Well-Being, Quality of Life, and Personality in German Heart Transplant Patients ()
1. Introduction
The process of heart transplantation (HTX) places high demands on the mental stability of patients [1]. In this context, various influencing factors are discussed that can contribute to maintaining and promoting the mental health of heart transplant patients. One supporting resource, among many others, is resilience. Nevertheless, despite mental health, subjective well-being may be impaired during the transplant process [2]-[4].
From a psychological perspective, the process of a transplant can be divided into several phases, which also include the long-term course [5]. “Transplantation is […] a process of hope and quality of life, but also a tightrope walk with an uncertain outcome” [5]. The current state of research shows that a heart transplant influences mental health [6]. The patients’ perceived quality of life is particularly affected [7]-[10]. Research results to date have mostly been based on prospective longitudinal studies to determine quality of life before and after heart transplantation. The majority of the results of various studies indicate an improvement in quality of life after HTX [7]-[10]. This underlines not only the medical but also the psychosocial necessity of transplant medicine.
There are currently various definitions of the concept of quality of life (QoL). QoL is multidimensional and has a significant component of an individual’s subjective experience. Important factors here include socio-economic status and life satisfaction. Health-related quality of life (HRQoL) must be distinguished from general QoL. HRQoL, in turn, reflects the effects that (chronic) illnesses can have on quality of life [9]. These patient-related influencing factors include social resources, certain personality traits, possible physical complaints, and individual disease management. Another important factor in this context that can influence subjective well-being is the doctor-patient relationship. However, as this is not a patient-related factor, it will not be discussed further here [11].
A meta-analysis comprising 62 studies with a total of 282,367 HTX patients examined various variables associated with 1-year mortality after HTX [12]. The mental health of organ recipients is not included in these studies. This underlines the fact that the factors of physical and mental health are often still considered separately from one another, even though the WHO’s definition of health made a clear connection as early as 1948. The WHO defines health as: “A state of complete physical, mental and social well-being and not merely freedom from disease and infirmity” [13]. Nevertheless, this definition of health must be viewed very critically, as transplanted patients or patients with other disabilities, for example, can no longer be considered healthy, as complete physical well-being is not achievable for many. This criticism is not an isolated case and is also generally known [14], which is why there have been other attempts to define health over time, such as the eight maxims of health and illness by Hurrelmann and Richter [15], which include subjective assessment and personal conditions, among other things. However, an essential aspect that is retained for the definition of health is the connection between physical, mental, and social well-being. It is therefore essential to take mental and social factors into account when considering physical health and vice versa. A further meta-analysis of 22 studies on health-related quality of life in adult heart transplant patients [10] includes social support, but individual personality traits and coping with illness are not taken into account. This is where our study comes in and exploratively investigates the influence of personality traits on coping with illness. Positive influences of emotional stability and extraversion are conceivable. Due to the lack of studies on HTX patients, no specific expectations can be formulated. Likewise, there do not seem to be any studies on disease management with regard to sex differences. However, we do not pursue this aspect [10].
With regard to the cardiovascular system, it is known that the psyche can influence it, but also that the psyche and subjective well-being can be negatively affected by cardiovascular diseases [16]-[19]. Another factor found in the literature that influences well-being after a heart transplant is age. Older age is expected to have a more positive influence on subjective well-being [9].
For the subsequent interpretation of the findings, it should be noted in advance that late complications such as tumor diseases, transplant vasculopathy, renal insufficiency, and other side effects associated with immunosuppression can lead to phases in the lives of heart transplant patients in which their physical condition is not classified as good [20].
In the studies mentioned above [7]-[10], which deal with the quality of life of patients after heart transplantation, it should also be noted that the connection between quality of life and outcome is not taken into account, although it has long been known that psychosocial factors and quality of life are also important indicators for the success of HTX [21]. Consequently, it is clear that although the importance of the relationship between physical and psychological factors in heart transplant patients is known, there is also a lack of corresponding studies [10] [21]. In this respect, the aim of the present study is to identify specific factors influencing subjective well-being in order to derive implications for practice.
