
==== Front
BMC Cardiovasc Disord
BMC Cardiovasc Disord
BMC Cardiovascular Disorders
1471-2261
BioMed Central London

4176
10.1186/s12872-024-04176-4
Research
Mediating effect of coping strategy and psychological status between illness perception and quality of life among patients with atrial fibrillation: a cross-sectional study
Minjie Zheng
Zhijuan Xie
Xinxin Shi
Shan Qu qu1983shan1120@outlook.com

https://ror.org/035adwg89 grid.411634.5 0000 0004 0632 4559 Department of Medical Psychology, Peking University People’s Hospital, Beijing, China
19 9 2024
19 9 2024
2024
24 50431 5 2024
9 9 2024
© The Author(s) 2024
2024
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Background

This study investigated the mediating effects of coping strategies and psychological status on the relationship between illness perception and health-related quality of life (HRQoL) among patients with atrial fibrillation (AF).

Methods

This cross-sectional study enrolled 178 patients with AF who were admitted to a tertiary hospital in Beijing City in mainland from March 2020 and June 2022. Assessments were made for HRQoL using the Short Form Health Survey depressive symptoms using the Patient Health Questionnaire-9, anxiety using the Generalized Anxiety Disorder-7 (GAD-7), illness perception using the Brief Illness Perception Questionnaire (BIPQ), AF symptoms using the Atrial Fibrillation Severity Scale (AFSS), and coping strategies using the Brief-COPE Scale.

Results

Significant correlations were observed between illness perception, emotional variables, coping strategies, and HRQoL scores. The regression analysis found that BIPQ, GAD, Maladaptive coping and Problem-focused coping are significant predictors of PCS (F = 20.906, R2 = 0.326, p < 0.01) and MCS (F = 31.24, R2 = 0.419, p < 0.01). Bootstrap samples were used to conduct mediation analysis. The indirect effects of GAD-7 and Problem-focused coping (PC) on the impact of BIPQ on QoL were significant. GAD accounted for 13.2–19.3% of the variance in the total effect across different models, while PC accounted for 22.1–25.8%. The results also indicated a significant chain effect in the illness percepitong-anxiety-coping style-QoL model, which can explain 4.3–10.2% of the total effect, respectively.

Conclusions

The perception of illness significantly influenced HRQoL in patients with AF, as mediated by emotional symptoms and coping strategies. This highlights the importance of anxiety and problem-focused coping mechanisms. These findings underscore the need for a holistic, patient-centered approach to AF management that incorporates emotional well-being and coping strategies.

Trial registration

Retrospectively registered with ClinicalTrials.gov (NCT05974098). The date of registration: 1 August 2023.

Keywords

Atrial fibrillation
Illness perception
Quality of life
Coping strategies
Psychological status
Peking University People’s Hospital Scientific Research Development FundsProject RDJ2022-36 Project RDJ2022-36 Project RDJ2022-36 Project RDJ2022-36 National Natural Science Foundation of ChinaProject No. 61972046 issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcBackground

Atrial fibrillation (AF) is the most prevalent type of cardiac arrhythmia, conferring a substantial increase in the risk of mortality, stroke, congestive heart failure, cognitive decline, and dementia, thereby exerting a profound detrimental impact on the quality of life (QoL) of affected individuals. The prevalence of AF among the adult Chinese population ranges from 0.72 to 1.6%, with a notable increase in incidence with advancing age [1, 2]. As the demographic shift towards an aging population progresses, the aggregate number of individuals afflicted with this condition is anticipated to increase progressively.

Health-related quality of life (HRQoL)

HRQoL is conceptualized as an individual’s subjective appraisal of their life state in relation to their personal aspirations or expectations [3]. Post-intervention, although patients with AF may exhibit significant improvements in disease symptoms and cardiac functionality, it remains evident that extra-cardiac factors continue to affect their QoL negatively. Consequently, the HRQoL assessment has emerged as a pivotal referential metric for evaluating the holistic health status of patients with AF. Current scientific reports indicate that a constellation of factors, including illness perception, psychological attributes, and symptom burden, along with the presence of physical comorbidities, synergistically influence the HRQoL of individuals with AF [4, 5]. However, the interrelationships among these influencing factors remain unclear.

Emotional well-being

Individuals with AF often experience heightened anxiety and depression [6, 7], which are linked to concerns about the severe consequences of the disease, such as stroke, and the adverse effects of AF symptoms on their overall HRQoL and functional capabilities. The post-diagnosis unique challenges patients experience include delayed diagnosis, a sense of isolation, disillusionment due to recurrent treatment setbacks, and the unpredictability of symptomatic episodes, which further impair their emotional well-being [8, 9]. Additionally, sympathetic nervous system overactivity increases the likelihood of AF episodes [10]. Consequently, the presence of anxiety and depressive symptoms is recognized as a significant factor affecting the HRQoL in patients with AF.

Illness perception and coping strategy

Educational demands concerning the management of AF remain unmet, with patients potentially gravitating towards the allure of unverified methodologies that proliferate on the internet [11]. This trend may potentially have adverse effects on their QoL. A limited understanding of AF or the inability to effectively manage the condition can trigger a pernicious cycle characterized by persistent avoidance or engagement in extreme behaviors, leading to withdrawal from activities that were once sources of enjoyment [12]. Patient adherence to medical regimens is significantly influenced by their beliefs about health and attitudes toward medication. Notably, providing structured support to patients is paramount to augment the safety and efficacy of anticoagulation therapies [13, 14].

