Effects of Ward Noise on Psychological Health and Sleep Quality during Recovery of Patients Who Underwent Surgery for Haemorrhagic Stroke

Abstract

Objective:

This study aimed to investigate the impact of ward noise on psychological health and sleep quality in patients recovering from haemorrhagic stroke (HS) surgery.

Methods:

A retrospective clinical study was conducted in 230 patients who underwent surgery for HS. Patients were assigned to groups on the basis of admission timing relative to ward renovation completion, with a buffer period of 1 month. The patients were sequentially enrolled into the following two groups: a regular ward group (n = 105) before noise reduction renovations and a noise-reduction group (n = 125) after renovations. Noise levels were measured in both ward environments. Psychological health was assessed using the Hospital Anxiety and Depression Scale (HADS). Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Recovery outcomes were measured using the National Institutes of Health Stroke Scale (NIHSS) and the Modified Rankin Scale (mRS). Data were collected on postoperative days 1 and 14. Statistical analyses were performed using independent t-tests for between-group comparisons, paired t-tests for within-group changes and one-way analysis of variance (ANOVA) with Tukey’s HSD post-hoc analysis for multi-period noise level comparisons (α = 0.05).

Results:

On postoperative day 14, the noise-reduction group demonstrated lower total HADS scores (P < 0.001) and lower global PSQI scores (P < 0.001). The noise-reduction group had lower NIHSS scores and lower mRS scores on postoperative day 14 (P < 0.001). Hospital stay duration was shorter in the noise-reduction group, and patient satisfaction scores were significantly higher (both P < 0.001).

Conclusion:

Noise reduction in hospital wards significantly improves psychological health, sleep quality and recovery outcomes in patients recovering from surgery after HS. These findings underscore the importance of optimising the hospital environment to support recovery.

KEY MESSAGES

• (1)Noise reduction method significantly improves anxiety and depression in patients with HS during recovery.
• (2)Hospital noise control enhances sleep quality across multiple domains in patients with HS post-surgery.
• (3)Noise-reduced environments are associated with shortened hospital stays and improved patient satisfaction.

INTRODUCTION

Haemorrhagic stroke (HS), a major category of cerebrovascular disease, is characterised by the rupture of cerebral blood vessels.[1,2] Despite advances in surgical techniques and critical care management, HS remains associated with high mortality rates of 30–50% and significant disability amongst survivors.[3,4] The recovery process following HS is particularly critical for long-term outcomes. Patients with HS frequently experience psychological disturbances, including anxiety and depression.[5,6] These psychological factors significantly influence rehabilitation engagement, functional recovery and quality of life.[5] Similarly, sleep disturbances affect 40–78% of patients suffering from stroke, and they are particularly pronounced following HS.[7] Compromised sleep architecture disrupts neuroplasticity processes that are crucial for brain recovery, impairs cognitive function, exacerbates fatigue and further contributes to psychological distress, thus delaying recovery.[7,8]

Whilst considerable attention has been directed towards pharmacological therapy, rehabilitation protocols and patient-centred care in stroke management, environmental factors affecting recovery remain relatively unclear. Amongst these, hospital noise is an unavoidable environmental stressor.[9] Modern hospital wards frequently record noise levels of 55–75 dB, substantially exceeding the World Health Organization’s recommendations of 35 dB during daytime and 30 dB during nighttime for healthcare facilities.[9] Previous studies indicated that environmental noise can induce physiological stress responses, including increased blood pressure, increased heart rate (HR), altered cortisol secretion and enhanced sympathetic nervous system activity.[10] These alterations can be particularly concerning for cerebrovascular patients with already compromised regulatory mechanisms. Noise-induced sleep fragmentation can further compound these physiological perturbations.[11] However, research specifically examining how hospital noise affects psychological health and sleep quality amongst patients with HS during recovery is limited. The current noise reduction therapy in healthcare settings has shown mixed results, with some studies reporting modest improvements in patient sleep and satisfaction and others demonstrating limited clinical benefits.[12,13] Moreover, most existing research has focused on general medical populations rather than specific patient groups with heightened vulnerability to environmental stressors.[13,14]

