The Effect of the Bright White Light Application to Cancer Patients Receiving Palliative Care on Their Fatigue Level and Sleep Quality: A Randomized Control Trial

Abstract

This study aimed to examine the effect of bright white light on the fatigue level and sleep quality of cancer patients receiving palliative care. The study sample consisted of 52 patients who met the inclusion criteria and were assigned to the study or control group by stratified randomization. The bright white light (10,000 lux) or dim red light (<50 lux) was applied for 30 minutes every morning for 14 days to the patients in the study and control group. In the study, bright white light significantly decreased the level of fatigue and the level of fatigue-related effect on daily life activities, improved sleep quality and increased total sleep time (p < 0.05). It was found that dim red light significantly decreased the level of fatigue and increased the sleep quality, but this change was lower than the study group (p < 0.05).

Keywords

cancer fatigue sleep quality palliative care nursing

Background

Cancer-related fatigue is a symptom that can be frequently seen in cancer patients depending on the disease and treatment. It affects the quality of life negatively, and its incidence is reported to be 59–100%. In cancer patients receiving palliative care, fatigue is among the most common symptoms, and its incidence is 80–99%. It is reported that awareness of the fatigue symptom experienced by cancer patients in the palliative care process is low and often its management is neglected. (Ingham & Urban, 2020; Nzwalo et al., 2020).

Cancer-related sleep disorders are another disturbing symptom that patients experience quite frequently and can be seen in all stages of the disease, especially in advanced stages. Cancer patients experience sleep disturbances due to multiple factors such as preexisting conditions, pain, side effects of cancer treatment, fatigue, stress, anxiety, and depression. Previous studies indicated that the prevalence of sleep disorders was 5–35% in the general population and 25–95% in cancer patients (Guiteras et al., 2021; Hugel et al., 2004; Lavdaniti, 2019).

Cancer-related fatigue and sleep disorders are closely related symptoms, commencing before the diagnosis of cancer, increasing during the treatment, and can often be seen after the treatment too. Fatigue and sleep disorders have been reported to negatively affect patients physically, psychologically, cognitively, and socially in multiple aspects (i.e., functional independence, muscle strength, concentration, perception, work, family care, social relations, and sexuality) and reduce their quality of life, especially in advanced-stage cancers (Bozkurt Kozan & Uğur, 2018; Charalambous & Kouta, 2016; LaVoy et al., 2016; O’Higgins et al., 2018). In the palliative care of cancer patients, regular evaluation of the symptoms of fatigue and sleep disorders through the patients’ expressions both quantitatively and qualitatively, determining related factors, and implementing appropriate interventions are important. Pharmacological and non-pharmacological methods are recommended to be used together in the management of fatigue and sleep disorders. (NCCN, 2020; Nzwalo et al., 2020; Özkan & Akın, 2017; Strik et al., 2021; Thong et al., 2020; Verkissen et al., 2019).

The use of bright white light (BWL) is one of the alternative methods used in the management of fatigue and sleep disorders associated with cancer. Compared to other methods, the BWL instigates less cost and less burden for patients and is one of the alternative approaches recommended in clinical guidelines. BWL is applied in the early hours of the morning, often for 30–90 minutes, through exposure to high-intensity fluorescent light (10,000 lux) emitted from a light source. BWL regulates the circadian rhythm by stimulating the suprachiasmatic nucleus in the hypothalamus. Studies have reported that the BWL corrected the disorders in circadian rhythm and had positive effects on fatigue and sleep quality (Ancoli-Israel et al., 2012; NCCN, 2020; Redd et al., 2014; Wu et al., 2018).

Bright white light is an easy-to-use tool that can be employed among nursing interventions for the management of fatigue and sleep disorders of the cancer patients in the palliative care and can increase the patients’ quality of life. It is important for nurses to be aware of pharmacological and non-pharmacological methods for the management of fatigue and sleep disorders and to include these methods in nursing interventions during patient care (Bozkurt Kozan & Uğur, 2018; Charalambous & Kouta, 2016; LaVoy et al., 2016; O’Higgins et al., 2018). BWL could strengthen the interventions by nurses, who play a key role in delivering a holistic patient care, to control symptoms during palliative care of cancer patients. In this context, this study aimed to determine the effect of the BWL on the fatigue level and sleep quality of cancer patients hospitalized in the palliative care unit.

Methods

Study Design

This study was a randomized controlled trial, which investigated the of BWL with a luminescence of 10,000 lux on the fatigue level and the sleep quality of the patients by comparing it with dim red light (DRL) at a luminescence of less than 50 lux.

