Abstract
Objective:
This study aimed to compare the therapeutic effects of music therapy and white noise on sleep quality and psychological resilience enhancement in night-shift nurses.
Methods:
A quasi-experimental retrospective analysis was performed on 100 night-shift nurses enrolled in hospital-based health management programs between April 2024 and April 2025. The participants were categorised by program type: the music group (n = 52) received music-based care from April 2024 to September 2024, and the white noise group (n = 48) underwent white noise exposure from October 2024 to April 2025. The following were assessed before the program and at 4-week post-implementation: sleep quality (Pittsburgh Sleep Quality Index [PSQI], circadian flexibility (Circadian Type Inventory-11 [CTI-11] with Flexibility/Rigidity [FR] and Languidness/Vigorousness [LV] subscales), psychological resilience (10-item Connor-Davidson Resilience Scale [CD-RISC-10], occupational burnout (Maslach Burnout Inventory-General Survey [MBI-GS] and emotional labour management (Emotional Labor Scale [ELS]. An independent sample t-test was used to compare the differences between groups, and the effect size of the differences was quantified by Cohen’s d.
Results:
At 4-week post-implementation, the white noise group demonstrated significantly lower PSQI scores (P < 0.05), CTI-11 LV subscale scores (P < 0.05), CD-RISC-10 scores (P < 0.05) and diminished genuine emotion expression dimension scores on the ELS (P < 0.05) compared with the music group. Conversely, the white noise group had significantly higher CTI-11 FR subscale scores (P < 0.05), MBI-GS scores (P < 0.05) and surface acting plus deep acting dimension scores on the ELS (P < 0.05) compared with the music group.
Conclusion:
Music therapy and white noise exposure effectively enhance sleep quality, circadian adaptability, psychological resilience, occupational burnout recovery and emotional labour regulation in night-shift nurses. White noise demonstrates greater efficacy for sleep quality and circadian rhythm optimisation. Music therapy provides superior psychological resilience enhancement, burnout reduction and emotional labour management.
Keywords: music therapy, nurses, psychology, sleep quality
KEY MESSAGES
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(1)
Music therapy and white noise can help improve the sleep quality, circadian rhythm flexibility, psychological resilience, job burnout and emotional labour management of night-shift nurses.
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(2)
Compared with music therapy, white noise has more advantages in improving sleep quality and circadian rhythm flexibility.
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(3)
Compared with white noise, music therapy has more advantages in improving psychological resilience, job burnout and emotional labour management.
Introduction
Night-shift nurses, defined as healthcare professionals responsible for nocturnal patient care and emergency medical management, play an indispensable role in maintaining continuous healthcare system operations.[1] A growing body of research indicates that working night shifts or consecutive night shifts significantly contributes to sleep disorders and poor sleep quality among healthcare professionals.[2,3] Compared with the general population, prolonged exposure to circadian-disrupted environments results in significantly higher prevalence of sleep disorders among night-shift nurses, with approximately 80% experiencing varying degrees of sleep disturbances.[2,3,4] Compromised sleep quality adversely impacts physical health, diminishes work efficiency, impairs care quality and elevates medical error risks. Furthermore, psychological resilience − a core capacity for stress adaptation − becomes progressively impaired under sustained occupational stress and sleep fragmentation, undermining nurses’ ability to maintain psychological equilibrium during high-intensity clinical scenarios. This phenomenon consequently exacerbates occupational burnout and emotional labour strain, establishing night-shift nurses as a priority population for occupational health initiatives.[5,6] The 2021 American Academy of Sleep Medicine clinical guidelines for shift work disorder recommend mitigating physiological and psychological risks through schedule optimisation and enhanced health management protocols.[7] Additionally, the 2024 Mental Health Support Guidelines of the International Council of Nurses emphasise that nurse psychological well-being is fundamental to healthcare quality, advocating for the institutional establishment of supportive environments with evidence-based resources.[8] Chronic circadian disruption places night-shift nurses in persistent physiological stress states, compounded by high emotional labour demands and work–family conflicts. Consequently, this group exhibits reduced psychological resilience and heightened perceived stress/burnout vulnerability compared with their day-shift counterparts.[9,10] These findings underscore an urgent need for developing safe, feasible and efficient strategies to enhance holistic health outcomes in this workforce.
