between physical symptoms and depressive symptoms, which supported hypothesis 3 of this study. That is, the indirect effect of physical symptoms on depressive symptoms through illness perceptions and acceptance–resignation was significant. According to the CSM, individuals created perceptions based on their experience of the illness, which helped them make sense of the illness and guided them to use coping strategies to manage the disease.¹⁰ A meta-analyses supported the direct effects of illness perceptions on psychological well-being and the indirect effects mediated by coping.³⁸ When heart failure patients feel hopeless about recovery, they may generate negative perceptions about disease. In addition, illness perceptions were shaped directly in response to an illness and thus influenced coping strategies to deal with the condition.³³ Acceptance–resignation as a maladaptive coping strategy tended to predispose individuals to ascribe more symptoms and perceptions to the disease, resulting in a failure to engage in self-monitoring and rehabilitation from heart failure.³⁹ Therefore, healthcare providers should understand heart failure patients’ reactions to the illness, improve illness perceptions and help them develop appropriate coping strategies to reduce depressive symptoms.

Limitations

This study has several limitations that should be considered. First, our study design was cross-sectional in nature; therefore, cause-and-effect relationships could not be suggested in our analysis. Moreover, illness perception and coping strategy are the situational process that should be measured at multiple time points during the illness trajectory. Thus, longitudinal studies are needed to further elucidate causality. Second, the CSM recognized bidirectional feedback loops between the model components; however, the present study design did not allow for an evaluation of the bidirectional pathways of physical symptoms, illness perceptions, coping strategies and depressive symptoms. Third, the participants were from a large general hospital in China with NYHA class II–IV. This group may not be sufficient to represent the population, thus generalizability of the findings is limited. Fourth, the measurement of physical symptoms, illness perceptions, coping strategies and depressive symptoms was based on patients’ self-reports and may affect the measurements’ precision.

Conclusions

These findings support the theoretical relationships between physical symptoms, illness perceptions, coping strategies and health outcomes and expanded the CSM to the heart failure research area. Physical symptoms, together with illness perceptions and acceptance–resignation coping strategy, had a direct and an indirect effect on depressive symptoms. Additionally, illness perceptions and acceptance–resignation played a serial mediation role in the relationship between physical symptoms and depressive symptoms. Therefore, the treatment of depressive symptoms in heart failure patients might benefit from a psychological intervention focused on patients’ illness representations and acceptance–resignation coping. Thus, healthcare providers should take interventions focused on changing illness perceptions and reducing acceptance–resignation coping to improve health outcomes in patients with heart failure.

Footnotes

Acknowledgements

We are grateful to the healthcare providers and staff of the cardiovascular unit of the hospital for giving us permission to recruit patients. We also acknowledge the contributions of the patients who participated in this study. Author contribution: CC was involved in data analysis, data interpretation and the drafting of the manuscript. WF was responsible for data acquisition. YA and LW participated in analysis and interpretation. XF made substantive intellectual contributions to the conception of the work and the interpretation of the data and revised the manuscript. All authors have read and approved the final manuscript.

Implications for practice

Physical symptoms, illness perceptions and acceptance–resignation are positively associated with depressive symptoms.

Illness perceptions and acceptance-resignation play a serial mediation role in the relationship between physical symptoms and depressive symptoms.

Interventions focused on changing illness perceptions and reducing acceptance–resignation coping may be beneficial to relieve depressive symptoms in patients with heart failure.

Declaration of conflicting interests

The authors declare that there is no conflict of interest.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Shandong Key Research and Development Plan (grant number 2016GSF201046).

References

Ponikowski

Voors

Anker

, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 2016; 18: 891–975.

Sokoreli

de Vries

JJG

Pauws

, et al. Depression and anxiety as predictors of mortality among heart failure patients: Systematic review and meta-analysis. Heart Fail Rev 2016; 21: 49–63.

Rutledge

Reis

Linke

, et al. Depression in heart failure a meta-analytic review of prevalence, intervention effects, and associations with clinical outcomes. J Am Coll Cardiol 2006; 48: 1527–1537.

Yancy

Jessup

Bozkurt

, et al. 2013 ACCF/AHA Guideline for the management of heart failure: Executive summary: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2013; 128: 1810–1852.

Walke

Byers

Tinetti

, et al. Range and severity of symptoms over time among older adults with chronic obstructive pulmonary disease and heart failure. Arch Intern Med 2007; 167: 2503–2508.

Scherer

Himmel

Stanske

, et al. Psychological distress in primary care patients with heart failure: A longitudinal study. Br J Gen Pract 2007; 57: 801–807.

Gallo

Wenzel

, et al. Heart failure rehospitalization and delayed decision making the impact of self-care and depression. J Cardiovasc Nurs 2018; 33: 30–39.

Gathright

Dolansky

Gunstad

, et al. The impact of medication nonadherence on the relationship between mortality risk and depression in heart failure. Health Psychol 2017; 36: 839–847.

Morys

Pachalska

Bellwon

, et al. Cognitive impairment, symptoms of depression, and health-related quality of life in patients with severe stable heart failure. Int J Clin Health Psychol 2016; 16: 230–238.

