Different nursing interventions on sleep quality among... : Medicine (original) (raw)

1. Introduction

Adequate rest plays a crucial role in maintaining homeostasis, particularly during the recovery phase from an illness. Nevertheless, research has underscored the prevalence of sleep disruptions and inadequate rest among patients in intensive care units.[1–3] These disruptions manifest as suboptimal sleep quality, difficulties in falling asleep, fragmented sleep patterns, frequent nocturnal awakenings, and diminished periods of deep, slow-wave sleep.[4,5]

Disturbed sleep has been associated with compromised immune function, prolonged stays in critical care units, an elevated risk of delirium among critically ill patients, and increased mortality rates within this population.[6,7] Furthermore, inadequate sleep can persist for up to 6 months after discharge from the critical care unit, significantly impacting individuals’ quality of life.[8] Several factors contribute to disrupted sleep in the critical care setting, including postoperative pain, medical or nursing interventions, as well as environmental disturbances such as noise and light.[9]

While pharmacological approaches have been extensively used to enhance subjective or objective sleep quality in critically ill individuals, there has been no systematic comparison of the effects of these pharmacological agents,[10] leaving their effectiveness uncertain.[11] Non-pharmacological interventions primarily target modifiable risk factors, such as sensory deprivation, sleep deprivation, and immobilization, and are recommended for addressing sleep disturbances in critical care unit patients.

To date, only one meta-analysis has explored the efficacy of non-pharmacological interventions, such as the use of eye masks, earplugs, relaxation techniques, and music, in alleviating sleep disruptions among critically ill individuals.[12] However, this analysis was limited by the inclusion of a small number of studies and substantial heterogeneity among them. Nonetheless, it did find evidence suggesting that the use of earplugs or eye masks, or both, can extend total sleep duration.

Traditional pairwise meta-analyses have limitations as they only directly compare 2 interventions, making it challenging to simultaneously assess the comparative effectiveness of all available interventions—an essential consideration in clinical practice. Consequently, selecting the optimal non-pharmacological intervention, whether a single approach or a combination, for managing sleep disturbances in critically ill patients remains a complex task for healthcare professionals.

To address this disparity, a network meta-analysis methodology can be employed to combine both direct and indirect evidence while concurrently evaluating numerous treatment options.[13] This approach serves to inform clinical decision-making. Therefore, the study aimed to conduct a comprehensive comparison of the effects of various non-pharmacological interventions on sleep quality among critically ill patients in need of intensive care.

2. Methods

The current study, a systematic review and network meta-analysis, strictly adhered to the reporting guidelines set forth in the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) extension statement, which focuses on the reporting of systematic reviews that incorporate network meta-analyses.[14] Ethical approval was not deemed necessary for this study, as it involved a meta-analysis of existing articles, thus eliminating the requirement for handling individual patient data.

2.1. Search strategy

randomized controlled trials (RCTs) that compared different nursing interventions on sleep quality among critically ill patients were searched in electronic databases including PubMed, Embase and Cochrane Library (Cochrane Central Register of Controlled Trials) databases. All relevant RCTs will be collected from the inception of each database to July 15, 2023. We will use the MeSH/Emtree terms, combining free-text words that were properly adjusted for the different databases in all of the search strategies. Search terms used were ICU, intensive care unit, critically ill OR critical illness AND (relaxation combined with imagery (RI) OR nursel, music + earplugs + eye masks, music, eye masks, earplugs + eye masks, earplugs, aromatherapy, Warm footbath combined with acupoint exercise (WFA), Virtual reality meditation (VR)). Ongoing trials or unpublished studies were also searched in ClinicalTrials.gov. Two reviewers (D.H. and Y.L.) independently read titles and abstracts for preliminary screening and reviewed full-text eligibility. Any disagreements were resolved by discussion with a third party or by consultation with the investigator (Y.L.).

2.2. Inclusion criteria and exclusion criteria

Studies were included if the following inclusion criteria (PICOS) were met: Population (P): Critically ill patients; Interventions (I): RI, nursel, music + earplugs + eye masks, music, eye masks, earplugs + eye masks, earplugs, aromatherapy, WFA, VR; Control (C): routine care; Outcomes (O) sleep quality; Study (S): All relevant randomized controlled trials were included. Exclusion criteria were as follows: case reports and comments; studies with insufficient data; reviews or meta-analyses studies; studies with only case group; and no follow-up after discharge.