Nonpharmacological modalities have garnered increasing attention because of their safety profiles and practical implementability. Music therapy and white noise—both acoustics-based approaches—demonstrate promising effects on sleep quality and psychological states.[11,12] Music therapy employs structured auditory experiences (e.g., rhythmic entrainment and melodic guidance) to modulate autonomic nervous system activity and elicit relaxation responses. Its efficacy has been established in improving sleep quality among abdominal surgical patients in the intensive care unit (ICU) and adults with depression-related insomnia and reducing anxiety/perceived stress in emergency nurses during the coronavirus disease 2019 (COVID-19) pandemic.[13,14,15] White noise, characterised by uniform acoustic energy distribution across frequencies, masks environmental noise pollutants to create stable rest environments. It can enhance visual working memory performance and improve sleep quality.[16,17] Despite the high prevalence of sleep–psychological comorbidity in night-shift nurses, comparative studies evaluating these two modalities remain scarce within this specialised population, with efficacy profiles inadequately characterised. On the basis of the aforementioned evidence, the following hypothesis was formulated: music therapy and white noise exposure improve sleep quality, circadian flexibility, psychological resilience, occupational burnout and emotional labour management in night-shift nurses. For the testing of this hypothesis, a retrospective cohort study was conducted to examine the effects of music-based protocols versus white noise exposure on sleep quality and psychological resilience in this population.
MATERIALS AND METHODS
Participants
A total of 105 participants were initially enrolled in the Hefei First People’s Hospital-based health support program. Following the application of the predefined eligibility criteria, five individuals were excluded for the following reasons: use of hormonal medications within 3 months prior to enrolment (n = 1), fixed night-shift assignment duration of less than 6 months (n = 1), recent experience of divorce (n = 1) and position changes during the study period (n = 2). Consequently, 100 eligible participants were included in the final analysis. A quasi-experimental retrospective study was conducted on the clinical records of 100 night-shift nurses participating in hospital-based health support initiatives between April 2024 and April 2025. The participants were stratified into two groups according to initiative type: the music group (n = 52) received music-based protocols from April 2024 to September 2024, and the white noise group (n = 48) underwent white noise exposure from October 2024 to April 2025. All participants provided written informed consent. This study complied with the ethical principles of the Declaration of Helsinki[18] and was approved by the Review Committee of Hefei First People’s Hospital (Ethics Approval No. 202507026).
Inclusion and Exclusion Criteria
(1) The inclusion criteria were as follows: ① valid nursing licensure with ≥1 year clinical experience, ② fixed night-shift assignment duration ≥6 months with ongoing night duties during the study period, ③ night-shift frequency ≥2 weekly, ④ complete baseline data and scale assessments, ⑤ no position changes during the study, ⑥ age <45 years and ⑦ absence of uncontrolled chronic conditions (e.g., hypertension, diabetes and thyroid dysfunction).
(2) The exclusion criteria were as follows: ① absence from duty due to leave, training or education; ② probationary, visiting or rehired retired nurses; ③ pregnancy or lactation status; ④ major stressful life events within 3 months (e.g., bereavement, marital infidelity, divorce and critical illness of offspring); ⑤ study withdrawal; ⑥ hypnotic/hormonal medication use or sleep-affecting comorbidities within 3 months pre-enrolment; ⑦ history of anxiety/depressive disorders and ⑧ auditory impairment (pure-tone average >25 dB HL) or vestibular dysfunction (e.g., Ménière’s disease, vestibular neuritis and benign paroxysmal positional vertigo).
