Introduction
According to the World Health Organization (WHO), palliative care is defined as care to improve the quality of life of patients who face challenges associated with life-threatening physical, psychological, social or spiritual illness, and their families. It also improves the quality of life of caregivers. Annually, an estimated 40 million people need palliative care; 78% of them live in low- and middle-income countries. Worldwide, only 14% of people in need of palliative care can currently receive it. To increase access, adequate national policies, programs, resources, and training on palliative care for health professionals are needed. The need for palliative care will continue to grow worldwide as a result of the aging of the population and the increasing burden of nontransmittable diseases and some transmittable diseases. Early delivery of palliative care reduces unnecessary hospitalizations and utilization of health services. Palliative care is a fundamental human right for all people, regardless of disease type, income, or age (WHO 2022). Palliative care benefits patients, their families, and the health system by improving symptom management and patient/family satisfaction, reducing unnecessary hospitalizations and procedures for patients approaching the end of their lives, and reducing prolonged grief and post-traumatic time (Çamcı and Oğuz Reference Çamcı and Oğuz2018, Reference Çamcı and Oğuz2023; Çamcı et al. Reference Çamcı, Oğuz and Özdemir2024).
Sleep problems are among the most common and unsustainable symptoms in palliative care patients. This is a burden not only for the patient but also for his/her family and caregivers (Davies Reference Davies2019; Jeon et al. Reference Jeon, Allcroft and Brown2024; Wilson et al. Reference Wilson, Padin and Birmingham2019). More than 60% of palliative care patients have sleep disorders which are strongly associated with increased pain, inflammation, development of depression and delirium, and increased potential for falls (Medic et al. Reference Medic, Wille and Hemels2017; Mercadante et al. Reference Mercadante, Aielli and Adile2015). Poor sleep quality such as falling asleep late, waking up early in the morning, prolonged night awakening periods, nonrestful sleep, and daytime sleepiness are common sleep problems in palliative patients (He et al. Reference He, Sun and Peng2022a; Mercadante et al. Reference Mercadante, Adile and Ferrera2017, Reference Mercadante, Aielli and Adile2015). It has been reported that these problems are present in 30–50% of patients after diagnosis or initiation of treatment. Causes of poor sleep quality may include anxiety, depression, pain, opioid use, fatigue, the cancer treatment itself, and its side effects. Furthermore, symptoms of anxiety and depression can be worsened by poor sleep quality (He et al. Reference He, Sun and Peng2022a; Mercadante et al. Reference Mercadante, Adile and Ferrera2017). In a study conducted with lung cancer patients, it was found that the prevalence of sleep quality, anxiety, and depression were 56.1%, 48.9%, and 56.1%, respectively (He et al. Reference He, Sun and Peng2022a). Sleep disorders are frequently seen in palliative care patients and may be associated with psychological problems. Sleep disorders and psychological issues significantly affect the quality of life. Therefore, it is important to identify and manage sleep quality, anxiety, and depression in palliative care patients (Mercadante et al. Reference Mercadante, Adile and Ferrera2017). This study aimed to determine sleep quality, anxiety, and depression in palliative care patients.
Material and methods
Research objective
This descriptive and correlational study was designed to determine sleep quality, anxiety, and depression in palliative care patients.
Research questions
How is sleep quality in palliative care patients?
What are the anxiety and depression levels of palliative care patients?
Is there a correlation between sleep quality with depression and anxiety in palliative care patients?
Are anxiety and depression significant predictors of sleep quality?
Research place and time
The study was carried out between May 1 and October 31, 2023 in the palliative care wards of a state hospital and a training and research hospital in Istanbul, Turkey.
Research sample
The size of the study sample was calculated using the G*Power 3.1.9.7 program (Faul et al. Reference Faul, Erdfelder and Lang2007). In the calculation, the sample size was calculated for the correlation: bivariate normal model. In the calculation, the sample size was calculated as 84 considering two tails, an effect size of 0.30 (r = 0.30) (Cohen Reference Cohen1988; Polit and Beck Reference Polit and Beck2008), a margin of error of 5% (α = 0.05), a power of 80% (1-β = 0.80), and an h0 correlation value of 0. However, the aim was to reach the largest sample size in the study. In the post hoc power analysis, the power was determined as 0.999 based on two-way analysis, an effect size of 0.421 (correlation between total PSQI and depression r: 0.421), a total sample size of 150, and an h0 correlation value of 0. The sample size was found to be adequate.
