Introduction
The sleep-wake cycle results from a process that interacts with the homeostatic sleep process and the circadian rhythm. The endogenous circadian clock is compatible with the individual’s sleep-wake cycle. The time individuals prefer to perform their daily activities and the time they prefer to sleep may vary. Circadian rhythms also adapt to these external factors. The differences resulting from this adaptation are called chronotype [1].
Sleep is very important and necessary for physical and mental health. In sleep deprivation, dysfunctions in the immune system, cardiovascular system, metabolic disorders, memory, and consciousness disorders might be observed. Therefore, sleep-related problems in environments that affect sleep, such as the intensive care environment, can bring pain, anxiety, and delirium, and may be associated with prolonged stay in intensive care and higher mortality [2, 3]. Frequent use of artificial lighting, noise, care and treatment practices, diagnostic procedures, and drugs such as sedatives in intensive care environments; and pathophysiological reasons such as stress, organ dissections, pain, anxiety, delirium and inflammatory response caused by the disease reduce sleep quality in intensive care [4, 5]. Chronic pain patients are reported to be up to 18 times more likely to be diagnosed with clinical insomnia compared to those without pain [6]. This highlights the direct impact of chronic pain on sleep quality and its implications for overall health, particularly in intensive care settings. It is emphasized in the literature that conditions frequently encountered in intensive care, such as pain [7], anxiety [8, 9] and delirium [10, 11], may negatively affect sleep quality and cause disruptions in circadian rhythm. Anxiety, commonly observed in intensive care patients, also significantly impairs sleep quality [3]. Thus, reducing or eliminating anxiety is crucial for improving sleep quality [12], and nurses play an essential role in achieving this [13, 14]. Delirium, a severe health issue associated with a twofold increase in mortality risk, reduced physical functioning, and higher healthcare costs, is also linked to sleep deprivation in intensive care settings [15]. Environmental factors such as stress and noise in intensive care units create conditions that predispose patients to delirium [10, 11]. Therefore, managing circadian rhythms, supporting uninterrupted sleep at night, and minimizing stimuli are critical for improving sleep quality and preventing delirium [16]. In the intensive care environment, it has been reported that the circadian rhythm is severely disrupted by frequent awakening, lack of deep sleep, and abnormal daily distribution of the sleep-wake cycle [2].
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In the light of this information, determining chronotypes and providing appropriate nursing care in terms of maintaining circadian rhythm, especially in intensive care patients, is quite significant in preventing pain, sleep problems, delirium, and many physiological issues and comorbid diseases. Furthermore, the roles of nurses in managing sleep, pain, anxiety, and delirium are explicitly outlined in official regulations, highlighting their responsibility in providing holistic and patient-centered care [17]. Nurses provide services for protecting, developing, and improving individual, family, and community health. Nurses, who play a primary role and have an important role in the implementation, evaluation, and organization of this service, aim to provide quality and effective nursing care to individuals. When the literature is scanned, it is seen that the studies mostly focus on circadian rhythm and psychological disorders and problems, obesity, cancer, etc. There is no study examining the effect of nursing care given according to circadian rhythm. In this context, no study evaluating the effect of nursing care in accordance with patients’ circadian rhythms has been found in the literature. For this reason, the study aimed to examine the effect of nursing care given to coronary intensive care patients on sleep quality, pain, anxiety, and delirium according to their circadian rhythms. Unlike patients in other intensive care units, coronary patients are often fully conscious and less likely to receive sedation. This makes them more aware of their unfamiliar surroundings, including exposure to various devices and noises, which can exacerbate their anxiety levels. The heightened anxiety experienced by these patients, combined with the challenges of the intensive care environment, further disrupts their circadian rhythms and sleep quality. By focusing on this specific group, the study aimed to address these unique challenges and evaluate the effectiveness of circadian rhythm-based nursing care in mitigating anxiety and improving sleep quality. In this context, the following hypotheses were tested in this study;
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Nursing care provided in accordance with the circadian rhythm affects sleep quality.
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Nursing care provided in accordance with the circadian rhythm affects pain level.
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Nursing care provided in accordance with the circadian rhythm affects anxiety level.
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Nursing care provided in accordance with the circadian rhythm affects Intensive Care Delirium Screening Checklist (ICDSC) score.