Methods
Music Group
This group received music therapy care. (1) Before night shift: 30 minutes before the start of work, the nurses wore noise-cancelling headphones in the restroom to listen to music. The music playlist was selected according to the types of music verified to reduce stress and promote relaxation, as measured by physiological indicators such as heart rate variability, combined with the principle that familiar music can suppress alpha and low-beta brain waves, and further tailored to the nurses’ personal preferences.[19,20] Baroque classical music and nature melody fusion music were mainly chosen (such as Bach’s ‘Air on the G String’, the first movement of Vivaldi’s ‘The Four Seasons − Spring’ and the combination of flowing water and bird chirping with the piano melody of ‘River Flows in You’). For the first 30 minutes, the rhythm was lively but not rushed, and the headphones played music and mindfulness voiceovers such as imagining the music transforming stress into energy and guiding each participant into a focused state, and that music can help them efficiently handle nursing challenges. The volume was gradually reduced to 25–30 dB, and the melody weakened in the last 15 minutes. (2) During night shift breaks: During the mandatory rest periods of the night shift, the nurses wore noise-cancelling headphones in the restroom to listen to music for 60 minutes. The music playlist was selected according to the types of low-frequency music and brainwave music that improve sleep quality, choosing low-frequency music with a tempo of 60–80 BPM (including jazz light music, pure music of ethnic instruments and brainwave music [alpha + theta waves], such as the scientifically proven sleep aid ‘Weightless’, Dave Koz’s ‘Take Five’, the first half of the guzheng piece ‘Fisherman’s Song at Dusk’).[21,22] The volume, melody and rhythm were clear and distinguishable for the first 10 minutes (usually 40–50 dB), and the sound intensity was below the auditory threshold for the next 50 minutes (usually ≤30 dB). Before the caring method, the nurses were guided to learn to match their breathing to the music rhythm using the 4-7-8 abdominal breathing technique (inhale for 4 seconds − hold for 7 seconds − exhale for 8 seconds) and were awakened after 60 minutes through gentle vibration. (3) After night shift and on rest days: After the night shift and whilst the nurses were returning to their residence to prepare for sleep, the music player was turned on to listen to music (the music playlist was selected based on types that improve sleep quality) and played continuously until falling asleep, with the maximum playing time not exceeding 60 minutes. On rest days, 60 minutes of music listening was also conducted before going to bed at night. The caring method lasted for 4 consecutive weeks.
White Noise Group
This group received white noise care. The white noise frequency parameters were selected on the basis of the resting-state frequency analysis and the response mechanisms of auditory midbrain neurons to varying background white noise.[23] (1) Before night shift: 30 minutes before work, the nurses wore noise-cancelling headphones in the restroom to listen to the white noise mode before night shift. The white noise selected was steady-state, low-frequency white noise (with the main frequency concentrated at 200–500 Hz). The volume was set at 40–50 dB for the first 15 minutes, and a pre-recorded rhythm guidance voice was played simultaneously (such as ‘White noise will shield surrounding disturbances, help you focus, and fully prepare you for the challenges of the night shift’). The volume was gradually reduced to 25–0 dB for the next 15 minutes, and white noise was continuously played until the start of work. (2) During night shift rest periods: During the mandatory rest periods of the night shift, the nurses wore headphones in the restroom and listened to slow-wave white noise (with a main frequency of 8–12 Hz, simulating the brain’s alpha/theta wave rhythm) for 60 minutes. The volume was set at 40–50 dB for the first 10 minutes, and the nurses simultaneously performed 4-7-8 abdominal breathing (i.e., inhale for 4 seconds − hold for 7 seconds − exhale for 8 seconds). The volume was gradually decreased to 30–35 dB for the next 40 minutes whilst continuously playing steady-state white noise. The volume was gradually increased to 35–40 dB for the last 10 minutes, and a gentle wake-up prompt sound (such as a gradually increasing bird chirping sound) was played simultaneously, followed by a voice guidance (i.e., ‘Rest is over, energy is fully restored, get ready for the next tasks’). (3) After night shift and on rest days: After the night shift and whilst the nurses were returning to their residence and preparing to sleep, a player was used at the bedside to play sleep repair white noise (with a main frequency of 5–10 Hz) until falling asleep. An automatic shutdown function was set, with a maximum playing time of no more than 60 minutes (approximately, 35–40 dB for the first 30 minutes and 25–30 dB for the next 30 minutes). On rest days, before going to bed at night, the nurses listened to the same 60-minute white noise, with the selection and process being the same as after the night shift. Continuous care was provided for 4 weeks.
Implementation Methods and Quality Control
(1) Equipment standardisation and infection control: All nursing personnel were equipped with portable, lightweight, noise-cancelling headphones featuring volume control and auto-off functionality. The devices were utilised during preshift (30-minute) and intrashift rest periods, with identical devices employed for home-based sessions postshift and on–off duty days. A standardised disinfection protocol was implemented. Each headphone was fitted with disposable medical ear-covers, placed in sterilisation bags after use and centrally collected by the hospital infection control department for ultraviolet C (UV-C) irradiation disinfection. The devices were redistributed daily, with weekly ethanol-based housing disinfection and maintenance of sterilisation logs.
(2) Protocol adherence monitoring: Curated audio materials were preloaded onto devices by institutional technicians. All participants received uniform training on operational procedures and safety considerations prior to implementation. A digital monitoring group was established for compliance tracking, requiring timestamped electronic logs after preshift sessions, intrashift breaks and off-day sessions. Valid execution was defined as ≥25 minutes for preshift sessions and ≥50 minutes for intrashift/off-day sessions. Randomised weekly telephone verification was performed.