Study Setting

The study was conducted between November 15, 2018, and November 15, 2019, in the Palliative Care Unit (PCU) of a university hospital. The unit is part of a research center and provides services to all patients in need of palliative care and their families. The BWL or DRL were applied in the rooms where the patients were hospitalized.

Study Participants

The study included 52 cancer patients, 26 in the study group and 26 in the control group, among the cancer patients who were hospitalized in the PCU of a university hospital in the last year. The individuals were assigned to the study or control group in equal numbers and randomly by a biostatistician using the stratified (by sex) randomization method. The individuals were initially stratified according to sex, then males and females were included in the study and control groups in a balanced way by block randomization method. The randomization list was created with R software (version: 3.5.3, package: blockrand, R Foundation for Statistical Computing, Vienna, Austria; http://r-project.org). The researchers and patients were blinded to the randomization list until the time of light application.

Inclusion Criteria

(a) Being 18–65 years old; (b) Being conscious and able to communicate; (c) Scoring 5 points or above in the Pittsburgh Sleep Quality Index (PSQI); (d) Scoring 4 points or above on the Brief Fatigue Inventory (BFI); (e) Not having photosensitivity, eye disease, or contact lenses

Exclusion Criteria

(a) Being under 18 or over 65; (b) Being pregnant; (c) Having a history of traumatic brain injury; (d) Taking medications that may cause photosensitivity; (e) Having a history of eye trauma or acute optic neuritis within the last 3 months; (f) Having head and neck cancers or metastases in this area.

Baseline Period

In the initial interview (Day 0/Z1), the patients were informed about the purpose of the study. The participants were informed about how, when, and how often the researcher would use the lightbox; they were allowed to ask questions about the procedures; and their written informed consent was obtained. In the interview, Patient Information Form (PIF), Brief Fatigue Inventory (BFI), and the Pittsburgh Sleep Quality Index (PSQI) were used to evaluate the eligibility of the patients to participate. The patients included in the study were given smart wristbands to measure their sleep times, which were accessed through an application installed on participants’ smartphones. (Figure 1).

Figure 1.

Consort diagram.

Practice Period

During the practice period, bright white light (BWL) and dim red light (DRL) were applied to the study and control group, respectively. A standard intensity light source with a luminescence of 10,000 lux was used for the BWL; a light source with a luminescence of below 50 lux was used for the DRL. For both groups, the researcher performed the light application at a distance of approximately 20–30 cm to the field of view (the distance was determined by a digital light meter) for 30 minutes every morning for 14 days after their wake-up time (generally between 7 and 10 a.m.). BFI and PSQI were reapplied on day 14 (Z2) and day 28 (Z3). Sleep time measurements were repeated with smart wristbands on day 7 and day 14. During the light application phase of the study (the first 14 days), the factors that may affect patients’ sleep quality and the side effects of light applications were evaluated and recorded in the Patient Monitoring Form by the investigator every day (Figure 1).

Study Instruments

Patient information form included 17 questions produced based on literature review and probed descriptive characteristics of the patients, including socio-demographic features, height, weight, and disease diagnosis, stage, and duration (Bozkurt Kozan & Uğur, 2018; Charalambous & Kouta, 2016; LaVoy et al., 2016; O’Higgins et al., 2018).

Brief fatigue inventory consists of 10 questions that evaluate the general fatigue level and the effect of fatigue on daily activities. The scale is scored from 0 to 10: 0 indicates no fatigue and no effect, 1–2 very low level of fatigue or effect, 3–4 low level, 5–6 medium level, 7–8 high level, 9–10 very high level (Mendoza et al., 1999).

Pittsburgh sleep quality index consists of 24 questions seven components (Subjective sleep quality, Sleep latency, Sleep duration, Sleep efficiency, Sleep disorder, Use of sleep medication, and Daytime dysfunction). Total PSQI score ranges from 0 to 21 where higher scores indicate poor sleep quality. A PSQI score above five indicates significantly impaired sleep quality (Faulkner & Sidey-Gibbons, 2019).

Patient monitoring form recorded environmental factors that may affect the patient’s sleep quality, such as temperature, lighting, and noise in the room where the patient sleeps. PMF also recorded daily the side effects (burning, itching, etc. of the eye) that patients might have experienced due to the light exposure.