Despite evidence documenting noise effects in general medical populations, patients with HS represent a uniquely vulnerable cohort due to compromised neuroplasticity mechanisms, disrupted autonomic regulation and heightened susceptibility to environmental stressors during critical recovery periods. This population-specific vulnerability remains inadequately characterised in existing literature. The present study investigated the relationship of ward noise levels with psychological health parameters and sleep quality during the critical postoperative recovery period following cerebral haemorrhagic surgery. By comparing outcomes between patients in standard versus noise-reduced environments, this study aimed to elucidate the potential benefits of noise mitigation strategies for this patient population and provide evidence-based recommendations for optimising hospital environments to support recovery.

MATERIALS AND METHODS

Study Design and Participants

A total of 263 patients were assessed for eligibility between January 2023 and January 2024. Amongst them, 21 were excluded due to incomplete data, 10 were excluded due to severe comorbidities and 2 were excluded due to being deceased. Ultimately, 230 cases were enrolled in the final analysis. The patients were divided into two groups: the regular ward group (n = 105) hospitalised before noise reduction renovations (from January 2023 to June 2023) and the noise-reduction group (n = 125) hospitalised after renovations (from August 2023 to January 2024). A gap of 1 month (July 2023) was maintained between groups to ensure complete implementation of noise reduction measures. The study protocol was approved by the Institutional Ethics Committee of Plastic Surgery Hospital, Chinese Academy of Medical Sciences (Approval No. 2025062019332289), and all patients provided informed consent.

The inclusion criteria were as follows: (1) diagnosis of HS confirmed by computed tomography or magnetic resonance imaging[15]; (2) aged 18–75 years; (3) surgical noise reduction method for HS; (4) 2–4 weeks post-onset (subacute phase); (5) volume of bleeding <30 mL (specifically including patients with smaller haemorrhages requiring surgery due to mass effect, deteriorating neurological status or accessible location) and (6) hospital stay of at least 14 days.

The exclusion criteria included the following: (1) severe cognitive impairment preventing completion of assessments; (2) pre-existing hearing impairment; (3) history of psychiatric disorders (history of psychiatric disorders, including major depressive disorder, generalised anxiety disorder, bipolar disorder, schizophrenia spectrum disorders or any condition requiring psychotropic medication within 6 months pre-admission, as documented in medical records or confirmed through structured clinical interviews); (4) severe comorbidities affecting recovery (such as severe cardiac, pulmonary, hepatic or renal dysfunction) and (5) use of sedatives or hypnotics unrelated to the current condition.

Noise Reduction

The wards underwent environmental enhancements integrated with routine clinical care. All wards were completed renovated and fully functional prior to the enrolment of the noise-reduction group. Key modifications encompassed the following: (1) architectural sound management: installation of sound-attenuating ceiling panels, multilayer acoustic wall boards, resilient flooring systems and airtight door seals to establish spatial acoustic isolation with measured overall noise reduction of 2–15 dB depending on time periods; (2) medical equipment optimisation: modification of care devices featuring vibration-dampening bases, alarm systems with adjustable sensitivity thresholds and routine mechanical audits to minimise operational noise and achieve 5–10 dB reduction in peak noise levels; (3) clinical behaviour modification: implementation of staff training modules emphasising nocturnal voice modulation, mandatory use of wireless notification systems and scheduled equipment calibration during low-activity periods; and (4) visitor management: restricting visitors to two persons per day, limiting meeting hours to between 10:00 and 20:00 and providing guidance on noise restrictions.