Observation Indicators
(1) Sleep quality and circadian rhythm flexibility: Before the program and after 4 weeks of care, the Pittsburgh Sleep Quality Index (PSQI) and Circadian Type Inventory (CTI-11) were used for assessment. The PSQI was developed by Buysse et al.[24] and translated into Chinese by Liu and Tang.[25] It consists of seven aspects, including the use of sleeping pills and sleep onset latency and has a total score ranging from 0 to 21, where a low score indicates good sleep quality. The CTI-11 was developed by Folkard et al.,[26] revised by Barton et al.[27] and Smith et al.[28] and translated and validated into Chinese by Qi et al.[29] It contains two subscales with 11 items in total, each scored on a 5-point Likert scale (from almost never to almost always, scored 1–5). The subscales are flexibility/rigidity (FR) (five items, 5–25 points) and sleepiness/vigilance (LV) (six items, 6–30 points). A high score on the FR subscale indicates great circadian rhythm flexibility, and a high score on the LV subscale indicates low energy levels and weak ability to overcome sleepiness. In this study, the Cronbach α coefficients of the PSQI, the FR subscale of the CTI-11 and the LV subscale of the CTI-11 were 0.875, 0.767 and 0.738, respectively.
(2) Psychological resilience and job burnout: Before the program and after 4 weeks of care, the Connor-Davidson Resilience Scale (CD-RISC-10) and Maslach Burnout Inventory-General Survey (MBI-GS) were used for assessment. The CD-RISC-10 was developed by Connor et al.,[30] revised by Campbell-Sills and Stein[31] and translated into Chinese by Cheng et al.[32] It consists of 10 items, each scored on a 5-point Likert scale (from never to almost always, scored 0–4), with a total score ranging from 0 to 40. A high score indicates good psychological resilience. The MBI-GS was developed by Maslach et al.,[33] and validated by Bravo et al.[34] and translated into Chinese by Li et al.[35] and Zhu et al.[36] It contains 16 items across three dimensions, namely, emotional exhaustion (five items), depersonalisation (five items) and reduced personal accomplishment (six items). Each item is scored on a 7-point Likert scale (from never to very often, scored 0–6). The emotional exhaustion and depersonalisation dimensions are scored positively, whereas the reduced personal accomplishment dimension is scored negatively. The total score ranges from 0 to 96, where a high score indicates severe job burnout. In this study, the Cronbach α coefficients of the CD-RISC-10 and MBI-GS were 0.924 and 0.893, respectively.
(3) Emotional labour management: Before the program and after 4 weeks of care, the Emotional Labor Scale (ELS) was used for assessment. The ELS was developed by Diefendorff et al.[37] on the basis of the concept of emotional labour proposed by Brotheridge and Lee[38] and translated and validated into Chinese by Yao et al.[39] It consists of 14 items, each scored on a 6-point Likert scale (from extremely inconsistent to extremely consistent, scored 1–5) across three dimensions, namely, surface acting (7 items, 7–35 points), deep acting (4 items, 4–20 points) and genuine emotion expression (3 items, 3–15 points). A high score on each dimension indicates a high frequency of using that performance strategy at work. In this study, the Cronbach α coefficients of the total ELS and its three dimensions were 0.849, 0.821, 0.805 and 0.868.
Statistical Methods
Data organisation and table generation were performed using Microsoft Excel (Version 2206, Microsoft Corporation, Redmond, WA, USA). Statistical analyses were conducted with SPSS software (IBM Corp., Armonk, NY, USA, Version 27.0). Normally distributed continuous data were presented as mean ± standard deviation (x̄±s). Normality was assessed using the Shapiro–Wilk test, and data conforming to a normal distribution (P > 0.05) were further evaluated for homogeneity of variance using Levene’s test. When variances were homogeneous (P > 0.05), intergroup comparisons were performed using the independent samples t-test (two-tailed) and intragroup comparisons (pre-implementation vs. post-implementation) were performed using the paired samples t-test (two-tailed). When variances were heterogeneous, the corrected t-test (t′-test) was applied. Between-group differences at the same time point were analysed using the independent t-test. The magnitude of between-group differences was quantified using Cohen’s d, with effect sizes interpreted as follows: |d| < 0.2, small; 0.2 ≤ |d| < 0.8, medium; and |d| ≥ 0.8, large.[40] Categorical data were expressed as n (%). Comparisons were made using the χ2 test; when the minimum expected count was <5, Yates’ correction for continuity was applied. Fisher’s exact probability test was used when the total sample size was <40 or any expected count was <1. A two-tailed P-value of <0.05 was considered statistically significant.