Light Sources and Other Tools Used in the Study

The light source used for the BWL was a specially designed lightbox with a light intensity of 10,000 lux and a lighting surface of 45 × 31 cm. The lightbox had two 36-Watt fluorescent lamps with a color temperature of 6500 K and did not emit ultraviolet light. A red LED light source with less than 50 lux was used for the DRL.

Smart wristbands were used in the study to monitor the sleep times of patients who were exposed to light.

Digital light meter was used to apply the light at the determined luminescence values in a standardized manner by measuring the distance to obtain 10,000 lux for the BWL and 50 lux for the DRL and placing the light source at this distance.

Statistical Analyses

Data analyses were performed with the SPSS statistics package (SPSS Statistics for Windows, Version 25.0, IBM Corp. Armonk, NY) and R software (Version 3.5.2, Package: nparLD, R Foundation for Statistical Computing, Vienna, Austria; http://r-project.org). Numerical data were presented as mean, standard deviation (SD), median, minimum, maximum values; categorical data were presented as frequency and percentages. The level of significance (p-value) was set at 0.05 in all analyses (excluding interaction, p < 0.1). The assumption of normality in quantitative variables was checked separately with the Shapiro-Wilk test for the groups and time points to be compared. The duration of the disease was compared using the Mann–Whitney U test. The socio-demographic characteristics of the participants were analyzed using the Pearson chi-square test. Time-dependent changes in the fatigue level, the fatigue-related effect on daily life activities, and total sleep time for the groups were analyzed with Brunner-Langer model (F1-LD-F1 design), a non-parametric method, using R. When the time-dependent changes in the groups were not similar in the Brunner-Langer model (interaction <0.1), the comparison in each group was performed separately with Brunner Langer (LD-F1 design) and the paired comparisons were given with Bonferroni correction. For the first follow-up period, the groups were compared using the Mann–Whitney U test. Then, the Z2-Z1 and Z3-Z1 differences were taken and the groups were compared with the same test. The changes in total PSQI scores of the groups were analyzed using a linear mixed model (LMM) where the individuals were considered as a random effect (as the random cut-off point for each person) and the time and groups were taken as the fixed effect. When the interaction was found to be statistically significant, the time-dependent change in each group was examined separately, and pairwise time comparisons were performed by applying Bonferroni correction to the t-test results using the differences between least-squares estimates.

Results

Information on the socio-demographic and clinical characteristics of the patients in the study and control groups are presented in Table 1. Analyses indicated that the groups were similar in terms of socio-demographic and clinical characteristics (p > 0.05) (Table 1).

Table 1.

Socio-Demographic and Clinical Characteristics of the Patients.

Variables	Study Group (n = 26)		Control Group (n = 26)		Total (n = 52)		p
Variables	n	%	n	%	n	%	p
Age Groups (years)
<57 years	12	46.2	14	53.8	26	50.00	0.579
>57 years	14	53.8	12	46.2	26	50.00	0.579
Sex
Female	13	50.00	13	50.00	26	50.00	1.000
Male	13	50.00	13	50.00	26	50.00	1.000
Education
Primary Education	18	69.23	9	34.62	27	51.92	0.044
Secondary Education	4	15.38	9	34.62	13	25.00
Undergraduate/Postgraduate	4	15.38	8	30.77	12	23.08
Occupation
Housewife	11	42.31	5	19.23	16	30.77	0.071
Officer	0	0.00	5	19.23	5	9.62
Employee	2	7.69	3	11.54	5	9.62
Retired	10	38.46	12	46.15	22	42.31
Other	3	11.54	1	3.85	4	7.69
Marital Status
Married	21	80.77	16	61.54	37	71.15	0.126
Single	5	19.23	10	38.46	15	28.85	0.126
Diagnosis Time (months)
<23 months	13	50.00	13	50.00	26	50.00	1000
>23 months	13	50.00	13	50.00	26	50.00	1000
Cancer Type
Breast Cancer	3	11.54	4	15.38	7	13.46	0.508
Gynecological Cancer	5	19.23	1	3.85	6	11.54
Gastrointestinal Cancer	7	26.92	12	46.15	19	36.54
Lung Cancer	2	7.69	1	3.85	3	5.77
Head and Neck Cancer	4	15.38	4	15.38	8	15.38
Urological Cancer	5	19.23	4	15.38	9	17.31
Cancer Stage
Stage II	2	7.69	2	7.69	4	7.69	0.504
Stage III	8	30.77	12	46.15	20	38.46
Stage IV	16	61.54	12	46.15	28	53.85
Past Treatments
Chemotherapy	17	65.38	15	57.69	32	61.54	*
Radiotherapy	4	15.38	6	23.08	10	19.23
Surgical Treatment	4	15.38	7	26.92	11	21.15
Hormone Therapy	1	3.85	0	0	1	1.92
Current Treatments
Pain Treatment	5	19.23	2	7.69	7	13.46	0.276
Medical Nutrition	1	3.85	0	0.00	1	1.92
Antibiotic Therapy	1	3.85	0	0.00	1	1.92
Medical Nutrition + Pain treatment + Antiemetic Therapy	19	73.08	24	92.31	43	82.69
Non-Cancer Comorbidity
Yes	7	26.92	6	23.08	13	25.00	0.943
No	19	73.08	20	76.92	39	75.00	0.943