2.3. Data extraction

Two authors (J.Y. and C.L.) independently screen literature, extract data, and cross-check them. In case of disagreements, a third reviewer is consulted to assist with the judgment, and any missing information is supplemented by contacting the author as much as possible. When screening literature, the title and abstract are read first, and after excluding obviously irrelevant literature, the full text is further read to determine whether it should be included. The main content of data extraction includes: first author and publication year, country, design, intervention, control, frequency, lasting days, measurement, number of the patients, age of the patients, male patients, ICU type (cardiac surgical intensive care unit (CSICU), coronary care unit (CCU), medical intensive care unit (MICU), surgical intensive care unit (SICU) and ICU days, sedation use, mechanical ventilation (MV) use and Acute Physiology and Chronic Health Evaluation-II (APACHE-II) score.

2.4. Quality assessment

The risk of bias in RCTs was assessed by 2 reviewers (D.H. and Y.L.) using the Cochrane Collaboration’s risk of bias tool as depictive in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions, version 5.1.0), which comprised items such as random sequence generation, allocation concealment, blinding of participants and outcome assessors, incomplete outcome data, reporting bias, and other bias. Each domain was assessed as low, unclear and high according to the instruction. In case of any discrepancies in the evaluations between the 2 reviewers, a third reviewer (Y.L.) was consulted to resolve them.

2.5. Statistical analysis

A Bayesian network meta-analysis with a random-effect model was performed using gemtc package in R, version 3.6 (R Foundation for Statistical Computing) and rjags package. Simulations were allowed to burn-in for 10,000 Markov Chain Monte Carlo (MCMC) iterations (using the WinBUGS default Gibbs sampling method), which in our study were sufficient for all parameter estimates to stabilize and converge between 2 chains with different initial values. A burn-in phase of 20,000 iterations was followed by 50,000 updates, where the number of burn-in iterations was chosen according to the Brooks-Gelman-Rubin method for convergence checks. Median values from the posterior distribution were used to calculate estimated outcomes, represented as standard mean differences (SMDs), along with their corresponding 95% credible interval (CrI). Statistically significant differences were considered when the 95% CrI did not encompass 0 for mean differences. The significance level was set at P < .05. Furthermore, surface under the cumulative ranking curve (SUCRA) values were employed to rank the different interventions, where higher SUCRA values indicated more effective interventions. To evaluate heterogeneity, the _I_2 test was used, with a threshold of 50% indicating low heterogeneity. Global inconsistency was assessed by comparing the fit of consistency and inconsistency models using the deviance information criterion (DIC), with similar DIC values across different models indicating good consistency. For local inconsistency, node-splitting analysis was utilized, and a P value greater than .05 suggested no significant inconsistency between the direct pairwise results and the indirect results. We conducted a Bayesian hierarchical framework network meta-regression with random-effects using the gemtc package in R. This package automatically assigns uninformative prior distributions to all parameters in our model, a common practice in NMA. Comparison-adjusted funnel plots were performed by Stata 14.2 (Stata Corp, College Station, TX) to assess publication bias for network meta-analyses.

3. Results

3.1. Study selection

Of the 855 relevant publications that were identified through the electronic search and additional sources, 202 were excluded because they were duplicates. After the title and abstract were screened, further 638 studies were excluded. After verifying the remaining 15 full-text reports, 31 RCTs met the inclusion criteria and were included in the network meta-analysis.[7,15–44] The study selection process is shown in Figure 1.

Figure 1.:

Flow diagram of the literature selection process.