Methods
Study design
This study is a randomized controlled trial (pretest-posttest controlled). The individuals in the intervention and control groups and the statistician were blinded. Due to the nature of the study, the researcher could not be blinded. Participants were informed of what they were expected to do. However, they were not told that the study had an intervention and control group and which group they were in. Therefore, participants did not know which group they were in. Since patients from the intervention and control groups were not in the unit at the same time, they had no chance of hearing or noticing each other.
Population and sample of the study
The study population consisted of all patients treated in the coronary care unit of a training and research hospital between September 2022 and February 2023.
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G-Power statistical analysis was used to determine the sample size in the study. The findings of a study in the literature [18] were used for sample calculation. Considering the rates related to the sleep quality scale in the control and intervention groups, it was calculated that a total of 32 patients, 16 intervention and 16 control groups. With a 95% confidence level, 0.5% effect size, and 95% power, 22 patients for intervention group and 22 patients for control group, were included in the analyses, taking into account data loss. For the reliability of the study results, patients were selected for the study groups by stratified randomization method. Patients were randomly assigned to intervention (M) and control (C) groups according to gender and age. Randomization was performed using the “ball drawing” method to ensure equal distribution of intervention and control groups. Balls with the letters “M” (intervention) and “C” (control) were placed in a bag in equal numbers. For each participant, a person independent of the study randomly drew a ball from the bag and the participant was assigned to the relevant group according to the letter drawn. This method was used to ensure completely random and unbiased assignment. The flow chart of the study is shown in Supplemental Fig. 1, and the CONSORT table in Supplemental Fig. 2. As a result of the post hoc power analysis applied with the G-Power 3.1.9.7 program, the power level was determined as = 1.000 according to the type 1 error: 0.05 and effect size = 3.395 for the determination of the difference between the groups in terms of SQ-CC measurements.
Ethical aspects of the research
The present study was prepared with the approval of Sakarya University Faculty of Medicine Clinical Research Ethics Committee numbered 03 and revised with the ethics committee decision numbered 14. Before the ethics committee approval, the unit manager approval was obtained, which was also added to the ethics committee documents.
This research was conducted in accordance with the principles stated in the Declaration of Helsinki. Participants in the research were informed before the interview and verbal and written consent was obtained.
The Graduate Thesis Projects of Sakarya University Scientific Research Projects Coordination Office supported this study. In addition, the research registration was created for this phase in ClinicalTrials.gov (Identifiers: NCT04934436//Date: 21 June 2021).
Inclusion and exclusion criteria
Patients who were 18 years and older age, who did not have communication problems due to sensory losses, who volunteered to participate, who did not have a psychiatric diagnosis by a specialist physician, and who were admitted to the coronary intensive care unit due to acute coronary syndrome were included in this study, while patients with intermediate chronotype, diagnosed or had previous delirium, receiving ventilator support, using sleeping pills, having a diagnosis of dementia, having insomnia or tendency to sleep as a side effect of the medication used, and using drugs that may cause sedation were not included in the study.
Data collection tools used in the research and their properties
Patient information form prepared by the authors [19, 20], Visual Analogue Scale (VAS) to evaluate pain [21], Morningness-Eveningness Questionnaire (MEQ) to determine the chronotypes of patients [22‐24], Sleep Quality Scale in Coronary Intensive Care Patients (SQ- CC) developed by the authors to determine the patients’ sleep quality [25], Hospital Anxiety and Depression Scale (HADS) to evaluate anxiety [26, 27], Intensive Care Delirium Screening Checklist (ICDSC) to calculate delirium scores [28] were applied to both intervention and control groups to obtain data in line with the purpose of the study. Permission was obtained by e-mail for the scales used in the study.
Patient information form
Visual analogue scale (VAS)
The Visual Analogue Scale (VAS) is applied by marking a one hundred millimeter line. At the 0 mm point of this line, there is “no pain”; at the 100 mm point, there is “the most severe pain.” Based on these two criteria on the scale, the patient marks the current pain level. Scoring is done by measuring with the help of a ruler starting from the left side of the marked point to the place determined by the patient [21].