Hypothesis

The Common Sense Model (CSM), introduced by Leventhal, Meyer, and Gerber, highlights the importance of an individual’s subjective interpretations of health-related information and the emotional responses that guide health behavior decision-making [15]. According to CSM, perceptions of illness can trigger emotional reactions and influence the adoption of coping strategies, which subsequently shape health outcomes. In light of this model, the present study aimed to substantiate the notion that, in the context of AF, the degree of illness perception can influence HRQoL by mediating the effects of emotional symptoms and coping strategies.

Methods

Study design

This cross-sectional study was conducted among patients with AF at the Department of Cardiology and Medical Psychology of a comprehensive tertiary hospital in Beijing, China from March 2020 to June 2022. Participants were predominantly recruited through research posters and referrals by specialists in cardiology. The patients were invited to participate voluntarily and they all provided written informed consent.

The study was approved by the regional ethics review board of Peking University (approval number: 2020PHB151). The research was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and the findings were reported following the STROBE checklist. This study was performed following the Declaration of Helsinki.

Participants and sample size

The inclusion criteria for the study were as follows: (1) aged between 18 and 75 years; (2) a diagnosis of AF according to the 2020 European Society of Cardiology Guidelines for Atrial Fibrillation [16], confirmed from formal medical records, a 12-lead ECG, or a Holter monitor report, and verified by a cardiologist; and (3) proficiency in reading and writing in Chinese.

The exclusion criteria comprised: (1) unstable coronary artery disease; (2) severe left ventricular systolic dysfunction with heart failure (ejection fraction ≤ 35%); (3) recent thoracic surgery; (4) terminal illnesses, including malignant diseases with a 1-year survival rate; (5) psychiatric conditions with daily functioning impairments, such as schizophrenia and delusions; (6)cognitive impairment that impedes involvement in the study. An a priori power analysis conducted using G*Power (version 3.1) with an effect size of 0.3, an error probability (alpha) of 0.05, and a power of 0.95 determined the required sample size to predict QoL with eight predictor variables. This threshold was met and exceeded 134 participants.

Outcomes and measurements

12-Item short Form Health Survey (SF-12)

HRQoL was assessed with the SF-12, a 12-item instrument derived from the longer SF-36. The SF-12 evaluates two primary domains: the physical component summary (PCS) and the mental component summary (MCS), both scored on a scale from 0 to 100; higher scores indicate superior health status [17].

PHQ-9

To evaluate depressive symptoms experienced in the last fortnight, we utilized the Patient Health Questionnaire-9 (PHQ-9), which has a scoring range of 0 to 27 [18]. The choice of the PHQ-9 was influenced by its simple application process and recognized efficacy, which surpasses those of structured interviews, as outlined in the Diagnostic and Statistical Manual of Mental Disorders IV [19]. The Chinese adaptation of the PHQ-9 exhibited an internal consistency of 0.82, and its test-retest reliability was reported at 0.76 [20].

Generalized anxiety disorder-7 (GAD-7)

The GAD-7, a scale comprising seven items, evaluates the presence and severity of anxiety symptoms through responses to a four-point Likert scale. Total GAD-7 scores ranged from 0 to 21. The GAD-7 demonstrated strong internal consistency, with a Cronbach’s alpha of 0.92. Additionally, its stability over time was confirmed, with a test-retest intraclass correlation coefficient of 0.83 [21]. Owing to its dependable diagnostic accuracy and proven validity, the GAD-7 has become widely recognized and utilized in clinical settings as well as in research.

Brief illness perception questionnaire (BIPQ)

The BIPQ, a nine-item instrument, was employed to assess patient perceptions of their illness across nine dimensions. The BIPQ yields a composite score that quantifies the psychological impact of illness, with higher scores reflecting greater illness burden. This aggregate score is derived from summing the individual item scores, with items 3, 4, and 7 being reverse-scored. The total score potential spans from 0 to 80, where higher scores suggest a more substantial negative perception of the disease [22]. The Chinese adaptation of the BIPQ demonstrated favorable psychometric properties, with a Cronbach’s alpha of 0.78 [23].

University of Toronto atrial fibrillation severity scale (AFSS)

The AFSS) is a condition-specific instrument divided into three sections. To evaluate AF symptoms, we selected the symptomatic component from the third section, which included seven prevalent symptoms: heart palpitations, rest-related shortness of breath, activity-induced shortness of breath, exercise intolerance, dizziness, resting fatigue, and chest discomfort. This component of the AFSS quantifies symptom severity using a 6-point scale, with each symptom scored from 0 to 5. The aggregate score for this scale ranges from 0 to 35, with higher scores reflecting greater severity of AF symptoms. The scale exhibits good internal consistency, with Cronbach’s α values of 0.67 for healthcare usage, 0.94 for the burden of AF, and 0.72 for the severity of AF. The test-retest reliability over 3 months was moderate to strong, with correlation coefficients of 0.71 for healthcare usage, 0.75 for AF burden, and 0.64 for AF severity [24].

Carver brief coping questionnaire (Brief-COPE scale)

The Brief-COPE includes 28 items that measure 14 conceptually differentiable coping reactions [25]. The Brief-COPE questionnaire consists of three subscales. The maladaptive coping (MC) scale is based on 12 items (self-distraction, denial, substance use, behavioral disengagement, venting, self-blame) and has good internal consistency (α = 0.71). The Emotion-Focused Coping scale is based on 10 items (emotional support, positive reframing, humor, acceptance, religion) and also has good internal consistency (α = 0.74). Lastly, the Problem-Focused Coping scale is based on six items (active coping, instrumental support, planning) and demonstrates good internal consistency (α = 0.85). A 4-point rating scale was used, for example: “1 [I have not been doing this at all] to 3 [I have been doing this a lot].” The scores for these three subscales were calculated as the averages of the respective item scores.