3.2. Study characteristics

The included studies were published between 1998 and 2023. Three studies were originated from USA, 1 from Thailand, 3 from India, 7 from Iran, 4 studies originated from Turkey, one originated from France, 2 originated from China, 2 originated from South Korea, 2 originated from Australia, 2 originated from Taiwan and 1 study from Egypt. Twenty-eight studies were parallel studies and the rest studies were crossover studies. A total of 11 treatments (routine care, aromatherapy, ear plugs, ear plugs + eye mask, eye mask, music, music + ear plugs + eye mask, nursel, RI, VR, and WFA) were included in this network meta-analysis. The duration of ICU stay varied, spanning from 1 to 5 days. Sleep quality assessment included Richards-Campbell Sleep Questionnaire (RCSQ), Verran and Snyder-Halpern sleep scales (VSH), Pittsburgh Sleep Quality Index (PSQI), St Mary’s Hospital Sleep Questionnaire (SMHSQ) Visual analogue scale (VAS). Number of patients ranged from 8 to 112. Mean age of the patients ranged from 46.9 to 76. And Male patients ranged from 0% to 74%. ICU type included MICU, CCU and SICU. ICU days ranged from 2.13 to 4.32 day. Detailed information can be seen in Tables 1 and 2.

Table 1 - General characteristic of the included studies.

C = control group, E = experiment group, EE = earplugs combined with eyes mask, MEE = music combined with earplugs and eye mask, NR = not report, NurseI = nurse intervention, PSQI = Pittsburgh Sleep Quality Index, RCSQ = Richards-Campbell Sleep Questionnaire, RI = relaxation combined with imagery, SMHSQ = St Mary’s Hospital Sleep Questionnaire (SMHSQ), VAS = visual analogue scale, VR = virtual reality meditation, VSH = Verran and Snyder-Halpern sleep scales, WFA = warm footbath combined with acupoint exercise.

Table 2 - General characteristic of the included studies.

CCU = coronary care unit, CSICU = cardiac surgical intensive care unit, ICU = intensive care unit, MICU = medical intensive care unit, MV = mechanical ventilation, NR = not reported.

3.3. Risk of bias

The risk of bias summary and risk of bias graph for the included trials is shown in Figures 2 and 3 respectively. Five trials were graded as having a low risk of bias, 10 trials were at an unclear risk of bias and the rest studies were rated as high risk of bias. Twenty included trials reported an appropriate random sequence generation. Nine studies were rated as low risk of bias for allocation concealment and 6 studies were rated as unclear risk of bias. Six studies were rated as low risk of bias for blinding of participants and personnel. Seven studies were at unclear risk of bias for blinding of outcome assessment. Fourteen studies were rated as low risk of bias for incomplete outcome data and selective reporting. Eighteen studies were rated as low risk of bias for other bias.

Figure 2.:

Risk of bias summary of the included studies.

Figure 3.:

Risk of bias graph of the included studies.

3.4. Sleep quality

Figure 4 illustrates a network plot of sleep quality. All included RCTs used two-arm study designs. The plot revealed 11 treatments in the 31 RCTs, namely the use of routine care, RI, nursel, music + earplugs + eye masks, music, eye masks, earplugs + eye masks, earplugs, aromatherapy, WFA, and VR. Two closed loops were formed in the network meta-analysis; thus, inconsistency testing was conducted in the 2 loops.

Figure 4.:

Network structure diagrams of sleep quality.

Network meta-analysis showed significantly heterogeneity with global (_I_2 = 98.2%, Fig. 5). In head-to-head comparison, eye masks (SMD = 40.0, 95%CrI: 15.0–65.0, P < .05, Fig. 6; Table 3) and earplugs + eye masks (SMD = 34.0, 95%CrI: 16.0–51.0, P < .05, Fig. 6; Table 3) were associated with an increase of the sleep quality than routine care.

Table 3 - Efficacy of different comparisons for sleep quality by SMDs and corresponding 95% CrIs.

Figure 5.:

Heterogeneity analysis of the sleep quality.

Figure 6.:

Forest plot of the sleep quality as compared with routine care.

The SUCRA shows that eye masks ranked first (SUCRA, 84.6%), earplugs + eye masks ranked second (SUCRA, 77.7%), earplugs ranked third (SURCA, 63.8%) and aromatherapy ranked the last (SUCRA, 18.5%, Fig. 7). There was no indication of publication bias as shown by the symmetrical funnel plot (Fig. 8).

Figure 7.:

Surface under the cumulative ranking curve (SUCRA) probabilities of different treatments for sleep quality.