Horne-Ostberg Morningness-Eveningness Questionnaire (MEQ)
The questionnaire developed by Horne and Ostberg (1976) was adapted into Turkish by Pündük et al. in 2005. The Likert-type scale consists of 19 questions evaluating parameters such as bedtime and wake-up time and preferred time for physical and mental activities. Pündük et al. found the Cronbach’s Alpha value as 0.81. A score of 16–30 points is considered as “Definitely Evening Type,” 31–41 points as “Close to Evening Type,” 42–58 points as “Intermediate Type,” 59–69 points as “Close to Morning Type” and 70–86 points as “Definitely Morning Type” [22]. Some studies consider 59–69 points as the intermediate type, below 59 as the evening type, and above 69 as the morning type [22‐24].
Sleep quality scale in coronary intensive care patients (SQ-CC)
The scale developed by the researchers consists of two sub-dimensions (self-assessment and environmental factors) and 15 items to evaluate the sleep quality of patients treated in the coronary intensive care unit. Items 2, 3, 8, and 9 of the 5-point Likert-type scale are reverse-coded. The lowest score of 14 and the highest score of 70 is obtained from the scale, and sleep quality decreases as the score increases. When calculating the scale’s total score, the scores obtained from 14 items are summed, and the first item, which determines the sleeping and waking hours of individuals, does not participate in the total score evaluation. The Cronbach’s Alpha coefficient calculated in the development phase of the scale was 0.816 [25]. The Cronbach’s Alpha values calculated in the second stage of this study were 0.859 and 0.904 for the self-evaluation sub-dimension, 0.675 and 0.958 for the environmental factors sub-dimension, and 0.764 and 0.950 for the total scale score, respectively.
Hospital anxiety and depression scale (HADS)
The Hospital Anxiety and Depression Scale (HADS) was developed by Zigmond and Snaith in 1983, and its validity and reliability were performed by Aydemir et al. in 1997. It consists of 14 questions and two subscales, seven indicating anxiety (HAD- A) and seven indicating depression (HAD-D). In the 4-point Likert-type scale, each question is scored between 0 and 3. Each subscale can be scored between 0 and 21 [26, 27]. As the scores obtained from the scale increase, the severity of anxiety and depression increases. The Cronbach’s Alpha value calculated in this study was 0.842 in the pre-test, 0.880 in the post-test for HAD-A, 0.870 in the pre-test, and 0.890 in the post-test for HAD-D.
Intensive care delirium screening checklist (ICDSC)
ICDSC, developed by Bergeron et al. in 2001, was developed in line with DSM-IV criteria and aims to identify delirium. In this context, the scale shows 99% sensitivity and 64% specificity in diagnosing delirium. A Turkish validity and reliability study was conducted by Köse et al. in 2016. It consists of eight items related to a change in the level of consciousness, inattention, disorientation, hallucination-delusion-psychosis, psychomotor agitation or regression, inappropriate (inappropriate) speech and mood, disruption of sleep/wake cycle and fluctuation of symptoms, and a score between 0 and 8 can be obtained, and four and above is defined as delirium. It can be used by physicians and nurses with or without training in psychiatry [28].
Smartwatch
Xiaomi Mi 4 bands were used to determine the patients’ deep sleep, light sleep, total sleep time and awake time.
Melatonin and cortisol measurements
Saliva samples were taken into 2 ml Eppendorf tubes and stored at -20 °C for the first evaluation and the last evaluation to look at cortisol and melatonin levels (no fee was requested from the patient for this measurement, which was not routinely performed, and was covered within the scope of the financial support of the study), including the patients in the control group. The samples were centrifuged before analysis and evaluation using the ELISA method. “Microplate Reader RT 2100 C and Microplate Washer RT 2600 C” devices were used for the analyzes performed using Bostonchem brand kits.
Decibel measurement
To demonstrate the necessity of the earplugs with objective measurement, the sound level of the environment in which the study was conducted and measured using the SNDWAY 525B model device at 2-second intervals throughout the data collection process. For noise measurement, the device was placed at a height of approximately 1.5–2 m on a wall in the middle of the intensive care unit, equidistant from all patients. The location was chosen to avoid specific devices that might affect the sound level, and there were no windows nearby to interfere with the measurements.