Data collection

Patients with AF provided details regarding their age, sex, marital status, insurance status, educational level, and employment status. Data collection was completed using a paper-and-pencil survey with administrative staff available to answer the relevant questions. Clinical information was also retrieved from patient medical records.

Data analyses

We employed SPSS, version 26 (IBM Corp., Armonk, NY, USA), for all statistics analyses. Sociodemographic data were described as mean ± SD for normally distributed data; otherwise, we used median (interquartile range [IQR]). We analyzed categorical data using the chi-square test or Fisher’s exact test. Spearman’s correlation coefficient was used to assess the correlation between the variables. Alongside the descriptive analysis of the psychometric instruments, multiple linear regression models were used. Prior to conducting the analysis, we assessed the assumptions of linear regression, such as verifying independence using the Durbin-Watson test and checking for multicollinearity using the variance inflation factor (VIF) (all VIF values were < 2). To enhance the reliability of our findings, we employed the bootstrap function from the boot package, applying the bootstrapping method with 5000 resamples to estimate the coefficient distribution, assess coefficient bias and standard error, and evaluate the mediator models. Model 6 was selected for the mediation analysis to investigate the sequential mediation effects between the two mediator variables. The mediation effect was considered statistically significant if the confidence intervals of the bootstrap method did not span zero. The mediation analysis was conducted using the PROCESS macro (version 4.1) in SPSS.

Results

Demographics

We enrolled 178 patients with AF (97 females and 81 males). The mean patient age was 66 years (IQR 7 years). The majority of the participants were married (78.1%) and had insurance (74.4%) (Table 1). Outcomes of illness perception, coping strategies, psychological status, AF symptoms, and QoL are presented in Table 2.

Table 1 Sociodemographic and clinical characteristics of patients with AF (N = 187)

Variables	N	%	
Sex			
Male	81	45.5	
Female	97	54.5	
Marital status			
Single	10	5.6	
Married	139	78.1	
Divorced	24	13.5	
Widowed	5	2.8	
Monthly income(¥)			
<5000	58	32.6	
5000 ~ 10,000	74	41.6	
>10,000	46	25.8	
Medical insurance			
No	45	25.3	
Yes	133	74.7	
Employment status			
Employed	32	18.0	
Unemployed	22	12.4	
Retired	124	69.7	
Education			
Elementary school	22	12.4	
High school	66	37.1	
College/university	90	50.6	
Comorbidity			
No	95	53.4	
Yes	83	46.6	
Type of AF			
Permanent	47	26.4	
Paroxysmal	90	50.6	
Persistent	41	23.0	
AF, atrial fibrillation

Table 2 Scores of illness perception, coping strategy, psychological, AF symptoms, and quality of life

	Mean/Median	SD /IQR	
BIPQ	46	9	
   Consequences	5	2	
   Timeline	6	4	
   Personal control	6	2	
   Treatment control	5	3	
   Identity	5	3	
   Illness concern	7	3	
   Understanding	7	2	
   Emotional response	5	2	
Brief-COPE			
   Maladaptive coping	1.42	0.50	
   Emotion-focused coping	1.90	0.30	
   Problem-focused coping	2.50	0.66	
GAD-7	6	8	
PHQ-9	11	10	
AFSS symptoms scales	13	5	
AFSS burden scales	11	8	
SF-12 PCS	37.389	7.247	
SF-12 MCS	38.643	6.607	
AF, atrial fibrillation; AFSS, Atrial Fibrillation Severity Scale; BIPQ, Brief Illness Perception Questionnaire; GAD-7, Generalized Anxiety Disorder-7; IQR, interquartile range; MCS, mental component summary; PCS, physical component summary; PHQ-9, Patient Health Questionnaire-9; SD, standard deviation; SF-12: 12-Item Short Form Health Survey

Correlations between variables

Our results indicated a significant correlation between illness cognition, emotional variables, and coping strategies with QoL scores. Specifically, BIPQ, MC, GAD-7, AFSS symptom subscale scores, and AFSS burden subscale scores were negatively correlated with PCS scores. Conversely, emotion-focused coping and problem-focused coping were positively correlated with PCS scores. Similarly, BIPQ, MC, GAD-7, AFSS symptom subscale, and AFSS burden subscale scores were negatively correlated with MCS, while problem-focused coping (PC) was positively correlated with MCS scores (Table 3).

Table 3 Spearman correlation between variables

	1	2	3	4	5	6	7	8	9	10	
1. BIPQ	1										
2. Maladaptive coping	0.015	1									
3. Emotion-focused coping	0.032	-0.168*	1								
4. Problem-focused coping	-0.196**	-0.386**	0.332**	1							
5. GAD-7	0.217**	0.117	-0.219**	-0.310**	1						
6. PHQ-9	0.030	0.046	-0.075	-0.129	0.412**	1					
7. AFSS symptoms scales	-0.115	0.599**	-0.137	-0.269**	0.081	-0.004	1			.	
8. AFSS burden scales	-0.174*	0.658**	-0.060	-0.199**	-0.069	-0.108	0.731**	1			
9. SF-12 PCS	-0.271**	-0.323**	0.164*	0.414**	-0.343**	-0.224**	-0.258**	-0.195**	1		
10. SF-12 MCS	-0.291**	-0.430**	0.061	0.498**	-0.360**	-0.099	-0.332**	-0.229**	0.289**	1	
Significance * p < 0.05, ** p < 0.01; **: p < 0.01; *: p < 0.05

