ABSTRACT
Objective
The aim of this study is to investigate the relationship between well-being, self-compassion, and adaptation to chronic diseases in older adults.
Methods
The descriptive and correlational study was conducted through face-to-face interviews with older adults with chronic disease who were inpatients at a University of Health Sciences Türkiye, İzmir Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital in İzmir between March 2024 and June 2024. A sampling method for known populations was used to select the sample (n=405). A sociodemographic questionnaire, the Warwick-Edinburgh Mental Wellbeing scale, the self-compassion scale, and the Assessment Scale for Adaptation to Chronic Disease were used as instruments for data collection.
Results
The mean age of the patients was 70.69±3.96 years, 58.3% were male. A positive correlation was found between the participants’ levels of mental well-being and their adaptation to chronic disease (β=0.389) (p<0.01).
Conclusion
The well-being levels of older adults positively affect adaptation to chronic disease.
INTRODUCTION
Chronic illnesses associated with aging, such as diabetes, hypertension, and cardiovascular disorders, adversely affect older adults’ health, particularly in developed countries.1 The World Health Organization (WHO) states that chronic illnesses are long-term non-communicable diseases that typically progress slowly. WHO data show that 41 million people die of chronic diseases each year worldwide, accounting for 74% of global deaths.2 TURKSTAT data show that 78.7% of adults over the age of 65 have at least one chronic illness, such as hypertension, diabetes, or heart disease. These illnesses have a serious impact on older adults’ activities of daily living and increase their dependency.3 In this context, well-being and self-compassion can facilitate adaptation to chronic diseases.
For older adults with chronic illnesses who wish to preserve their quality of life, well-being is a crucial concept. The state of well-being is not limited to physical health; it is also determined by how individuals cope with their illness, the extent of the social support they receive, and their overall satisfaction with life.4 Mental well-being means that the individual is able to cope with stress, form healthy relationships, and contribute to society.5 Studies show that people with an elevated state of mental well-being have stronger immune systems, engage in healthy social relationships, and live longer.6 Self-compassion is defined as individuals’ ability to treat themselves with kindness and compassion.7 This notion refers to the individual’s acceptance that the difficulties faced in life and the pain and disappointments one encounters are a natural part of life and not a cause for merciless self-criticism.8 Self-kindness is the ability to treat oneself with compassion when facing challenges; a sense of common humanity involves understanding that others may be experiencing similar difficulties.9, 10 While self-compassion increases an individual’s ability to be kind to oneself, it also reduces self-criticism and reminds the person that they are not alone. This helps maintain an emotional equilibrium resulting from accepting that negativities are, by nature, part of the human experience.11
As the aging process progresses, the number of chronic diseases increases, and these conditions affect older adults’ physical, mental, and social well-being. The aim of this study is to investigate the relationship among well-being, self-compassion, and adaptation to chronic diseases in older adults.
Research questions
1. Is there a relationship between older adults’ well-being and their adaptation to chronic diseases?
2. Is there a relationship between older adults’ self-compassion and their adaptation to chronic diseases?
METHODS
This is a descriptive and correlational study. This research was conducted from March to June 2024 among patients 65 and older who were inpatients at University of Health Sciences Türkiye, İzmir Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital for pulmonary diseases.
Sample
The study population consisted of inpatients at University of Health Sciences Türkiye, İzmir Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital for pulmonary diseases who were deemed competent to provide informed consent and were conscious, cooperative, and willing to participate in the research. The number of patients included in the sample was calculated using the formula for determining sample size for a known population. Using the formula n=N.t2 pq/d2(N–1) + t2pq, the sample size was computed to be 405 participants. Thus, the study sample comprised 405 inpatients aged 65 and older who volunteered for the research and had at least one chronic illness. According to the post-hoc power analysis conducted after the study, the effect size (ρ) was found to be 0.329.
Significance level (α) 0.05, and the study’s power (1-β) 100%.
Inclusion Criteria: Being age 65 or older, having at least one chronic illness, and consenting to participate in the study.
Exclusion Criteria: Since the instruments used in the study relied on self-reporting, individuals who could not communicate verbally, were not fluent in Turkish, had a mental disability that could hinder comprehension of or response to the questions, or were diagnosed with Alzheimer’s disease were excluded from the study.
Data Collection Instruments
The descriptive data questionnaire prepared by the researchers based on the literature consisted of nineteen items.1, 12 The items queried the patients’ income status, their smoking and alcohol consumption status, and perceived health status.
The Warwick-Edinburgh Mental Wellbeing scale (WEMWBS) was used to measure the participants’ level of mental wellbeing. Developed by Tennant et al.13, this measure was adapted to Turkish by Keldal.5 Higher scores indicate better mental health. Cronbach’s alpha coefficient for the WEMWBS is 0.89.
The self-compassion scale was developed by Neff7 (2003a) to measure self-compassion. The scale is a Likert-type instrument that allows individuals to provide information about themselves. The self-compassion scale consists of 26 items.7 The scale adapted by Deniz et al.14 reported a single-factor structure. In the Turkish adaptation, item analysis indicated an internal consistency reliability coefficient of 0.89.
