Ye Liu1,2
Lihao Bao- 1Beilun Branch, First Affiliated Hospital of Zhejiang University School of Medicine, Ningbo, Zhejiang, China
- 2Department of Otolaryngology, Ningbo Beilun People’s Hospital, Ningbo, Zhejiang, China
Introduction: Tinnitus is commonly accompanied by emotional distress and sleep disturbances, yet the extent to which these characteristics relate to cochlear electrophysiologic findings remains unclear. This study examined associations between electrophysiologic measures and emotional and sleep parameters in adults with subjective tinnitus.
Methods: This retrospective study included 120 adults with tinnitus. Data collected included demographics, cochlear electrophysiologic measures (electrocochleography and auditory brainstem response), emotional characteristics (perceived stress, depressive symptoms, anxiety, emotion regulation), and sleep parameters (sleep quality, insomnia severity, daytime sleepiness). Correlation analyses and multivariate regression models were applied.
Results: The mean age of the cohort was 62.35 years (SD 9.45), and 64.17% were male. A very weak negative correlation was observed between depressive symptoms and Wave III latency (r = –0.196, P = 0.03), but the small magnitude suggests minimal explanatory value. The summating potential/action potential ratio was not significantly correlated with sleep quality (r = –0.181, P = 0.05). In multivariate models, anxiolytic use was associated with a lower risk of poor sleep (adjusted odds ratio [aOR] = 0.262; 95% confidence interval [CI]: 0.078–0.881; P = 0.030), whereas antidepressant use was associated with a higher risk (aOR = 2.628; 95% CI: 1.027–6.724; P = 0.044). For insomnia, higher pure-tone average thresholds (aOR = 0.948 per dB; 95% CI: 0.906–0.992; P = 0.007) and hearing aid use (aOR = 3.396; 95% CI: 1.085–10.623; P = 0.036) were significant determinants. The only significant factor associated with quality of life was tinnitus duration, with longer duration associated with lower WHOQOL-BREF scores (β = –2.74; P = 0.020). No electrophysiologic parameter demonstrated significant associations in the multivariate models.
Conclusion: Within the constraints of this study, cochlear electrophysiologic measures showed limited observable associations with emotional or sleep characteristics. Factors related to hearing status and medication use demonstrated stronger statistical associations with sleep outcomes, while tinnitus duration was linked to quality-of-life scores. These findings contribute to the growing body of descriptive evidence on tinnitus-related characteristics, although further research with larger cohorts and longitudinal designs is needed to clarify these relationships.
1 Introduction
Tinnitus—defined as the perception of sound in the absence of an external auditory stimulus—affects approximately 10–15% of adults and is frequently associated with reduced quality of life (1). Emotional distress is highly prevalent among individuals with tinnitus, with prior studies documenting elevated levels of stress (2), depression (3), and anxiety (3), all of which can exacerbate patients’ subjective symptom burden (4). Sleep disturbances, reported in up to 70% of tinnitus patients (5), further contribute to distress and functional impairment. Although these domains—emotional health, sleep quality, and tinnitus perception—are frequently interrelated in clinical practice, the neurobiological pathways that link them remain incompletely understood.
Objective auditory measures such as electrocochleography (ECochG) and auditory brainstem response (ABR) are commonly used to assess peripheral and brainstem auditory pathway function (6–9). These measures are grounded in established auditory physiology: the SP/AP ratio reflects cochlear hair cell and endolymphatic function (10), whereas ABR Wave I and Wave III latencies index auditory nerve and pontine transmission timing (11). Although aberrant auditory processing has been reported in subsets of tinnitus patients (7–9), prior work has not demonstrated consistent associations between ECochG or ABR parameters and subjective symptoms such as emotional distress or sleep impairment. For example, Kehrle et al. (12) reported ABR alterations in tinnitus but found no relationship with depression or anxiety scores, illustrating that electrophysiologic abnormalities may occur independently of psychological symptom severity.
Research on tinnitus-related emotional distress (13), sleep disturbances (14, 15), and auditory electrophysiology (16) has largely progressed in parallel rather than in an integrated manner. Most electrophysiology studies have focused on auditory pathway structure and timing without incorporating psychological or sleep measures, whereas studies examining emotional or sleep outcomes seldom include ECochG or ABR testing (17).