Inclusion criteria
Agreeing to participate in the research\approving the informed consent form.
Being able to answer the questionnaire independently or with the help of the researcher.
Being aged over 18 years.
Being hospitalized in a palliative care unit for at least 1 week.
Exclusion criteria
Wishing to voluntarily withdraw from the study during the study period
Having a psychiatric diagnosis
Data collection method and tools
A Patient Information Form, the Pittsburgh Sleep Quality Index, and the Hospital Anxiety and Depression Scale were used for data collection. Data were collected face-to-face in patients’ rooms. It took approximately 20 minutes to answer the questions.
Patient information form
The Patient Information Form was prepared based on the literature review (He et al. Reference He, Sun and Peng2022a; Mercadante et al. Reference Mercadante, Adile and Ferrera2017, Reference Mercadante, Aielli and Adile2015) and consists of 11 questions regarding the patient’s demographic (age, marital status, sex, smoking status, etc.) and medical characteristics (comorbidities, medical diagnosis, etc.).
Pittsburgh Sleep Quality Index
The Pittsburgh Sleep Quality Index (PSQI) was developed by Buysse et al. in 1989. The index questions are answered by considering the last 1 month. In this index, which consists of 24 questions in total, 19 questions are answered by the respondent and 5 questions are answered by the respondent’s bedmate or roommate. The 19 questions answered by the respondents are used in the evaluation of sleep quality. Therefore, these 19 questions in the index were asked of the participants. The 5 questions answered by the person’s bedmate or roommate were not asked. The instrument consists of 7 subscales. These are Subjective sleep quality, Sleep latency, Sleep duration, Habitual sleep efficiency, Sleep disturbances, Use of sleep medication, and Daytime Dysfunction. Each subcomponent is scored between 0 and 3. The scores on the subcomponents are then summed and a total PSQI score is obtained between 0 and 21. A PSQI score below 5 indicates good sleep quality, while a score of 5 or above indicates poor sleep quality (Buysse et al. Reference Buysse, Reynolds and Monk1989). Ağargün et al. determined that it is a valid and reliable instrument in Turkey in 1996 (Ağargün et al. Reference Ağargün, Kara and Anlar1996). In this study, the Cronbach alpha coefficient of the index was 0.72.
Hospital Anxiety and Depression Scale (HADS)
The Hospital Anxiety and Depression Scale was developed by Zigmond and Snaith in 1983. This scale is not a diagnostic tool. It allows for rapid assessment of patients and determination of risk. The scale consists of a total of 14 questions; odd-numbered items identify anxiety and even-numbered items identify depression. Items are scored on a scale between 0 and 3. Items 1, 3, 5, 6, 8, 10, 11, and 13 are scored as 3, 2, 1, 0. Items 2, 4, 7, 9, 12, and 14 are scored as 0, 1, 2, 3. Depression and anxiety are separately scored and a maximum score of 21 is calculated for each (Zigmond and Snaith Reference Zigmond and Snaith1983). The Turkish validity and reliability study of HADS was conducted by Aydemir et al. in 1997. The cut-off point of the anxiety subscale is 10 and the cut-off point of the depression subscale is 7. Values above these are included in the risk group. The Cronbach alpha coefficient was 0.85 for the anxiety subscale and 0.77 for the depression subscale (Aydemir Reference Aydemir1997). In this study, the Cronbach alpha coefficient was 0.66 for anxiety and 0.75 for depression.
Ethical consideration
Verbal and written informed consent was taken from the participants. Ethical approval was granted by the noninvasive clinical trials ethics committee of a university (29.12.2022/133).
Statistical analysis
The data obtained in the study were evaluated in the SPSS statistical program. Frequency and percentage analyses were utilized to determine the descriptive characteristics of the patients, and mean and standard deviation statistics were used to examine the scale. Skewness and Kurtosis values were examined to determine whether the research variables showed normal distribution. Skewness/Kurtosis values were calculated as = −.435/.165 for sleep quality scale, −.051/.642 for anxiety and −.064/.677 for depression. The kurtosis and skewness values of the variables between + 1.5 and − 1.5 or + 2.0 and − 2.0 indicate normal distribution (George and Mallery Reference George and Mallery2019). It was determined that the variables showed normal distribution. Parametric methods were used in data analysis. The correlations between the patients’ scale scores and continuous variables were analyzed using Pearson correlation analysis. Correlation coefficients (r) of 0.00–0.10 were evaluated as insignificant, 0.10–0.39 as weak, 0.40–0.69 as moderate, 0.70–0.89 as high, and 0.90–1.00 as very high (Schober et al. Reference Schober, Boer and Schwarte2018). A multiple linear regression analysis (enter model) was performed to determine the effect of anxiety and depression on sleep quality.