Figure 8.:

Funnel plot of the different treatments for sleep quality.

We used the node-splitting method and its Bayesian P value to report the inconsistency of our results. For the majority of our results, the confidence intervals from direct and indirect evidences are in general consistent, with minor differences (Fig. 9).

Figure 9.:

Node-split analysis of the different treatments for sleep quality.

4. Discussion

4.1. Main finding

This study performed a network meta-analysis of 31 RCTs involving 2036 patients, which is based on the largest sample size to date, with an estimated sample size increase of 59.3% compared with the sample size in a previous meta-analysis (1207 patients).[12] Our findings revealed that eye masks (SMD = 40.0, 95%CrI: 15.0–65.0, P < .05) and earplugs + eye masks (SMD = 34.0, 95%CrI: 16.0–51.0, P < .05) were associated with an increase of the sleep quality than routine care. Moreover, eye masks ranked first (SUCRA, 84.6%), earplugs + eye masks ranked second (SUCRA, 77.7%), earplugs ranked third (SURCA, 63.8%), emerged as particularly effective interventions in enhancing sleep quality. Critical care nurses should consider integrating these evidence-based interventions into their daily care routines to address sleep issues in critically ill patients within intensive care units. Our approach incorporated data from studies that couldn’t directly compare eligible interventions, resulting in more precise estimates of their effects.

4.2. Compared with previous meta-analysis

A previous network meta-analysis on the same topic was done by Shih et al[12] and published in 2011. In detail, the previous meta-analysis included 21 RCTs for analysis involving a total of 1207 subjects, and showed that the eye masks alone and music combined with earplugs and eye masks appear to be the most effective interventions for improving sleep quality in people who are critically ill. Our meta-analysis reinforces earlier results by including 10 recently published RCTs. These studies were high-quality and included an additional 829 patients. Another traditional meta-analyses suggested that using both eye masks and earplugs together could enhance sleep in critically ill individuals,[10,45,46] our study reveals a different perspective. Specifically, our findings indicate that the use of eye masks alone, rather than in conjunction with earplugs, holds promise for improving sleep quality in critical care units.

The potential discomfort associated with earplugs may account for the discrepancy between our findings and previous meta-analysis.[47] Factors such as discomfort, ear soreness, and anxiety stemming from the absence of background noise could contribute to the reluctance to use earplugs.[30,46,48] Consequently, our study supports the argument that using earplugs as a standalone intervention may not significantly enhance-and could even potentially impair – sleep quality in critically ill individuals when compared to standard care. In summary, our findings suggest that critically ill individuals who use earplugs during the night may experience poorer sleep quality.

The potential effectiveness of eye masks in improving sleep quality can be attributed to the interaction between the circadian rhythm and the diurnal-nocturnal cycle. In critical care settings, the lack of natural light due to the absence of windows and continuous exposure to artificial lighting both day and night are the primary triggers for sleep disturbances. Consequently, an altered light-dark cycle can disrupt the nocturnal release of melatonin from the pineal gland. Using an eye mask during the sleep period has the potential to increase melatonin levels, thereby contributing to an improvement in sleep quality.[49]

In view of these findings, it is advisable for critical care nurses to gauge the receptiveness of their patients toward the use of eye masks and earplugs. Furthermore, they should offer their expertise and support to help individuals choose the most suitable sleep-enhancing tool during their stay in critical care units. Future research initiatives should delve deeper into the hypothesis that eye masks might exhibit superior efficacy in improving the sleep quality of critically ill patients compared to earplugs.

A holistic approach to sleep care, designed to alleviate anxiety, reduce noise disruptions, and manage lighting conditions, has been proposed as a promising strategy for addressing sleep-related challenges in critical care environments.[50,51] Our study unveiled that a comprehensive treatment regimen, which included music, eye masks, and earplugs, particularly the combination of music with earplugs and eye masks, led to a noteworthy improvement in sleep quality when compared to standard care and select alternative interventions among adult patients in critical care units. Moreover, the efficacy of music as a non-pharmacological intervention to enhance sleep in critically ill individuals finds support in recent meta-analysis findings from 202.[52] These results align with our own investigation, which highlighted the beneficial impact of music on sleep quality, even if it didn’t reach statistical significance.

