Sleep, anxiety, depression, and stress in critically ill patients: a descriptive study in a Portuguese intensive care unit

Abstract

Background

Sleep disorders are common among patients admitted to intensive care units (ICUs). This study aimed to assess the perceptions of sleep quality, anxiety, depression, and stress reported by ICU patients and the relationships between these perceptions and patient variables.

Methods

This cross-sectional study used consecutive non-probabilistic sampling to select participants. All patients admitted for more than 72 hours of ICU hospitalization at a Portuguese hospital between March and June 2020 were asked to complete the “Richard Campbell Sleep Questionnaire” and “Anxiety, depression, and Stress Assessment Questionnaire.” The resulting data were analyzed using descriptive statistics, Pearson’s correlation coefficient, Student t-tests for independent samples, and analysis of variance. The significance level for rejecting the null hypothesis was set to α ≤0.05.

Results

A total of 52 patients admitted to the ICU for at least 72 hours was recruited. The mean age of the participants was 64 years (standard deviation, 14.6); 32 (61.5%) of the participants were male. Approximately 19% had psychiatric disorders. The prevalence of self-reported poor sleep was higher in women (t[50]=2,147, P=0.037) and in participants with psychiatric problems, although this difference was not statistically significant (t[50]=–0.777, P=0.441). Those who reported having sleep disorders before hospitalization had a worse perception of their sleep.

Conclusions

Sleep quality perception was worse in female ICU patients, those with psychiatric disorders, and those with sleep alterations before hospitalization. Implementing early interventions and designing nonpharmacological techniques to improve sleep quality of ICU patients is essential.

INTRODUCTION

In the intensive care unit (ICU), nurses must continuously assess vital signs, implement and evaluate treatment plans, administer medications, and anticipate and prevent adverse patient outcomes [1]. However, the methods required to care for these patients may limit family participation in decision making, and the patients’ psychosocial needs may be neglected [2]. Previous reports have indicated a link between sleep disturbance in critical-care patients and increased incidences of delirium, mortality rates, and hospital stay [3]. Additionally, sleep disturbances have been shown to be associated with short-term symptoms like lethargy, fatigue, irritability, confusion, memory issues, and loss of muscle, which may hinder the recovery process and potentially impact the patient's quality of life in the longer term [4-7].

Sleep deprivation is a common issue faced by patients during hospitalization and ICU care and may be attributed to several factors. The ICU environment may contribute to sleep disruption due to the noise and light and the need for patient care activities, diagnostic procedures, and mechanical ventilation. Sleep quality while in hospital may also be a function of factors related to the patient's health, such as pre-existing sleep disorders, severity and/or acute onset of illness, organ dysfunction, and pain; these factors may also increase stress and anxiety [7,8], which may further disrupt sleep and induce additional stress and anxiety [8].

As sleep disturbance is considered a risk factor for anxiety [9-11], complaints of sleep disturbances are generally regarded as diagnostic criteria for anxiety disorders [12,13]. Furthermore, depression, anxiety, and stress are common in patients who have suffered traumatic brain injury and should be anticipated in critically ill patients [14].

Sleep disturbances among ICU patients are well known but are not currently addressed in a consistent manner. Indeed, in recent years, various strategies have been implemented to promote and improve sleep. However, hospitalized patients often cannot achieve good-quality sleep [15]. Due to the tremendous impact of sleep disturbance on healthcare services, it is crucial to identify patients at higher risk of sleep and mental health disorders after hospitalization to prevent rather than react to possible adverse patient outcomes. Thus, this study aimed to describe and predict the quality of sleep of critically ill patients and to predict possible correlations of sleep disturbances with anxiety, depression, and stress.

MATERIALS AND METHODS

This single-center, cross-sectional, and correlational study analyzed adult patients admitted to a Portuguese ICU between March and June 2020. The hospital's Ethics Committee approved the study (authorization 2020.053, 043-DEFI/045-CE). Informed consent was obtained from all participants after providing them with all necessary information.

