Abstract
Objective:
The study aims to investigate the effect of ward nighttime noise management on sleep quality and negative emotions in postoperative patients with osteonecrosis of the femoral head (ONFH) within an Enhanced Recovery After Surgery (ERAS) framework.
Methods:
A single-center retrospective, controlled study was conducted. Clinical data of 140 ONFH patients who underwent total hip arthroplasty (THA) between January 2022 and March 2025 were analyzed. Based on the implementation timeline of ERAS-based ward nighttime noise management at Luoyang Orthopedic-Traumatological Hospital of Henan Province (Henan Provincial Orthopedic Hospital), patients admitted from January 2022 to June 2023 without the noise management protocol (n = 72) were assigned to the conventional group, and those admitted from July 2023 to March 2025 with the protocol (n = 68) were assigned to the noise-reduction group. Sleep quality [using the Richards–Campbell Sleep Questionnaire (RCSQ) and polysomnography (PSG)] and negative emotions [using the short-form Depression, Anxiety, and Stress Scales (DASS-C21) and the Positive and Negative Affect Schedule (PANAS)] were compared between the two groups at admission and 1 week after hospitalization.
Results:
Compared with baseline at admission, both groups showed improved RCSQ scores, prolonged deep sleep and total sleep time measured by PSG, and reduced frequency of nighttime awakenings after 1 week of hospitalization (all P < 0.05). The noise-reduction group demonstrated significantly better outcomes in all sleep parameters compared with the conventional group (P < 0.05). Similarly, DASS-C21 scores and PANAS negative affect scores decreased, and PANAS positive affect scores increased in both groups after 1 week relative to admission (P < 0.05). The noise-reduction group demonstrated significantly lower ward nighttime noise intensity compared with the conventional group (P < 0.05).
Conclusion:
Incorporating ward nighttime noise management into ERAS protocols improves sleep quality, reduces negative emotions, and effectively lowers noise levels in ONFH patients after THA.
Keywords: enhanced recovery after surgery, noise, sleep quality
KEY MESSAGES
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(1)
Noise reduction strategies under the Enhanced Recovery After Surgery (ERAS) framework are beneficial for sleep quality improvement after total hip arthroplasty (THA) in patients with osteonecrosis of the femoral head.
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(2)
Implementation of ERAS-guided nighttime noise reduction is associated with reduced negative emotions in patients with osteonecrosis after THA.
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(3)
The integration of structured noise control strategies within ERAS frameworks effectively lowers ambient noise levels in wards during nighttime hours for enhanced recovery after hip replacement surgery.
Introduction
Osteonecrosis of the femoral head (ONFH) refers to a common condition leading to hip joint dysfunction. Total hip arthroplasty (THA) serves as an effective treatment, and it involves resection of the necrotic femoral head and worn acetabular cartilage, followed by prosthetic implantation to restore joint anatomy and function.[1,2] However, postoperative patients often experience sleep disturbances and negative emotions, which may reduce rehabilitation adherence and hinder recovery.[3] The World Health Organization (WHO) Night Noise Guidelines and the European Environmental Noise Directive indicate that the period between 22:00 and 06:00 is critical for rest, during which noise exerts more pronounced effects on sleep architecture and health.[4,5] Nighttime noise exposure is closely associated with metabolic disorders and mental health issues. Gulam et al.[6] and Jensen et al.[7] identified ward nighttime noise as a core environmental factor disturbing sleep and mood in orthopedic inpatients. Enhanced Recovery After Surgery (ERAS) is a multidisciplinary perioperative management model emphasizing multimodal optimization.[8] Although ERAS can shorten hospital stays and reduce readmission rates or mortality in patients undergoing surgery for intertrochanteric fracture or pancreatic disorders, noise management remains an underemphasized component in current practice.[9,10] The Chinese Expert Consensus on Enhanced Recovery After Hip and Knee Arthroplasty—Perioperative Pain and Sleep Management also notes that inpatient environmental factors, such as quietness and comfort, are crucial contributors to perioperative insomnia in ONFH patients; however, it does not provide specific noise management strategies.[11]
Ward noise management refers to a clinical model that employs various measures to reduce noise levels; it improves the rehabilitation environment for patients and the working conditions for healthcare staff. The WHO explicitly recommends that hospital nighttime ward noise should be controlled below 30 dB. However, for postoperative ONFH patients—who face restricted mobility, surgical pain, and frequent turning—nighttime noise often exceeds this standard. The effect of ward noise is particularly pronounced in this population and poses challenges to the clinical working environment and care efficiency. Although noise management exerts certain beneficial effects on sleep and mood of patients in surgical intensive care units and those undergoing cesarean section, targeted research focusing specifically on ONFH patients after THA remains limited.[12,13] Furthermore, existing studies are largely confined to the examination of short-term correlations between noise and sleep or emotion, and systematic data regarding the indirect improvements to the clinical working environment resulting from their combined effects are still lacking. Furthermore, current ERAS practices predominantly emphasize pain control and early mobilization, with few reports integrating nighttime noise management within the ERAS framework. Incorporating acoustic management as an environmental dimension into ERAS holds crucial public health implications for the development of a comprehensive perioperative care model. Based on these gaps, this study proposes the following hypothesis: Implementation of ERAS-based ward nighttime noise management can effectively reduce noise intensity, which considerably improves sleep quality and alleviates negative emotions in ONFH patients after THA. The present study aimed to test this hypothesis and explore the potential value of such a management model in the construction of a more holistic ERAS-based perioperative system for orthopedic patients and optimization of the quality of the clinical environment.