Assessment Scale for Adaptation to Chronic Diseases (ASACD) was developed by Kacaroğlu Vicdan and Birgili15 to assess individuals’ adaptation to chronic illnesses; validity and reliability testing was carried out. In the validity and reliability study, Cronbach’s alpha reliability coefficient was 0.83. The respondent’s adaptation to chronic ailments increases as the score rises.
Data Collection
The researchers collected data while the patients were receiving treatment at the clinics and in the patients’ rooms.
Data Evaluation
Data were presented as numerical values, percentage distributions, means, and standard deviations. The results were evaluated using 95% confidence intervals and a significance level of p<0.05.
The suitability of the data for a normal distribution was determined using a normality test. Statistical analyses included the t-test, chi-squared test, correlation coefficient (r), Independent samples t-test, one-way ANOVA, Kruskal-Wallis test, Mann-Whitney U test, and Spearman’s correlation analysis. Tukey’s HSD post-hoc test was employed to ascertain differences among several groups.
Ethics Approval
Ethical approval for the study was obtained from the İzmir Bakırçay University Ethics Committee (dated: 21.02.2024, approval number: 1463) and from the University of Health Sciences Türkiye, İzmir Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital where the study was conducted (dated: 28.02.2024, approval number: 4/4). The participants were informed in detail about the objective of the study and the confidentiality of the information, after which their written and verbal consent was obtained.
RESULTS
The average age in the study is 65 years and over (70.69±3.96); 87.7% were between the ages 65-75, 58.3% were males, 72.1% were primary school graduates, 83.2% were married, 71.4% were overweight (body mass index =25-29.9), 66.2% reported income less than their expenditure (Table 1).
A significant difference (p<0.05) was observed between participants’ ages and the ASACD physiological subscale; however, no difference was detected between participants’ ages and the ASACD overall mean score (p>0.05). The study indicated a difference (p<0.05) in the ASACD social and spiritual subscales by participants’ civil status; however, no difference was observed in the overall mean score of the ASACD by civil status (p>0.05). The study revealed a significant difference (p<0.05) in the ASACD spiritual subscale across individuals’ income levels; however, there was no statistically significant difference between economic status and the ASACD total mean score (p>0.05). A significant difference was observed between the participants’ perceived health status and the ASACD overall and subscale mean scores (p<0.05). It was observed that those who perceived their health to be “average” had significantly higher mean scores in their adaptation to their illness (KW =6.625, p=0.036) (Table 2).
A significant difference was observed when comparing the participants’ hospital admissions in the last 6 months with their social subscale and total ASACD mean scores (p<0.05). A difference in knowledge about the illness was observed when comparing the physiological and psychological subscales with the overall ASACD mean score (p=0.003); in the advanced analysis, variances were homogeneous (p>0.05), and therefore the Tukey honestly significant difference (HSD) test was applied. The difference was attributable to the participants with low and moderate levels of knowledge. Those who had a “very sufficient” level of knowledge about their illness had significantly higher mean adaptation scores than those with other levels of knowledge. A difference was found between the physiological and psychological subscale scores for meeting self-care needs and the total ASACD mean score (p<0.01). In the post-hoc analysis, the variances were homogeneous (p>0.05), and the Tukey HSD test was applied (Table 3).
Multiple linear regression analysis revealed that WEMWBS scores accounted for 15.1% of ASACD (adjusted R2 =0.151; F=37.064, p<0.001). A unit increase in the wellbeing scale was found to cause a 0.363-unit increase on the ASACD scale (B=0.363, p<0.001). No statistically significant relationship was found between the self-compassion scale scores and the ASACD (p>0.05) (Table 4).
DISCUSSION
Owing to increasing life expectancy in contemporary populations, the incidence of chronic diseases has risen.16 This study was conducted with a group of individuals with different chronic diseases rather than with individuals with a single disease; when the individuals’ adaptation to their illness was assessed, it was found to be at a moderate level. In the study by Abdan17 individuals diagnosed with chronic illness exhibited an adaptation mean score of (66.38±7.83). Diagnoses among the participants in this study were cardiovascular disease (77.3%), cancer (61%), chronic airway diseases (60.2%), diabetes mellitus (51.6%), and thyroid disease (25.7%). There are similar studies in the literature. In the study by Bilgiç and Pehlivan16 conducted with a group of individuals with different chronic diseases instead of with a group with only a particular disease, it was found that the individuals’ adaptation to their illness was at above moderate. Some studies examining hypertensive patients’ adaptation to drug therapy found high levels of adaptation.18, 19 Another study, however, noted that adaptation to therapy was low.20 Researchers working with individuals with MS found low levels of adaptation to treatment.21 A study of individuals with diabetes reported that psychosocial adaptation to the illness was moderate.22
No statistically significant correlation was identified between participants’ age and their ability to adapt to their illnesses. Özdemir et al.23 similar to Abdan17 no significant association was discovered between age groups and adaption to chronic illness. This result shows that adaptation to chronic disease is not simply tied to age, but other factors can also play an important role in this process. In the study by Cezik24, participants with hypertension had significantly higher ASACD scores. According to the study data, no significant relationship was found between the participants’ gender and their adaptation to chronic disease (p=0.437). The results reported in the literature are similar to ours. For example, Abdan17 and Cezik24 did not detect a significant relationship between chronic disease and gender in their studies, concluding that gender may not be a determining factor in the adaptation process. The results of Abdan’s study17 support this finding. The lack of a significant association between participants’ gender and adherence to antihypertensive therapy in the study conducted by Özdemir et al.23 on geriatric hypertensive patients reflects the general trend observed in the literature. On the other hand, Gupta et al.25 reported in their study conducted in the Czech Republic and in the UK that women show 55% greater maladaptation than men, which suggests that in some cases, gender can have an impact on the adaptation process. In contrast, Shea et al.26 and Ross et al.27 and other researchers have shown that women’s adaptation to treatment is better than men’s. These contradictory findings suggest that the impact of gender on adaptation to chronic disease is associated not only with biological factors but also with socioeconomic conditions, cultural norms, regional differences, and other environmental factors. When considering gender as a determining factor in adaptation to chronic disease, social and cultural factors should also be evaluated. Various findings in the literature stress that considering gender as one of many dynamics influencing adaptation would be a better approach. Health statistics indicate differences in the distribution of chronic illnesses by gender and type.28 In this study, the number of males with chronic disease (58.3%, n=236) was greater than that of females, which is contrary to what is reported in the literature.