Results
Of the patients, 59.3% were male, 76.7% were married, 45.3% had a cancer diagnosis, 28.7% had a medical diagnosis of cardiovascular diseases, 10.7% had a medical diagnosis of COPD. Of the patients, 64.7% were aged 65 years or over, 52% were illiterate/literate, 72% were unemployed, 78.7% had an income/expense balance, 93.3% lived with their families; 60% quit smoking, 39.3% had hypertension, and 9.3% had diabetes mellitus. The mean body mass index of the patients was 23.88 ± 2.46 kg/m2 (Table 1).
Table 1. Distribution of patients according to descriptive characteristics (n = 150)
The scores of the patients on the seven subscales of PSQI were 1.82 ± .79 for subjective sleep quality, 1.57 ± .84 for sleep latency, 0.40 ± .59 for sleep duration, 1.20 ± 1.42 for habitual sleep efficiency, 2.06 ± .59 for sleep disturbance, 1.47 ± 1.05 for use of sleep medication, and 1.60 ± .86 for daytime dysfunction. The total PSQI score was 10.14 ± 3.54. The mean HADS scores were 11.66 ± 3.60 for anxiety and 11.24 ± 3.76 for depression. The total HADS score was 22.90 ± 6.85. According to the cut-off values of the scales, 89.3% of the patients had poor sleep quality, 61.3% had anxiety, and 86.7% had a risk of depression (Table 2).
Table 2. Sleep quality, anxiety and depression scores of patients (N : 150)
PSQI:Pittsburgh Sleep Quality Index; HADS:Hospital Anxiety and Depression Scale.
There was a moderate positive correlation between subjective sleep quality and HADS-anxiety (r = .431; p < .001), HADS-depression (r = .417; p < .001), and HADS-total (r = .455; p < .001). There was a positive moderate correlation between the total PSQI and HADS-anxiety (r = .466; p < .001), HADS-depression (r = .421; p < .001), and HADS-total (r = .476; p < .001). There was a weak positive correlation between sleep latency, sleep duration, sleep disturbance, use of sleep medication, and daytime dysfunction and HADS-depression and HADS-total (Table 3).
Table 3. Correlation between patients’ sleep quality, anxiety and depression
* < 0.05; ** < 0.01; r: Pearson Correlation; PSQI: Pittsburgh Sleep Quality Index; HADS:Hospital Anxiety and Depression Scale.
A multiple linear regression analysis was performed to determine the effect of anxiety and depression on sleep quality. The model was statistically significant (F(2,147) = 22.024; p < .001). Anxiety (p = .002) was a statistically significant predictor of sleep quality. These variables explained 22% of the total variance of sleep quality (adjusted R 2 = .220) (Table 4).
Table 4. Effect of anxiety and depression on sleep quality
CI.:confidence interval; SE: standard error; β:standardized regression coefficient; HADS:Hospital Anxiety and Depression Scale.
Discussion
In this study, patients were found to have poor sleep quality and a high risk of anxiety and depression (Table 2). In a study conducted with patients with advanced liver disease, the risks of poor sleep quality, anxiety, and depression were reported to be 56.1%, 48.9%, and 56.1%, respectively (He et al. Reference He, Sun and Peng2022b). Mercadante et al. revealed that more than 60% of palliative care patients had sleep disorders (Mercadante et al. Reference Mercadante, Aielli and Adile2015). In some studies, the prevalence of poor sleep in palliative care patients has ranged between 60% and 80%(Bernatchez et al. Reference Bernatchez, Savard and Ivers2016, Reference Bernatchez, Savard and Savard2018; Hugel et al. Reference Hugel, Ellershaw and Cook2004; Mercadante et al. Reference Mercadante, Adile and Ferrera2017; Renom-Guiteras et al. Reference Renom-Guiteras, Planas and Farriols2014; Sela et al. Reference Sela, Watanabe and Nekolaichuk2005). In studies, approximately 50% of palliative care patients have been found to be at risk for anxiety and depression (Atinafu et al. Reference Atinafu, Demlew and Tarekegn2022; Bužgová et al. Reference Bužgová, Jarošová and Hajnová2015; Delgado-Guay et al. Reference Delgado-Guay, Parsons and Li2009; Gontijo Garcia et al. Reference Gontijo Garcia, Meira and de Souza Ah2023; Wilson et al. Reference Wilson, Chochinov and Graham Skirko2007). In this study, similar results to the above-mentioned studies were observed. Sleep problems, anxiety, and depression are very common in palliative care patients. Symptom control is important in palliative care patients. Good symptom management results in a better quality of life. Therefore, pharmacological and nonpharmacological methods should be implemented for sleep problems, anxiety, and depression in patients.