MATERIALS AND METHODS
Study Design
Between January 2022 and March 2025, a total of 145 patients were assessed for eligibility. Among them, two were excluded due to incomplete data, one due to a history of previous ankle surgery, one due to comorbid rheumatoid arthritis, and one due to congenital hip dysplasia. Consequently, 140 patients were included in the final analysis. A retrospective analysis was performed on the clinical data of these 140 ONFH patients who underwent THA at Luoyang Orthopedic-Traumatological Hospital of Henan Province (Henan Provincial Orthopedic Hospital) between January 2022 and March 2025. The patients were categorized into two groups based on the implementation date of the ERAS-based ward nighttime noise management protocol. Data from 72 patients admitted from January 2022 to June 2023, prior to the protocol implementation, were assigned to the conventional group. Data from 68 patients admitted from July 2023 to March 2025, following protocol implementation, were assigned to the noise-reduction group. All patients and their families were informed about the study content and provided signed informed consent. This study was conducted in compliance with the ethical principles outlined in the World Medical Association Declaration of Helsinki.[14] This study was approved by the Luoyang Orthopedic-Traumatological Hospital of Henan Province (Henan Provincial Orthopedic Hospital) Ethics Committee (Approval No.: 202505027).
Inclusion and Exclusion Criteria
Inclusion criteria were as follows: (1) met the diagnostic criteria for ONFH[15]; (2) complete clinical data; (3) classified as the association research circulation osseous (ARCO) stage IIIB to IV with concomitant acetabular wear[16]; (4) aged between 18 and 70 years; (5) indicated for THA, undergoing their first surgical intervention via elective unilateral THA using a posterolateral approach; (6) received intrathecal anesthesia combined with sciatic nerve block; (7) postoperative hospital stay of ≥1 week; (8) classified as American Society of Anesthesiologists (ASA) physical status I to III.[17]
Exclusion criteria comprised the following: (1) concomitant autoimmune diseases, malignancies, or severe respiratory disorders; (2) acute or chronic infections, severe bleeding tendencies, or coagulation abnormalities; (3) history of cardiovascular or cerebrovascular diseases or long-term use of analgesic medications; (4) other hip disorders or intraoperative periprosthetic fracture affecting postoperative rehabilitation; (5) psychiatric disorders, cognitive impairment, or communication barriers precluding completion of scale assessments; (6) previous surgical history on the ipsilateral hip or major lower limb surgery within the preceding 6 months; (7) pure-tone average thresholds >35 decibels hearing level (dB HL) according to the WHO hearing impairment grading standard after hearing assessment[18]; (8) history of significant noise exposure.
Methods
Conventional Group
Patients in the conventional group received comprehensive perioperative clinical management based on the ERAS protocol.
Preoperative clinical evaluation and preparation: (1) Condition assessment and clinical education: On the day of admission, a preoperative assessment was conducted by the attending surgeon in collaboration with an anesthesiologist and a rehabilitation specialist. During preoperative rounds, patients were informed about the etiology of ONFH, the principles of THA, surgical procedures, expected outcomes, and potential risks (e.g., prosthesis loosening, intraoperative bleeding). Key milestones in postoperative recovery were clarified. Using a “clinical case + imaging comparison” approach, the clinical significance of postoperative positioning restrictions, pain control targets, and functional exercises was explained to patients and their families. (2) Nutritional support: A clinical nutritionist performed nutritional risk screening using the Mini Nutritional Assessment.[19] For patients with moderate to severe nutritional risk, a tailored clinical nutrition support plan was formulated. (3) Optimization of preoperative clinical parameters: The surgical team guided patients to complete preoperative tests, including blood count, coagulation profile, and cardiopulmonary function. In collaboration with relevant specialties (e.g., endocrinology), active management was implemented to control parameters such as blood pressure within safe ranges for surgery. Preoperative fasting and fluid restriction times were minimized in strict accordance with anesthesia guidelines to maintain intraoperative glycemic stability.
