Impact of perceived fatigue on sleep quality among critical care nurses in a selected hospital

Abstract

BACKGROUND:

Fatigue and tiredness significantly affect sleep duration and timing, especially in critical care nurses working consecutive shifts without adequate rest. Symptoms such as lethargy, tiredness, and a constant need for sleep are commonly linked to fatigue and insufficient sleep, which can compromise nurse performance and patient care. This study aimed to evaluate fatigue and sleep quality among critical care nurses, explore their correlation, and examine associations with demographic factors.

MATERIALS AND METHODS:

A quantitative, nonexperimental descriptive correlational study was conducted among 100 critical care nurses at SRM Medical College Hospital and Research Centre from January to March 2023. Data were collected using the Fatigue Assessment Scale and the Pittsburgh Sleep Quality Index. Statistical analysis, including Chi-square tests, was performed using SPSS version 16, with significance set at P < 0.05.

RESULTS:

The analysis revealed no significant associations between most demographic factors and fatigue or sleep quality. However, age showed a statistically significant correlation with both fatigue and sleep quality (χ² = 16.298, P = 0.038).

CONCLUSION:

This study highlights the link between increased perceived fatigue and sleep disturbances among critical care nurses. Targeted interventions to address fatigue and enhance sleep quality are crucial to improve nurse well-being and patient care outcomes. These findings underscore the importance of addressing occupational fatigue in critical care settings.

Introduction

Fatigue is a complex phenomenon that negatively impacts multiple facets of life, including emotional, cognitive, and physical components. It severely diminishes an individual’s capacity to concentrate, perform, and retain information, while augmenting irritation and cognitive lethargy.[1] Fatigue impairs cognitive processes, diminishes perception and reaction times, and obstructs communication skills, thereby lowering overall efficiency.[2] In healthcare, weariness presents distinct issues, especially for nurses, owing to the rigorous demands of their vocation. Nurses are more susceptible to exhaustion due to shift work, inconsistent schedules, and prolonged hours of care providing.[3]

Nursing is a physically and intellectually rigorous vocation that needs continuous vigilance and alertness.[4] Nurses frequently encounter unpredictable work schedules, extended hours, and recurrent disruptions to their circadian rhythms, particularly during night shifts. These variables lead to enduring exhaustion that includes physical, mental, and emotional fatigue. Recent studies indicate that nurses in tertiary care environments face an elevated risk of chronic exhaustion owing to substantial patient loads and the necessity for ongoing critical care.[5] Fatigue among healthcare personnel greatly escalates during crises, such as the COVID-19 pandemic, due to extended working hours and increased stress levels.

The quality of sleep is inherently connected to weariness. Subjective sleep quality pertains to a nursing profession that demands both physical and intellectual rigor, necessitating constant vigilance and attentiveness. Nurses often face erratic work schedules, prolonged hours, and consistent disturbances to their circadian cycles, especially during night shifts. These variables result in persistent exhaustion including physical, mental, and emotional fatigue. Recent studies demonstrate that nurses in tertiary care settings have a heightened risk of chronic fatigue due to significant patient volumes and the requirement for continuous critical care.[6]

Fatigue among healthcare personnel markedly escalates during crises, such as the COVID-19 pandemic, due to extended working hours and increased stress levels. An individual’s evaluation of their whole sleep experience, including aspects such as duration, continuity, and the feeling of refreshment upon waking. In contrast, objective sleep quality considers measurable factors including total sleep duration, sleep architecture, and nocturnal awakenings.[7] Research indicates that shift workers, including nurses, experience irregular and inconsistent sleep patterns, often resulting in heightened fatigue levels.[8] A recent meta-analysis revealed that more than 50% of shift-working nurses suffer from poor sleep quality, negatively affecting their health and job performance.[9] The disruptions are especially evident for nurses on rotating day and night shifts since their sleep patterns are continuously altered, leading to inadequate rest and recovery.[10]

The outcomes of exhaustion resulting from inadequate sleep quality are significant. Cognitive deficits, including decreased alertness, prolonged reaction times, and worse decision-making capabilities, are commonly observed in fatigued persons.[11] These limitations elevate the probability of workplace errors and mishaps, especially in high-stakes settings like critical care units. Moreover, studies indicate that shift workers frequently endure increased psychological distress, particularly when engaged in extended shifts, night shifts, or beyond 40 h per week.[11,12] The correlation between chronic fatigue and heightened vulnerability to anxiety, despair, and burnout is well-established, especially among critical care nurses who encounter additional physical and emotional pressures.[13]