In this study, a moderate positive correlation was determined between total sleep quality score and anxiety and depression (Table 3). In a study conducted with patients with advanced liver disease, it was found that there was a correlation between sleep quality, anxiety, and depression (He et al. Reference He, Sun and Peng2022b). Mercadante et al. and Yennurajalingam et al. reported a positive correlation between anxiety and depression scores and sleep disorders (Mercadante et al. Reference Mercadante, Aielli and Adile2015; Yennurajalingam et al. Reference Yennurajalingam, Tayjasanant and Balachandran2016). In several studies, a correlation has been found between sleep quality score and anxiety and depression (Mercadante et al. Reference Mercadante, Adile and Ferrera2017; Renom-Guiteras et al. Reference Renom-Guiteras, Planas and Farriols2014; Sela et al. Reference Sela, Watanabe and Nekolaichuk2005; Zengin and Soyaslan Reference Zengin and Soyaslan2024). Similar results have been found in the above-mentioned studies. The psychological state of patients affects their sleep quality. Even sleep problems may cause psychological problems.
In this study, anxiety was found to be a statistically significant predictor of sleep quality whereas depression was not (Table 4). In the study conducted by Mercadante et al. with palliative care patients, anxiety and depression were found to affect sleep quality according to multivariate regression analysis (Mercadante et al. Reference Mercadante, Adile and Ferrera2017). In another study, it was found that hopelessness was a predictor of sleep quality in the multiple regression analysis. Depression was not found to be a significant predictor (Mystakidou et al. Reference Mystakidou, Parpa and Tsilika2007). The results of the study of Mercadante et al. do not support this study, while the study conducted by Mystakidou et al. revealed similar results to this study. Anxiety, unhappiness, and stress affect sleep quality due to excessive secretion of sympathetic hormones. Depression symptoms differ between individuals. Some individuals experience insomnia, while others tend to sleep. For this reason, only anxiety is considered to be a significant predictor in this study.
Conclusion
It was found that patients had poor sleep quality and a high risk of anxiety and depression. A moderate positive correlation was found between total sleep quality score and anxiety and depression. Anxiety was determined to be a statistically significant predictor of sleep quality. Sleep disorders are quite common in palliative care patients. It significantly affects the quality of life of patients suffering from terminal illnesses. It is important to realize that poor sleep quality is not an inevitable and untreatable consequence of the end-of-life process. Palliative patients do not report or are not adequately questioned by health professionals. Sleep can be improved through various pharmacological and nonpharmacological interventions. Poor sleep affects quality of life and can increase the severity of symptoms such as pain, depression, or anxiety. Moreover, psychological problems affect sleep quality. The high prevalence of anxiety and depressive symptoms indicates a need for psychological support.
Data availability statement
The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.
Acknowledgments
We would like to thank all participants who took part in our study.
Author contributions
G.Ç., S.O., Ö.O., and Ö.A. made a substantial contribution to the concept and design of the work. G.Ç., Ö.O., and Ö.A. led the data aggregation. G.Ç., S.O., Ö.O., and Ö.A. substantially contributed in the interpretation of data. G.Ç., S.O., Ö.O., and Ö.A. drafted the article and all authors revised it critically. All authors reviewed the manuscript for intellectual content. All authors have reviewed and agreed this version.
Funding
No funding was received for this project.
Competing interest
All authors declare that they have no competing interests.
Ethical Approval
Ethical approval for the study was obtained from Marmara University, Faculty of Health Sciences, Non-Invasive Clinical Research Ethics Committee (29.12.2022/133).
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