The data collection instruments included sociodemographic and clinical characterization and the “Richard Campbell Sleep Questionnaire (RCSQ)” and “Depression, Anxiety and Stress Scale 21 (DASS-21).” The RCSQ is frequently used to assess sleep quality in ICU patients, and many clinical practice guidelines recommend its use [16]. This instrument includes six items (sleep depth, falling asleep, awakenings, return to sleep, sleep quality, and an additional item addressing noise levels) and uses a visual analog scale. The score for each item ranges from 0 (indicating the worst possible sleep) to 100 (indicating the best sleep). A total sleep score is obtained for each patient by summing the individual scores on the five sleep items and dividing the result by five (to obtain a final RCSQ score of 0 to 100). Those within the lowest quartile (scores from 0 to 25) are considered to have the worst sleep, and those within the highest quartile (76 to 100) are deemed to have excellent sleep.

The DASS-21 [17] consists of 42 items evenly distributed across depression, anxiety, and stress subscales [18]. Each scale comprises seven items, each of which is scored with a four-point Likert scale, ranging from 0 ("strongly disagree") to 3 ("strongly agree"). The final result is obtained by summing the scores of the items in each subscale. The cutoff points, indicative of severity, are described in Table 1. This instrument has strong evidence for its validity in various areas including bifactor structural, internal consistency, criterion, and construct validity [19]. The DASS-21 is a high-quality tool used to assess emotional states, although it has inherent limitations with respect to assessing the individual severities of depression, anxiety, and stress [20]. However, given the reliability, validity, and ease of use, the DASS is considered a useful tool for research and clinical settings [21].

Table 1.

DASS-21 severety score

Variable	Percentile	Depression	Anxiety	Stress
Normal	0–78	0–4	0–3	0–7
Mild	78–87	5–6	4–5	8–9
Moderate	87–95	7–10	6–7	10–12
Severe	95–98	11–13	8–9	13–16
Extremely severe	98–100	>14	>10	>17

DASS-21: Depression, Anxiety and Stress Scale 21.

Population and Sample

In a consecutive non-probabilistic sampling process, all patients admitted to the ICU who met the following inclusion criteria completed the data collection process: ICU stay longer than 72 hours and able to complete the questionnaire themselves or indicate their answer to the researcher. All patients younger than 18 years, with an ICU stay less than 72 hours, who experienced confusional states (all psychic and autopsychic disorientation states, including delirium), or had been prescribed medication that alters sleep patterns (e.g., sedatives, anxiolytics, and/or analgesics) were excluded.

Data Collection

Firstly, the study's objective and methods were presented to the nursing team. Prior to obtaining informed consent of the participants, the patients who met the inclusion criteria were provided the study objectives and a description of the study design and were asked for their free and informed participation. The principal researcher provided all the necessary information to participants and the authorization to be signed; permission was obtained through a fingerprint (preferably from the index finger of the dominant hand) for those who could not sign. The participants were invited to complete the data collection instruments autonomously. Whenever the patient demonstrated incapacity or a preference for assistance, the researcher filled out the questionnaires according to the indications/answers of the user and revalidated them.

Statistical Analysis

The patients’ sociodemographic data were first described using measures of central tendency and dispersion for quantitative variables and absolute and relative frequencies for qualitative variables. The outcomes, including dimensions and total scale, were described using the mean and standard deviation (SD). In all analyses, significance was assessed using an alpha of 0.05. Cronbach's alpha coefficient (a measure of internal consistency), Pearson's correlation coefficient, Student t-test for independent samples, and the multivariate analysis of variance (ANOVA) test were used for analysis. The normality of the data distributions was analyzed using the Shapiro-Wilk test, and the homogeneity of the variance was analyzed using the Levene test. All data were analyzed using the IBM SPSS version 27.0 (IBM Corp.).

RESULTS

Fifty-two participants completed the survey during the study period (Table 2). The mean age was 64±14.6 years (range, 20–84 years); 32 (61.5%) were men, and 32 were married (62.7%). The median length of stay was 6±3.64 days (range, 3–290 days). About 19% of participants had a history of psychiatric illness.

Table 2.

Sociodemographic and clinical characterization (n=52)

Variable	Value
Age (yr)	64±15
Sex
Female	20 (38.5)
Mele	32 (61.5)
Marital status
Single	8 (15.7)
Married	32 (62.7)
Divorced	5 (9.8)
Widowed	6 (11.8)
Length of stay in ICU (day)	6.0±3.6
Psychiatric history
No	42 (80.8)
Yes	10 (19.2)
Sleep disturbances (before ICU)
No	21 (40.4)
Yes	31 (59.6)
Sleep medication (before ICU)
No	10 (19.6)
Yes
Sleep medication (during ICU stay)	41 (80.4)
No	11 (22.9)
Yes	37 (77.1)

Values are presented as mean±standard deviation or number (%).