The roles and responsibilities of critical care nurses surpass their professional duties, incorporating personal and social problems that exacerbate exhaustion. Nurses in critical care units must exercise continuous awareness, make rapid choices, and deliver empathetic care to patients and their families. This elevated workload frequently results in greater fatigue and interrupted sleep, exacerbating stress and diminishing job satisfaction.[14] Furthermore, the emotional burden of tending to critically sick patients, coupled with insufficient recuperation periods, renders critical care nurses especially vulnerable to burnout.

The implications of exhaustion and inadequate sleep quality beyond personal health to encompass patient safety. Overworked nurses are more prone to making medical errors, potentially resulting in severe repercussions for patient outcomes.[15] For example, diminished reaction times and compromised decision-making skills in weary nurses can postpone essential actions in emergencies. Furthermore, persistent fatigue has been associated with diminished job performance, decreased retention rates, and increased occurrences of burnout among nurses.[16] Burnout adversely impacts nurses’ mental health and exacerbates workforce shortages, hence placing more pressure on healthcare systems.

Confronting these difficulties is crucial for safeguarding the welfare of nurses and the safety of their patients. Interventions designed to mitigate fatigue and enhance sleep quality can yield significant advantages. For example, managing work schedules to ensure sufficient rest hours, improving sleep hygiene, and providing psychological support might alleviate the detrimental effects of fatigue.[17] Additionally, organizational policies that emphasize nursing well-being, such as restricting overtime hours and facilitating access to wellness programs, can foster a supportive work environment.[18]

This study aims to assess the correlation between fatigue and sleep quality in critical care nurses, investigating the impact of demographic characteristics including age, gender, and years of experience on these elements. This research seeks to identify the primary factors contributing to exhaustion and suboptimal sleep quality, thereby offering practical insights for the formulation of tailored therapies. Comprehending these obstacles is essential for augmenting the health and job satisfaction of nurses, as well as for boosting patient safety and treatment results in critical care environments.

Materials and Methods

Study design and setting

The current study was a quantitative, nonexperimental descriptive research approach conducted correlational design. Data collection took place in the Critical Care Units of SRM Medical College Hospital and Research Centre (SRM MCH and RC) from January to March 2023.

Study participants and sampling

The sample size was calculated using the z-based sample size calculation formula at a confidence level of 95% and a power of 80%, the required sample size for the study was estimated to be 100 participants.[19] Sampling was conducted using a quota method combined with convenience sampling to select critical care nurses. The inclusion criteria for participation included nurses currently working in critical care units, holding a nursing degree, having a minimum of 6 months of work experience, and at least 3 months of experience in their current department. Additionally, participants were required to have no history of psychiatric consultations or use of medication for mental health issues in the past year and no experience of significant stressful or anxiety-provoking events in the past 6 months, such as severe illness, the loss of a loved one, or major family discord. Exclusion criteria included incomplete completion of questionnaires and withdrawal of consent during the data collection process.

Data collection tool and technique

A self-structured questionnaire divided into three sections was used for data collection. Part I focused on demographic information, including five items to gather data on age, education level, marital status, area of residence, and employment status.

Part II Occupational Fatigue Exhaustion/Recovery (OFER) Scale. This scale comprises 15 items across three subscales, with Items 9, 10, 11, 13, and 15 reverse-scored. Responses are rated on a 7-point Likert scale (0 = strongly disagree to 6 = strongly agree), yielding a total score range of 0–90, where higher scores indicate greater fatigue. The OFER Scale demonstrated a Cronbach’s alpha of 0.84.[20]

Part III Pittsburgh Sleep Quality Index (PSQI). This instrument measures subjective sleep quality over the past month via seven components scored on a 4-point Likert scale (0 = no difficulty to 3 = severe difficulty). The total score ranges from 0 to 21, with scores ≥5 indicating poor sleep quality. The PSQI demonstrated a Cronbach’s alpha of 0.83.[21]

Statistical analysis

The data analysis was performed utilizing SPSS version 16 (IBM). Descriptive statistics, encompassing frequency, percentage, mean, standard deviation, range, and quartiles, were computed to encapsulate the data. Chi-square tests were utilized to investigate correlations between certain demographic variables and levels of exhaustion and sleep quality, whilst Pearson’s correlation coefficient was applied to assess the relationships among fatigue, sleep quality, and additional variables. A 95% confidence level was utilized, and a P value < 0.05 was deemed statistically significant.