RESULTS
Baseline Characteristics
Baseline characteristics demonstrated a satisfactory balance between the groups. No statistically significant differences were observed in age, gender, professional title, work experience, marital status, department, education level, parity, shift duration, weekly night shifts, monthly income, body mass index or protocol adherence rate (all P > 0.05; Table 1).
Table 1.
Comparison of baseline characteristics between the music and white noise cohorts of night-shift nurses
| Indicator | Music group (n = 52) | White noise group (n = 48) | χ 2/t | P | |
|---|---|---|---|---|---|
| Age (years) | 28.21 ± 3.47 | 28.06 ± 3.52 | t = 0.215 | 0.831 | |
| Gender [n (%)] | Male | 4 (7.69) | 2 (4.17) | χ 2 = 0.103a | 0.749 |
| Female | 48 (92.31) | 46 (95.83) | |||
| Professional title [n (%)] | Nurse | 37 (71.15) | 31 (64.58) | χ 2 = 0.873a | 0.646 |
| Senior nurse | 10 (19.23) | 13 (27.08) | |||
| Nurse manager | 5 (9.62) | 4 (8.33) | |||
| Work experience [n (%)] | <3 years | 9 (17.31) | 7 (14.58) | χ 2 = 0.288 | 0.866 |
| 3–8 years | 36 (69.23) | 33 (68.75) | |||
| ＞8 years | 7 (13.46) | 8 (16.67) | |||
| Marital status [n (%)] | Unmarried | 12 (23.08) | 11 (22.92) | χ 2 = 0.271a | 0.873 |
| Married | 38 (73.08) | 36 (75.00) | |||
| Divorced | 2 (3.85) | 1 (2.08) | |||
| Department [n (%)] | Surgical | 30 (57.69) | 31 (64.58) | χ 2 = 0.498 | 0.480 |
| Medical | 22 (42.31) | 17 (35.42) | |||
| Education [n (%)] | Junior college | 23 (44.23) | 26 (54.17) | χ 2 = 0.986 | 0.321 |
| Bachelor degree or above | 29 (55.77) | 22 (45.83) | |||
| Parity [n (%)] | Nulliparous | 13 (25.00) | 14 (29.17) | χ 2 = 0.236 | 0.889 |
| 1 child | 27 (51.92) | 24 (50.00) | |||
| ≥ 2 children | 12 (23.08) | 10 (20.83) | |||
| Shift duration | 8 h | 14 (26.92) | 15 (31.25) | χ 2 = 0.227 | 0.634 |
| 10 h | 38 (73.08) | 33 (68.75) | |||
| Weekly shifts [n (%)] | 2 | 34 (65.38) | 35 (72.92) | χ 2 = 0.662 | 0.416 |
| 3 | 18 (34.62) | 13 (27.08) | |||
| Monthly income (¥) | 7429.58±103.25 | 7451.62±105.57 | t = 1.055 | 0.294 | |
| BMI (kg/m2) | 22.18±1.06 | 22.34±1.09 | t = 0.744 | 0.459 |
Notes : BMI stands for Body Mass Index. a indicates the use of Yates’ continuity correction.
Sleep Quality and Circadian Flexibility
Significant reductions in PSQI scores, CTI-11 LV subscale scores and elevated CTI-11 FR subscale scores (P < 0.05) were documented in both groups at 4-week post-implementation relative to pre-program baselines. Between-group comparisons demonstrated superior outcomes in the White Noise Group versus the Music Group, manifesting as lower PSQI scores, reduced CTI-11 LV scores and higher CTI-11 FR scores (P < 0.05; Table 2).
Table 2.