ICU: intensive care unit.

There were various reasons for ICU admission (Table 3), ranging from gastrointestinal impairment (27.0% of patients) to nervous system impairment (1.9%). The reliability of the questionnaire scales was estimated using Cronbach's alpha coefficient: there was variation observed among the scores of the diverse dimensions between 0.647 (weak but acceptable) to 0.871 (good) [22] and is presented in Table 4.

Table 3.

Reason for ICU admission (n=52)

Reason for ICU admission	No. (%)
Gastrointestinal	14 (26.9)
Sepsis	10 (19.2)
Vascular	9 (17.3)
Cardiovascular	5 (9.6)
Multiple trauma	4 (7.7)
Respiratory	3 (5.8)
Endocrine	2 (3.9)
Orthopedic	2 (3.9)
Renal	2 (3.9)
Neurological	1 (1.9)

ICU: intensive care unit.

Table 4.

Scale reliability

Scale	α Of the dimension	Number of items
RCSQ	0.837	6
DASS-21
Depression	0.871	7
Anxiety	0.647	7
Stress	0.756	7

RCSQ: Richard Campbell Sleep Questionnaire; DASS-21: Depression, Anxiety and Stress Scale 21.

The correlations between anxiety, depression, stress, and sleep quality were statistically significant, positive, and moderate (Table 5). Thus, the higher were the values of anxiety, depression, and stress, the worse was the perception of sleep quality.

Table 5.

Correlations between anxiety, depression, anxiety, and stress and sleep

Scale	Depression	Anxiety	Stress
Depression	-	-	-
Anxiety	0.626	-	-
Stress	0.682	0.608	-
RCSQ total	0.452	0.355	0.324

RCSQ: Richard Campbell Sleep Questionnaire.

With this study, we aimed to test the following hypotheses: H1: women have a worse perception of sleep than men; H2: patients with psychiatric problems have a worse perception of sleep; H3: patients with sleep disorders before hospitalization have worse sleep perception; H4: patients who have experienced sleep disorders in the past may exhibit changes in stress, depression, and anxiety; H5: patients with a history of any reported psychiatric illness may exhibit changes in stress, depression, and anxiety; Regarding H1, the ICU patients’ perception of their sleep quality was significantly worse in women than in men (t(50)=2.147, P=0.037) (Table 6).

Table 6.

Relationship between sex and sleep quality

	Female	Male	P-value
Sleep quality	5.2±2.3	3.8±2.1	0.037

Values are presented as mean±standard deviation.

Regarding H2, the ICU patients’ perception of their sleep quality was worse in those with psychiatric problems (Table 7), although the difference was not significant (t(50)=–0.777, P=0.441). Regarding H3, the ICU patients’ perception of their sleep quality was worse in those who reported sleep disturbances prior to hospitalization (Table 7), although the difference was not statistically significant (t(50)=1.831, P=0.073).

Table 7.

Relationship between psychiatric history and sleep quality and sleep quality in ICU

	Psychiatric history		P-value
	Yes	No
Sleep quality	4.8±3.0	4.2±2.1	0.441
Sleep quality in ICU	5.0±2.4	3.9±2.1	0.073

Values are presented as mean±standard deviation.

ICU: intensive care unit.

Regarding H4, the multivariate ANOVA results indicated that differences in reported stress, depression, or anxiety among the patients who have experienced sleep disorders in the past were not significant (Λ=0.904, F(3.48)=1.708, P=0.178) (Table 8). Regarding H5, a significant positive correlation was found between reported stress, depression, or anxiety and psychiatric history (Table 9). The ICU patients with a history of psychiatric illness more frequently reported more severe depression (7.50 vs. 3.26) and stress (9.50 vs. 5.80).

Table 8.

Relationship between depression, anxiety, and stress and previous sleep changes

	Previous sleep change		P-value
	Yes	No
Depression	3.95±4.56	4.6±4.70	0.874
Anxiety	5.95±4.11	4.35±2.96	0.110
Stress	6.61±4.66	6.45±3.32	0.880

Values are presented as mean±standard deviation.