Chronotype appropriate nursing care
In the coronary intensive care unit where the study was conducted, nursing care practices related to hygiene were carried out at night. Patients stated that the phone on the nurse’s desk rang frequently. In addition, patients were often woken up at night due to procedures such as bed baths, changing of sheets, routine blood collection from each patient at night, ECG for each patient, and treatment. When patients were interviewed, it was stated that they were woken up an average of 5–6 times at night for various reasons. In this context, patients were given earplugs and sleeping glasses to help them sleep uninterruptedly throughout the night. Nursing care was planned before the patient went to sleep at times appropriate to their circadian rhythms. These were referred to as care appropriate to circadian rhythms throughout the study.
Data collection
In the study, the patients were first evaluated after they were admitted to the intensive care unit and slept in the intensive care unit for one night. Intervention and control groups were formed by stratified randomized method from patients who met the research criteria. All questionnaires to be used in the study were applied to both groups at the first interview. Morning patients in the intervention group were given eye masks and earplugs (otiflex sleep earplugs) to use while sleeping. An android smartwatch (Xiaomi Mi 4 bands) was used to determine the patients’ sleeping and waking hours and sleep depth. Circadian rhythms of the patients were determined, and morning patients were not awakened at night except in case of emergency intervention. This study was conducted in a 10-bed ICU. In the study unit, no standardized guidelines existed for managing the evaluated parameters. Before the study, the nurses working in the unit were trained on circadian rhythm, the study’s purpose, patient expectations, not removing wristwatches, monitoring sleep glasses use at night, patient examination protocols, and saliva collection/storage procedures to provide care in accordance with circadian rhythm and chronotype, and cooperation was ensured in care. The researcher also made phone reminders to avoid oversights during busy hours. Due to the difficulty finding patients who met the study’s criteria, intervention and control groups did not contamination between both groups. Monitoring of the patient’s use of the equipment at the desired level was carried out by the researcher and the nurse providing primary care. In this context, in cases where the researcher was not available, the nurse caring for the patient checked the patient. The patients who stayed for a total of three days were followed up in this way. During this period, saliva samples were taken into Eppendorf tubes. During this period, no intervention was made to the control group, and their routine care was continued in accordance with intensive care unit functioning. On the 3rd day, the questionnaires were administered to both groups again. In many studies in the literature, it has been reported that the noise in hospital environments is higher than WHO recommendations [29‐32]. Therefore, to demonstrate the necessity of the earplugs for objective measurement, the sound level of the environment in which the study was conducted was measured using the device.
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Evaluation of research data
The data of the study were transferred to the IBM SPSS Statistics 23 program. Before the data were sent for analysis, they were coded as group A and B to blind the statistical expert. Thus, it was ensured that the statistical expert did not know the intervention and control groups. The normality of the data distribution was assessed using the Kolmogorov-Smirnov test, skewness and kurtosis values within the ± 1 range, and the alignment or proximity of the arithmetic mean, mode, and median. Parameters meeting the criteria for normal distribution were analyzed using parametric tests [32‐36]. Based on the results of the normality tests, appropriate statistical methods were applied. Independent sample t-tests were used to compare mean scores between the intervention and control groups for normally distributed data, while dependent sample t-tests were used to compare pre-test and post-test scores within the same group. The Wilcoxon signed-rank test was applied for paired data that did not meet the normality assumption. Repeated measures ANOVA was utilized to analyze changes over time within groups. The Mann-Whitney U test was employed to compare two groups when data did not meet normality criteria, and the chi-square test was used to compare categorical variables between groups. Cohen’s d was also calculated to determine the effect size and interpret the magnitude of differences between and within groups over time. The results were evaluated at a 95% confidence interval and significance at p < 0.05 level.
Results
Findings related to sociodemographic characteristics of participants and their comparison according to groups
The average age of the intervention group was 67.57 ± 12.53 and 72.7% (n:16) were male; the average age of the control group was 60.36 ± 11.28 and 77.3% (n:17) were male. There was no statistically significant difference between the groups in terms of age, gender, marital status, educational status, family structure, income, comorbidities, smoking, and alcohol use (p > 0.05), and the groups were homogenous. The statistics related to the sociodemographic data of the patients are presented in Supplemental Table 1.