Intraoperative clinical procedures and monitoring: (1) Precise anesthesia management: The depth of anesthesia was accurately regulated using Bispectral Index monitoring to avoid postoperative delayed emergence due to excessive anesthesia. (2) Standardized surgical technique: Minimally invasive principles were strictly followed during the procedure. The gluteus maximus was carefully dissected via anatomical landmarks to avoid injury to the sciatic nerve. (3) Temperature management: Active warming measures, including forced-air warming blankets, warmed intravenous fluids, and warmed irrigation fluids, were employed to maintain the patient’s core temperature above 36°C, with continuous intraoperative temperature monitoring.
Postoperative management: (1) Pain management: Multimodal analgesia was administered based on individual patient profiles. (2) Clinical rehabilitation guidance: On postoperative day 1, an individualized rehabilitation plan was formulated by a rehabilitation therapist based on the patient’s recovery from anesthesia and surgical site pain score. During the bed-rest phase, patients were instructed to perform quadriceps isometric contractions and ankle pump exercises. Within 24 to 48 hours postoperatively, after the surgeon evaluated prosthesis stability, patients were guided to stand with the assistance of a walking aid (e.g., a walker) while avoiding early weight-bearing to prevent prosthesis dislocation. (3) Drain and incision management: The timing of drain removal was determined within 24 to 48 hours postoperatively based on drainage volume and characteristics to reduce infection risk. The incision site was kept clean and dry and monitored for signs of redness, swelling or exudate, and dressings were changed regularly. (4) Complication management: Appropriate physical measures (graduated compression stockings, intermittent pneumatic compression devices) and pharmacological prophylaxis (anticoagulants) were used to promote lower-limb venous return and prevent deep-vein thrombosis.
Noise-Reduction Group
Patients in the noise-reduction group received comprehensive perioperative clinical management based on the ERAS protocol (identical to the conventional group) supplemented with ERAS-based ward nighttime noise management.
Enhanced intelligent management of medical equipment noise: (1) A nighttime silent mode was implemented for in-room medical devices (e.g., electrocardiogram monitors, pulse oximeters, and infusion pumps). Silent fans were adopted to optimize the internal cooling fan structures to reduce mechanical operational noise. (2) Noise-reducing medical equipment, such as silent treatment carts and low-noise suction devices, was introduced. Sound-absorbing foam or damping pads were installed on older devices, and wheel bearings were regularly lubricated. (3) New intelligent infusion pumps were deployed to precisely control flow rates, which minimized the alarm frequency caused by flow instability. (4) Air conditioner interiors were routinely cleaned of debris and dust accumulation. Fan blade angles were adjusted to reduce operational noise, and units with relatively high noise levels were replaced with low-noise models.
Mitigation of human-generated noise: (1) Standardization of healthcare staff conduct: Nightshift behavioral guidelines were established, mandating strict adherence to the “Four Quietness” principle within patient wards. Unnecessary conversations among staff were minimized. Work-related discussions were conducted in low tones, and such communications were scheduled in nonpatient areas, such as the nurses’ station whenever possible. Nonurgent care procedures were centralized after 07:00. For procedures required before 07:00, a standardized gentle awakening protocol was implemented. (2) Management of patient and family behavior: An informational leaflet on ward nighttime noise management was distributed to patients and families, detailing the importance of maintaining quietness and relevant precautions to secure their understanding and cooperation. Patients and families were instructed to set mobile phones to reasonable ring volumes, preferably vibration mode, and prohibited from using external speakers on electronic devices after 22:00. Dedicated personnel conducted nighttime rounds to promptly remind and advise those violating noise regulations. Patients repeatedly noncompliant after reminders could be relocated to single rooms to minimize disturbance to others.
Diversion of patient attention from noise: Patients were provided with earplugs for use as necessary to attenuate the effect of external noise. Patients were instructed to utilize noise-canceling headphones after 20:00 to play soft, soothing music at a volume deemed not to interfere with rest, facilitating relaxation and diverting attention from ambient noise.
Other auxiliary measures: Sound-absorbing materials, such as acoustic panels and foam, were installed on ward walls and ceilings. Anti-slip, silent flooring was laid, and gaps in doors and windows were sealed with acoustic strips. Sound-absorbing carpets were installed in corridors to absorb and block noise originating from outside and inside the wards, which reduced overall noise intensity.