Table 9.

Relationship between depression, anxiety and stress and psychiatric history

	Psychiatric history		P-value
	Yes	No
Depression	7.50±5.06	3.26±4.14	0.008
Anxiety	6.30±4.90	4.69±3.11	0.197
Stress	9.50±4.67	5.80±3.35	0.006

Values are presened as mean±standard deviation.

DISCUSSION

In the ICU, numerous stimuli can interfere with the quality of sleep and, consequently, with the outcomes of hospitalized patients [23]. For various reasons, stimuli such as noise are increased in the ICU. On the other hand, beneficial stimuli such as natural light are limited [23,24]. Sleep is an essential biological function and is considered fundamental for good health and quality of life. Sleep quality modulates many body functions, including immune system function, removal of cellular toxins, and control of body temperature, blood pressure, pulse, and hormone production [4,25].

Many ICU patients experience sleep disorders of varying severity related to both intrinsic and extrinsic factors. The ICU staff have an important role in reducing the extrinsic factors that impact sleep quality in the ICU to minimize adverse events. In this study, we assessed the sleep quality of ICU patients and investigated associations between some intrinsic factors and sleep quality in the ICU. The results may allow early identification of ICU patients at higher risk of sleep disturbances during their hospital stay.

The average age of the study participants was 64 years, which is slightly higher than in previous studies [20] but within the reported range. As expected, the participants' sleep quality during hospitalization was reported to be poorer, as age and sleep quality are highly negatively correlated. Although the questionnaire responses indicated that 59.6% of the study participants reported previous sleep disturbances, 80% of the patients also reported use of prescription medications prior to hospitalization, and 77.1% continued to receive their medication during hospitalization.

Critical illness can cause physiological and emotional disorders that can negatively impact sleep quality, regardless of the reason for hospitalization. According to the findings of this study, the participants' mean perception of their sleep quality is below 50%, which could indicate significant changes in sleep patterns, similar to the findings of other studies [7,24]. However, the perception of sleep quality by the participants, given the average length of stay of six days, with a range of 3 to 290 days, may have been related to extrinsic factors not evaluated in this study, including environment, noise, luminosity, and temperature [7,26,27].

Most ICU patients rate their sleep quality as low [7,24], corroborating the data of this investigation. Low-quality sleep is characterized by a high proportion of stages 1 and 2, fragmented sleep, with circadian rhythm changes; stage 3 and REM sleep may be significantly decreased or absent [28-32]. Reduced sleep quality may increase the length of hospitalization by delaying weaning from ventilation support [33] and increasing the incidence of delirium and, consequently, adverse outcomes [34,35]. Longer length of stay and a weakened immune system due to lack of quality sleep increase the risk of healthcare-associated infection [34,36].

Methods to promote better sleep can include medications, such as benzodiazepines, which may result in changes to cognitive function, increased risk of tolerance and dependence, ventilatory impairment, and adverse effects on sleep patterns [37]. Alternatively, non-pharmacological approaches may be employed, including mental or behavioral interventions, breathing exercises, music therapy, aromatherapy, massage, guided imagery, acupuncture, environmental changes (e.g., synchronization of ICU activities with daylight, noise reduction], social support (e.g., family assistance), and equipment modification [4,24].

However, the use of such strategies may not influence the patient’s anxiety and stress and so not improve sleep [9]. The ICU patient typically has abnormally high levels of anxiety and depression [38]. In the present study, the participants’ self-reported scores were consistent with moderate depression and stress and mild anxiety, perhaps because the sample demonstrated variability in disease severity and most had short hospital stays. The patient hospitalized in the ICU is subject to numerous stress factors, the most prevalent of which are being thirsty, having invasive devices in the nose and mouth, not being able to communicate, decreased mobility due to invasive and non-invasive devices, not being able to sleep, and loss of autonomy [39]. The data from this study are consistent with the above-noted stressors: the higher were the self-reported scores for anxiety, stress, and depression, the worse was the perception of sleep.

Some studies have reported that sleep duration and quality changes are associated with increased incidence of mental health disorders, including depression and anxiety [40]. Conversely, no relationship between previous sleep alterations and stress, depression, or anxiety was found in this study, and there may be other predictive factors of greater importance.