In this respect, the present study is intended to contribute to clarifying the following research questions: 1) How can the subjects’ coping with the disease and their physical and psychological complaints be described, and are there significant differences compared to other (comparable) patients? 2) Is there a correlation between personality traits, age, time after heart transplantation, physical complaints, and well-being? 3) Which variables of coping with illness and personality predict life satisfaction and mood levels?
2. Methods
2.1. Sample
The sample consisted of N = 97 heart-transplanted participants. 58.8% of the participants were male, 42.1% female, and 0% diverse. At the time of data collection, the average age of the participants was 48.5 years (SD = 15.7), with the youngest participant being 19 and the oldest 97 years old. The subjects were on average 40.6 years (SD = 17) old at the time of HTX. On average, the transplantation was 7.8 years (SD = 8.7) ago. The shortest transplanted have been transplanted for less than one year, while the longest transplanted person for 35 years, which exceeds the mean survival time of 12.5 years by 22.5 years [22]. 36.1% of participants reported spontaneous onset of disease, while 63.9% reported chronic disease. In the spontaneous cases, diseases such as a heart attack or myocarditis were responsible, whereas chronic cases were caused by genetic defects or congenital heart defects, for example. Approximately 54% of the participants reported complications (subjective representation). With regard to marital status, the majority of participants stated that they were married (54.6%), 23.7% stated that they were single, 15.5% stated that they were in a partnership, and 2.1% of participants stated that they were divorced, separated, or widowed.
2.2. Procedure
The data collection is based on an online survey in a cross-sectional design with a random sample from the population of heart transplant patients. All participants gave their informed consent. The data were collected anonymously in accordance with the currently valid data protection regulations and do not allow any conclusions to be drawn about personal data. The data collection lasted 3 weeks. Recruitment took place via the email distribution list of self-help groups and Instagram; therefore, the exact number of individuals who received the invitation cannot be determined. All persons aged 18 and over who had undergone a heart transplant due to a spontaneous or chronic illness were eligible to participate.
2.3. Measures
First, sociodemographic data (e.g., gender, age) were collected. Subsequently, information was collected on the reason for the heart transplant, the age at transplantation, the time in years since transplantation, and subjectively perceived complications. The participants then completed the following measurements:
The Habitual Subjective Well-Being Scale (HSWBS) enables the “measurement of the cognitive dimension of habitual subjective well-being using the General Life Satisfaction Scale and the measurement of the emotional dimension using the Mood Level Scale” with 13 items. The psychometric properties can be considered satisfactory [23].
The Munich Quality of Life Dimensions List (MLDL) with 19 items “is a cross-disease instrument for the dimensional assessment […] of satisfaction with individual areas of quality of life” [24]. It comprises the scales of physical, psychological, and social well-being as well as functional capacity [24] [25].
The End-Stage Renal Disease Symptom Checklist-Transplant Module (ESRD-SCL TM), with 43 items, “is a disease-specific self-assessment method for recording the psychological and physiological quality of life of patients after kidney transplantation with a focus on the side effects of therapy with immunosuppressants” [26] [27]. The subscales used are impaired physical performance, impaired cognitive performance, cardiac and renal dysfunction, cortisone-related side effects, increased hair and gum growth, transplant-associated psychological stress, and the Global Score [27]. However, these subscales are equally suitable for heart and kidney transplant patients.
The Essener Illness Management Questionnaire (EFK) is “a screening procedure for all illnesses […] to record a person’s current coping efforts on an emotional, cognitive, and behavioral level” [28]. It contains 45 items, which are divided into nine subscales [28].
The Big Five Inventory-10 (BFI-10) has ten items to measure and describe overall personality. The five-factor model contains the five abstract dimensions of extraversion, agreeableness, conscientiousness, neuroticism, and openness [29].
The reliability of the questionnaires used, determined by Cronbach’s α, is mostly in the acceptable to very good range (HSWBS questionnaire scales α = 0.915 - 0.916, MLDL questionnaire scales α = 0.86 - 0.91, SUCE-4 α = 0.78, UGTS α = 0.71, ESRD-SCL TM questionnaire scales α = 0.54 - 0.84); for the EFK questionnaire scales, the internal consistency with Cronbach’s α = 0.10 - 0.85 is partly in the insufficient range, as is the case for the BFI-10 scales (Cronbach’s α = 0.30 - 0.68).