Outcome Measures
Ward Nighttime Noise Intensity
Nighttime ward noise intensity was measured using a digital sound level meter (PCE Instruments GmbH, Germany, Model: PCE-332A). For the conventional group, the average noise intensity was calculated over the 7 days prior to the implementation of noise reduction measures. For the noise-reduction group, the average was determined over the 7-day period following the implementation of the measures. Noise monitoring was conducted at 28 locations in the conventional group wards (27 patient rooms + 1 nurses’ station) and 26 locations in the noise-reduction group wards (25 patient rooms + 1 nurses’ station). Monitoring was performed daily during the following time intervals: 20:00–21:00, 22:00–23:00, 00:00–01:00, 02:00–03:00, 04:00–05:00, and 06:00–07:00. The average value across these intervals was calculated for each monitoring location. The overall ward nighttime noise intensity was then determined as the average value across all monitoring locations. The sound level meter was calibrated daily prior to use. Measurements were obtained at a height of 1.2 m above the floor (simulating the patient’s ear position). Each monitoring session lasted 1 minute, with sampling conducted hourly.
Sleep Quality
At the time of admission and 1 week after hospitalization, sleep quality was assessed in both groups using the Richards–Campbell Sleep Questionnaire (RCSQ) and polysomnography (PSG) [manufactured by Jiangsu Zhong’an Biological (Group) Co., Ltd., Model: 401, Medical Device Registration Certificate No.: Xiang 20192070393]. PSG monitoring was conducted from 22:00 to 06:00, and data were analyzed using the RemLogic software (Natus Medical, USA). (1) RCSQ, originally developed by Richards et al.[20] and translated into Chinese by Chen et al.,[21] comprises five dimensions: sleep depth, sleep latency, number of awakenings, difficulty returning to sleep, and overall sleep quality. Each dimension is scored on a 0 to 100 mm visual analog scale (patients mark a point on a 100 mm line where 0 mm represents the poorest sleep and 100 mm the best sleep). The total score refers to the average of the five-dimension scores, ranging from 0 to 100, with high scores indicating desirable sleep quality. In this study, the Cronbach’s α coefficient for the RCSQ was 0.887. (2) PSG was used to monitor the duration of deep sleep, total sleep time, and the number of nighttime awakenings in both groups.
Negative Emotions
At the time of admission and 1 week after hospitalization, negative emotions were evaluated using the short-form Depression, Anxiety, and Stress Scales (DASS-C21) and the Positive and Negative Affect Schedule (PANAS). (1) DASS-C21, originally developed by Lovibond and Lovibond,[22] modified by Antony et al.[23] and translated and validated in Chinese by Wang et al.,[24] consists of three factors (depression, anxiety, and stress) with 21 items total (7 items per factor). Each item is rated on a 4-point Likert scale (0 = did not apply to me at all, 3 = applied to me very much, or most of the time). The total score ranges from 0 to 63, with low scores indicating mild negative emotional symptoms. (2) PANAS, developed by Watson et al.[25] and translated and validated by Liu et al.,[26] includes two dimensions (positive affect and negative affect) with 10 items each. Items are rated on a 5-point Likert scale (1 = very slightly or not at all, 5 = extremely). Each dimension score ranges from 10 to 50. A high positive affect score indicates positive emotions, and a high negative affect score denotes negative emotions. In this study, the Cronbach’s α coefficients for the DASS-C21 and PANAS were 0.903 and 0.876, respectively.
Details of Assessment Implementation
Questionnaire Administration and Collection
The distribution, completion, and collection of the questionnaires were managed by designated nurses who had undergone systematic training and passed a qualification assessment. The training covered the meaning of questionnaire items, communication techniques with patients, and standardized procedures for distribution and collection to ensure that the nurses could clearly explain the questions to patients without using leading language. The questionnaires were administered in paper format, and patients were instructed to complete them independently. For patients unable to complete the forms themselves, the questionnaires were verbally administered, and their responses were recorded by the nurse.
Assessment Timeline
RCSQ, DASS-C21, and PANAS were administered by designated nurses at two time points: at admission (15:00–17:00 on the day before surgery) and 1 week after hospitalization (15:00–17:00 on postoperative day 7).
Collection of Baseline Data
A general information questionnaire was designed based on the study objectives, and it encompassed the following variables: age, gender, disease duration, body mass index, ONFH type [traumatic (i.e., ONFH caused by interruption of femoral head blood supply due to trauma), steroid-induced (ONFH associated with long-term or high-dose glucocorticoid use),[27] alcohol-induced (ONFH related to chronic excessive alcohol consumption)],[28] ARCO stage, hip prosthesis material (femoral head material: metal, ceramic; liner material: highly cross-linked polyethylene, ceramic), ASA classification, affected side, educational level, preoperative Harris Hip Score (HHS) (the HHS ranges from 0 to 100, with ≥90 indicating excellent hip function, 80–89 good, 70–79 fair, and <70 poor),[29] operation time, intraoperative blood loss, incision length, and 24-hour postoperative drainage volume.
