Status quo and factors influencing dyadic disease appraisal in chronic heart failure based on latent profile analysis in Northern Sichuan Province, China

Convenience sampling was employed to select the study participants from among the CHF patients admitted to the cardiology departments of 2 tertiary hospitals in Nanchong City, China, from June 2022 to November 2022, and their caregivers. The inclusion criteria for patients were as follows: 1- formal diagnosis of HF (verified by an HF cardiologist); 2- age ≥ 18 years; 3- clear consciousness, no cognitive dysfunction, and communication disorder; 4- willingness to participate in this study; and 5- evident symptoms of HF (New York Heart Association [NYHA] class I–IV). The exclusion criteria for patients were as follows: 1- affliction with heart failure for less than a year; 2- receiving a mechanical circulatory support device, undergoing transplantation, or having another terminal condition; and 3- unwillingness of the support person to participate in the study. The inclusion criteria for caregivers were as follows: (1) age ≥ 18 years and (2) unpaid individuals who were primarily responsible for caregiving and were spending at least 4 h per day providing care in the hospital [12]. Moreover, the exclusion criteria for caregivers were as follows: (1) affliction with major physical or mental disorders; (2) suffering from cognitive impairments; and (3) not living with the patient for a minimum of one year. The sample size was calculated using the following formula: n = u1-α/2σ/δ) 2. Assuming α = 0.05, u1-α/2 = 1.96, δ = 0.1, and σ = 0.753, based on previous studies, the sample size was obtained 225.

The demographics of patients and their caregivers (i.e., age, gender, etc.) were obtained through in-person surveys. Moreover, the clinical characteristics of patients (i.e., severity of heart failure and number of hospitalizations) were obtained by reviewing their electronic medical records (Table 1).

A face-to-face survey using paper-based questionnaires was conducted on hospitalized CHF patients and their caregivers in the cardiology department of two tertiary hospitals in Nanchong City, China, from June 2022 to November 2022. Before conducting the survey, the researchers provided unified training in the research topic to two nursing graduates to ensure their understanding of the experimental process and survey tools, standardize the methods of asking survey questions, and familiarize them with the necessary precautions for conducting questionnaire surveys and completing them accurately. In cases where individuals could not complete the questionnaires due to factors such as old age, impaired vision, or illiteracy, the researchers verbally presented the items and response options to the participants. The participants then provided their responses orally, and the researchers recorded their answers on their behalf. Immediately following the survey, the researchers verified the accuracy and integrity of the obtained data by promptly rectifying any missing items or misinformation. In this study, a total of 274 questionnaires were distributed among the participants. After excluding 12 questionnaires that were deemed invalid(the number of missed answers is ≥ 2/3 of the total number of questions), the data from the remaining 262 questionnaires were used for analysis, resulting in an effective rate of 95.6% (262/274).

The data obtained were analyzed statistically in SPSS 26.0. The count data were presented as frequencies and percentages, while the measurements were presented as mean ± standard deviation (x ̅ ± s). A Pearson correlation analysis was conducted. The Mplus 7.0 software was utilized to model the potential profiles. The fit indices used in this analysis include the Akaike information criterion (AIC), Bayesian information criterion (BIC), and corrected Bayesian information criterion (BIC). Smaller mean values of these indices indicate a better fit for the model. The entropy index, which ranges from 0 to 1, provides a measure of accuracy. A value closer to 1 indicates a more accurate model. Specifically, if the entropy index is greater than 0.6, it suggests that the model has better classification accuracy. To compare different models, a likelihood test called the Bootstrap-based likelihood test (BLRT) and the LMR likelihood ratio test (LMR) were performed. A significance level of P < 0.05 indicates that k-1 category models were rejected, while k-1 category models were supported. The comparison between the two groups was conducted using a two independent samples t-test if the data followed a normal distribution. For multi-group comparisons, analysis of variance (ANOVA) was used for between-group comparisons. If the data was non-normal, the rank-sum test (Kruskal–Wallis H) was used for comparison between two and multiple samples. The χ2 test was used for counting data. A multiple logistic regression analysis was conducted to examine the factors that influence the formation of potential categories of differences in dyadic disease appraisal in patients with CHF. The analysis used a significance level of P < 0.05.

This study was approved by the medical ethics committee of the studied hospital (2022R375-1).

A binary logistic regression analysis was conducted to examine the potential categories of differences in dyadic disease appraisal as dependent variables. The independent variables also included the patient's disease course, self-care ability, social support, Caregivers gender, age, educational attainment, relationship with the patient, frequency of communication with the patient's symptoms, patient's dependence score, Caregivers anxiety, and Caregivers burden. The findings indicated that patients who had a shorter disease course and less social support, were receiving care from female caregivers, were 65 years old, had lower educational attainment, and had higher levels of Caregivers' anxiety and burden were statistically more likely to fall into the potential category of dyadic disease appraisal (P < 0.05) (Table 10).

This study combined patients with CHF and their caregivers as a unit of analysis and employed LPA for the first time to determine subgroups for dyadic disease appraisal in Chinese populations of CHF patients. This study enhanced the existing body of knowledge on how CHF patients perceive and evaluate diseases in their relationships. It demonstrated that different subgroups of individuals, who were assessed for various diseases in their relationships, exhibited significant differences in terms of their sociodemographic and clinical characteristics, as well as the levels of social support they received and the anxiety and burden experienced by their caregivers. In this study, the dyadic disease appraisal in CHF patients was divided into two potential categories: "negative difference group" and "positive or consistent group".