Noise Measurement

Three-channel continuous monitoring was performed using sound analysers (NL-52, Rion) positioned 1.50 m above ground level, maintaining 1 m clearance from reflective surfaces. Placement covered patient resting zones, care activity hubs and transitional areas. Data acquisition occurred at 300-second intervals over consecutive 168-hour cycles, capturing A-weighted parameters: equivalent continuous sound pressure (LAeq), peak transient levels (LAmax) and baseline ambient noise (LAmin). Continuous monitoring occurred over three non-consecutive 72-hour periods per ward (totalling 216 hours), with measurements recorded at 300-second interval, yielding 2592 data points per monitoring cycle to ensure temporal representativeness across circadian variations and weekly patterns. Metrological validation included pre-deployment calibration against reference standards and periodic in situ verification. Historical noise data from the same period in the previous year were collected as an additional control to control for potential seasonal variations in noise levels.

Routine Nursing Care

Both groups received standardised postoperative care for subacute cerebral haemorrhage, including neurological monitoring (Glasgow Coma Scale assessment every 8 hours and vital sign monitoring every 4 hours), head positioning at 15°–30° elevation, swallowing function assessment within 24 hours with modified diet textures as needed and psychological support through active listening and family education. A progressive mobilisation protocol was implemented as follows: passive range-of-motion exercises (days 1–3), active-assisted exercises (days 4–7) and supervised ambulation (week 2 onwards). Secondary complication prevention strategies included deep vein thrombosis prophylaxis, pneumonia prevention and pressure ulcer prevention through standard protocols. Blood pressure was maintained at systolic 140–180 mmHg with multimodal pain management.

Data Collection

(1) Demographic and clinical data, including age, gender, body mass index (BMI), medical history, haemorrhage characteristics, surgical details and length of hospital stay, were collected from medical records.

(2) Psychological health was assessed using the Hospital Anxiety and Depression Scale (HADS).[16,17] This scale has a validated 14-item instrument with separate anxiety (HADS-A) and depression (HADS-D) subscales, each consisting of seven items scored from 0 to 3 (total score range of 0–21 for each subscale). Scores of 0–7, 8–10 and 11–21 indicate normal, borderline and clinical anxiety or depression, respectively. The total score of HADS ranges from 0 to 42, and higher scores represent worse psychological distress. HADS has Cronbach’s α = 0.80. It was administered on postoperative days 1 (baseline) and 14 (outcome) for both groups.

(3) Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI), a 19-item self-report questionnaire assessing seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication and daytime dysfunction.[18,19] Each component is scored 0–3, yielding a global score of 0–21, with scores >7 indicating worsened sleep quality. PSQI has Cronbach’s α = 0.84. PSQI was assessed at baseline (pre-surgery) and on postoperative day 14.

(4) The National Institutes of Health Stroke Scale (NIHSS) and the Modified Rankin Scale (mRS) were used to assess neurological function and recovery amongst patients.[20,21,22] NIHSS is a 15-item scale that evaluates neurological function in patients with stroke, with scores ranging from 0 (no deficit) to 42 (severe deficit). The scale includes assessments of consciousness, visual field, motor function, sensation, coordination, language and speech. A higher NIHSS score indicates more severe neurological impairment. NIHSS demonstrated good inter-rater reliability, with intraclass correlation coefficients ranging from 0.95 to 0.99, and good internal consistency, with Cronbach’s α = 0.74–0.92. Meanwhile, mRS is used to assess overall disability, with scores ranging from 0 (no symptoms) to 6 (death). Both scales were assessed at baseline (pre-surgery) and on postoperative day 14 to determine the neurological status and degree of disability amongst the patients, offering a comprehensive view of their recovery.

(5) Patient satisfaction was assessed using the Patient Satisfaction Questionnaire-18 (PSQ-18), an 18-item tool that evaluates satisfaction across several domains,[23,24] including technical quality (four items), interpersonal manner (two items), communication (two items), time spent with healthcare providers (two items), accessibility (four items) and environment comfort (four items). Each item is scored on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating greater satisfaction. The total score ranges from 18 points to 90 points, with higher values reflecting better patient satisfaction. PSQ-18 has been widely used and validated in healthcare settings, and in this study, the Chinese version of PSQ-18 demonstrated strong internal consistency (Cronbach’s α = 0.87), indicating reliable measurement of patient satisfaction. This scale was administered on postoperative days 1 (baseline) and 14 (outcome) in both groups to assess changes in satisfaction levels following noise reduction.