Ethical considerations

The Research Committee of SRM College of Nursing at SRMIST and the Institutional Review Committee (IEC-SRM 01/021) approved the study. Further authorization was acquired from the Dean of SRM College of Nursing. Informed consent was obtained in writing from all participants, who were guaranteed the confidentiality and anonymity of their responses. Participants were apprised of their right to withdraw at any stage of the study.

Results

Table 1 shows that most staff nurses in the critical care unit were women, with 86% of them being married, 61% being Hindu, 57% residing in an urban region, 64% having finished a professional or honors course, and 54% having a monthly family income of between Rs. 47,266 and Rs. 63,178.

Table 1.

Distribution of demographic variables by frequency and percentage for staff nurses in the critical care unit (n=100)

Demographic variables		Frequency		Percentage
Age in Years
21–24		44		44.0
25–28		40		40.0
29–32		5		5.0
>32		1		11
Gender
Male		14		14.0
Female		86		86.0
Marital status
Married		56		56.0
Unmarried		44		44.0
Religion
Hindu		61		61.0
Christian		29		29.0
Muslim		10		10.0
Others		-		-
Living area
Urban		57		57.0
Semi-urban		16		16.0
Rural		27		27.0
Educational status
Profession or honors		64		64.0
Graduate		32		32.0
Intermediate		1		1.0
High school certificate		1		1.0
Middle school certificate		1		1.0
Primary school certificate		1		1.0
Illiterate		-		-
Family monthly income
Rs. 126,360		5		5.0
Rs. 63,182–126,356		13		13.0
Rs. 47,266–63,178		54		54.0

Table 2 indicates that most staff nurses (82%) in the critical care unit reported mild levels of weariness, whereas 18% had moderate fatigue, and none reported excessive fatigue. Concerning sleep quality, 48% exhibited good sleep quality, 47% demonstrated moderate sleep quality, and 5% indicated poor sleep quality. These findings indicate that although exhaustion levels are generally low, sleep quality exhibits significant variability among nurses. The high incidence of moderate and poor sleep quality indicates a necessity for specific therapies to improve rest and recovery. Enhancing sleep quality may significantly contribute to diminishing fatigue and improving general well-being.

Table 2.

Frequency and percentage distribution of perceived fatigue levels and sleep quality levels among staff nurses in the critical care unit (n=100)

Category		Level		Frequency		Percentage
Perceived fatigue		Low fatigue (0–30)		82		82.0
		Moderate fatigue (31–60)		18		18.0
		High fatigue (61–90)		0		0
Sleep quality		Good		48		48.0
		Moderate		47		47.0
		Poor		5		5.0

Table 3 shows that the average scores for sleep quality and fatigue were 19.9211.79 and 8.03.74, respectively. The estimated Karl Pearson’s correlation value of r = 0.450, which was understood to be statistically significant at P = 0.001, indicates a favorable correlation between tiredness and sleep quality. This clearly suggests that staff nurses’ levels of fatigue in the critical care unit increase in direct proportion to their sleep disturbances.

Table 3.

Correlation between perceived fatigue and sleep quality among staff nurses in the critical care unit (n=100)

Variables		Mean		Standard deviation		Karl Pearson’s correlation and P
Fatigue		8.00		3.74		r=0.450
Sleep quality		19.92		11.79		P=0.000

Table 4 illustrates that among the staff nurses employed in the critical care unit, there was a statistically significant correlation between age (2 = 16.298, P = 0.038) and the quality of sleep. At the 0.05 level, there was no statistically significant association between the other demographic component and the degree of fatigue or quality of sleep. The level of weakness and sleep quality among staff nurses performing in the critical care unit did not differ statistically significantly based on demographic characteristics.

Table 4.