2.4. Data Analysis and Statistics
All calculations were performed using IBM SPSS Statistics 29 for Windows. Means (M) and standard deviations (SD) were reported for descriptive data. The assumptions for the calculation of Pearson correlations and t-tests can be assumed to be met. The Pearson correlation coefficient “r” is used to indicate the strength of a relationship. Values of r = 0.2 - 0.3 are considered low, r = 0.3 - 0.5 are considered moderate, and values of r > 0.5 are considered highly significant [30]. Tables three and four only show significant results. Effect sizes were prioritized over p-values because they provide a direct measure of the magnitude and practical significance of an effect, rather than just its statistical detectability.
3. Results
First of all, it should be noted that there were no significant correlations between the age at HTX, the age at the time of the study, the waiting time, and the examined variables of personality, the experience of the disease, and the coping with the disease.
The basic aim of the data collection is to determine specific factors that can influence subjective well-being. In the following, the subjects’ coping with illness, tolerance of uncertainty, and physical and psychological complaints are described and, if available, compared with reference values. When looking at the scores of heart transplant patients in the EFK for coping with illness, it is noticeable that significantly higher scores were achieved in every scale compared to the reference values of chronically ill patients [31] (Table 1). With the exception of the distance and self-construction scale, these mean differences are significant [31]. The values for depressive processing and trivialization are also significantly higher [31].
Only reference values from kidney transplant patients are available for the physical and psychological complaints that were recorded with the ESRD-SCM TM. The impaired physical and cognitive performance are significantly increased compared to the reference values, as are the cortisone side effects and the transplant-associated psychological stress (Table 2).
Table 1. Sickness management surveyed by the EFK in various samples.
Scales |
Present
sample
N = 97 |
Comparative data
for chronically ill
N = 1815 [22] |
t |
p |
M (SD) |
M (SD) |
Action-oriented, problem-oriented coping |
2.52 (0.66) |
2.24 (0.88) |
3.08 |
<0.01 |
Distance & self-assembly |
2.09 (0.63) |
1.96 (0.78) |
1.61 |
<0.12 |
Trivialization, wishful thinking,
threat defense |
1.79 (0.5) |
1.22 (0.71) |
7.8 |
<0.01 |
Depressive processing |
1.21 (0.67) |
0.71 (0.7) |
6.87 |
<0.01 |
Being able to accept help well |
1.89 (0.6) |
1.48 (0.76) |
5.22 |
<0.01 |
Active search for social inclusion |
2.25 (0.81) |
1.93 (0.89) |
3.46 |
<0.01 |
Trust in the art of medicine |
2.76 (0.86) |
2.46 (0.79) |
3.63 |
<0.01 |
Developing inner stability |
1.55 (0.75) |
1.32 (0.81) |
2.73 |
<0.01 |
Notes. M = Mean, SD = Standard deviation, t = t-test for independent samples, p < 0.05.
Table 2. Complaints recorded by the ESRD-SCL TM in various samples.
Scales |
Heart transplant patients in this study
(N = 97) |
Comparative data for kidney transplant patients N = 458 [19] |
t |
p |
M (SD) |
M (SD) |
Impaired physical performance |
1.09 (0.64) |
0.82 (0.61) |
3.93 |
<0.01 |
Impaired cognitive performance |
1.02 (0.66) |
0.75 (0.62) |
3.85 |
<0.01 |
Cardiac and renal dysfunction |
0.76 (0.55) |
0.76 (0.64) |
0 |
1.00 |
Cortisone side effects |
0.9 (0.8) |
0.51 (0.61) |
5.8 |
<0.01 |
Increased hair and gum growth |
0.48 (0.5) |
0.68 (0.7) |
2.49 |
<0.01 |
Transplant-associated psychological stress |
1.06 (0.75) |
0.7 (0.59) |
5.19 |
<0.01 |
Notes. M = Mean, SD = Standard deviation, t = t-Test for independent samples, p < 0.05.