Comparative analysis of sleep and circadian metrics between the music and white noise cohorts of night-shift nurses (points)
| CTI-11 | ||||||
|---|---|---|---|---|---|---|
| PSQI | FR | LV | ||||
| Group | Baseline | 4-week post-implementation | Baseline | 4-week post-implementation | Baseline | 4-week post-implementation |
| Music group (n = 52) | 13.71 ± 2.54 | 6.53 ± 1.36* | 10.46 ± 2.18 | 15.58 ± 3.37* | 21.76 ± 3.15 | 15.54 ± 2.38* |
| White noise group (n = 48) | 13.93 ± 2.59 | 4.37 ± 1.15* | 10.78 ± 2.23 | 19.42 ± 4.06* | 22.39 ± 3.46 | 10.42 ± 1.57* |
| t | 0.429 | 8.540 | 0.725 | 5.161 | 0.953 | 12.587 |
| P | 0.669 | <0.001 | 0.470 | <0.001 | 0.343 | <0.001 |
| Cohen’s d | −0.09 | 1.72 | −0.15 | −1.03 | −0.19 | 2.54 |
Notes : * P < 0.05 versus pre-program within group; CTI-11, Circadian Type Inventory-11; FR: Flexibility/Rigidity; LV: Languidness/Vigorousness; PSQI: Pittsburgh Sleep Quality Index;.
Resilience and Burnout Metrics
Compared with pre-program baselines, significant improvements in psychological resilience (manifesting as elevated CD-RISC-10 scores) and reduced occupational burnout (reflected in decreased MBI-GS scores) were observed in both groups at 4-week post-implementation (P < 0.05). Between-group analyses demonstrated superior outcomes in the music group relative to the white noise group, manifesting as significantly higher CD-RISC-10 scores and lower MBI-GS scores (P < 0.05; Table 3).
Table 3.
Comparative analysis of resilience and burnout metrics between the music and white noise cohorts of night-shift nurses (points)
| CD-RISC-10 | MBI-GS | |||
|---|---|---|---|---|
| Group | Baseline | 4-week post-implementation | Baseline | 4-week post-implementation |
| Music group (n = 52) | 19.22 ± 3.38 | 33.37 ± 4.16* | 61.73 ± 5.36 | 35.34 ± 2.78* |
| White noise group (n = 48) | 20.04 ± 3.56 | 29.49 ± 4.07* | 62.15 ± 5.58 | 38.25 ± 3.12* |
| t | 1.182 | 4.708 | 0.384 | 4.932 |
| P | 0.240 | <0.001 | 0.702 | <0.001 |
| Cohen’s d | −0.24 | 0.94 | −0.08 | −0.99 |
Notes : * P < 0.05 vs. baseline; CD-RISC-10, 10-item Connor–Davidson Resilience Scale; MBI-GS, Maslach Burnout Inventory-General Survey.
Emotional Labour Dimensions
Significant reductions in surface acting and deep acting dimensions of the ELS and elevations in genuine emotion expression were documented in both groups at 4-week post-implementation compared with pre-program baselines (P < 0.05). Between-group analyses demonstrated superior emotional labour regulation in the music group relative to that in the white noise group, manifesting as significantly lower surface acting, reduced deep acting and enhanced genuine expression (P < 0.05; Table 4).
Table 4.
Comparative analysis of emotional labour dimensions between the music and white noise cohorts of night-shift nurses (points)
| Surface acting | Deep acting | Genuine expression | ||||
|---|---|---|---|---|---|---|
| Group | Baseline | 4-week post-implementation | Baseline | 4-week post-implementation | Baseline | 4-week post-implementation |
| Music group (n = 52) | 28.22 ± 3.35 | 15.14 ± 2.07* | 14.13 ± 1.92 | 7.59 ± 1.16* | 6.34 ± 1.18 | 12.36 ± 2.23* |
| White noise group (n = 48) | 27.76 ± 3.18 | 18.39 ± 2.63* | 13.81 ± 1.97 | 9.87 ± 1.58* | 6.57 ± 1.25 | 9.72 ± 1.86* |
| t | 0.703 | 6.894 | 0.822 | 8.269 | 0.947 | 6.400 |
| P | 0.484 | <0.001 | 0.413 | <0.001 | 0.346 | <0.001 |
| Cohen’s d | 0.14 | −1.37 | 0.16 | −1.65 | −0.19 | 1.29 |
Notes : * P < 0.05 versus Baseline.
DISCUSSION
Superior Efficacy of Music Therapy in Enhancing Psychological Resilience and Mitigating Occupational Burnout/Emotional Labour
The present findings demonstrated significantly higher CD-RISC-10 scores and genuine emotion expression dimension scores on the ELS, and lower MBI-GS scores and reduced surface/deep acting dimension scores in the music group relative to those in the white noise group at 4-week post-implementation. These results align with prior investigations by Sharma et al.[41] and Yıldırım and Çiriş Yıldız,[42] collectively indicating music therapy’s superior benefits for psychological resilience enhancement, burnout mitigation and emotional labour optimisation in night-shift nurses. Although nurse-specific minimal clinically important difference thresholds for CD-RISC-10 and MBI-GS remain undefined, extant literature provides contextualised references. Cheng et al.[32] established that a ≥10-point increase in CD-RISC-10 significantly improves stress coping capabilities among Chinese healthcare workers, and Bravo et al.[34] validated that a ≥20-point reduction in MBI-GS total scores effectively alleviates core burnout symptoms in Colombian medical populations. On the basis of the magnitude of score changes observed in the present study, corroborating evidence from healthcare groups and the distinctive occupational context of night-shift nursing, these improvements may be regarded as clinically meaningful.