Tinnitus-related burden spans multiple functional levels: cochlear and brainstem activity measured through electrophysiologic testing (18), perceptual–emotional experiences such as stress, anxiety, and depression (13), behavioral manifestations including sleep disruption (19), and higher-order regulatory processes such as cognitive reappraisal and expressive suppression (20). These levels are clinically interconnected, as emotional distress can heighten the salience of tinnitus and influence sleep quality (19), while coping and emotion regulation styles may shape how strongly the percept intrudes on daily functioning (20). Considering these domains together therefore provides a coherent view of how distinct aspects of tinnitus burden may converge or diverge within the same individual (21). This conceptual structure motivates the present study’s descriptive aim: to determine whether these domains display measurable correspondence or remain largely independent, thereby clarifying which assessments offer complementary clinical information (13, 18).
Given this fragmentation in the literature, a unified examination of auditory physiology, emotional characteristics, sleep quality, and emotion regulation may help clarify which symptom domains tend to cluster together and which remain distinct. Such an approach does not aim to test mechanistic pathways or causal models but rather to provide a descriptive assessment of whether these commonly evaluated domains show measurable correspondence within the same patient cohort. Understanding these relationships may assist clinicians in determining which assessments offer complementary information and which domains may not meaningfully align with electrophysiologic findings.
This study therefore seeks to characterize the degree of correspondence among cochlear electrophysiologic parameters (ECochG and ABR), emotional and psychological features (stress, depression, anxiety), sleep-related measures, and emotion regulation strategies in patients with tinnitus. By evaluating these domains concurrently, we aim to clarify whether objective auditory measures relate to psychological or sleep outcomes and to identify potential areas where routine screening may—or may not—provide additional clinical value.
2 Methods
2.1 Study design and setting
This retrospective observational study analyzed prospectively collected data from adult patients with subjective tinnitus who attended the Department of Otolaryngology at Ningbo Beilun People’s Hospital between January 2024 and January 2025. The study was conducted to examine whether psychological disturbances—such as stress, depression, anxiety, emotion regulation patterns, and sleep impairment—show measurable associations with cochlear electrophysiologic parameters. All procedures complied with the Declaration of Helsinki. Ethical approval was granted by the Institutional Ethical Review Board of Ningbo Beilun People’s Hospital (Approval number: 2024LP035). Written informed consent was obtained from all participants.
2.2 Study population
A total of 120 consecutive adults diagnosed with subjective tinnitus were recruited from the outpatient otology clinic.
Inclusion criteria:
● Age ≥ 18 years.
● Diagnosis of subjective tinnitus confirmed through clinical otologic evaluation, audiometry, and exclusion of alternative auditory symptoms (e.g., pulsatile vascular tinnitus, objective middle ear sources).
● Ability to provide informed consent and complete study questionnaires.
Exclusion criteria:
● History of Meniere’s disease, vestibular schwannoma, or otosclerosis.
● Major psychiatric illness documented in the electronic medical record, including schizophrenia, bipolar disorder, psychotic disorders, or severe major depressive disorder requiring psychiatric care.
● Use of ototoxic medications within the past 6 months.
● Cognitive impairment interfering with questionnaire completion.
Identification of psychiatric illness:
Diagnoses were extracted from the hospital’s electronic medical record, which uses ICD-10–based coding. All psychiatric diagnoses were made by board-certified psychiatrists or neurologists as part of routine clinical care. These diagnoses—not questionnaire scores—served as the basis for exclusion. Screening instruments (BDI-II, GAD-7, PSS) were used only to assess symptom severity, not to establish or exclude psychiatric diagnoses.
2.3 Data collection
All participants underwent comprehensive audiological, electrophysiological, and psychological assessments. Data were collected using standardized questionnaires and objective tests. A single researcher administered all tests to minimize variability in data collection. The data collection process followed a consistent sequence: each patient first completed baseline demographic and tinnitus-related questionnaires, followed by audiometric and electrophysiologic testing (ECochG, ABR, and OAE). Subsequently, standardized self-report questionnaires assessing stress, depression, anxiety, emotion regulation, and sleep quality were administered in a dedicated counseling session on the same day.
2.3.1 Baseline clinicodemographic data
Collected variables included age, sex, tinnitus duration, tinnitus laterality, hearing thresholds (dB), pure-tone audiometry, and tinnitus severity. Tinnitus severity was evaluated using the Tinnitus Handicap Inventory (THI), scored from 0 to 100 and interpreted as: 0–16 slight/no handicap, 18–36 mild, 38–56 moderate, 58–76 severe, and 78–100 catastrophic.