AFSS, Atrial Fibrillation Severity Scale; BIPQ, Brief Illness Perception Questionnaire; GAD-7, Generalized Anxiety Disorder-7; MCS, mental component summary; PCS, physical component summary; PHQ-9, Patient Health Questionnaire-9; SD, standard deviation; SF-12: 12-Item Short Form Health Survey

Mediation effect analysis

Sociodemographic factors (age, sex, marital status, and income), clinical conditions (including comorbidities and type of AF), and observational variables were all considered potential influencing factors in the regression equation and analyzed using the stepwise method. Regression analysis revealed that BIPQ, GAD, MC, and problem-focused coping were significant predictors of PCS (F = 20.906, R2 = 0.326, p < 0.01) and MCS (F = 31.24, R2 = 0.419, p < 0.01) (Table 4).

Table 4 Multiple linear regression to identify predictors for the PCS and MCS of the SF-12

Outcome	Predicators	B	Std. Error	Beta	t	p	
PCS	BIPQ	-0.179	0.062	-0.190	-2.887	0.004	
Maladaptive coping	-4.422	1.553	-0.202	-2.848	0.005	
Problem-focused coping	4.284	1.191	0.273	3.597	< 0.001	
GAD7	-0.264	0.109	-0.165	-2.425	0.016	
MCS	BIPQ	-0.149	0.052	-0.174	-2.837	0.005	
Maladaptive coping	-5.868	1.314	-0.293	-4.467	< 0.001	
Problem-focused coping	4.110	1.008	0.287	4.078	< 0.001	
GAD-7	-0.263	0.092	-0.180	-2.857	0.005	
BIPQ, Brief Illness Perception Questionnaire; GAD-7, Generalized Anxiety Disorder-7; MCS, mental component summary; PCS, physical component summary; SF-12: 12-Item Short Form Health Survey; Std, standard

Mediation analyses with 5000 bootstrap samples were conducted to examine the potential roles of GAD, MC, and PC as mediators between illness perception and QoL. Upon conducting a rigorous analysis, we observed that both the direct and indirect effects were significant in the Model BIPQ-GAD-QoL and BIPQ-PC-QoL. However, the sequential mediation effect was significant only in the BIPQ-GAD-PC-QoL model. Conversely, the mediating effect of the BIPQ-GAD-MC-QoL model was not statistically significant. (Fig. 1; Table 5).

Fig. 1 Chain mediating effect of generalized anxiety disorder (GAD) and coping strategies. Nonstandardized coefficients are reported, and dashed lines represent statistical insignificance. *p < 0.05 and **p < 0.01.C indicates total effect; C’ indicates direct effect

Table 5 Indirect and chain effect of perception emotion coping strategy QoL model

Model	Effect	Boot SE	Boot LLCI	Boot ULCI	Ratio of indirect to total effect	Ratio of indirect to total effect	
Total indirect effects	-0.079	0.041	-0.167	-0.007	26.1%		
BIPQ-GAD-PCS	-0.054	0.024	0.108	0.014		17.8%	
BIPQ-MC-PCS	-0.011	0.023	-0.062	0.032		-	
BIPQ-GAD-MC-PCS	-0.013	0.009	-0.035	-0.001		4.3%	
Total indirect effects	-0.135	0.047	-0.233	-0.051	44.6%		
BIPQ-GAD- PCS	-0.040	0.023	-0.093	-0.005		13.2%	
BIPQ- PC-PCS	-0.067	0.030	-0.133	-0.014		22.1%	
BIPQ-GAD-PC-PCS	-0.027	0.013	-0.056	-0.007		8.9%	
Total indirect effects	-0.083	0.042	-0.169	-0.004	30.2%		
BIPQ-GAD- MCS	-0.053	0.021	-0.097	-0.017		19.3%	
BIPQ- MC-MCS	-0.014	0.027	-0.068	0.038		-	
BIPQ-GAD-MC-MCS	-0.016	0.010	-0.039	-0.002		5.8%	
Total indirect effects	-0.140	0.050	-0.247	-0.050	50.9%		
BIPQ-GAD- MCS	-0.041	0.019	-0.083	-0.008		14.9%	
BIPQ- PC-MCS	-0.071	0.033	-0.145	-0.015		25.8%	
BIPQ-GAD-PC-MCS	-0.028	0.013	-0.058	-0.008		10.2%	
BIPQ, Brief Illness Perception Questionnaire; GAD, generalized anxiety disorder; LLCI, lower limit confidence interval; MCS, mental component summary; PCS, physical component summary; QoL, quality of life; SE, standard error; ULCI, upper limit confidence interval

Discussion

This study investigated the potential mediating and moderating roles of emotional symptoms and coping mechanisms among individuals with AF in relation to their illness perception and QoL. The findings demonstrated a significant negative correlation between distorted illness perceptions and QoL. Furthermore, the findings identified anxiety symptoms and coping strategies as pivotal mediators in the interplay between cognitive and emotional biases and QoL, thereby confirming the sequential process that unfolds from disease perception to emotional and behavioral responses to the ultimate evaluation of one’s QoL. Within this complex process, the mediating effects of anxiety symptoms and the use of various coping strategies have shown a range of influential effects.