Statistical Analysis

Data were analysed using SPSS (version 25.0, IBM Corp., Armonk, NY, USA), and tables were created using Microsoft Excel 2021 (Microsoft Corporation, Redmond, WA). The Shapiro–Wilk test was used to verify the normality of continuous variables. Continuous variables with normal distribution were presented as mean ± standard deviation (SD) and compared using independent t-tests between groups and paired t-tests within groups. For continuous variables that were not normally distributed, data were presented as median (interquartile range) and compared between groups by using Mann–Whitney U test (non-parametric). One-way ANOVA was used to compare noise levels amongst three periods (historical control, pre-renovation and post-renovation). Categorical variables were presented as frequencies (percentages) and compared using χ²-square tests. Statistical significance was set at P < 0.05.

RESULTS

Demographic and Clinical Characteristics

As shown in Table 1, no significant differences were observed between the groups in terms of age, gender, BMI, haemorrhage volume, haemorrhage location, surgical approach and comorbidities (all P > 0.05), indicating comparable baseline characteristics.

Table 1.

Demographic and clinical characteristics of patients

Characteristic	Regular ward group (n = 105)	Noise-reduction group (n = 125)	t/χ2	P
Age (years)	62.32 ± 4.62	62.67 ± 5.26	0.531	0.596
Gender, n (%)
Male	58 (55.24)	72 (57.60)	0.127	0.722
Female	47 (44.76)	53 (42.40)
BMI (kg/m2)	24.15 ± 2.57	24.76 ± 2.41	1.855	0.065
Haemorrhage volume (mL)	14.74 ± 3.61	14.86 ± 4.69	0.214	0.831
Haemorrhage location, n (%)
Basal ganglia	42 (40.00)	48 (38.40)	0.316	0.957
Thalamic	28 (26.67)	35 (28.00)
Lobar	23 (21.90)	29 (23.20)
Cerebellar	12 (11.43)	13 (10.40)
Surgical approach, n (%)
Craniotomy	67 (63.81)	78 (62.40)	0.047	0.829
Minimally invasive	38 (36.19)	47 (37.60)
Comorbidities, n (%)
Hypertension	73 (69.52)	89 (71.20)	0.074	0.786
Diabetes mellitus	31 (29.52)	35 (28.00)	0.065	0.799
Coronary heart disease	18 (17.14)	24 (19.20)	0.148	0.700

Note: BMI, body mass index.

Noise Levels

As shown in Table 2, noise measurements showed significant reductions in daytime and nighttime noise levels following renovation. The comparison revealed no significant differences between the historical control period and the regular ward group (P > 0.05), confirming temporal consistency and ruling out seasonal variations as confounding factors. However, the noise-reduction group showed significantly lower noise levels than the historical control period and the regular ward group (P < 0.05). The LAeq, LAmin and LAmax during daytime and nighttime in the noise-reduction group remarkably decreased compared with those in both control periods (P all < 0.001). These findings supported the effectiveness of noise reduction renovation in reducing environmental noise for patients whilst ruling out temporal confounding factors.

Table 2.

Ward noise indicators before and after renovation, dBA

Noise parameter	Historical control period	Regular ward group (n = 105)	Noise-reduction group (n = 125)	F	P
Daytime (06:00–22:00)
LAeq	55.97 ± 4.31	56.31 ± 4.25	44.01 ± 3.62*#	350.10	<0.001
LAmin	44.83 ± 3.89	45.16 ± 3.84	40.52 ± 3.83*#	52.70	<0.001
LAmax	71.18 ± 3.62	71.52 ± 3.56	65.81 ± 3.63*#	92.06	<0.001
Nighttime (22:00–06:00)
LAeq	42.29 ± 3.87	42.52 ± 3.94	39.92 ± 2.61*#	20.05	<0.001
LAmin	35.21 ± 2.83	35.44 ± 2.80	32.76 ± 2.59*#	34.49	<0.001
LAmax	51.61 ± 3.81	51.83 ± 3.77	45.61 ± 3.73*#	102.30	<0.001