2.3.2 Cochlear electrophysiologic measurements
Electrophysiologic measurements were obtained using Electrocochleography (ECochG) and Auditory Brainstem Response (ABR) testing.
● ECochG readings were classified into two categories: normal and abnormal.
● ABR testing was performed using a Neuro-Audio ABR System at an intensity of 80 decibels in normal Hearing Level (dBnHL). Latencies for ABR Wave I, III, and V were recorded. The SP/AP ratio was calculated from the summating potential to action potential measurements.
● Otoacoustic Emission (OAE) testing was conducted at 500 Hz to assess outer hair cell function, and results were recorded as either present or absent.
2.3.3 Emotional and psychological assessments
Psychological and emotional distress were assessed using validated Chinese-language versions of the following scales:
● Perceived Stress Scale (PSS): A 10-item scale used to measure the perception of stress. Total scores range from 0 to 40, with higher scores indicating greater perceived stress. Patients with scores ≥ 27 can be categorized as experiencing high stress (22).
● Beck Depression Inventory-II (BDI-II): A 21-item self-report inventory measuring depressive symptoms. Scores range from 0 to 63, with higher scores reflecting more severe depression. Participants with scores ≥ 20 can be categorized as having clinically significant depression (23).
● Generalized Anxiety Disorder-7 (GAD-7): A 7-item scale used to screen for anxiety disorders. Scores range from 0 to 21, with scores ≥ 10 indicative of moderate to severe (clinically significant) anxiety (24).
● Emotion Regulation Questionnaire (ERQ): A 10-item scale measuring two emotion regulation strategies: cognitive reappraisal and expressive suppression. The cognitive reappraisal domain is scored between 6 and 42, with scores above 26 being indicative of high cognitive reappraisal. The expressive suppression domain was scored from 4 to 28, with scores of 16 or above indicating high expressive suppression (25).
Each scale measures a distinct psychological construct; they were selected due to their established psychometric validity and widespread use in auditory and behavioral research.
2.3.4 Sleep characteristics and quality of life
Sleep disturbances were evaluated using the following standardized instruments:
● Pittsburgh Sleep Quality Index (PSQI): A self-rated questionnaire assessing sleep quality over the past month. Scores > 5 indicate poor sleep quality (26).
● Insomnia Severity Index (ISI): A 7-item scale evaluating the severity of insomnia. Scores ≥ 15 suggest clinically significant insomnia (27).
● Epworth Sleepiness Scale (ESS): An 8-item scale measuring daytime sleepiness. Patients with scores ≥ 11 can be considered to have excessive daytime sleepiness (28).
● World Health Organization Quality of Life (WHOQoL-BREF): A 26-item scale assessing overall quality of life across four domains: physical health, psychological health, social relationships, and environment. We analyzed the overall score, with higher scores indicating better quality (29).
2.4 Statistical analysis
All analyses were performed using Stata version 18 (StataCorp, College Station, TX). A two-sided p-value < 0.05 was considered statistically significant. Descriptive statistics were used to summarize demographic, clinical, electrophysiologic, psychological, and sleep-related variables. Continuous variables were reported as means and standard deviations or medians with interquartile ranges where appropriate, and categorical variables were expressed as frequencies and percentages. Pearson correlation coefficients were used to examine the association between continuous electrophysiologic parameters and psychological or sleep measures.
Regression analyses proceeded in two stages. First, univariate regression models were fitted for each outcome of interest, including high stress, clinically significant depression, moderate-to-severe anxiety, poor sleep quality, clinically significant insomnia, excessive daytime sleepiness, and overall quality of life. Univariate logistic regression was applied to binary outcomes, whereas linear regression was used for the WHOQOL-BREF score. Variables demonstrating an association with the outcome at a significance threshold of p < 0.10 in the univariate models were subsequently entered into multivariate models.
Multivariate logistic and linear regression models were then constructed using the selected variables. Prior to model fitting, multicollinearity was assessed using the Variance Inflation Factor (VIF), and predictors with VIF values greater than 10 were excluded to avoid collinearity effects. Model diagnostics included evaluation of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values, while goodness of fit for logistic regression models was assessed using the Hosmer–Lemeshow test. All final models report odds ratios for logistic regressions and beta coefficients for linear regressions, each accompanied by 95% confidence intervals.