Previous studies have reported that people with mental health issues were much more likely to have a shorter sleep duration and quality [40], as in the present study, in which the perception of sleep quality was worse in ICU patients with psychiatric illnesses. In this study, 80% of the participants patient had no history of mental illness. We also discovered that participants with a history of mental illness had significantly higher scores for self-reported depression and stress, consistent with previous findings [41,42], including those from studies of patients with traumatic brain injury [43], stroke patient [42] oncological disease [44,45], or cardiovascular disease [46-48] and of pregnant [49,50] or postpartum [49,51] women.

In the present study, the perception of sleep was worse in the female participants. A study of healthy adults in Canada found that 55% of women report problems falling asleep, which is higher than men. [52]. In contrast, another study of healthy participants found that women had a significantly longer sleep duration, a lower percentage of stage 1 sleep, and a higher percentage of slow-wave sleep compared to men [53].

Sleep disorders increase the risk of delirium, extend hospital stays, and are associated with prolonged mechanical ventilation. However, evidence-based practices are necessary to manage and improve sleep quality of hospital patients. There is a need to educate hospital nurses about the impact of sleep quality on patient outcomes to better enable them to assess overall condition and to implement appropriate measures to encourage sleep and minimize unfavorable outcomes.

A patient’s healthcare plan should include measures to manage sleep quality during hospitalization and strategies to manage sleep disorders and mitigate adverse effects when they occur. By being proactive in these areas, healthcare professionals can better support patients and promote positive outcomes.

There is a need for ICU nurses to employ high-quality, validated tools to monitor and evaluate the sleep quality of their patients and evidence-based strategies to achieve desired results. However, implementing evidence-based methods to assess sleep quality in clinical practice remains a challenge, as does improving the understanding of sleep and sleep disorders among medical staff caring for hospitalized patients. There are several obstacles to promoting sleep in the ICU, including the major trend of reducing sedation for critical patients.

It is essential to exercise caution when interpreting this study's results, as several limitations were involved. The coronavirus disease 2019 (COVID-19) pandemic caused disruptions during the first wave, leading to a reformulation of services and a subsequent reduction in the number of participants. The deteriorating epidemiological situation also necessitated reorganization of the data collection process, further limiting the number of participants.

It is important to consider external variables that may influence an individual's perception of sleep, such as noise, luminosity, and nursing activities. The use of self-reporting instruments, while helpful, may not provide a complete picture of an individual's sleep experience. The assessment of sleep quality is a multidimensional function that includes factors such as total sleep time, awakening, expectations, global perception, nocturnal awakenings, tiredness after waking, day-to-day energy, and other factors. As a result, various tools may be needed to assess different dimensions of sleep. 

Further research addressing the quality of sleep among ICU patients is needed. Many aspects of this field have not been adequately studied, including the influence of invasive ventilation and ventilatory modes on a patient's sleep or the impact of inotropic or cardiovascular-active drugs on sleep deprivation. Additional multicenter studies to test interventions and strategies to promote sleep and to minimize alterations of sleep-wake patterns in the ICU, taking into account factors such as disease severity, age, medications, and length of stay, are needed.

When patients are admitted to the ICU, the primary aim of healthcare professionals is to save their lives. However, some life-saving interventions can lead to adverse events and other adverse consequences in the short and medium term, including disruption of sleep. To address this issue, healthcare providers should identify factors that may disturb their patients' sleep and develop intervention plans based on evidence-based strategies.

To improve our understanding of the importance of sleep in ICU patients, we suggest using the scales outlined in this study as a routine practice. Additionally, healthcare providers should receive training on promoting sleep and evaluating its quality.

Data regarding the sleep quality of patents in the ICUs of Portuguese hospitals are limited, and this study provides new insight in this area. The findings support additional exploration of appropriate and practical tools to monitor and to evaluate the quality of sleep in critically ill patients.

KEY MESSAGES

▪ We suggest routine implementation of sleep quality assessment in intensive care unit patients, including the scales used in this study.

▪ It is essential to identify factors that may lead to sleep disturbance in critically ill patients.

▪ Therapeutics should be directed at all potential sleep-disturbing factors, optimizing the diurnal and nocturnal environment, and minimizing unnecessary sleep interruptions.