According to these results, no statistically significant difference was found between participants’ civil status and their ASACD scores (p=0.218). Findings in the literature support this result. Bilgiç and Pehlivan16 and Abdan17 report that they found no significant relationship between adaptation to chronic disease and civil status, while Özdemir et al.23 similarly reveal in their study with older adults that civil status does not make a significant impact on adaptation to drug therapy. These studies suggest that civil status alone may not predict the degree of adaptation to chronic disease. On the other hand, some studies report that civil status can affect adaptation to chronic disease. For example, it was found in Cezik’s24 study that divorced/widowed individuals had lower adaptation scores while Cooper et al.29 reported in a study conducted in 11 countries that older unmarried adults had lower scores related to their adaptation to drug therapy.
This study found no significant difference in ASACD scores by educational status (p=0.305). Erdoğan Yüce and Muz30, however, did find a relationship between education and adaptation to chronic disease. Individuals with lower educational attainment demonstrated poorer adaptation to chronic disease. Other studies have also reported that adaptation to illness increases with higher levels of patient education.16, 17, 24, 31-35
The relationship between chronic illnesses and income status has been explored in many studies. In particular, the number of chronic diseases is higher in societies with lower socioeconomic levels. It must be said, however, that this does not hold true for all chronic diseases: hypertension, breast cancer, and similar chronic illnesses are reported to be much more prevalent in societies where socioeconomic conditions are better.36
This study revealed a statistically significant correlation between participants’ income levels and the ASACD spiritual subscale (p<0.05); however, no statistically significant difference was observed between participants’ economic status and the total mean score of the ASACD (p>0.05). This suggests that, despite the psychological impact of income status on the ASACD, the overall ASACD score did not differ noticeably. Differing from our results in the literature, the studies on the relationship between income and chronic illness of Abdan17, Cezik24 Erdoğan Yüce and Muz30, and Callaghan37 indicated a significant association between income and adaptation to chronic disease. The WHO reports that low socioeconomic status is associated with poor adaptation to chronic disease.38 Especially if the chronic illness has led to lifestyle changes and dependence on others, the illness may be more difficult to accept, and adaptation may be more difficult.39
A significant difference in ASACD overall and subscale mean scores was found between study participants who were hospitalized in the last 6 months and those who were not (p=0.001). Review of the participants’ hospitalization histories showed that 70.4% had been admitted for a chronic disease in the previous 6 months, and 51.1% had been hospitalized at least once during that period. Since chronic illnesses inherently require longer hospital stays, they account for a significant portion of health service costs and job loss.40
Multiple linear regression analysis revealed that WEMWBS scores accounted for 15.1% of ASACD (adjusted R2=0.151; F=37.064, p<0.001). Since the variables measured in the model in this study are concepts specific to the social sciences and psychology, R-squared values as low as 0.10 to 0.30 are often considered acceptable.41Furthermore, regression analysis revealed no statistically significant relationship between self-compassion scale scores and the ASACD. This may be due to the inclusion of sociodemographic and clinical characteristics in the regression analysis.
Study Limitations
Limitations of the study included its conduct in a single facility and its cross-sectional design, conducted during a defined period.
CONCLUSION
A low, positive relationship was detected between the overall ASACD and WEMWBS. There is no significant association between older patients’ self-compassion and their adaptation to chronic disease. There is a significant association between their levels of mental well-being and their adaptation to chronic disease. Wellbeing is associated with adaptation to chronic disease. In an individual’s later years, a higher sense of mental well-being is conducive to better adaptation to chronic disease. Nurses play an important role in evaluating the well-being of older adults and in planning interventions to increase their well-being, thereby enhancing adaptation to chronic disease. It is recommended that well-being levels be examined in nursing research aimed at improving adaptation to chronic diseases in older adults, and that psychological nursing interventions be planned to enhance well-being.