Association of perceived fatigue and sleep quality among staff nurses with their selected demographic variables (n=100)

Demographic variables		Fatigue				Sleep Quality
		Chi-square		P (Chi-Square)		Chi-Square		P (Chi-Square)
Age in years     21–24     25–28     29–32     >32		χ2=2.531		0.639		χ2=16.298 S*		0.038
Gender     Male     Female		χ2=0.389 N.S.		0.823		χ2=1.970 N.S.		0.741
Religion     Hindu     Christian     Muslim		χ2=1.323 N.S.		0.516		χ2=3.711 N.S.		0.447
Living area     Urban     Semi-urban     Rural		χ2=0.019 N.S.		0.991		χ2=0.664 N.S.		0.956
Educational status     Profession or honors     Graduate     Intermediate (or) Diploma     High school certificate     Middle school certificate     Primary school certificate     Illiterate		χ2=3.773 N.S.		0.583		χ2=5.752 N.S.		0.836
Family monthly income     Rs. 126,360     Rs. 63,182–126,356     Rs. 47,266–63,178     Rs. 18,953–31,589     Rs. 6327–18,949     Rs. 6323		χ2=5.269 N.S.		0.384		χ2=3.115 N.S.		0.979

*P<0.05 considered statistically significant. NS: Not Significant

Discussion

The principal objective of this study was to assess exhaustion and sleep quality among nursing personnel operating in critical care units. Fatigue and sleep disorders are acknowledged as significant variables affecting nurses’ health and their capacity to provide appropriate patient care. A study conducted by Kris Kunnert et al. demonstrated notable disparities in fatigue levels between night-shift and day-shift nurses, with night-shift nurses exhibiting elevated exhaustion and reduced sleep quality.[22] Abdalkarem F Alsharari (2021) examined the effects of night shift rotations on nurses’ physiological health, job performance, and patient safety in Saudi Arabia. A predictive correlational approach was employed, with 1,256 nurses participating through self-administered questionnaires. Findings indicated that 85.7% encountered patient safety concerns, while 93.6% reported physiological difficulties. The study underscores the significance of counseling and support services for vulnerable nurses to enhance treatment quality.[23]

Van de Ven et al. (2021) investigated the immediate impacts of shift work patterns on fatigue and sleep quality in 223 shift workers by daily ecological assessments over an eight-week period. Night shifts, rapid turnarounds (less than 11 h), and irregular or fixed rotations correlated with heightened weariness and reduced sleep quality, especially among individuals with compromised health or non-evening chronotypes. The research recommends enhancing shift patterns by forward rotations and sufficient recovery periods to alleviate these impacts.[24] Elrefaey et al. (2024) examined exhaustion and sleep quality in 352 critical care nurses in Najran City, Saudi Arabia, employing the PSQI and exhaustion Severity Scale (FSS). The research indicated that 65.9% of nurses experienced inadequate sleep quality and 25.2% suffered from severe weariness, with significant associations observed between war-related injuries and fatigue (r = 0.71, P = 0.00001) as well as poor sleep quality (r = 0.62, P = 0.0001). The results underscore the necessity for counseling and stress management initiatives for nurses attending to war-related injuries.[25]

A further study investigating the relationship between exhaustion and sleep quality among critical care nurses indicated that 82% experienced low levels of weariness, whereas 18% reported moderate fatigue levels. Rana et al. (2021) evaluated fatigue and sleep quality in 151 staff nurses at Lumbini Medical College during the COVID-19 pandemic utilizing the OFER and PSQI. The findings indicated that 60.9% of nurses suffered from inadequate sleep, with notable connections between sleep quality and chronic fatigue (r = 0.4, P < 0.001), acute fatigue (r = 0.39, P < 0.001), and inter-shift recovery (r = −0.41, P < 0.001). The research underscores the pressing necessity for interventions aimed at alleviating exhaustion and enhancing sleep quality among nurses in times of crisis. This study revealed that participants exhibited moderate to high levels of acute weariness and elevated levels of chronic fatigue. They exhibited low to moderate inter-shift recovery. This indicated that the inter-shift recovery level concerning acute and chronic fatigue is minimal. This discovery aligns with other research.[26,27]