The mean scores of three-dimensional dyadic disease appraisal in CHF patients in the "negative difference group" were all negative. It is also possible that the inadequacy of caregivers to assist patients in coping with symptoms, provide emotional support, and facilitate decision-making may be the reason for a lower evaluation of patients' symptoms. Furthermore, caregivers may face challenges in accurately evaluating the patient's symptoms due to the patient's tendency to conceal their discomfort and their reluctance to seek assistance from caregivers [23].

The differences in the appraisal of physiological symptoms and heart failure symptoms in CHF patients in the "positive or convergence group" were divided into positive numbers, but the differences in the appraisal of psychological symptoms were divided into negative numbers, which may be related to heart failure. CHF is a persistent progressive cardiovascular disease associated with a high readmission rate, high morbidity, high mortality, and high financial burden, which often leads to common psychological disorders such as depression, anxiety, and insomnia [24]. Emotional issues are subjective feelings that are not readily apparent, and patients usually refrain from expressing their negative emotions, which makes it challenging for caregivers to identify them [25].

The study findings indicated that the "female support person" was a characteristic population that constitutes a "negative differential group". Specifically, the Caregivers disease appraisal was greater than the patient's self-disease appraisal. This is not consistent with the findings of Lee who showed that the difference in dyadic evaluation was relatively small when caregivers were female [26]. This can be attributed to the fact that female caregivers are more attentive and invest more time in care, which may lead to the overestimation of symptoms as a result of their increased sensitivity to changes in the disease symptoms [27]. In addition, female caregivers showed lower psychological resilience and were prone to higher levels of anxiety and care burden, which could affect disease appraisal [28]. Therefore, it is necessary to closely monitor the mental health status of female caregivers.

This study showed that the Caregivers educational attainment was one of the factors influencing the formation of a "negative difference group". Accordingly, caregivers with lower educational attainment evaluate the disease better than the patients do. This is consistent with the findings of Sharifi et al. [29]. who studied differences between patients with heart failure and their caregivers in the evaluation of disease symptoms and found that caregivers with lower educational attainment were more likely to exhibit high differences in dyadic disease appraisal. This can be attributed to the Caregivers low level of educational attainment, resulting in a lack of comprehension of the disease and disregard for changes in the patient's condition, consequently influencing the disease appraisal [30]. Consequently, medical staff should promptly assess the health knowledge requirements of caregivers with lower levels of educational attainment, offer disease knowledge training, develop strategies for their involvement in the identification and management of patient symptoms, and mitigate disparities in dyadic disease appraisal.

The potential classification of differences in the dyadic appraisal of CHF based on the age of the support person is a topic of controversy. Lyons found that young couples with prostate cancer were more likely to have inconsistent dyadic disease appraisal [31]. Lee reported that the dyadic disease appraisal was more pronounced when the caregivers for CHF patients were older [32]. Interestingly, this study showed that the age over 65 years for caregivers was the characteristic forming a "negative difference group". This means that the older the caregivers are, the more they overestimate the disease symptoms. Moreover, the caregivers' capacity to assess the health status of others tends to decline as they age, and they tend to overestimate the severity of the disease symptoms [32]. Furthermore, as caregivers grow older, their capacity to acquire and embrace the patient's knowledge about their disease diminishes, and their comprehension of the disease becomes ambiguous [33].

The study findings suggested “disease course” as another factor influencing the formation of a "negative difference group", which was consistent with the results of Pickard's [34]. Patients have a lower self-appraisal of the disease because of the short disease course and a lack of understanding of their disease [35]. Therefore, to facilitate patient recovery and enhance the quality of life of patients and their caregivers, medical staff should promptly communicate with patients and caregivers, thereby increasing their comprehension of the disease symptoms, reducing their stress, and facilitating their rapid integration into the patient's disease treatment process. This will establish a positive dyadic relationship of cooperation.

This study showed that the patient's social support is one of the factors influencing the potential categories of dyadic disease appraisal differences between CHF patients and their caregivers. The lower the patient's social support, the easier it is to form a "negative difference group". This is consistent with the findings of Cameron [36]. Elderly patients with chronic diseases often rely on their home-based caregivers, such as spouses, who themselves are also patients with chronic diseases. Other family members, such as children, friends, brothers, and sisters, take care of these caregivers. The dual evaluation of symptoms of patients and their spouses may be influenced by the engagement of other caregivers [32]. Due to the reduced number of migrant workers caused by the COVID-19 pandemic during this study, the majority of caregivers were the children of patients. They communicated less and spent less time with patients, and influenced disease appraisal. Consequently, it is necessary to develop structured and family-centered health educational interventions for such patients. Participation of patients' family members in educational courses helps to establish a "hand-in-hand plan", form a "disease management knowledge sharing" model, enhance patients' social support, and mitigate discrepancies in dyadic disease appraisal [37].

This study proposed “Caregivers’ anxiety and burden” as one of the factors influencing the potential categories of dyadic disease appraisal differences between CHF patients and their caregivers. The formation of a "negative difference group" is facilitated by the increased anxiety and burden of caregivers. Lyons found a significant negative correlation between the psychological health of spouses of patients with lung cancer and differences in the dyadic disease appraisal [38]. Silveira also showed that caregivers with higher levels of depression overestimate the disease symptoms, resulting in differences in the dyadic disease appraisal [25]. Schulz reviewed studies on care for patients with chronic disease and reported that caregivers’ burden and psychological distress lead to the increased perception of symptoms in patients [39]. Therefore, nursing staff should pay attention to the mental health of caregivers and provide them with educational lectures on mental health [40]. It is important to utilize modern communication technologies like telephone and social networks (e.g., WeChat) for following up the patients and their caregivers after discharge. Such a strategy can help facilitate open communication with support, allowing them to express any negative emotions they may be experiencing. Additionally, this strategy can provide them with specific measures to help alleviate these negative emotions [41].