Statistical Methods
Data organization and table creation were performed using Microsoft Excel (Version 2206, Microsoft Corporation, Redmond, WA, USA). Statistical analyses were conducted with SPSS software (IBM Corp., USA, version 27.0). Continuous data conforming to a normal distribution are expressed as mean ± standard deviation (x̄±s). The normality of data was first assessed using Shapiro–Wilk test, with results indicating a normal distribution (P > 0.05). When homogeneity of variances was confirmed by Levene’s test (P > 0.05), intergroup comparisons were performed using independent‑samples t‑test, and intragroup comparisons using the paired‑samples t‑test (both two‑tailed). In cases of heterogeneity of variances, the corrected t‑test (t′‑test) was applied. Comparisons between the two groups at the same time point were conducted using independent t‑test. Categorical data are presented as n (%), and the chi‑square test was used for comparisons. A P‑value <0.05 was considered statistically significant.
Results
Baseline Data
The baseline data of the two groups showed good balance (P > 0.05; Table 1).
Table 1.
Comparison of Baseline Characteristics between the Two Groups.
| Indicator | Conventional Group (n = 72) | Noise-Reduction Group (n = 68) | χ 2/t | P |
|---|---|---|---|---|
| Age (years) | 59.46 ± 4.58 | 60.27 ± 4.63 | t = 1.040 | 0.300 |
| Gender [n (%)] | χ 2 = 0.212 | 0.646 | ||
| -Male | 43 (59.72) | 38 (55.88) | ||
| -Female | 29 (40.28) | 30 (44.12) | ||
| Disease duration (months) | 6.11 ± 0.29 | 6.18 ± 0.31 | t = 1.380 | 0.170 |
| BMI (kg/m2) | 22.07 ± 0.85 | 22.13 ± 0.82 | t = 0.425 | 0.672 |
| ONFH type [n (%)] | χ 2 = 0.238 | 0.888 | ||
| -Traumatic | 28 (38.89) | 25 (36.76) | ||
| -Steroid-induced | 31 (43.06) | 32 (47.06) | ||
| -Alcohol-induced | 13 (18.06) | 11 (16.18) | ||
| ARCO stage [n (%)] | χ 2 = 0.024 | 0.876 | ||
| -ⅢB | 8 (11.11) | 7 (10.29) | ||
| -Ⅳ | 64 (88.89) | 61 (89.71) | ||
| Prosthesis material [n (%)] | χ 2 = 0.242 | 0.886 | ||
| -Metal head + HXLPE Liner | 30 (41.67) | 31 (45.59) | ||
| -Ceramic head + HXLPE Liner | 37 (51.39) | 33 (48.53) | ||
| -Ceramic head + ceramic liner | 5 (6.94) | 4 (5.88) | ||
| ASA classification [n (%)] | χ 2 = 1.029 | 0.310 | ||
| Ⅱ | 33 (45.83) | 37 (54.41) | ||
| Ⅲ | 39 (54.17) | 31 (45.59) | ||
| Affected side [n (%)] | χ 2 = 0.296 | 0.587 | ||
| -Left hip | 34 (47.22) | 29 (42.65) | ||
| -Right hip | 38 (52.78) | 39 (57.35) | ||
| Educational level [n (%)] | χ 2 = 0.653 | 0.419 | ||
| -High school or below | 53 (73.61) | 54 (79.41) | ||
| -College or above | 19 (26.39) | 14 (20.59) | ||
| Preop. HHS score (points) | 45.78 ± 3.16 | 45.09 ± 3.04 | t = 1.315 | 0.191 |
| Operation time (min) | 83.84 ± 5.49 | 82.43 ± 5.87 | t = 1.469 | 0.144 |
| Intraop. blood loss (mL) | 265.82 ± 12.73 | 263.75 ± 12.86 | t = 0.957 | 0.34 |
| Incision length (cm) | 12.63 ± 1.05 | 12.74 ± 1.09 | t = 0.608 | 0.544 |
| 24 h Postop. drainage (mL) | 276.51 ± 13.38 | 279.42 ± 14.05 | t = 1.255 | 0.212 |
ARCO = Association Research Circulation Osseous, ASA = American Society of Anesthesiologists, BMI = body mass index, HHS = Harris Hip Score, HXLPE = highly cross-linked polyethylene, ONFH = osteonecrosis of the femoral head
Ward Nighttime Noise Intensity
The noise-reduction group demonstrated significantly lower ward nighttime noise intensity compared with the conventional group (P < 0.05; Table 2).