Scott et al. (2014) investigated the correlation between sleep characteristics, exhaustion, and choice regret in a cohort of 546 critical care nurses, of whom 29% reported experiencing decision regret. Nurses suffering from exhaustion, daily drowsiness, insufficient inter-shift recuperation, and subpar sleep quality were more likely to express regret. Key variables comprised male gender, 12-h shift work, and satisfaction with clinical decision-making, highlighting the necessity for methods to mitigate fatigue and enhance sleep among critical care nurses.[28] Zeng et al. (2024) investigated the correlation between sleep quality and occupational exhaustion among 258 endoscopy nurses in 25 hospitals in China, emphasizing the mediation influence of positive coping strategies. The results indicated that positive coping methods exhibited a negative correlation with sleep quality and occupational exhaustion (P < 0.001), mediating 42.10% of the overall effect. The research underscores the necessity for nurse managers to enhance sleep quality and cultivate effective coping mechanisms to mitigate occupational weariness.[29]

This research examined the correlation among demographic variables, weariness, and sleep quality. The results indicated that 48% of nurses exhibited high sleep quality, 47% demonstrated intermediate sleep quality, and 5% experienced poor sleep quality. Segon et al. (2022) observed analogous data, evaluating poor sleep quality and its associated factors among 510 nurses in Northwest Ethiopia, with a prevalence of 75.5%. Factors substantially correlated with poor sleep quality were female gender, depressive symptoms, anxiety, stress, and alcohol intake. The study emphasizes the necessity for tailored interventions to address these contributing factors in order to enhance nurses’ sleep quality and overall well-being.[30] Bayoumy et al. (2023) examined sleep quality and psychological aspects in 450 health professions students at King Saud Bin Abdulaziz University. Subpar sleep quality was seen in 69.6% of students, with notable correlations to sleep disruptions, sadness (38.9%), severe stress (56.7%), and anxiety (33.1%) (P < 0.01). The report underscores the necessity for academic institutions to enact programs targeting sleep and psychological issues among students.[31]

The relationship among fatigue, sleep quality, and demographic factors indicates that younger nurses may exhibit superior sleep quality relative to their older peers. This corresponds with previous studies demonstrating that age is a crucial factor influencing sleep habits. Nurses with elevated self-esteem and emotional awareness exhibited superior coping strategies, enabling them to manage work-related stress and sustain enhanced performance levels. Nurses with low self-esteem exhibited a greater tendency for suboptimal performance, resulting from less confidence and increased stress under demanding circumstances. A recent study conducted by Supian and Ibrahim (2024) examined the determinants of sleep quality among 470 nurses in tertiary hospitals in Kelantan, Malaysia, revealing a 69.8% prevalence of inadequate sleep quality. Critical factors encompassed reduced sleep duration, limited work experience, participation in medication errors, and accidents sustained during commuting. The research underscores the necessity for treatments such as sleep hygiene initiatives, stress management seminars, and adaptable schedules to enhance nurse well-being and ensure patient safety.[32]

This study’s primary strength is in its emphasis on critical care nurses, a demographic often subjected to significant occupational stress, rendering the findings especially pertinent to their well-being and job performance. The utilization of approved instruments to evaluate fatigue and sleep quality enhances the reliability and validity of the findings. This study contributes to the expanding literature highlighting the necessity for organizational actions to improve nurses’ health and performance.

Limitation and recommendation

This study’s focus on critical care nurses and validated instruments ensures trustworthy and contextually relevant results. Inclusion of self-reported measures, correlational design, and single-site sample limit generalizability. Future studies should use longitudinal, diversified, and multi-data sources. These findings confirm the need for targeted fatigue and sleep therapies.

Conclusion

Addressing fatigue and sleep disturbances among critical care nurses is crucial for optimizing healthcare outcomes. This study highlights the significant impact of age on fatigue and sleep quality, suggesting the need for targeted interventions. Health policymakers should prioritize age-specific fatigue management programs, such as tailored work schedules, stress reduction initiatives, and sleep health education. Establishing mandatory workplace wellness policies and monitoring systems can help reduce fatigue-related risks. By focusing on these strategies, healthcare institutions can enhance nurse well-being, improve patient care, and reduce errors associated with fatigue in critical care settings. Further research should refine and evaluate these interventions.

Author’s contribution

NM: Conceptualized the study and designed the methodology. UM: Supervised the research, and wrote the initial draft of the manuscript, assisted with manuscript editing, and ensured adherence to journal submission guidelines. Provided critical revisions, verified the analytical methods, and approved the final version of the manuscript. SV: Reviewed the literature, and assisted with manuscript editing. SR: Conducted data collection, performed statistical analyses, and contributed to the interpretation of results.

Conflicts of interest

There are no conflicts of interest.

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Funding Statement

Nil.