Pre-test and post-test SQ-CC results of intervention and control groups
The mean scores of the individuals in the intervention and control groups regarding the SQ-CC scale and its sub-dimensions are presented in Table 1. While there was no statistically significant difference between the groups in terms of self-assessment and environmental factors sub-dimension pre-test (p > 0.05) scores of the SQ-CC scale a statistically significant difference was found between the groups in the post-test score comparisons (p < 0.05). It was observed that the intervention group had better sleep quality than the control group in both sub-dimensions (Table 1). As a result of the linear regression analysis, the groups (intervention and control groups) had a statistically significant effect on sleep quality (p < 0.05) (Supplemental Table 2).
Table 1
Examination of SQ-CC and sub-dimensions and differences within and between groups
Intervention Group | Control Group | t1 | p | Cohen d (%95CI) | |||
|---|---|---|---|---|---|---|---|
mean | sd | mean | sd | ||||
Self-assessment (pre-test) | 28,18 | 8,74 | 24,68 | 6,90 | 1,474 | 0,148 | -0,445 (-1,043 − 0,154) |
Self-assessment (post-test) | 14,27 | 5,28 | 25,64 | 7,47 | -5,826 | < 0,001*** | 1,758 (1,062 − 2,454) |
t2/p | 7,131/<0,001*** | -0,492/0,628 | |||||
Cohen d (%95CI) | -1,278 (-1,870- -0,573) | 0,110 (-0,508-0,675) | |||||
Environmental Factors (pre-test) | 24,82 | 4,73 | 22,73 | 4,86 | 1,446 | 0,156 | -0,436 (-1,034 − 0,162) |
Environmental Factors (post-test) | 8,14 | 2,93 | 24,82 | 4,68 | -14,175 | < 0,001*** | 4,272 (3,202-5,343) |
t2/p | 14,143/<0,001*** | -1,694/0,105 | |||||
Cohen d (%95CI) | -2,509 (-2,934- -1,354) | 0,354 (-0,298-0,893) | |||||
SQ-CC (pre-test) | 53,00 | 10,28 | 47,41 | 7,85 | 2,027 | 0,049* | -0,611 (-1,216- -0,007) |
SQ-CC (post-test) | 22,41 | 6,67 | 50,45 | 10,63 | -10,483 | < 0,001*** | 3,160 (2,274-4,046) |
t2/p | 13,142/<0,001*** | -1,318/0,202 | |||||
Cohen d (%95CI) | -2,392 (-3,026- -1,478) | 0,336 (-0,351-0,840) | |||||
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Pre-test and post-test VAS results of intervention and control groups
The pre-test and post-test VAS score averages of the intervention and control groups are presented in Table 2. There was no statistically significant difference between the groups in terms of VAS score in both pre-test and post-test measurements (p > 0.05) (Table 2).
Table 2
Examination of VAS scores and differences within and between groups
Intervention Group | Control Group | t1 | p | Cohen d (%95CI) | |||||
|---|---|---|---|---|---|---|---|---|---|
mean | sd | Min-max | mean | sd | Min-max | ||||
VAS score (pre-test) | 1,55 | 2,15 | 0–7 | 1,45 | 2,44 | 0–9 | 0,131 | 0,896 | -0,043 (-0,635-0,548) |
VAS score (post-test) | 0,68 | 2,21 | 0–8 | 0,64 | 1,47 | 0–5 | 0,080 | 0,936 | -0,021 (-0,612-0,570) |
t2/p | 2,241/0,036* | 1,547/0,137 | |||||||
Cohen d (%95CI) | -0,489 (-1,183-0,017) | -0,275 (-0,865-0,323) | |||||||
Pre-test and post-test HADS results of intervention and control groups
The pre-test and post-test HADS results of the intervention and control groups are presented in Table 3. While there was no statistically significant difference between the groups in terms of pre-test anxiety and depression mean scores (p > 0.05), there was a statistically significant difference in terms of post-test anxiety and depression mean scores (p < 0.05). Accordingly, post-test anxiety and depression scores were higher in the control group than in the intervention group (Table 3).