Table 2.
Comparison of Nighttime Noise Intensity between the Two Groups (dB).
| Group | Number of Monitoring Points | Nighttime Noise Intensity |
|---|---|---|
| Conventional group (n = 72) | 28 | 45.63 ± 4.42 |
| Noise-reduction group (n = 68) | 26 | 32.36 ± 3.15 |
| t | 12.617 | |
| P | <0.001 |
Sleep Quality
Compared with their respective preadmission baselines, both groups exhibited significant improvements after 1 week of hospitalization: RCSQ scores were increased, PSG-monitored deep-sleep duration and total sleep time were prolonged, and the number of nighttime awakenings was reduced (all P < 0.05). Furthermore, compared with the conventional group, the noise-reduction group demonstrated significantly higher RCSQ scores, longer deep sleep duration and total sleep time, and fewer nighttime awakenings (P < 0.05; Table 3).
Table 3.
Comparison of Richards–Campbell Sleep Questionnaire Scores and Polysomnography Parameters between the Two Groups Before and 1 Week After Hospitalization.
| Group | RCSQ Score (Points) | PSG Parameters | ||||||
|---|---|---|---|---|---|---|---|---|
|
|
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| Deep Sleep Time (h) | Total Sleep Time (h) | No. of Nighttime Awakenings | ||||||
|
|
|
|
||||||
| At Admission | After 1 Week of Hospitalization | At Admission | After 1 Week of Hospitalization | At Admission | After 1 Week of Hospitalization | At Admission | After 1 Week of Hospitalization | |
| Conventional group (n = 72) | 57.59 ± 4.64 | 71.82 ± 5.43* | 1.45 ± 0.31 | 2.18 ± 0.44* | 5.46 ± 0.83 | 6.82 ± 0.94* | 5.17 ± 0.48 | 2.23 ± 0.39* |
| Noise-reduction group (n = 68) | 58.12 ± 4.71 | 79.75 ± 6.28* | 1.51 ± 0.34 | 2.59 ± 0.57* | 5.58 ± 0.86 | 7.93 ± 0.98* | 5.23 ± 0.43 | 1.39 ± 0.28* |
| t | 0.671 | 8.005 | 1.092 | 4.780 | 0.840 | 6.840 | 0.777 | 14.565 |
| P | 0.504 | <0.001 | 0.277 | <0.001 | 0.402 | <0.001 | 0.438 | <0.001 |
Compared with preadmission baselines within the same group; PSG = polysomnography, RCSQ = Richards–Campbell Sleep Questionnaire; * P < 0.05.
Negative Emotions
Compared with their respective preadmission baselines, both groups demonstrated significant reductions in DASS-C21 scores and PANAS negative affect scores, along with an increase in PANAS positive affect scores after 1 week of hospitalization (all P < 0.05). Furthermore, compared with the conventional group, the noise-reduction group exhibited significantly lower DASS-C21 scores, lower PANAS negative affect scores, and higher PANAS positive affect scores (P < 0.05; Table 4).
Table 4.
Comparison of the Short-Form Depression, Anxiety, and Stress Scales and Richards–Campbell Sleep Questionnaire Scores between the Two Groups Before and 1 Week After Hospitalization (Points).
| Group | DASS-C21 | PANAS | ||||
|---|---|---|---|---|---|---|
|
|
||||||
| Positive Affect | Negative Affect | |||||
|
|
|
|||||
| At Admission | After 1 Week of Hospitalization | At Admission | After 1 Week of Hospitalization | At Admission | After 1 Week of Hospitalization | |
| Conventional group (n = 72) | 41.48 ± 4.35 | 26.27 ± 2.86* | 24.26 ± 3.35 | 33.59 ± 4.06* | 37.39 ± 4.64 | 23.25 ± 2.76* |
| Noise-reduction group (n = 68) | 42.02 ± 4.48 | 22.39 ± 2.25* | 25.13 ± 3.47 | 38.37 ± 4.82* | 38.15 ± 4.71 | 20.39 ± 2.05* |
| t | 0.724 | 8.887 | 1.509 | 6.359 | 0.962 | 6.928 |
| P | 0.471 | <0.001 | 0.134 | <0.001 | 0.338 | <0.001 |
Compared with preadmission baselines within the same group; DASS-C21 = the short-form Depression, Anxiety, and Stress Scales, PANAS = Positive and Negative Affect Schedule; * P < 0.05.