p < 0.05; Significance level.

*Due to the insufficient number of cases in the groups, the results were presented as descriptive only, no test statistics were given.

The patients in the study and control groups were monitored in terms of their sleep environments and the side effects that may develop during light application throughout the study period. All of the patients (100%) were found to avoid stimuli such as tea/coffee/alcohol before sleep, the sleep environments were dimly lit and had temperatures of 24–25°C, and their sleep was not interrupted by any sound or noise. None of the patients (0%) developed side effects such as dryness, stinging, and burning in the eyes, redness in the face/arms, skin sensitivity, irritability, headache, nausea and vomiting, and changes in body temperature during the light application.

It was found that the BWL significantly reduced the fatigue level score (by 25.09%) at the end of the application. The DRL applied to the control group also reduced fatigue level score significantly although the reduction was smaller (by 4.08%) than it was with the BWL. In terms of the change in the fatigue level during the follow-up periods in the study and control groups, it was found that the interaction (p < 0.001) and the time-dependent change were significant (p < 0.05). In the pairwise comparisons of the fatigue levels at various follow-up time points in the study and control groups, the changes between Z1 and Z2 and between Z1 and Z3 timepoints were significant (p < 0.05) for both groups but the change between the Z2 and Z3 timepoints was not significant for either group (p > 0.05) (Table 2).

Table 2.

The Comparison of Patients’ Brief Fatigue Inventory Sub-Dimension Scores.

	Fatigue Level (N = 52)		Fatigue-Related Effect on Daily Life Activities (N = 52)
	Study Group (n = 26)	Control Group (n = 26)	Study Group (n = 26)	Control Group (n = 26)
Follow-up Periods	Mean ± SD	Mean ± SD	Mean ± SD	Mean ± SD
Z1	7.77 ± 1.10	7.84 ± 0.79	7.44 ± 1.25	7.66 ± 0.80
Z2	5.82 ± 1.11	7.52 ± 0.95	5.50 ± 1.22	7.40 ± 1.01
Z3	5.91 ± 0.92	7.48 ± 0.91	5.57 ± 1.11	7.44 ± 0.89
Interaction	p < .001		p < .001
Group	p < .001		p < .001
Time	p < .001		p < .001
Timepoint Comparisons	Study Group (n = 26)	Control Group (n = 26)	Study Group (n = 26)	Control Group (n = 26)
(Z1, Z2, Z3)	p < .001	p < .001	p < .001	p = .012
Z1–Z2	p < .001	p = .010	p < .001	p = .115
Z1–Z3	p < .001	p < .001	p < .001	p = .117
Z2–Z3	p = 1.000	p = .946	p = 1.000	p = 1.000

Abbreviations: SD: Standard deviation; Z1: day 0; Z2: day 14; Z3: day 28.

p < 0.05 Significance level.

It was found that the BWL significantly reduced the BFI subscale scores indicating the fatigue-related effect on daily life activities in the study group (by 26.07%). A significant but smaller decrease (by 2.10%) was found in the control group. In terms of the change in the fatigue-related effect on daily life activities during the follow-up periods in the study and control groups, it was found that the interaction (p < 0.001) and the time-dependent change were significant (p < 0.05). In the pairwise comparisons of the fatigue-related effect on daily life activities at various follow-up time points in the study group, the changes between Z1 and Z2 and between Z1 and Z3 timepoints were significant (p < 0.05) but the change between the Z2 and Z3 timepoints was not significant (p > 0.05). In the control group, however, no significant difference was found between the scores at different time points (p > 0.05; Table 2).