Several mechanisms have been proposed to explain the impact of music on sleep, which include relaxation, distraction, rhythmic entrainment, and masking.[53] The implementation of a sleep care bundle, encompassing music, eye masks, and earplugs, has demonstrated effectiveness in mitigating sleep disruptions in critical care units. The synergistic effects of this comprehensive approach are plausible. Our research findings suggest that both the integration of music with earplugs and eye masks and the use of eye masks alone have the potential to be effective strategies for addressing sleep disturbances in critically ill individuals. Notably, the integration of music with earplugs and eye masks represents a multifaceted intervention, while the use of eye masks alone can be viewed as a single-component approach. This raises the question of why both interventions yielded similar outcomes in improving sleep quality.

The introduction of earplugs as part of the combined intervention might potentially explain the observed phenomenon, as our research results indicate that earplugs had a counterproductive effect on enhancing sleep in critically ill patients when compared to standard care. Therefore, while both music and eye masks independently contribute to enhanced sleep quality, the inclusion of earplugs may attenuate the cumulative benefits, resulting in a scenario where using music in combination with earplugs and eye masks yields sleep improvements on par with those achieved with eye masks alone.

In light of our study’s findings, it is worth highlighting the remarkable effectiveness of aromatherapy in improving the sleep quality of critically ill patients compared to standard care. It is plausible to suggest that the reduction in anxiety and stress levels may be a pivotal factor in explaining the positive impact of aromatherapy on sleep quality in this specific population. This assertion aligns with previous research demonstrating that lavender essential oil, a commonly used element in aromatherapy, significantly alleviates anxiety and stress levels in patients admitted to critical care units.[24,54]

The principle of transitivity, a fundamental assumption in network meta-analyses, shaped our research methodology.[55] To mitigate both within- and between-study heterogeneity, we implemented rigorous search strategies and inclusion criteria. While our study utilized a random-effects model to accommodate heterogeneity and assess inconsistencies, it is important to recognize the possibility of unmeasured effect modifiers that might impact the results of direct and indirect comparisons.

The interpretation of the findings derived from this network meta-analysis requires careful consideration of several noteworthy limitations. Primarily, as is common in meta-analyses, heterogeneity poses a substantial challenge. In our study, the presence of diverse participant characteristics, varied study attributes (encompassing a range of interventions and study designs), the inclusion of comparisons involving routine care, and relatively modest sample sizes within the randomized controlled trials we examined may potentially impact the internal validity of our results. Furthermore, it’s essential to acknowledge that the quality of the data included heavily influences the efficacy of a study’s findings. In the context of this specific network meta-analysis, a significant proportion of the randomized controlled trials (18 out of 20) displayed deficiencies in either adequately documenting or appropriately executing an allocation concealment procedure. Moreover, certain studies raised concerns or were considered to carry a substantial risk of bias regarding missing outcome data. They either did not utilize an intention-to-treat approach to address missing data or failed to adequately disclose the rationale behind data gaps. However, the incorporation of studies addressing these issues may pose a threat to the internal validity of our study. Furthermore, although our current network meta-analysis did not identify significant discrepancies, it did not provide sufficient evidence to unequivocally confirm the overall consistency of the network. Nevertheless, this analysis has highlighted the potential effectiveness of both music combined with earplugs and eye masks, as well as the use of eye masks alone, in enhancing sleep quality among critically ill patients in need of intensive care. Another significant finding from this study suggests that the use of earplugs may have adverse effects on sleep within critical care units.

Given that music combined with earplugs and eye masks, as well as eye masks alone, represent low-cost and highly feasible interventions, we propose that healthcare professionals consider these options as non-pharmacological strategies for enhancing sleep quality in critically ill patients. Such interventions have the potential not only to improve sleep but also to reduce the risk of delirium, shorten critical care unit stays, and decrease mortality rates among critically ill patients requiring intensive care.