Table 3
Examination of HADS scores and differences within and between groups
Intervention Group | Control Group | t | p | Cohen d (%95CI) | |||
|---|---|---|---|---|---|---|---|
mean | sd | mean | sd | ||||
Anxiety (pre-test) | 7,59 | 4,85 | 8,91 | 5,73 | -0,824 | 0,415 | 0,249 (-0,345-0,842) |
Anxiety (post-test) | 3,18 | 3,29 | 8,50 | 5,66 | -3,809 | 0,001** | 1,149 (0,511-1,787) |
t2/p | 4,639/<0,001*** | 0,482/0,635 | |||||
Cohen d (%95CI) | -0,869 (-1,546- -0,327) | -0,102 (-0,739-0,444) | |||||
Depression (pre-test) | 5,73 | 4,68 | 6,00 | 4,83 | -0,190 | 0,850 | 0,057 (-0,534-0,648) |
Depression (post-test) | 3,32 | 2,53 | 6,73 | 5,17 | -2,775 | 0,009** | 0,838 (0,221-1,454) |
t2/p | 2,845/0,010* | -0,976/0,340 | |||||
Cohen d (%95CI) | -0,531 (-1,228- -0,025) | 0,217 (-0,292-0,893) | |||||
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Pre-test and Post-test ICDSC results of intervention and control groups
The pre-test and post-test ICDSC results of the intervention and control groups are presented in Table 4. While there was no statistically significant difference between the groups in terms of pre-test delirium score (p > 0.05), there was a statistically significant difference in terms of post-test delirium score (p < 0.05). Accordingly, no patient scored 4 or more, which is the cut-off point of the delirium scale, but the post-test delirium score of the control group was higher than the intervention group (Table 4).
Table 4
Examination of ICDSC scores and differences within and between groups
Intervention Group | Control Group | t1 | p | Cohen d (%95CI) | |||
|---|---|---|---|---|---|---|---|
mean | sd | mean | sd | ||||
Delirium score (pre-test) | 1,27 | 0,46 | 1,09 | 0,43 | 1,366 | 0,179 | -0,404 (-1,001 − 0,193) |
Delirium score (post-test) | 0,32 | 0,48 | 1,18 | 0,50 | -5,857 | < 0.001*** | 1,755 (1,059 − 2,450) |
t2/p | 7,780/<0.001*** | -1,449/0,162 | |||||
Cohen d (%95CI) | -1,674 (-2,014- -0,641) | 0,340 (-0,099 − 1,091) | |||||
Comparison of melatonin and cortisol levels of intervention and control groups
Pre-test and post-test melatonin measurements of the participants are shown in Fig. 1, and cortisol measurements are shown in Fig. 2.
Fig. 1
Pre-test and Post-test Melatonin Levels in the Intervention and the Control Groups
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Fig. 2
Pre-Test and Post-Test Cortisol Levels in the Intervention and the Control Groups
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There was no statistically significant difference between the groups regarding melatonin and cortisol levels (p > 0.05). However, there was a significant increase in melatonin levels in the intervention and control groups, while there was a significant decrease in cortisol levels (p < 0.05) (Supplemental Table 5).
Discussion
This study investigated the effect of nursing care given to coronary intensive care patients according to their circadian rhythms on sleep quality, pain, anxiety, and delirium. In line with this aim and the hypotheses, the most important and unique result of the study was the sleep quality, anxiety, and delirium scores of the patients with morning chronotypes who used eye masks and ear plugs and whose nursing care was given at hours appropriate for the morning chronotypes and who slept at night without being woken up as much as possible increased, and anxiety and delirium scores decreased.
Impact of circadian rhythm-based nursing care on sleep quality
When evaluated in terms of the results related to sleep quality, it was determined that the patients in both groups were homogeneous before the intervention. After the intervention, the intervention group’s sleep quality increased compared to the control group. Light, noise, and various nursing interventions in intensive care negatively affect patient sleep [37], practices such as quiet time application are effective in improving the sleep quality of patients, and night care and treatment practices should be postponed [38, 39]. In addition, studies reporting that the application of eye patches, earplugs, and quiet time improves sleep quality in patients receiving intensive care treatment [40, 41].