Illness perceptions have been shown to directly affect disease-related QoL [26]. This correlation is not limited to cardiovascular diseases; it extends to various other chronic medical conditions, including cancer, diabetes mellitus, and inflammatory bowel disease [27–29]. The chronic disease transition perspective model proposed by Paterson suggests that subjective perceptions of reality rather than objective measures form the basis of how patients with chronic conditions interpret and manage their health challenges [30]. This highlights the importance of a robust interdisciplinary approach in which close collaboration between psychiatry and cardiology is crucial for establishing a comprehensive and long-term approach to managing cardiac patients throughout the chronic phase of their illness.

Anxiety symptoms mediate the impact of distorted disease perceptions on QoL, as evidenced by the clear relationship in where greater severity of cognitive biases leads to heightened anxiety levels, which, in turn, adversely affect QoL. This sequential mediation, commonly known as the chain mediation effect, implies that anxiety symptoms could further degrade QoL by exacerbating MC mechanisms and reducing problem-focused coping strategies. This elucidates the mechanism through which anxiety symptoms influence the QoL of patients with AF, underscoring the critical importance of identifying and addressing anxiety symptoms in this patient population to enhance their QoL. Our findings are supported by previous research that successfully mitigated anxiety levels and concurrently improved QoL in patients with paroxysmal AF through a 10-week course of Cognitive Behavioral Therapy (CBT) while also addressing distorted disease cognition, particularly concerning perceived consequences, control over treatment, and overall disease understanding [31]. Another study also suggests that online CBT can significantly improve atrial fibrillation-specific quality of life and reduce medical costs [32]. Contrary to the results reported by Le Grande et al. [33], we did not identify depression as a significant factor. It is important to note that the study sample exclusively comprised females, a demographic that has been observed to have a higher incidence of AF, poorer QoL, and increased symptomatology than males [34]. These sex-specific disparities may have contributed to the elevated levels of depression observed in this cohort, and the impact of such psychological comorbidities may have been more pronounced in this particular group.

Our study also suggests that MC strategies do not serve as mediators between the impact of distorted disease perceptions and QoL. Instead, they primarily act as mediators in the relationship between emotion-related perception and QoL. These nuanced findings emphasize the importance of considering specific pathways through which different factors influence QoL, highlighting the need for targeted interventions that address the emotional well-being of individuals. Conversely, problem-focused coping strategies directly mediate the effects of disease perception on QoL and the interaction between emotions-related perception and QoL. Lazarus and Folkman’s foundational theory of stress and coping suggests that a deeper understanding of a disease’s impact can empower individuals to adopt problem-focused coping strategies more readily, particularly in situations where individuals perceive greater control [35]. Several factors influence the selection and efficacy of various coping strategies. Despite the increasing recognition of psychological well-being, the focus and clinical evaluation of patient behavioral strategies remains insufficient. It is recommended to seamlessly integrate proactive coping strategies, including seeking constructive advice and engaging in planning as problem-focused strategies, into existing treatment protocols and actively communicate them to patients as part of their therapeutic process.

This study had several limitations that must be acknowledged. First, there was a recognized lack of objective physiological markers for patients with AF that could accurately reflect the severity of the condition. This absence may have affected the comprehensive assessment of the disease’s impact and the subsequent evaluation of the intervention’s effectiveness. Second, the study did not consider the duration of illness, which could have influenced patient perceptions and adaptation strategies over time [30]. Thirdly, this is a cross-sectional study, and we cannot ascertain the existence of a causal relationship between variables. The follow-up of patients or the establishment of a control group to account for confounding factors should be considered in future relevant research.

Conclusion

This study underscores the importance of considering patient multifaceted perceptions of their illness, including emotional and cognitive aspects, as part of disease management in future clinical practice. By addressing the complex interactions among illness perception, emotional well-being, and coping strategies, healthcare providers can promote a more holistic and patient-centered approach to disease management.

Acknowledgements

We acknowledge everyone who contributed towards the article who does not meet the criteria for authorship including anyone who provided professional writing services or materials.

Author contributions

ZM was responsible for research design, formal analysis and was a major contributor in writing the original draft. XZ participated in data curation and writing review. SX implemented investigation and project administration. QS was responsible for funding acquisition and provided guidance on research design, data statistical analysis, and manuscript writing. All authors read and approved the final manuscript.

Funding

The funds for this research supported by the National Natural Science Foundation of China (Project No. 61972046) and the Peking University People’s Hospital Scientific Research Development Funds (Project RDJ2022-36).

Data availability

Please contact the corresponding author for reasonable data requests.

Declarations

Ethics approval and consent to participate

This research was sanctioned by Ethics Review Committee of Peking University People’s Hospital in accordance with ethical protocol (2020PHB151).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Abbreviations