The average sleep quality score of the patients in the study group was 16.69 ± 2.18 at Z1 timepoint, 8.96 ± 2.59 at Z2, and 9.07 ± 2.81 at Z3. These scores were 14.34 ± 3.86, 13.38 ± 3.91, and 12.76 ± 4.25 in the control group, respectively. In the analyses of the changes in the sleep quality scores during the follow-up period, the interaction (p < 0.001) and the time-dependent changes were statistically significant (p < 0.05). In the pairwise comparison of the sleep quality scores at different time points, the differences between Z1 and Z2 and between Z1 and Z3 were found to be statistically significant in both groups (p < 0.05). However, no significant difference was found between the scores at Z2 and Z3 timepoints (p > 0.05) It was found that the time-dependent change in the total sleep time of the patients in the study group was statistically significant (p < 0.001), but the change in the control group was not significant (p > 0.05) (Table 3).

Table 3.

The Comparison of the Pittsburg Sleep Quality Index Scores and Total Sleep Times.

	Pittsburg Sleep Quality Index (N = 52)		Total Sleep Time (Minutes) (N = 52)
	Study Group n = 26	Control Group (n = 26)	Study Group (n = 26)	Control Group (n = 26)
Follow-up Periods	Mean ± SD	Mean ± SD	Mean ± SD	Mean ± SD
Z1	16.69 ± 2.18	14.34 ± 3.86	335.30 ± 80.59	351.07 ± 74.69
Z2	8.96 ± 2.59	13.38 ± 3.91	388.57 ± 82.43	354.69 ± 64.91
Z3	9.07 ± 2.81	12.76 ± 4.25	387.34 ± 72.50	358.61 ± 68.41
Interaction	p < .001		p < .001
Group	p = .026		p = .259
Time	p < .001		p < .001
Timepoint comparisons	Study group (n = 26)	Control group (n = 26)	Study group (n = 26)	Control group (n = 26)
(Z1, Z2, Z3)	p < .001	p = .003	p < .001	p = .061
Z1–Z2	p < .001	p = .037	p < .001	p = .326
Z1–Z3	p < .001	p < .001	p < .001	p = .094
Z2–Z3	p = .800	p = .180	p = .171	p = .896

Abbreviations: SD, Standard deviation; Z1, day 0; Z2, day 14; Z3, day 28.

p < 0.05 Significance level.

Discussion

The use of BWL therapy is one of the recommended interventions in the management of cancer-related fatigue and sleep disorders. Due to its role in regulating the circadian rhythm, the National Comprehensive Cancer Network (NCCN) and the American Oncology Nursing Association (ONS) recommend the BWL therapy involving the exposure to high-intensity fluorescent light at 10,000 lux for 30–90 minutes in the early morning hours as a non-pharmacological intervention. (NCCN, 2020; ONS, 2018).

Previous studies reported positive effects of BWL on the fatigue symptom perceived by patients at all stages of the cancer process. Redd et al. investigated the effect of the systematic light application on the fatigue levels of 36 patients who had been diagnosed with breast and gynecological cancer and completed their treatment programs and demonstrated that BWL resulted in a significant reduction in the fatigue levels of the patients (Redd et al., 2014). In another study, 39 newly diagnosed breast cancer patients received stage I–III chemotherapy accompanied by a 30-minutes-long BWL or DRL exposure in the morning during the first four cycles of the treatment (Ancoli-Israel et al., 2012). The BWL was found to prevent severe fatigue during chemotherapy. Weiss et al. (2018) reported that the BWL application in the morning hours for a week was sufficient to reduce fatigue and improve sleep quality (Weiss et al., 2018). They also showed that the level of fatigue remained low after light therapy. A randomized controlled trial by Johnson et al. (2018) compared the effects of a month-long BWL and DRL therapies on the fatigue, mood, and quality of life in individuals who survived cancer and demonstrated the reduction in the fatigue levels of the individuals receiving the BWL therapy was 17% larger than that in the individuals receiving the DRL therapy (Johnson et al., 2018). The results of this study were in line with previous studies and demonstrated that BWL therapy is an effective treatment to reduce the fatigue levels in cancer patients receiving palliative care. In addition, it was shown that the positive effects of BWL therapy continued after the application and there was no increase in patients’ fatigue levels. The study is of clinical significance because it includes cancer patients receiving palliative care where symptom management is critical and there is a lack of studies targeting this patient group.