5. Conclusions

In conclusion, eye masks and earplugs + eye masks are the most effective interventions for improving sleep quality in critically ill patients. We recommend that researchers design large-scale, high-quality randomized controlled trials, with a particular focus on implementing adequate allocation concealment and effective missing data management. These trials should further investigate the treatment effects of non-pharmacological interventions on sleep disturbances in critically ill individuals. Additionally, future research should explore the effects of combining music with eye masks to validate the inferences made in the present network meta-analysis.

Author contributions

Methodology: Jing Ye.

Project administration: Jing Ye.

Software: Daijin Huang, Dongyan Shen.

Supervision: Daijin Huang.

Validation: Chang Liu.

Visualization: Yumei Li, Chang Liu, Dongyan Shen, Yunhui Lv.

Writing – original draft: Yumei Li, Yunhui Lv.

Abbreviations:

RCTs

randomized controlled trials

References

[1]. Bahcecioglu Turan G, Gürcan F, Özer Z. The effects of eye masks and earplugs on sleep quality, anxiety, fear, and vital signs in patients in an intensive care unit: a randomised controlled study. J Sleep Res. 2023.

[2]. Kakar E, Ottens T, Stads S, et al. Effect of a music intervention on anxiety in adult critically ill patients: a multicenter randomized clinical trial. J Intensive Care. 2023;11:36.

[3]. Ahn YH, Lee HY, Lee SM, et al. Factors influencing sleep quality in the intensive care unit: a descriptive pilot study in Korea. Acute Crit Care. 2023;38:278–85.

[4]. Pelin M, Sert H. Development of the sleep quality scale for coronary care patients (SQ-CC). Intensive Crit Care Nurs. 2023;79:103485.

[5]. Teng J, Qin H, Guo W, et al. Effectiveness of sleep interventions to reduce delirium in critically ill patients: a systematic review and meta-analysis. J Crit Care. 2023;78:154342.

[6]. Alegria L, Brockmann P, Repetto P, et al. Improve sleep in critically ill patients: study protocol for a randomized controlled trial for a multi-component intervention of environment control in the ICU. PLoS One. 2023;18:e0286180.

[7]. Kiliç G, Kav S. Effect of using eye masks and earplugs in preventing delirium in intensive care patients: a single-blinded, randomized, controlled trial. Nurs Crit Care. 2023;28:698–708.

[8]. Tonna JE, Dalton A, Presson AP, et al. The effect of a quality improvement intervention on sleep and delirium in critically ill patients in a surgical ICU. Chest. 2021;160:899–908.

[9]. Aparício C, Panin F. Interventions to improve inpatients’ sleep quality in intensive care units and acute wards: a literature review. Br J Nurs. 2020;29:770–6.

[10]. Locihová H, Axmann K, Padyšáková H, et al. Effect of the use of earplugs and eye mask on the quality of sleep in intensive care patients: a systematic review. J Sleep Res. 2018;27:e12607.

[11]. Jun J, Kapella MC, Hershberger PE. Non-pharmacological sleep interventions for adult patients in intensive care units: a systematic review. Intensive Crit Care Nurs. 2021;67:103124.

[12]. Shih CY, Gordon CJ, Chen TJ, et al. Comparative efficacy of nonpharmacological interventions on sleep quality in people who are critically ill: a systematic review and network meta-analysis. Int J Nurs Stud. 2022;130:104220.

[13]. Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med. 2004;23:3105–24.

[14]. Bae JH, Park EG, Kim S, et al. Comparative renal effects of Dipeptidyl Peptidase-4 inhibitors and Sodium-Glucose Cotransporter 2 inhibitors on individual outcomes in patients with type 2 diabetes: a systematic review and network meta-analysis. Endocrinol Metab (Seoul). 2021;36:388–400.

[15]. Arttawejkul P, Reutrakul S, Muntham D, et al. Effect of nighttime earplugs and eye masks on sleep quality in intensive care unit patients. Indian J Crit Care Med. 2020;24:6–10.

[16]. Borromeo AR. The Effects of Aromatherapy on the Patient Outcomes of Anxiety and Sleep Quality in Coronary Care Unit Patients. Texas Woman’s University; 1998.