DISCUSSION
This study focused on the influence of ERAS-based ward nighttime noise management on ONFH patients following THA. The core findings revealed the following:
Improvement in sleep quality: After 1 week of hospitalization, the noise-reduction group showed a 0.41-hour prolongation in PSG-monitored deep-sleep time compared with the conventional group (2.59 vs. 2.18 hours), a 1.11-hour extension in total sleep time (7.93 vs. 6.82 hours), a reduction of 0.84 in nighttime awakenings (1.39 vs. 2.23 times), and an increase of 7.93 points in the RCSQ score (79.75 vs. 71.82 points). According to clinical research on the application of the RCSQ scale, a score improvement of ≥5 points indicates clinical improvement in sleep quality.[21]
Alleviation of negative emotions: After 1 week, the noise-reduction group exhibited a 4.78-point increase in the PANAS positive affect score (38.37 vs. 33.59 points), a 2.86-point decrease in the PANAS negative affect score (20.39 vs. 23.25 points), and a 3.88-point reduction in the DASS-C21 score (22.39 vs. 26.27 points) compared with the conventional group. These reductions align with the clinical threshold for “mild-to-moderate relief” of anxiety and depressive symptoms.[24]
Noise level control: The nighttime noise intensity in the noise-reduction group decreased to 32.36 dB, approaching the WHO-recommended standard of below 30 dB. All these changes indicated that ERAS-based nighttime noise management has clinical relevance for the improvement of sleep quality and negative emotions.
In comparison with previous studies, Hurley-Wallace et al.[30] demonstrated that noise reduction improved sleep quality in hospitalized patients. The present findings are consistent with these conclusions. By integrating subjective and objective sleep assessment tools (RCSQ and PSG), this study provides more objective and robust evidence supporting the benefits of noise reduction management.
Although nighttime ward noise intensity was significantly reduced after the implementation of noise control measures—from 45.63 ± 4.42 to 32.36 ± 3.15 dB—the noise level remained close to the WHO-recommended hospital nighttime threshold of 30 dB. This finding underscores the persistent challenge of environmental noise control in hospital settings. From a public health and health policy perspective, sustained excessive noise not only impairs patient recovery but also poses a long-term challenge to healthcare workers’ occupational health, which conflicts with the goal of building a high-quality care environment. Therefore, incorporating systematic noise management into hospital accreditation standards and core ERAS components and promoting the establishment of “quiet wards” would have profound implications for the improvement of overall healthcare quality and the safeguarding of the occupational well-being of medical staff.
Noise can be perceived as a threatening stimulus by brain structures, such as the amygdala, activating the hypothalamic–pituitary–adrenal (HPA) axis and sympathetic nervous system (SNS). This condition leads to elevated levels of stress hormones, including cortisol and adrenaline, which trigger physiological responses, such as increased heart rate, elevated blood pressure, and muscle tension.[31,32] Patients post-THA are already in a state of physiological stress related to surgical trauma. Noise can act as an additional chronic stressor; it continuously activates the HPA/SNS axis and induces a state of physiological hyperarousal, which severely hinders the initiation and maintenance of sleep.[33,34] Furthermore, noise, especially sudden and unpredictable high-intensity noise, can cause sleep arousals or full awakenings, disrupt sleep cycles, and reduce sleep efficiency. These effects are specifically manifested as a shortening of deep sleep (N3 stage) and a reduction in total sleep time.[35] The influence of noise on negative emotions may be associated with neuromodulatory mechanisms. Noise-induced sleep deprivation and activation of the HPA/SNS axis promote pain sensitization, lower pain thresholds, and heighten patients’ sensitivity to postoperative pain, which exacerbates negative emotions such as anxiety and depression.[36] Moreover, prolonged or repeated noise exposure may induce mild neuroinflammation by activating glial cells in the hippocampus, which compromises blood–brain barrier integrity and subsequently disrupts the balance of mood-regulating neurotransmitters, such as serotonin and dopamine.[37]
From the physiological perspective outlined above, noise primarily interferes with sleep via the “stress activation–sleep cycle disruption” pathway, and its effect on negative emotions mainly involves neuromodulatory pathways. In this study, measures such as equipment silencing and reduction of human-generated noise lowered the overall noise levels in wards and nursing stations, minimized unnecessary noise incidents, and reduced persistent auditory stimulation. This approach may help interrupt the initial stage of the noise–stress neural activation cascade, which contributes to the alleviation of negative emotions. The study population consisted primarily of middle-aged and elderly patients, a demographic generally more sensitive to nighttime ward noise and with relatively weaker postoperative adaptive capacity. In clinical practice, we observed that extending the quiet-hour protocol to cover the period before morning rounds (adjusted to 20:00–07:00), which encouraged earplug use when needed and maintained low-volume communication among healthcare staff at night collectively enhanced patients’ sleep experience. These low-cost, highly feasible measures should be standardized and promoted as fundamental components of high-quality clinical care. Ligree et al.