With regard to the examined correlation of personality and physical complaints with well-being, significant moderate positive correlations were found between the personality traits emotional stability and mood level (r = 0.33, p < 0.01), as well as with agreeableness (r = 0.27, p < 0.01). A significant negative correlation was found between neuroticism and mood level (r = −0.40, p < 0.01). Significant moderate negative correlations were found between neuroticism and physical condition (r = −0.28, p < 0.01), mental state (r = −0.46, p < 0.01), and functional capacity (r = −0.26, p < 0.01). The subscales of EFK inner support and problem coping also showed significant moderate positive correlations with both mood level and life satisfaction (see Table 4). There were also moderate positive correlations between the subscales of the EFK and the MLDL with regard to inner support and physical condition (r = 0.32, p < 0.01), inner support and mental state (r = 0.41, p < 0.01), inner support and social life (r = 0.39, p < 0.01), and trust in doctors and physical condition (r = 0.31, p < 0.01), and between problem coping and mental state (r = 0.27, p < 0.01). The subscales of the ESRD-SCL TM were all significantly moderately negatively correlated with those of the HSWBS Table 3. The same was shown for the correlation of the subscales of the ERSD-SCL TM with the subscales of the HSWBS (Table 3). Only the subscales impaired physical performance and social life showed a significant but weak correlation (r = −0.23, p < 0.05), and the subscales cortison side effects and physical condition (r = −0.20, p < 0.05) as well as functional capacity (r = −0.20, p < 0.05).
Table 3. Pearson correlation (r) of personality and physical complaints with well-being.
Questionnaires |
Scales |
BFI-10 |
EFK |
ESRD-SCL TM |
N |
E |
O |
A |
C |
Inner support |
Trust in Doctors |
Problem Coping |
Impaired physical performance |
Impaired cognitive Performance |
Cortisone side effects |
HSWBS |
Mood level |
−0.40** |
0.33** |
0.10 |
0.27** |
0.23* |
0.35** |
0.22* |
0.37** |
−0.50** |
−0.39** |
−0.32** |
Life satisfaction |
−0.32** |
0.25* |
0.16 |
0.25* |
0.18 |
0.40** |
0.20* |
0.34** |
−0.48** |
−0.36** |
−0.29** |
MLDL |
Physical condition |
−0.28** |
0.22* |
0.08 |
0.22* |
0.29 |
0.32** |
0.31** |
0.22* |
−0.42** |
−0.42** |
−0.20* |
Mental
state |
−0.46** |
0.14 |
0.07 |
0.21* |
0.12 |
0.41** |
0.19 |
0.27** |
−0.37** |
−0.42** |
−0.32** |
Social life |
−0.20* |
0.14 |
−0.04 |
0.24* |
0.04 |
0.39** |
0.24* |
0.26* |
−0.23* |
−0.32** |
−0.31** |
Functional capacity |
−0.26** |
0.22* |
0.08 |
0.18 |
0.21* |
0.38 |
0.23* |
0.21* |
−0.38** |
−0.40** |
−0.20* |
Notes. * = Correlation is significant at the <0.05 level (2-tailed), ** = Correlation is significant at the <0.01 level (2-tailed).
In a linear regression model with the aim of quantifying how changes in developing inner stability and neuroticism affect life satisfaction, both independent variables were significant predictors of life satisfaction. The model explained 23.1% of the variance in life satisfaction (R2 = 0.231, adjusted R2 = 0.215). The overall model was significant (F = 14.148, p < 0.001) (Table 4).
Table 4. Linear regression model for predicting life satisfaction.
Variable |
B |
Beta |
SE |
T |
Sig. |
Constant |
4.787 |
|
0.322** |
|
|
Neuroticism |
−0.259 |
−0.269 |
0.088* |
14,857 |
<0.001 |
Developing inner Stability |
0.418 |
0.365 |
0.105** |
−2946 |
0.004 |
R2 |
0.231 |
|
|
|
|
Notes. B = Unstandardized Coefficient, SE = Standard Error, Beta = Standardized Coefficient, *p < 0.005, **p < 0.001.