AF Atrial fibrillation

AFSS Atrial fibrillation severity scale

BIPQ Brief illness perception questionnaire

CSM Common sense model

ECG Electrocardiogram

GAD 7-Generalized anxiety disorder-7

HRQoL Health-related quality of life

IQR Interquartile range

PC Problem-focused coping

PCS Physical component summary

PHQ 9-Patient health questionnaire-9

SPSS Statistical package for the social sciences

SD Standard deviation

SF 12-12-Item short form health survey

MCS Mental component summary

MC Maladaptive coping

QoL Quality of life

VIF Variance inflation factor

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. Shi S Tang Y Zhao Q Yan H Yu B Zheng Q Prevalence and risk of atrial fibrillation in China: a national cross-sectional epidemiological study Lancet Reg Health West Pac 2022 23 100439 10.1016/j.lanwpc.2022.100439 35800039
Shi S, Tang Y, Zhao Q, Yan H, Yu B, Zheng Q, et al. Prevalence and risk of atrial fibrillation in China: a national cross-sectional epidemiological study. Lancet Reg Health West Pac. 2022;23:100439. 10.1016/j.lanwpc.2022.100439.35800039
2. Li C Wang H Li M Qiu X Wang Q Sun J Epidemiology of atrial fibrillation and related myocardial ischemia or arrhythmia events in Chinese community population in 2019 Front Cardiovasc Med 2022 9 821960 10.3389/fcvm.2022.821960 35445083
Li C, Wang H, Li M, Qiu X, Wang Q, Sun J, et al. Epidemiology of atrial fibrillation and related myocardial ischemia or arrhythmia events in Chinese community population in 2019. Front Cardiovasc Med. 2022;9:821960. 10.3389/fcvm.2022.821960.35445083
3. Son YJ, Baek KH, Lee SJ, Seo EJ. Health-related quality of life and associated factors in patients with atrial fibrillation: an integrative literature review. Int J Environ Res Public Health. 2019;16. 10.3390/ijerph16173042.
4. Sadlonova M, Senges J, Nagel J, Celano C, Klasen-Max C, Borggrefe M, et al. Symptom severity and health-related quality of life in patients with atrial fibrillation: findings from the observational ARENA study. J Clin Med. 2022;11. 10.3390/jcm11041140.
5. Samuel M Khairy P Champagne J Deyell MW Macle L Leong-Sit P Association of atrial fibrillation burden with health-related quality of life after atrial fibrillation ablation: substudy of the cryoballoon vs contact-force atrial fibrillation ablation (CIRCA-DOSE) randomized clinical trial JAMA Cardiol 2021 6 1324 28 10.1001/jamacardio.2021.3063 34406350
Samuel M, Khairy P, Champagne J, Deyell MW, Macle L, Leong-Sit P, et al. Association of atrial fibrillation burden with health-related quality of life after atrial fibrillation ablation: substudy of the cryoballoon vs contact-force atrial fibrillation ablation (CIRCA-DOSE) randomized clinical trial. JAMA Cardiol. 2021;6:1324–28. 10.1001/jamacardio.2021.3063.34406350
6. Patel D Mc Conkey ND Sohaney R Mc Neil A Jedrzejczyk A Armaganijan L A systematic review of depression and anxiety in patients with atrial fibrillation: the mind-heart link Cardiovasc Psychiatry Neurol 2013 2013 159850 10.1155/2013/159850 23710335
Patel D, Mc Conkey ND, Sohaney R, Mc Neil A, Jedrzejczyk A, Armaganijan L. A systematic review of depression and anxiety in patients with atrial fibrillation: the mind-heart link. Cardiovasc Psychiatry Neurol. 2013;2013:159850. 10.1155/2013/159850.23710335
7. Polikandrioti M Koutelekos I Vasilopoulos G Gerogianni G Gourni M Zyga S Anxiety and depression in patients with permanent atrial fibrillation: prevalence and associated factors Cardiol Res Pract 2018 2018 7408129 10.1155/2018/7408129 29670767
Polikandrioti M, Koutelekos I, Vasilopoulos G, Gerogianni G, Gourni M, Zyga S, et al. Anxiety and depression in patients with permanent atrial fibrillation: prevalence and associated factors. Cardiol Res Pract. 2018;2018:7408129. 10.1155/2018/7408129.29670767
8. Wang J Liu S Bao Z Gao M Peng Y Huang Y Patients’ experiences across the trajectory of atrial fibrillation: a qualitative systematic review Health Expect 2022 25 869 84 10.1111/hex.13451 35174590
Wang J, Liu S, Bao Z, Gao M, Peng Y, Huang Y, et al. Patients’ experiences across the trajectory of atrial fibrillation: a qualitative systematic review. Health Expect. 2022;25:869–84. 10.1111/hex.13451.35174590
9. McCabe PJ Schumacher K Barnason SA Living with atrial fibrillation: a qualitative study J Cardiovasc Nurs 2011 26 336 44 10.1097/JCN.0b013e31820019b9 21263348
McCabe PJ, Schumacher K, Barnason SA. Living with atrial fibrillation: a qualitative study. J Cardiovasc Nurs. 2011;26:336–44. 10.1097/JCN.0b013e31820019b9.21263348
10. Linz D van Hunnik A Ukena C Ewen S Mahfoud F Schirmer SH Renal denervation: effects on atrial electrophysiology and arrhythmias Clin Res Cardiol 2014 103 765 74 10.1007/s00392-014-0695-1 24682223
Linz D, van Hunnik A, Ukena C, Ewen S, Mahfoud F, Schirmer SH, et al. Renal denervation: effects on atrial electrophysiology and arrhythmias. Clin Res Cardiol. 2014;103:765–74. 10.1007/s00392-014-0695-1.24682223
11. Redman K Thorne S Lauck SB Taverner T What else can I do? Insights from atrial fibrillation patient communication online Eur J Cardiovasc Nurs 2017 16 194 200 10.1177/1474515116678103 28240140