• Cited Here

[17]. Chaudhary A, Kumari V, Neetu N. Sleep promotion among critically ill patients: earplugs/eye mask versus ocean sound-a randomized controlled trial study. Crit Care Res Pract. 2020;2020:8898172.

[18]. Daneshmandi M, Neiseh F, SadeghiShermeh M, et al. Effect of eye mask on sleep quality in patients with acute coronary syndrome. J Caring Sci. 2012;1:135–43.

[19]. Demoule A, Carreira S, Lavault S, et al. Impact of earplugs and eye mask on sleep in critically ill patients: a prospective randomized study. Crit Care. 2017;21:284.

[20]. Díaz-Alonso J, Smith-Plaza AM, Suárez-Mier B, et al. Impact of a nurse intervention to improve sleep quality in intensive care units: results from a randomized controlled trial. Dimens Crit Care Nurs. 2018;37:310–7.

[21]. Hajibagheri A, Babaii A, Adib-Hajbaghery M. Effect of rosa damascene aromatherapy on sleep quality in cardiac patients: a randomized controlled trial. Complement Ther Clin Pract. 2014;20:159–63.

[22]. Hansen IP, Langhorn L, Dreyer P. Effects of music during daytime rest in the intensive care unit. Nurs Crit Care. 2018;23:207–13.

[23]. Hu RF, Jiang XY, Hegadoren KM, et al. Effects of earplugs and eye masks combined with relaxing music on sleep, melatonin and cortisol levels in ICU patients: a randomized controlled trial. Crit Care. 2015;19:115.

[24]. Karadag E, Samancioglu S, Ozden D, et al. Effects of aromatherapy on sleep quality and anxiety of patients. Nurs Crit Care. 2017;22:105–12.

[25]. Lee SY, Kang J. Effect of virtual reality meditation on sleep quality of intensive care unit patients: a randomised controlled trial. Intensive Crit Care Nurs. 2020;59:102849.

[26]. Litton E, Elliott R, Ferrier J, et al. Quality sleep using earplugs in the intensive care unit: the QUIET pilot randomised controlled trial. Crit Care Resusc. 2017;19:128–33.

[27]. Mahran GS, Leach MJ, Abbas MS, et al. Effect of eye masks on pain and sleep quality in patients undergoing cardiac surgery: a randomized controlled trial. Crit Care Nurse. 2020;40:27–35.

[28]. Moeini M, Khadibi M, Bekhradi R, et al. Effect of aromatherapy on the quality of sleep in ischemic heart disease patients hospitalized in intensive care units of heart hospitals of the Isfahan University of Medical Sciences. Iran J Nurs Midwifery Res. 2010;15:234–9.

[29]. Obanor OO, McBroom MM, Elia JM, et al. The impact of earplugs and eye masks on sleep quality in surgical ICU patients at risk for frequent awakenings. Crit Care Med. 2021;49:e822–32.

[30]. Richardson S. Effects of relaxation and imagery on the sleep of critically ill adults. Dimens Crit Care Nurs. 2003;22:182–90.

[31]. Ryu MJ, Park JS, Park H. Effect of sleep-inducing music on sleep in persons with percutaneous transluminal coronary angiography in the cardiac care unit. J Clin Nurs. 2012;21:728–35.

[32]. Sha Y, Kong Q, He H, et al. Effect of individualised music intervention on sleep quality for patients in ICU after thoractomy. J Nurs Train. 2013;23:1451–3.

[33]. Su CP, Lai HL, Chang ET, et al. A randomized controlled trial of the effects of listening to non-commercial music on quality of nocturnal sleep and relaxation indices in patients in medical intensive care unit. J Adv Nurs. 2013;69:1377–89.

[34]. Zhou D, Binhong Y, Chaoliang S. Influence of acupoint exercise on sleep and anxiety in patients with sleep deprivation in intensive care unit Chin. Nurs Res. 2017;31:2589–92.

[35]. Altintaş S, Çelik S, Karahan E. The effects of ergonomic sleep mask use on sleep quality and comfort in intensive care patients. J Sleep Res. 2023:e13966.

[36]. Akpinar RB, Aksoy M, Kant E. Effect of earplug/eye mask on sleep and delirium in intensive care patients. Nurs Crit Care. 2022;27:537–45.