The results of this study show that the intervention effectively improved sleep quality in patients and is consistent with existing literature. Data from Android smartwatches revealed a significant increase in deep sleep and total sleep duration in the intervention group, while the control group showed a significant decrease in deep sleep duration. Factors such as light and noise in intensive care environments negatively impact sleep quality [6]. Erim’s (2018) study also showed that longer stays in intensive care reduced sleep quality [42]. In light of the literature, the decrease in deep sleep duration in the control group and the increase in the intervention group support the effectiveness of the intervention. Initially, there was no significant difference in melatonin and cortisol measurements between the intervention and control groups. However, over time, melatonin levels increased and cortisol levels decreased in both groups. The literature presents contradictory findings: some studies report an increase in melatonin with no change in cortisol [19], others report no changes in either hormone [43], while others observe positive changes in both [44]. One study found variations depending on measurement timing but no differences at similar times, consistent with the present study’s findings [45]. Although the results are partially consistent with previous studies, discrepancies may also stem from methodological differences, such as sample size and intervention duration. The observed increase in melatonin levels and decrease in cortisol levels in both groups on day 3 of the study may be attributed to the patients entering the recovery phase. This improvement could be linked to the general condition of the patients, including those in the control group, improving over time with a reduction or complete disappearance of pain and growing acclimatization to the intensive care environment and its associated sounds. Additionally, the timing of saliva sample collection may not have coincided with the peak or trough levels reported in other studies, which could contribute to the lack of significant differences. Technical challenges during the laboratory process, particularly when saliva samples were centrifuged and analyzed using ELISA, may have affected the precision of the measurements. For instance, variations in density during pipetting could have introduced variability in hormone levels.
Pain and chronotype interactions
It has been reported that pain shows circadian rhythmicity in experimental studies evaluating healthy individuals or postoperative periods and pathological conditions [46]. At the same time, studies have shown that chronotype is associated with different types of pain such as migraine and fibromyalgia, and that morning chronotype often predicts these types of pain [47‐50]. Although no significant difference was found between the groups as a result of the study, there was a significant decrease in the pain score in the intervention group. In addition, the article by Mun et al. (2022) states that chronotype may be effective on pain, and chronobiological interventions may also promote healing in individuals with pain [7]. Based on this, it can be said that the significant decrease in the pain score of the intervention group in the current study according to time is similar to the literature. Although there was a significant difference according to time, no significant difference was found in terms of pain scores compared to the control group. This may be due to the fact that the patients included in the study were intervened as soon as possible after their admission to the intensive care unit so that the patients in both the intervention and control groups were relieved from acute pain caused by acute coronary syndrome. Patients in the intervention and control groups were experiencing pain when they arrived at the unit at the beginning of the study, but pain may have naturally decreased during the treatment process for both groups. This may have masked the effect of the intervention. Additionally, since pain perception is a personal experience, some patients may have had difficulty expressing their pain.
Reduction of anxiety and depression
Another finding of the study is the effect of nursing care given according to circadian rhythm on anxiety. Accordingly, the anxiety of the intervention group decreased significantly compared to the control group. Sipilä et al. (2010) reported that genes that contribute to circadian rhythms may also play a role in anxiety disorders [9]. There are also different studies in the literature stating that anxiety and circadian rhythm are related [50, 51]. In light of this information, it can be said that the anxiety-related data obtained in the current study are compatible with the literature. Although the evaluation of depression was not the primary goal of the study, it was observed that there was a significant decrease in depression scores. It has been reported in the literature that the change in chronotype preference affects depressive symptoms [52‐54]. In this study, it is thought that both depression and anxiety scores decreased because chronotype-appropriate care was provided, the intensive care environment was prevented from causing a phase shift in the chronotype of the person, and sleep quality was improved.
Prevention of delirium via circadian rhythm management
In the study, it was observed that there was a significant decrease in the mean delirium scores of the intervention group compared to both the intervention group and the control group. Mulkey et al. (2019) stated that one of the first four most important interventions in evidence-based nursing interventions for delirium day/night routines [54]. Under these headings, interventions such as minimizing nocturnal practices and not waking up the patient at night or waking up less, reducing lights and sound, quiet time practice, and sleep hygiene practice were classified similarly to circadian rhythm nursing care in the current study. In the article, it is stated that the circadian rhythm (sleep/wake cycle) is controlled by a complex system that responds to internal and external stimuli and that disturbance, interruption, and deficiency in the sleep cycle is the most fundamental factor in the development of delirium. In the study of Chen et al. (2022), it was stated that E4bp4, one of the circadian clock genes, plays a role in the development of delirium, and therefore, delirium may develop as a result of disruptions in circadian rhythm [11]. In the article by Pisani and D’Ambrosio (2020), it was reported that delirium could be reduced by interventions such as reducing noise, using earplugs or reducing the volume of alarms, reducing bright lights during sleeping hours by using eye masks, limiting daytime sleep, and relaxation techniques such as massage and reiki when appropriate [10]. When evaluated from this point of view, the recommendations support the effectiveness of the practices performed in the current study in preventing delirium. In recent studies, there are findings showing that the development of delirium is associated with disruption of circadian rhythm and decreased sleep quality in intensive care [55, 56]. When the literature is evaluated holistically, it is an expected result that the nursing care in accordance with the circadian rhythm applied in the current study is the recommended practice in preventing delirium and considering that the sleep quality of the intervention group increased in this study, the risk of delirium decreased.