Redman K, Thorne S, Lauck SB, Taverner T. What else can I do? Insights from atrial fibrillation patient communication online. Eur J Cardiovasc Nurs. 2017;16:194–200. 10.1177/1474515116678103.28240140
12. Taylor EC O’Neill M Hughes LD Carroll S Moss-Morris R It’s like a frog leaping about in your chest’: illness and treatment perceptions in persistent atrial fibrillation Br J Health Psychol 2018 23 3 21 10.1111/bjhp.12267 28875586
Taylor EC, O’Neill M, Hughes LD, Carroll S, Moss-Morris R. It’s like a frog leaping about in your chest’: illness and treatment perceptions in persistent atrial fibrillation. Br J Health Psychol. 2018;23:3–21. 10.1111/bjhp.12267.28875586
13. Osasu YM Cooper R Mitchell C Patients’ and clinicians’ perceptions of oral anticoagulants in atrial fibrillation: a systematic narrative review and meta-analysis BMC Fam Pract 2021 22 254 10.1186/s12875-021-01590-x 34937557
Osasu YM, Cooper R, Mitchell C. Patients’ and clinicians’ perceptions of oral anticoagulants in atrial fibrillation: a systematic narrative review and meta-analysis. BMC Fam Pract. 2021;22:254. 10.1186/s12875-021-01590-x.34937557
14. Khouja C Brunton G Richardson M Stokes G Blanchard L Burchett H Oral anticoagulants: a systematic overview of reviews on efficacy and safety, genotyping, self-monitoring, and stakeholder experiences Syst Rev 2022 11 232 10.1186/s13643-022-02098-w 36303235
Khouja C, Brunton G, Richardson M, Stokes G, Blanchard L, Burchett H, et al. Oral anticoagulants: a systematic overview of reviews on efficacy and safety, genotyping, self-monitoring, and stakeholder experiences. Syst Rev. 2022;11:232. 10.1186/s13643-022-02098-w.36303235
15. Meyer D Leventhal H Gutmann M Common-sense models of illness: the example of hypertension Health Psychol 1985 4 115 35 10.1037/0278-6133.4.2.115 4018002
Meyer D, Leventhal H, Gutmann M. Common-sense models of illness: the example of hypertension. Health Psychol. 1985;4:115–35. 10.1037/0278-6133.4.2.115.4018002
16. Hindricks G Potpara T Dagres N Arbelo E Bax JJ Blomström-Lundqvist C 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS): the Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC Eur Heart J 2021 42 5 507 10.1093/eurheartj/ehaa612
Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, et al. 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS): the Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC Eur. Heart J. 2021;42(5):507. 10.1093/eurheartj/ehaa612.
17. Ware J Jr Kosinski M Keller SD A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity Med Care 1996 34 220 33 10.1097/00005650-199603000-00003 8628042
Ware J Jr, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34:220–33. 10.1097/00005650-199603000-00003.8628042
18. Kroenke K Spitzer RL Williams JBW The PHQ-9: validity of a brief depression severity measure J Gen Intern Med 2001 16 606 13 10.1046/j.1525-1497.2001.016009606.x 11556941
Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606–13. 10.1046/j.1525-1497.2001.016009606.x.11556941
19. Löwe B Spitzer RL Gräfe K Kroenke K Quenter A Zipfel S Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians’ diagnoses J Affect Disord 2004 78 131 40 10.1016/s0165-0327(02)00237-9 14706723
Löwe B, Spitzer RL, Gräfe K, Kroenke K, Quenter A, Zipfel S, et al. Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians’ diagnoses. J Affect Disord. 2004;78:131–40. 10.1016/s0165-0327(02)00237-9.14706723
20. Yu X Tam WWS Wong PTK Lam TH Stewart SM The Patient Health Questionnaire-9 for measuring depressive symptoms among the general population in Hong Kong Compr Psychiatry 2012 53 95 102 10.1016/j.comppsych.2010.11.002 21193179
Yu X, Tam WWS, Wong PTK, Lam TH, Stewart SM. The Patient Health Questionnaire-9 for measuring depressive symptoms among the general population in Hong Kong. Compr Psychiatry. 2012;53:95–102. 10.1016/j.comppsych.2010.11.002.21193179
21. Spitzer RL Kroenke K Williams JBW Löwe B A brief measure for assessing generalized anxiety disorder: the GAD-7 Arch Intern Med 2006 166 1092 97 10.1001/archinte.166.10.1092 16717171
Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166:1092–97. 10.1001/archinte.166.10.1092.16717171
22. Broadbent E Petrie KJ Main J Weinman J The brief illness perception questionnaire J Psychosom Res 2006 60 631 37 10.1016/j.jpsychores.2005.10.020 16731240
Broadbent E, Petrie KJ, Main J, Weinman J. The brief illness perception questionnaire. J Psychosom Res. 2006;60:631–37. 10.1016/j.jpsychores.2005.10.020.16731240
23. Zhang N, Fielding R, Soong I, Chan KKK. Psychometric assessment of the Chinese version of the brief illness perception questionnaire in breast cancer survivors. PLoS ONE. 2017;12(3). 10.1371/journal.pone.0174093.
24. Dorian P Paquette M Newman D Green M Connolly SJ Talajic M Quality of life improves with treatment in the Canadian trial of atrial fibrillation Am Heart J 2002 143 984 90 10.1067/mhj.2002.122518 12075253
Dorian P, Paquette M, Newman D, Green M, Connolly SJ, Talajic M, et al. Quality of life improves with treatment in the Canadian trial of atrial fibrillation. Am Heart J. 2002;143:984–90. 10.1067/mhj.2002.122518.12075253