A further linear regression model was then used to test how changes in the previously used factors, developing inner stability and neuroticism, and the new factor extraversion, influence the mood level. The model’s summary statistics indicate a moderate overall fit, with an R2 of 0.274 (adjusted R2 = 0.251), suggesting that 27.4% of the variance in Mood Level can be explained by the model (Table 5). The overall model also shows significant results (F = 11.698, p < 0.001), in predicting Mood Level. The coefficients reveal that Neuroticism has a negative relationship with Mood Level (B = −0.378, p = 0.001), while developing inner stability and Extraversion show a positive trend. Developing inner stability is statistically significant (B = 0.386, p = 0.005), albeit Extraversion is not statistically significant (B = 0.216, p = 0.073) (Table 5).
Table 5. Linear regression model for predicting mood levels.
Variable |
B |
Beta |
SE |
T |
Sig. |
Constant |
3.907 |
|
0.600** |
|
|
Neuroticism |
−0.378 |
−0.309 |
0.113* |
6512 |
<0.001 |
Developing inner Stability |
0.386 |
0.266 |
0.133* |
−3350 |
0.001 |
Extraversion |
0.216 |
0.173 |
0.119 |
2897 |
0.005 |
R2 |
0.274 |
|
|
|
|
Notes. B = Unstandardized Coefficient, SE = Standard Error, Beta = Standardized Coefficient, *p < 0.005, **p < 0.001.
4. Discussion
The aim of the present study was to identify specific factors influencing subjective well-being in order to derive implications for practice. It became clear that physical well-being has a decisive influence on subjective well-being. However, the question arises as to how good mental well-being can be achieved independently of physical well-being. Even if their physical condition is not good at times, patients should be able to maintain their mental well-being as well as possible. Social life is an enormously important factor, as people who frequently engage in social activities have significantly lower levels of depressive processing, are sometimes able to develop better inner stability, have better coping mechanisms, and are more informed. Despite an increased risk of infection [20], transplant recipients should therefore be encouraged to be socially active and find hobbies that suit them, ideally one that is independent of their physical capacity. As the heart transplant patients in this survey have comparatively high levels of depressive processing and trivialization, the relevance of social activity is very clear.
Particularly in people with chronic heart disease, the levels of depressive processing should be monitored and, if necessary, intervened with before HTX. Personality traits also have an influence on coping with illness and well-being. People who have less control over their emotions and are more extraverted have a higher level of well-being. Since personality traits such as neuroticism are also modifiable factors [32] [33], people with high scores in this area should learn to allow and show their feelings. Psychological support before and immediately after heart transplantation is already common practice in most transplant centers. However, it should also be established in the long-term course to take stock of psychological well-being, coping with illness, and social life at regular intervals, using standardized survey methods. In this way, any need for intervention can be identified early enough and, ideally, the development of mental disorders can be prevented. As this collection, evaluation, and assessment of psychosocial factors entail a significant amount of additional work, it would make sense to hand over this area of follow-up to psychotherapists, psychiatrists, or social workers. These professions should also be involved preventively and not just when problems arise. In this context, psychoeducation on factors influencing subjective well-being and its connection to physical well-being could also be carried out. All patients should be enabled to develop appropriate strategies for coping with their illness and to acquire corresponding resources such as problem-oriented coping mechanisms, strategies for self-construction, opportunities for effective information searches, and much more in order to be able to deal adequately with the stressful experience.
Limitations
As recruitment was conducted through self-help groups and social media, a potential self-selection bias must be considered. This recruitment strategy may have led to an overrepresentation of patients who are more engaged in peer networks, more proactive in seeking information, and more open to participating in psychosocial research. Consequently, the sample cannot be regarded as representative of all heart transplant recipients, and the generalisability of the findings is limited. A key limitation of this study is its cross-sectional design, which precludes any conclusions regarding the direction or causality of the observed associations. While the findings highlight important relationships, they should be interpreted as correlational. Future research employing longitudinal designs would allow for the examination of temporal dynamics and provide stronger evidence regarding potential causal pathways. Furthermore, certain scales of the assessment instruments employed demonstrated only moderate reliability, which should be considered when interpreting the validity of the findings.