10.

Leventhal

Diefenbach

Leventhal

. Illness cognition: Using common sense to understand treatment adherence and affect cognition interactions. Cognitive Ther Res 1992; 16: 143–163.

11.

Leventhal

Contrada

. Self-regulation, health, and behavior: A perceptual-cognitive approach. Psychol Health 1998; 13: 717–733.

12.

Hagger

Orbell

. A meta-analytic review of the Common-Sense Model of Illness Representations. Psychol Health 2003; 18: 141–184.

13.

Richardson

Schüz

Sanderson

, et al. Illness representations, coping, and illness outcomes in people with cancer: A systematic review and meta-analysis. Psychooncology 2017; 26: 724–737.

14.

Dempster

Howell

McCorry

. Illness perceptions and coping in physical health conditions: A meta-analysis. J Psychosom Res 2015; 79: 506–513.

15.

Folkman

Lazarus

Gruen

, et al. Appraisal, coping, health status, and psychological symptoms. J Pers Soc Psychol 1986; 50: 571–579.

16.

Feifel

Strack

Nagy

. Coping strategies and associated features of medically ill patients. Psychosom Med 1987; 49: 616–625.

17.

Vollman

LaMontagne

Hepworth

. Coping and depressive symptoms in adults living with heart failure. J Cardiovasc Nurs 2007; 22: 125–130.

18.

Nahlén Bose

Elfström

Björling

, et al. Patterns and the mediating role of avoidant coping style and illness perception on anxiety and depression in patients with chronic heart failure. Scand J Caring Sci 2016; 30: 704–713.

19.

Trivedi

Blumenthal

O’Connor

, et al. Coping styles in heart failure patients with depressive symptoms. J Psychosom Res 2009; 67: 339–346.

20.

Faul

Erdfelder

Buchner

, et al. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods 2009; 41: 1149–1160.

21.

Jurgens

Lee

Riegel

. Psychometric analysis of the heart failure somatic perception scale as a measure of patient symptom perception. J Cardiovasc Nurs 2017; 32: 140–147.

22.

Broadbent

Petrie

Main

, et al. The Brief Illness Perception Questionnaire. J Psychosom Res 2006; 60: 631–637.

23.

Shen

Jiang

. Report on application of Chinese version of MCMQ in 701 patients. Chin J Behav Med Sci 2000; 9: 18–20.

24.

Doering

Dracup

Caldwell

, et al. Is coping style linked to emotional states in heart failure patients? J Card Fail 2004; 10: 344–349.

25.

Zigmond

Snaith

. The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand 1983; 67: 361–370.

26.

Bjelland

Dahl

Haug

, et al. The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res 2002; 52: 69–77.

27.

Preacher

Hayes

. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 2008; 40: 879–891.

28.

Zou

Tian

Chen

, et al. Coping styles mediate the relationship between self-esteem, health locus of control, and health-promoting behavior in Chinese patients with coronary heart disease. J Cardiovasc Nurs 2017; 32: 331–338.

29.

Rutledge

Reis

Linke

, et al. Depression in heart failure – a meta-analytic review of prevalence, intervention effects, and associations with clinical outcomes. J Am Coll Cardiol 2006; 48: 1527–1537.

30.

Bhatt

Kalogeropoulos

Dunbar

, et al. Depression in heart failure: Can PHQ-9 help? Int J Cardiol 2016; 221: 246–250.

31.

Steca

Greco

D’Addario

, et al. Relationship of illness severity with health and life satisfaction in patients with cardiovascular disease: The mediating role of self-efficacy beliefs and illness perceptions. J Happiness Stud 2013; 14: 1585–1599.

32.

Greco

Steca

Pozzi

, et al. Predicting depression from illness severity in cardiovascular disease patients: Self-efficacy beliefs, illness perception, and perceived social support as mediators. Int J Behav Med 2014; 21: 221–229.

33.

Morgan

Villiers-Tuthill

Barker

, et al. The contribution of illness perception to psychological distress in heart failure patients. BMC Psychol 2014; 2: 50.

34.

de Ridder

Geenen

Kuijer

, et al. Psychological adjustment to chronic disease. Lancet 2008; 372: 246–255.

35.

Rong

Peng

, et al. Factors associated with adoption of coping strategies among Chinese patients with heart failure in ethnic minority regions. J Clin Nurs 2018; 27: 3324–3334.

36.

Buetow

Goodyear-Smith

Coster

. Coping strategies in the self-management of chronic heart failure. Fam Pract 2001; 18: 117–122.

37.

Svensson

Inoue

Sawada

, et al. Coping strategies and risk of cardiovascular disease incidence and mortality: The Japan Public Health Center-based prospective Study. Eur Heart J 2016; 37: 890–899.

38.

Hagger

Koch

Chatzisarantis

, et al. The common sense model of self-regulation: Meta-analysis and test of a process model. Psychol Bull 2017; 143: 1117–1154.

39.

Pardaens

De Smedt

De Bacquer

, et al. Comorbidities and psychosocial characteristics as determinants of dropout in outpatient cardiac rehabilitation. J Cardiovasc Nurs 2017; 32: 14–21.