The possible reasons may be related to the following points: firstly, music with a tempo of 60–80 BPM has a moderate and soothing rhythm, which is close to the resting heart rate of the human body and can easily generate physiological resonance. Moreover, this rhythm can resonate with alpha brain waves (8–12 Hz), promoting an increase in blood flow to the prefrontal cortex (PFC). Listening to this type of music 30 minutes before work can help regulate the autonomic nervous system to a moderately aroused state, enhance neural excitability and prevent cognitive sluggishness caused by underestimating the circadian rhythm. Exposure to Baroque classical music stimulates the brain’s reward system, facilitating dopamine release, enhancing positive affective experiences and thereby counteracting the emotional exhaustion characteristic of occupational burnout. When integrated with mindfulness guidance, music-based protocols require active auditory engagement and emotional investment. This process potentially augments the top-down regulatory functions of PFC over limbic system activity, consequently strengthening nurses’ cognitive–emotional regulation capacities. Such enhanced neurocognitive flexibility enables adaptive emotional response strategies during stressful encounters, reducing reliance on effortful emotional labour management and diminishing emotional depletion.[43] Animal experiments provide strong evidence for these mechanisms. Flores-García et al.[44] found that music exposure reduced the decrease in nucleus accumbens (NAcc) activity in mice injected with complete Freund’s adjuvant inflammatory agents and improved dopamine dynamics in the NAcc. Cheng et al.[45] found that light music and classical music could reduce the depression induced by chronic unpredictable mild stress in mice through the brain-derived neurotrophic factor (BDNF) signalling pathway. Hung et al.[46] found that music regulated the fibronectin type III domain-containing protein 5/BDNF pathway mediated by methyl-CpG-binding protein 2 loss in the PFC of mice, promoting social function improvement. Listening to structured pleasant music can enhance the phase firing of neurons in the ventral tegmental area of the midbrain, which is part of two major dopamine neural pathways, and the release of dopamine in NAcc, enhancing individual motivation, attention and positive emotions and thereby improving the mental health of night-shift nurses.[47] Secondly, the Joint Commission on Accreditation of Healthcare Organizations in the United States recommends a 1-hour rest period to be set in the middle of the night shift to ensure the physical recovery of night-shift nurses. During this 60-minute rest period, the first 10 minutes should be music with clear volume, melody and rhythm which can maintain the brain’s alert state through auditory stimulation and prevent night-shift nurses from becoming drowsy or distracted. The remaining 50 minutes should be adjusted to a volume below the auditory detection threshold, imperceptible to the human ear but still has a weak influence through subconscious or physiological states. Through the gradual attenuation of sound intensity, this strategy can reduce the interference of auditory stimulation on the brain and allow for natural relaxation in accordance with the physiological rhythm, helping nurses achieve deep rest during the short break and quickly recover under work pressure and emotional labour.
Superior Efficacy of White Noise in Improving Sleep Quality and Circadian Flexibility
The results demonstrated significantly lower PSQI scores, reduced CTI-11 LV subscale scores and elevated CTI-11 FR subscale scores in the white noise group compared with those in the music group at 4-week post-implementation. These findings align with previous investigations by Nigg et al.[48] and Ebben et al.,[49] collectively indicate white noise’s superior efficacy in enhancing sleep architecture and circadian adaptability among night-shift nurses.