Note: LAeq, A-weighted equivalent continuous sound level; LAmin, minimum A-weighted sound pressure level; LAmax, maximum A-weighted sound pressure level; dBA, A-weighted decibel; ^*Indicates comparison with historical control period, P < 0.05; ^#Indicates comparison with regular ward group, P < 0.05.

Effects on Psychological Health

As shown in Table 3, both groups showed comparable HADS scores at baseline, with no significant differences between groups (P > 0.05). By day 14, both groups had an improvement in HADS scores compared with baseline, whereas the noise-reduction group exhibited significantly lower HADS subscales and total scores than the regular ward group (P < 0.001).

Table 3.

Psychological health indicators

Variables	Time	Regular ward group (n = 105)	Noise-reduction group (n = 125)	t	P
HADS-A	Postoperative day 1	8.21 ± 2.29	8.33 ± 2.32	0.393	0.695
	Postoperative day 14	6.42 ± 1.42*	5.35 ± 1.09*	6.459	<0.001
HADS-D	Postoperative day 1	8.03 ± 2.43	8.15 ± 2.57	0.362	0.718
	Postoperative day 14	6.36 ± 1.48*	5.31 ± 1.29*	5.478	<0.001
Total score	Postoperative day 1	16.24 ± 3.26	16.48 ± 3.53	0.611	0.510
	Postoperative day 14	12.54 ± 3.82	10.94 ± 2.91	3.602	<0.001

Note: HADS-A, Hospital Anxiety and Depression Scale-Anxiety subscale; HADS-D, Hospital Anxiety and Depression Scale-Depression subscale.; *Indicates comparison with baseline, P < 0.05.

Effects on Sleep Quality

The global PSQI scores and component scores for both groups are presented in Table 4. Whilst both groups showed poor sleep quality on postoperative day 1, the noise-reduction group demonstrated significantly improved sleep quality on postoperative day 14 compared with the regular ward group (P < 0.001).

Table 4.

Sleep quality measurements

PSQI	Regular ward group (n = 105)	Noise-reduction group (n = 125)	t	P
Postoperative day 1
Subjective sleep quality	2.42 ± 0.68	2.38 ± 0.71	0.435	0.664
Sleep latency	2.58 ± 0.74	2.61 ± 0.69	0.314	0.754
Sleep duration	2.31 ± 0.82	2.28 ± 0.77	0.284	0.777
Habitual sleep efficiency	2.19 ± 0.89	2.24 ± 0.85	0.435	0.664
Sleep disturbances	2.76 ± 0.58	2.79 ± 0.62	0.373	0.710
Use of sleep medication	1.85 ± 1.12	1.82 ± 1.18	0.197	0.844
Daytime dysfunction	2.67 ± 0.71	2.64 ± 0.74	0.310	0.757
Global PSQI score	16.78 ± 3.24	16.76 ± 3.18	0.047	0.963
Postoperative day 14
Subjective sleep quality	1.84 ± 0.69*	1.23 ± 0.58*	7.295	<0.001
Sleep latency	1.97 ± 0.71*	1.31 ± 0.62*	7.489	<0.001
Sleep duration	1.73 ± 0.68*	1.18 ± 0.54*	6.962	<0.001
Habitual sleep efficiency	1.68 ± 0.77*	1.09 ± 0.61*	6.413	<0.001
Sleep disturbances	2.21 ± 0.64*	1.67 ± 0.58*	6.845	<0.001
Use of sleep medication	1.24 ± 0.89*	0.87 ± 0.74*	3.508	<0.001
Daytime dysfunction	1.95 ± 0.73*	1.38 ± 0.62*	6.421	<0.001
Global PSQI score	12.62 ± 2.84*	8.73 ± 2.15*	11.853	<0.001

Note: PSQI: Pittsburgh Sleep Quality Index; *Indicates comparison with the baseline time of the corresponding group, P < 0.001.