[37]. Babaii A, Adib-Hajbaghery M, Hajibagheri A. Effect of using eye mask on sleep quality in cardiac patients: a randomized controlled trial. Nurs Midwifery Stud. 2015;4:e28332.

[38]. Baghaie Lakeh M, Baghaie Lakeh M, Khaleghdoost Mohammad T, et al. The effect of use of earplugs on sleep quality in coronary care units patients. J Holist Nurs Midwifery. 2018;28:93–100.

[39]. Bajwa N, Saini P, Kaur H, et al. Effect of ear plugs and eye mask on sleep among ICU patients: a randomized control trial. Int J Curr Res. 2015;7:23741–5.

[40]. Dave K, Qureshi A, Gopichandran L. Effects of earplugs and eye masks on perceived quality of sleep during night among patients in intensive care units. Asian J Nurs Educ Res. 2015;5:319–22.

[41]. Lin YC, Lin TJ, Liu C-H, et al. Effects of an earplug placement intervention on sleep quality in patients in a medical intensive care unit: a randomized controlled trial. Int J Nurs Pract. 2022;28:e13016.

[42]. Mashayekhi F, Arab M, Abazari F. The effects of earplug on perception of sleep in patients of Coronary Care Unit (CCU) educations. Middle East J Nurs. 2013;7:3–8.

[43]. Menger J, Urbanek B, Skhirtladze-Dworschak K, et al. Earplugs during the first night after cardiothoracic surgery may improve a fast-track protocol. Minerva Anestesiol. 2018;84:49–57.

[44]. Yazdannik AR, Zareie A, Hasanpour M, et al. The effect of earplugs and eye mask on patients’ perceived sleep quality in intensive care unit. Iranian J Nurs Midwifery Res. 2014;19:673–8.

[45]. Brito RA, do Nascimento Rebouças Viana SM, Beltrão BA, et al. Pharmacological and non-pharmacological interventions to promote sleep in intensive care units: a critical review. Sleep Breath. 2020;24:25–35.

[46]. Hu RF, Jiang XY, Chen J, et al. Non-pharmacological interventions for sleep promotion in the intensive care unit. Cochrane Database Syst Rev. 2015;2015:CD008808.

[47]. Huang HW, Zheng BL, Jiang L, et al. Effect of oral melatonin and wearing earplugs and eye masks on nocturnal sleep in healthy subjects in a simulated intensive care unit environment: which might be a more promising strategy for ICU sleep deprivation? Crit Care. 2015;19:124.

[48]. Scotto CJ, McClusky C, Spillan S, et al. Earplugs improve patients’ subjective experience of sleep in critical care. Nurs Crit Care. 2009;14:180–4.

[49]. Hu RF, Jiang XY, Zeng YM, et al. Effects of earplugs and eye masks on nocturnal sleep, melatonin and cortisol in a simulated intensive care unit environment. Crit Care. 2010;14:R66.

[50]. Huang YC, Chang YC, Wu CY, et al. Applying a sleep care bundle to improve quality of sleep in patients in the intensive care unit. Hu Li Za Zhi. 2020;67:98–105.

[51]. Patel J, Baldwin J, Bunting P, et al. The effect of a multicomponent multidisciplinary bundle of interventions on sleep and delirium in medical and surgical intensive care patients. Anaesthesia. 2014;69:540–9.

[52]. Kakar E, Venema E, Jeekel J, et al. Music intervention for sleep quality in critically ill and surgical patients: a meta-analysis. BMJ Open. 2021;11:e042510.

[53]. Dickson GT, Schubert E. How does music aid sleep? Literature review. Sleep Med. 2019;63:142–50.

[54]. Cho EH, Lee MY, Hur MH. The effects of aromatherapy on intensive care unit patients’ stress and sleep quality: a nonrandomised controlled trial. Evid Based Complement Alternat Med. 2017;2017:2856592.

[55]. Spineli LM. Modeling missing binary outcome data while preserving transitivity assumption yielded more credible network meta-analysis results. J Clin Epidemiol. 2019;105:19–26.

Keywords:

critically ill patients; network meta-analysis; nursing interventions; sleep quality

Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.