The reasons for the analysis are as follows: firstly, before night shifts, nurses need to quickly switch from their daily state to a work-ready mode. The hospital environment is often accompanied by noises such as footsteps and phone rings. Listening to steady-state low-frequency white noise, which has the characteristics of a uniform broadband spectrum and a monotonous steady state, using noise-cancelling headphones in the restroom 30 minutes before work can shield from the surrounding noises. Different from the processing of music melodies and lyrics, white noise does not require the brain to actively analyse sound wave information. When combined with rhythmic guidance voice, it can shift the nurses’ attention from daily trivialities and work pressure to thinking rumination, helping them clear their minds and focus on night-shift preparations and thereby enhancing their experience of the circadian rhythm between day and night. Additionally, the volume of white noise in the 30 minutes before work is played in a gradient form, with 40–50 dB for the first 15 minutes and gradually decreasing to 25–30 dB for the next 15 minutes. This strategy can simulate the natural transition of noise reduction, such as the wind gradually calming down in the evening. The high volume of white noise in the first half can stimulate the release of norepinephrine from the locus coeruleus to maintain moderate alertness, and the gradual decrease in volume in the second half activates the parasympathetic nervous system, thus increasing the high-frequency components of heart rate variability and helping the body transition into a work-ready state.[50] Secondly, some studies pointed out that the PFC is a key area in the brain responsible for advanced cognitive functions and emotional regulation. White noise can reduce the excitability of the PFC and exert a good sedative effect. Listening to slow-wave white noise during short breaks at work can simulate the brain’s alpha/theta wave rhythm, induce synchronous neuron discharge and quickly transform the brain from a work-awake state to a sleep-preparation state, helping nurses relax quickly.[51,52] Christensen et al.[53] found in animal experiments that background white noise can increase neuronal activity by reducing membrane fluctuations and slow-wave oscillations in the auditory cortex. Playing sleep-repairing white noise at a fixed time before sleep on rest days at home can send signals to the suprachiasmatic nucleus (SCN) through the auditory pathway. The SCN is known as the circadian rhythm pacemaker and can stabilise the expression of circadian rhythm genes, such as Per1/Bmal1, strengthen the rhythm boundary between sleep and wakefulness, reduce the splitting of melatonin secretion, improve sleep continuity and enhance the flexibility of the nurses’ circadian rhythm. Moreover, the main frequency of white noise is 8–12 Hz, which simulates the alpha wave rhythm. This steady frequency can drive the synchronous oscillation of alpha waves in sensory cortices such as the occipital and parietal lobes through the brainwave entrainment effect. The alpha wave-dominated brain state is highly related to sleep initiation and maintenance, which helps suppress high-arousal brain waves such as beta waves, lower the basal arousal level, induce a relaxation–rest state and efficiently optimise the physiological regulation of sleep and rhythm, thus improving sleep quality.[54] Both groups received equivalent exposure durations (30-minute preshift, 60-minute intrashift and 60-minute postshift), indicating that the superior sleep improvements associated with white noise are likely attributable to its intrinsic acoustic properties—such as broadband spectral uniformity, masking effects and neural entrainment capabilities—rather than temporal exposure differences.
Limitations
Notwithstanding the significant findings, several limitations should be noted. Firstly, the retrospective design set the sample size based on historical data rather than a priori power calculations that consider effect size, significance level and statistical power, possibly leading to insufficient power and reduced reliability. Secondly, including only 100 night-shift nurses from a single institution limits generalisability. Differences in workload, management models, stress profiles and sleep environments across hospitals may affect how participants respond to the caring method. Thirdly, the 4-week observation period was too short to assess long-term effects or sustainability.
CONCLUSION
Music-based protocols and white noise exposure effectively enhance sleep quality, circadian adaptability, psychological resilience, occupational burnout mitigation and emotional labour regulation in night-shift nurses. White noise demonstrates greater efficacy for optimising sleep architecture and circadian flexibility, whereas music-based approaches yield superior benefits for psychological resilience enhancement, burnout reduction and emotional labour management.
Availability of Data and Materials
The original contributions presented in the study are included in the article. Further enquiries can be directed to the corresponding authors.
Author Contributions
Fang Li designed the study; all authors conducted the study. WenQing Zhang collected and analyzed the data. Yan Li and WenQing Zhang participated in drafting the manuscript, and all authors contributed to critical revision of the manuscript for important intellectual content. All authors gave final approval of the version to be published. All authors participated fully in the work, take public responsibility for appropriate portions of the content, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or completeness of any part of the work are appropriately investigated and resolved.
Ethics Approval and Consent to Participate
All participants provided written informed consent. This study complied with ethical principles of the Declaration of Helsinki and was approved by the Review Committee of Hefei First People’s Hospital (Ethics Approval No. 202507026).
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgment
No.
Funding Statement
Key Research Project of Natural Science for Universities of the Department of Education of Anhui Province (KJ2021A1568).
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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 enquiries can be directed to the corresponding authors.