3 Results
3.1 Baseline data
This study enrolled 120 adult patients diagnosed with tinnitus, with a mean age of 62.35 ± 9.45 years, predominantly male (64.17%). The average hearing threshold was 67.49 ± 11.50 dB, and the mean tinnitus duration was 2.39 ± 0.94 years. Tinnitus was more commonly unilateral (75%), with 79.17% of patients not reporting hyperacusis. Tinnitus severity was categorized as moderate in 39.17% and severe in 20.83%, with catastrophic cases being rare (0.83%). The majority of patients used hearing aids (80.83%), while tinnitus masking devices were utilized by only 10% (Table 1).
Table 1. Baseline clinicodemographic and tinnitus-related data.
3.2 Cochlear electrophysiologic findings
Electrocochleography (ECochG) revealed abnormal readings in 43.33% of patients, while otoacoustic emissions at 500 Hz were absent in a similar proportion (43.33%). Auditory brainstem response (ABR) testing demonstrated mean latencies of 2.08 ± 0.28 ms, 4.34 ± 0.37 ms, and 6.00 ± 0.53 ms for Waves I, III, and V, respectively, with an average SP/AP ratio of 0.6 ± 0.2 (Supplementary Table S1).
3.3 Emotional and psychological profiles
patients exhibited significant emotional distress, with 40.83% classified as stressed (PSS ≥ 27) and 41.67% demonstrating clinically significant depressive symptoms (BDI-II ≥ 20). Moderate to severe anxiety was observed in 57.50% of participants (GAD-7 ≥ 10). Regarding emotion regulation strategies, high cognitive reappraisal and expressive suppression scores were noted in 73.33% and 68.33% of patients, respectively (Supplementary Table S2).
3.4 Sleep disturbances and quality of life
Sleep quality was notably impaired, with 70% of participants reporting poor sleep quality (PSQI > 5), while 40.83% met criteria for clinically significant insomnia (ISI ≥ 15). Excessive daytime sleepiness (ESS ≥ 11) was less prevalent, affecting 17.5%. The mean sleep duration was 5.03 ± 1.77 hours, with a mean sleep latency of 1.45 ± 0.85 hours. Frequent awakenings (mean = 1.52 ± 0.97 per night) further disrupted sleep. Quality of life assessments indicated a mean WHOQoL-BREF score of 67.49 ± 12.13, reflecting moderate impairment (Supplementary Table S3).
3.5 Correlation and regression analyses
No substantial correlations were identified between ABR or SP/AP ratios and emotional or psychological variables. A very weak negative correlation was observed between Wave III latency and depressive symptoms (r = –0.1958, P = 0.03), and the SP/AP ratio showed only a minimal, borderline correlation with sleep quality (r = –0.1808, P = 0.05). These small effect sizes indicate limited evidence of any meaningful association (Table 2).
Table 2. Correlation analysis between cochlear electrophysiologic parameters and emotional/psychological outcomes.
Univariate logistic regression results are presented in Supplementary Tables S4–S12, and variables with P < 0.10 were included in the multivariate models (Figure 1).
Figure 1. Forest plot showing adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for factors associated with sleep-related outcomes, psychological symptoms, and coping strategies in multivariable logistic regression models. Model fit indices, including Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), and goodness-of-fit (GOF) p-values are reported for each model. The vertical dashed line indicates the null value (aOR = 1).
3.5.1 Poor sleep
After controlling for confounders, anxiolytics were associated with a lower risk of poor sleep (aOR = 0.262; 95% CI: 0.078–0.881; P = 0.030), while antidepressants were associated with a higher risk (aOR = 2.628; 95% CI: 1.027–6.724; P = 0.044). Sleep medication use was not significantly associated (P = 0.807).
3.5.2 Insomnia
After adjustment, higher pure-tone average (PTA) thresholds were associated with a lower risk of insomnia (aOR = 0.948 per dB; 95% CI: 0.906–0.992; P = 0.007). Hearing aid use was associated with a higher risk of insomnia (aOR = 3.396; 95% CI: 1.085–10.623; P = 0.036). Bilateral tinnitus was not significantly associated (P = 0.148).
3.5.3 Stress
None of the included factors—age, Wave III latency, or use of tinnitus masking devices—were significantly associated with stress (all P ≥ 0.05).