Limitations
Since this study was conducted in a single center, it is limited to the data obtained from the participants there. Another limitation is that the study could only be completed with morning chronotype patients since the average age of the patients hospitalized in the intensive care unit where the study was conducted decreased the possibility of an evening chronotype. In addition, intermediate chronotypes were excluded from this study to ensure a clear evaluation of the intervention’s effectiveness. Future studies should consider including intermediate chronotypes to provide a more comprehensive understanding of the intervention’s impact across all chronotype groups. One of the limitations of this study is that only acute coronary syndrome patients were included in this study, and pre-existing sleep disorders, use of sleeping pills or dementia patients were excluded from the study. The sleep quality of these patients has a high potential to be affected, so further studies are needed to evaluate the effectiveness of nursing care appropriate to chronotype in these patients. In addition, since the nature of the study required that the patients’ night sleep should not be interrupted, only one measurement could be made for melatonin and cortisol. This can also be considered as a limitation. This study was conducted during the COVID-19 pandemic. For this reason, there were difficulties in the data collection process due to the fact that hospital admission rates were lower in this process compared to previous times, and the researcher could not enter the intensive care unit within the scope of pandemic and isolation measures. The Android watch was processing data through a phone application. The inability of the relevant application to record data at the same time has emerged as one of the important difficulties and limitations encountered in this study. Again, the coronary intensive care unit where the study was conducted was a unit where patients did not stay for a long time. Therefore, there were difficulties in finding patients who were followed up for three nights. Since the patients experienced acute pain due to their diseases, it is thought that the effect of the nursing care applied in the study on pain is quite limited.
Conclusion
In this study, it was determined that the nursing care given to coronary intensive care patients according to their circadian rhythms increased the sleep quality of the patients in total score and self-assessment and environmental factors sub-dimensions, decreased anxiety level, decreased delirium score, had no effect on pain, and did not affect melatonin and cortisol levels.
This study highlights the significant impact of the intensive care environment and patients’ current health conditions on sleep quality, with poor sleep quality contributing to increased delirium, anxiety, and pain perception. The findings demonstrate that determining patients’ circadian rhythms and providing care at appropriate times can significantly improve sleep quality, reduce anxiety, and lower delirium scores in crowded intensive care settings.
From a clinical practice perspective, it is recommended that nurses assess and align their care with the circadian rhythms of patients to minimize comorbid conditions and enhance overall care quality. Given the growing understanding of the circadian rhythm’s effects on human health, future research should focus on developing and testing nursing care models based on circadian alignment.
Additionally, further studies with larger sample sizes and frequent measurement of melatonin and cortisol levels, including serum or urine analyses, are needed to provide greater clarity on the hormonal changes associated with circadian rhythm-aligned care. These efforts will contribute to the advancement of evidence-based nursing practices in intensive care units.
Declarations
Ethics approval and consent to participate
This study was carried out in compliance with the principles of the Declaration of Helsinki. Ethics committee approval numbered 03 was obtained from a university’s Ethics Committee for Non-Drug Interventional Clinical Studies before the research and revised with the ethics committee decision numbered 14. In addition, permission numbered 18343338-434.99 was obtained from the management of a training and research hospital, the head of the clinic’s department where the research will be conducted, and the Provincial Health Directorate where the research was conducted. Participants were informed before the interview, and a verbal and written consent was obtained.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Other Information
This study was generated from the findings from the second phase of the first author’s doctoral thesis.
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