In the analysis of the change in the patients’ sleep quality throughout the follow-up time points, it was found that the sleep quality increased over time in both the study (BWL) and control (DRL) groups significantly. However, the increase was more pronounced in the BWL group. Moreover, it was found that there was no significant change in the sleep quality of the patients in these groups throughout the Z2 and Z3 follow-up timepoints, when there was no light therapy applied. It was found in previous studies that the BWL source did not produce the same effect on sleep quality in treatment groups and that the BWL on cancer patients receiving palliative care had an effect on sleep quality. In a randomized controlled trial, Özkaraman et al. (2018) applied BWL (10,000 lux) for 30 minutes a day for a week to breast cancer patients who reported low sleep quality and found that the patients in the treatment group had decreased sleep quality scores albeit not significantly (Özkaraman et al., 2018). They concluded that, unlike in this study, the BWL did not affect sleep quality. Improvement was reported in the sleep quality of patients in another similar study evaluating the effect of BWL on fatigue and sleep quality in patients with lung cancer.²¹ In another study, BWL (10,000 lux) was reported to improve sleep quality in elderly individuals (Akyar & Akdemir, 2011). Our research results support many studies in the literature and show the positive effect of BWL on the sleep quality of cancer patients receiving palliative care. In this study, in addition to the findings in the literature, it was shown that the positive effect of BWL application on sleep quality continued during the follow-up periods when the application was not performed. It is thought that our research results contribute to the literature in this respect.

Problems such as difficulty falling asleep, waking up frequently during the night, difficulty in returning to sleep, and waking up early in the morning are frequently reported by cancer patients and affect the sleep duration negatively. Other symptoms such as cancer-related fatigue and pain, cognitive problems, or depressed mood, which are often seen together in patients, prevent patients from getting adequate sleep (Hugel et al., 2004).

In this study, it was found that the total sleep duration of the patients in the BWL group increased significantly over time but the total sleep duration of the patients in the DRL group did not change significantly. In a study investigating the effect of BWL on sleep quality in patients with breast, gynecological and hematological cancer who reported fatigue, the sleep duration tended to increase over time in the BWL group albeit not significantly (Wu et al., 2018). In a controlled study of participants with sleep disorders, Lack et al. (2007) applied BWL in the morning hours for a week and found that the sleep duration was significantly prolonged in the treatment group compared to the control (DRL) group (Lack et al., 2007). The results of the study were similar to those in previous studies and indicated a significant increase in the total sleep time of the patients in the study group. Studies evaluating the effect of BWL on sleep duration are limited in the literature. In this study, the effect of BWL on sleep in cancer patients receiving palliative care was evaluated with different measurement tools. In addition to the sleep quality assessment based on the self-report of the patients, the sleep duration was measured with the smart wristband. In this respect, our research results provide objective data in the evaluation of the effect of BWL on sleep duration in cancer patients receiving palliative care.

Limitations of the Study

That the study was conducted with cancer patients receiving inpatient treatment in a single palliative care unit was among the limitations of the study.

Conclusion

The results of this study support the findings of previous studies and show that the BWL can have a positive effect on the management of fatigue and the improvement of sleep quality in cancer patients receiving palliative care. Therefore, we suggest that the cancer patients in palliative care should be evaluated for symptoms such as fatigue and sleep problems; BWL can be used for to manage fatigue and sleep disorders and increase the comfort and quality of life in cancer patients; the patients, their relatives, and health professionals, especially nurses, should be informed about BWL, the patients and their relatives should be encouraged to use BWL in cases of fatigue and sleep disorders outside the hospital.

Footnotes

Acknowledgments

We thank all of our patients who participated in the study and the Palliative Care Unit employees. We also thank Prof. Dr Mehmet Nurullah ORMAN, Head of Ege University Faculty of Medicine Department of Biostatistics and Medical Informatics who provided consultancy in the statistical evaluation of the study.

Ethical Approval

Written permission was obtained from the Clinical Research Ethics Committee at Ege University School of Medicine (Date: 01/11/2018/Number: 99166796-050,06,04) and the institution where the study was conducted (Number: 75885935-100). Permissions were obtained from the authors who conducted the validity and reliability study of the BFI and PSQI. Written informed consent was obtained from the participants of the study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Ege University Board for Scientific Research Projects within the scope of the graduate thesis (Approval #: TDK-2019-20473, Date: 11.01.2019).

ORCID iDs

Ayşegül Çelik

Öznur Usta Yeşilbalkan

Author Biographies

Celik Aysegul, RN, PhD Assistant Professor, Izmir Bakircay University Faculty of Health Science, Department of Nursing, Izmir,Türkiye.

Öznur USTA YEŞİLBALKAN, Prof. Dr. EGE ÜNİVERSİTESİ, HEMŞİRELİK FAKÜLTESİ, Türkiye.

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