Recovery Outcomes and Patient Satisfaction

Table 5 presents the recovery outcomes for both groups. The noise-reduction group showed shorter hospital stays and better patient satisfaction than the regular ward group (P < 0.001). Both groups showed significant improvement from pre-surgery to postoperative day 14 in the mRS and NIHSS scores, but the noise-reduction group demonstrated greater improvement (P < 0.001).

Table 5.

Neurological recovery outcomes and patient satisfaction

Parameter	Regular ward group (n = 105)	Noise-reduction group (n = 125)	t/U	P
Length of hospital stay (days)	18.42 ± 3.87	16.31 ± 2.94	7.981	<0.001
mRS score
Pre-surgery	5 (4–5)	4 (4–5)	6231	0.287
Postoperative day 14	2 (2–3)*	2 (2–2)*	4826	<0.001
NIHSS
Pre-surgery	16.73 ± 2.47	16.58 ± 2.69	0.437	0.662
Postoperative day 14	12.42 ± 3.58*	10.85 ± 3.21*	3.567	<0.001
PSQ-18 score	65.32 ± 7.23	71.43 ± 7.92	6.063	<0.001

Note: mRS, modified Rankin scale; NIHSS, National Institutes of Health NIH Stroke Scale; PSQ-18, Patient Satisfaction Questionnaire-18.; Indicates comparison with the pre-surgery time of the corresponding group, P < 0.001.

DISCUSSION

HS represents a category of diseases characterised by high mortality and morbidity rates. Despite aggressive and effective treatment therapy, approximately 80% of patients develop varying degrees of neurological dysfunction, with severe cases experiencing complete loss of independence in activities of daily living.[25] Following the acute phase of emergency management, as patients regain consciousness and develop a deeper understanding of their condition and prognosis, the presence of long-term sequelae, such as hemiplegia and aphasia, may gradually generate concerns regarding diminished personal quality of life, subsequently triggering emotional and somatic symptoms, including anhedonia, depressed mood and sleep disturbances. Research has documented that the overall prevalence rates of post-stroke depression and anxiety are 27% and 35%, respectively.[26,27] These psychological complications diminish patients’ rehabilitation motivation and participation, thereby impeding the recovery process.[28] Furthermore, studies have reported that post-stroke depression and anxiety are associated with increased risks of recurrence and mortality, significantly compromising patients’ physical and mental health and quality of life.[29]