25. Carver CS You want to measure coping but your protocol’s too long: consider the brief COPE Int J Behav Med 1997 4 92 100 10.1207/s15327558ijbm0401_6 16250744
Carver CS. You want to measure coping but your protocol’s too long: consider the brief COPE. Int J Behav Med. 1997;4:92–100. 10.1207/s15327558ijbm0401_6.16250744
26. Taylor EC O’Neill M Hughes LD Moss-Morris R Atrial fibrillation, quality. Of life and distress: a cluster analysis of cognitive and behavioural responses Qual Life Res 2022 31 5 1415 25 10.1007/s11136-021-03006-w 34618326
Taylor EC, O’Neill M, Hughes LD, Moss-Morris R. Atrial fibrillation, quality. Of life and distress: a cluster analysis of cognitive and behavioural responses. Qual Life Res. 2022;31(5):1415–25. 10.1007/s11136-021-03006-w.34618326
27. Ekholm M Krouwels M Knittle K Examining interactions of illness perceptions, avoidance behavior and patient status in predicting quality of life among people with irritable bowel syndrome Health Psychol Behav Med 2024 12 2311986 10.1080/21642850.2024.2311986 38322504
Ekholm M, Krouwels M, Knittle K. Examining interactions of illness perceptions, avoidance behavior and patient status in predicting quality of life among people with irritable bowel syndrome. Health Psychol Behav Med. 2024;12:2311986. 10.1080/21642850.2024.2311986.38322504
28. Herzog K Schepper F Kamm-Thonwart R Herrmann J Budich M Weiler-Wichtl L Trajectories of illness perceptions in paediatric cancer patients and their parents and associations with health-related quality of life: results of a prospective-longitudinal study Psycho-oncology 2024 33 e6332 10.1002/pon.6332 38520473
Herzog K, Schepper F, Kamm-Thonwart R, Herrmann J, Budich M, Weiler-Wichtl L, et al. Trajectories of illness perceptions in paediatric cancer patients and their parents and associations with health-related quality of life: results of a prospective-longitudinal study. Psycho-oncology. 2024;33:e6332. 10.1002/pon.6332.38520473
29. Holmlund L Hörnsten C Valham F Olsson K Hörnsten Å Ängerud KH Illness perceptions and health-related quality of life in women and men with atrial fibrillation J Cardiovasc Nurs 2024 39 49 57 10.1097/JCN.0000000000000995 37074949
Holmlund L, Hörnsten C, Valham F, Olsson K, Hörnsten Å, Ängerud KH. Illness perceptions and health-related quality of life in women and men with atrial fibrillation. J Cardiovasc Nurs. 2024;39:49–57. 10.1097/JCN.0000000000000995.37074949
30. Paterson BL The shifting perspectives model of chronic illness J Nurs Scholarsh 2001 33 21 6 10.1111/j.1547-5069.2001.00021.x 11253576
Paterson BL. The shifting perspectives model of chronic illness. J Nurs Scholarsh. 2001;33:21–6. 10.1111/j.1547-5069.2001.00021.x.11253576
31. Minjie Z Zhijuan X Xinxin S Xinzhu B Shan Q The effects of cognitive behavioral therapy on health-related quality of life, anxiety, depression, illness perception, and in atrial fibrillation patients: a six-month longitudinal study BMC Psychol 2023 11 431 10.1186/s40359-023-01457-z 38062475
Minjie Z, Zhijuan X, Xinxin S, Xinzhu B, Shan Q. The effects of cognitive behavioral therapy on health-related quality of life, anxiety, depression, illness perception, and in atrial fibrillation patients: a six-month longitudinal study. BMC Psychol. 2023;11:431. 10.1186/s40359-023-01457-z.38062475
32. Särnholm J Skúladóttir H Rück C Axelsson E Bonnert M Bragesjö M Cognitive behavioral therapy improves quality of life in patients with symptomatic paroxysmal atrial fibrillation J Am Coll Cardiol 2023 82 1 46 56 10.1016/j.jacc.2023.04.044 37380303
Särnholm J, Skúladóttir H, Rück C, Axelsson E, Bonnert M, Bragesjö M, et al. Cognitive behavioral therapy improves quality of life in patients with symptomatic paroxysmal atrial fibrillation. J Am Coll Cardiol. 2023;82(1):46–56. 10.1016/j.jacc.2023.04.044. https://www.jacc.org/doi/.37380303
33. Le Grande MR Salvacion M Shwaita L Murphy BM Jackson AC Alvarenga ME Does coping style mediate the relationship between knowledge and psychosocial outcomes in women with atrial fibrillation? Front Psychiatry 2024 15 1328111 10.3389/fpsyt.2024.1328111 38585480
Le Grande MR, Salvacion M, Shwaita L, Murphy BM, Jackson AC, Alvarenga ME. Does coping style mediate the relationship between knowledge and psychosocial outcomes in women with atrial fibrillation? Front Psychiatry. 2024;15:1328111. 10.3389/fpsyt.2024.1328111.38585480
34. Tamirisa KP Dye C Ekeruo I Volgman AS Atrial fibrillation in women: from epidemiology to treatment Curr Cardiovasc Risk Rep 2022 16 207 17 10.1007/s12170-022-00707-w
Tamirisa KP, Dye C, Ekeruo I, Volgman AS. Atrial fibrillation in women: from epidemiology to treatment. Curr Cardiovasc Risk Rep. 2022;16:207–17. 10.1007/s12170-022-00707-w.
35. Folkman S The Oxford handbook of stress, health, and coping 2010 Oxford Oxford University Press
Folkman S. The Oxford handbook of stress, health, and coping. Oxford: Oxford University Press; 2010. 10.1093/oxfordhb/9780195375343.001.0001.