[38] reported that noise-canceling headphones combined with music can facilitate noise isolation and alleviate patient anxiety and other negative emotions. In the present study, patients were instructed to use noise-canceling headphones and listen to soothing music starting at 20:00 each evening. This practice helps mask ambient noise, aligns with sleep-related brainwave frequencies, promotes the secretion of serotonin and melatonin, shortens sleep latency, regulates the autonomic nervous system to synchronize sleep cycles with circadian rhythms, and suppresses sympathetic excitation, resulting in the establishment of a favorable foundation for deep sleep.[39] It may also aid in remodeling of emotional regulation circuits, thereby enhancing patients’ emotional self-regulation capacity and fostering a clinical environment more conducive to psychological recovery.The hardware-based interventions implemented in this study—such as switching equipment alarms to gentle vibration modes and replacing conventional air conditioners with low-noise models—demonstrated high potential for adoption in other hospitals. From a technical perspective, most existing medical devices (e.g., patient monitors, infusion pumps) support mode-specific adjustments; silent alarm transitions can be achieved through system parameter optimization without large-scale equipment replacement. Low-noise infusion sets and silent treatment carts are already available as routine medical consumables and equipment upgrades on the market, which can be progressively introduced through phased procurement. The behavioral standardization for healthcare staff and patients represents a process-driven and institutional management approach, relying on systematic frameworks rather than high costs. This strategy can be readily integrated into existing nursing quality management systems and is applicable across primary care and general hospitals.
This study encountered several limitations. First, as a retrospective analysis conducted at a single center with a limited sample size of 140 patients, selection bias cannot be excluded. Moreover, external confounding factors—such as fluctuations in staffing, seasonal environmental variations, and other ward environmental conditions (e.g., temperature, humidity, and lighting)—were not fully controlled. Consequently, multiple factors might have jointly influenced the outcomes, making it difficult to precisely isolate the independent effect of noise management. Secondly, the study only assessed changes in outcome measures during the first week of hospitalization, leaving the longer-term sustainability of the effects unexplored. Thirdly, subgroup analyses based on individual patient factors, such as ONFH etiology or ARCO stage, were not performed, which might have introduced confounding. Fourthly, the intervention in the noise-reduction group included instructing patients to listen to soothing music, which might have inadvertently increased nursing attention toward these patients. Whether the observed improvements in sleep quality and negative emotions were attributable solely to noise reduction or resulted from a combination of factors, thereby weakening the specificity of the noise-reduction effect, remains unclear. Next, the potential influence of the Hawthorne effect was not controlled, and thus healthcare staff might have modified their behavior due to awareness of being observed, which could have introduced bias into noise level measurements and certain subjective assessments. Then, PSG monitoring was conducted only from 22:00 to 06:00, which, while aligning with the WHO-recommended core nighttime sleep window, might have failed to fully capture the sleep patterns of some patients outside this period, potentially compromising the comprehensiveness and accuracy of the sleep assessment.
Conclusion
The implementation of ward nighttime noise management within an ERAS context facilitates improvements in sleep quality, ameliorates negative emotions, and reduces nighttime noise intensity in ONFH patients following THA.
Availability of data and materials
The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.
Author contributions
LeiLei Zhang participated in study design, data collection, and manuscript drafting; HaoBo Liang assisted in data sorting and clinical follow-up of patients; ChenYi Zhu and YingJie Zhu engaged in implementation of ward nighttime noise management measures and outcome assessment (sleep quality and emotional state evaluation); YouWen Liu designed the overall study, supervised the research process, revised the manuscript, and took responsibility for the integrity of the study data. All authors read and approved the final manuscript.
Ethics approval and consent to participate
This study was conducted in accordance with the ethical principles of the World Medical Association Declaration of Helsinki and was approved by the Luoyang Orthopedic-Traumatological Hospital of Henan Province (Henan Provincial Orthopedic Hospital) Ethics Committee (Approval No.: 202505027). All patients and their families were fully informed of the study content and provided signed written informed consent.
Conflicts of interest
The authors declare that there are no conflicts of interest.
Acknowledgment
No.
Funding Statement
This study was supported by the 2025 Science and Technology Special Project of the National Administration of Traditional Chinese Medicine (GZY-KJS-2025-085).
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Associated Data
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Data Availability Statement
The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.