The findings of this study provided important insights into the relationship between hospital environmental factors and recovery outcomes in patients with HS. Environmental noise activates the hypothalamic-pituitary-adrenal axis, leading to increased cortisol levels and sustained sympathetic nervous system arousal.[30] This physiological stress response can exacerbate existing neuroinflammatory processes and compromise cerebral autoregulation mechanisms.[31] In addition, noise-induced sleep fragmentation disrupts the natural progression through sleep stages, particularly reducing slow-wave sleep and REM sleep phases that are crucial for neuroplasticity and cognitive recovery.[32] Sleep interruptions trigger micro-arousals that activate the autonomic nervous system, leading to increased HR variability and blood pressure fluctuations.[33] These physiological perturbations can delay the brain’s natural recovery processes, including glymphatic clearance of metabolic waste products and consolidation of neural pathways essential for functional restoration.[34] Continuous exposure to increased sound levels can heighten anxiety through classical conditioning responses, where patients develop anticipatory stress reactions to environmental sounds.[35] This chronic state of hypervigilance interferes with the parasympathetic nervous system’s restorative functions, perpetuating a cycle of psychological distress.[35] Furthermore, noise-induced sleep deprivation contributes to emotional dysregulation by affecting neurotransmitter balance, particularly serotonin and dopamine pathways involved in mood regulation.[11] Although the noise-reduction therapy implemented in the present study achieved significant improvements, the noise levels post-noise reduction method still exceeded the WHO recommendations (daytime: 44.01 vs. 35 dB; nighttime: 39.92 vs. 30 dB). However, achieving WHO-recommended noise levels remains challenging in real-world clinical settings due to essential medical equipment, emergency alarms and patient care activities. Despite not meeting these ideal standards, the findings demonstrated that feasible noise reduction therapy can still provide meaningful clinical benefits for patient recovery outcomes. A quieter environment may facilitate better communication between patients and healthcare providers, enhance treatment compliance and reduce the cognitive load associated with processing competing auditory stimuli. These factors collectively contribute to a more conducive healing environment that supports physical and psychological recovery processes. A fundamental methodological constraint inherent to the study design warrants explicit acknowledgment. The temporal cohort allocation strategy, whilst pragmatically necessitated by infrastructure renovation logistics, introduces potential confounding variables that preclude definitive causal attribution. Sequential enrolment based on admission timing relative to renovation completion inherently conflates the noise-reduction method with unmeasured temporal factors, including potential seasonal variations in clinical presentation, evolving care practices and observational effects subsequent to environmental modifications. Although historical noise data demonstrated temporal stability and clinical protocols remained standardised throughout the study period, the absence of concurrent control conditions represents an intrinsic limitation of quasi-experimental environmental modification studies. This methodological constraint necessitates interpretative circumspection. Whilst the observed associations between noise reduction and improved clinical outcomes demonstrated statistical robustness and clinical relevance, they cannot be definitively isolated from potential period effects. Future investigations employing cluster-randomised designs or interrupted time-series methodologies could provide enhanced causal inference capabilities.

This study has some limitations that should be considered. The retrospective design restricts the ability to draw causal conclusions regarding the relationship between noise reduction and improvements in psychological health and sleep quality. The potential confounding factors that were not measured could influence the outcomes. The study was conducted in a single-centre setting, which may limit the generalisability of the findings to other healthcare environments or patient populations. Moreover, the lack of long-term follow-up data prevents an assessment of the sustainability of the observed improvements in psychological well-being, sleep quality or recovery outcomes. Future research should aim to overcome these limitations by adopting a prospective, multi-centre approach to enhance the external validity of the findings. Long-term follow-up studies are needed to determine whether the benefits of noise reduction persist over time. Additionally, incorporating objective measures of sleep, such as polysomnography, could strengthen the evaluation of sleep quality. Exploring the impact of noise reduction on other factors, including cognitive function and overall quality of life, could provide a more comprehensive understanding of its role in improving recovery outcomes.

CONCLUSION

Hospital noise reduction therapy is associated with improvements in psychological health, sleep quality and selected recovery parameters amongst patients with HS. Environmental modifications may represent a valuable adjunct to standard stroke care protocols. Implementation of comprehensive noise reduction strategies in hospital settings warrants consideration to be a part of a holistic approach to stroke recovery management.

Availability of Data and Materials

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

Author Contributions

DongChao Pan (first author): Conceptualized and designed the study, conducted data analysis, and drafted the manuscript. Responsible for overall coordination of the research project and interpretation of results.

Long Yao (second author): Assisted in designing the methodology, including noise reduction method protocols, and contributed to data collection. Participated in manuscript revision.

LiYi Shen (third author): Responsible for statistical analysis and interpretation of data, particularly reflux events, gastric residual volume, and motility parameters.

JiDi Fu (corresponding author): Supervised the research, provided critical feedback on study design, analysis, and results interpretation. Managed manuscript revisions, and ensured all ethical considerations were met. Corresponding author and overall project oversight.

Ethics Approval and Consent to Participate

This study was approved by the Plastic Surgery Hospital, Chinese Academy of Medical Sciences (Approval No. 2025062019332289). All participants or their lethal guardians have provided written informed consents.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding Statement

None.