3.5.4 Anxiety
Wave III latency was the sole variable meeting the inclusion cutoff (p < 0.10) in the univariate mode. However, it was not significantly associated with anxiety (P = 0.088).
3.5.5 Depression
None of the variables retained significance in the adjusted model, including sex, tinnitus severity categories, ABR intensity (P = 0.059), or anxiolytic use (P = 0.073).
3.5.6 Cognitive reappraisal
Neither tinnitus masking devices (P = 0.058) nor antidepressants (P = 0.079) were significantly associated with high cognitive reappraisal.
3.5.7 Expressive suppression
After adjustment, use of tinnitus masking devices was associated with a lower risk of high expressive suppression (aOR = 0.272; 95% CI: 0.078–0.945; P = 0.040). Antidepressant use was not significantly associated (P = 0.066).
3.5.8 Excessive daytime sleepiness
Neither age nor bilateral disease was significantly associated with excessive daytime sleepiness (both P ≥ 0.05).
3.5.9 Quality of life
After controlling for age and other included variables, tinnitus duration was the only significant determinant of WHOQOL-BREF total score. Longer tinnitus duration was associated with lower quality-of-life scores (β = –2.74; P = 0.020; 95% CI: –5.04 to –0.45). No audiologic, electrophysiologic, or psychological measures demonstrated significant associations with quality of life.
Goodness-of-fit (GOF) values indicated acceptable model fit for all multivariate analyses.
4 Discussion
Tinnitus is widely recognized as a multidimensional condition with substantial effects on emotional well-being (13), sleep quality (30), and overall quality of life (31). In this cohort of 120 adults with subjective tinnitus, emotional distress and sleep impairment were common, whereas only limited and weak associations were observed between cochlear electrophysiologic measures and psychological or sleep-related parameters. By integrating audiologic, electrophysiologic, psychological, and sleep assessments, this study provides a comprehensive profile of symptom burden, although the strength and pattern of associations highlight the complexity and heterogeneity of tinnitus rather than a unified mechanistic pathway.
4.1 Principal findings
Three main observations emerged. First, emotional and sleep disturbances were highly prevalent, with more than half of participants reporting clinically relevant anxiety, depressive symptoms, or poor sleep, consistent with prior research (32). Second, electrophysiologic parameters (ECochG SP/AP ratio, ABR latencies) showed only weak correlations with psychological or sleep variables, and none retained significance after adjustment. The only correlation meeting statistical significance—between ABR Wave III latency and depressive symptoms—had a very small effect size (r≈–0.20), underscoring the minimal explanatory contribution of early auditory pathway measures. Third, multivariate analyses identified non-electrophysiologic variables associated with sleep or quality-of-life outcomes, including PTA thresholds, hearing-aid use, anxiolytic and antidepressant exposure, and tinnitus duration. None of the emotional distress measures nor electrophysiologic parameters were independently associated with stress, anxiety, depression, excessive daytime sleepiness, or emotion-regulation outcomes.
4.2 Comparison with existing literature
Previous studies have reported electrophysiologic abnormalities in subsets of tinnitus patients (33, 34), but the magnitude and clinical relevance of these findings have varied. The weak associations observed in this study align with reports showing that electrophysiologic parameters account for minimal variance in psychological outcomes.
Several mechanistic frameworks help contextualize these null results. Contemporary tinnitus models—including central gain enhancement, limbic–auditory coupling, and attentional salience mechanisms—emphasize alterations in central neural processing, rather than abnormalities in peripheral or early brainstem responses detectable through ECochG or ABR (35, 36). These models propose that emotional and cognitive influences on tinnitus distress arise from dysregulated corticolimbic networks (e.g., amygdala–hippocampal–prefrontal interactions) (37, 38) and heightened sensory precision or salience attribution (39), rather than from changes in cochlear or lower brainstem physiology (40). The absence of significant associations in this cohort is therefore consistent with the possibility that the psychological and sleep-related burden of tinnitus reflects central processing mechanisms not captured by peripheral or subcortical electrophysiologic testing.
Sleep disturbances were also common, consistent with previous reports (3, 30, 41, 42). The lack of association between sleep outcomes and electrophysiology supports prior work showing that sleep impairment in tinnitus is more closely related to emotional distress, hyperarousal, and disease severity (43, 44) than to cochlear or brainstem dysfunction. This aligns with the broader understanding that tinnitus-related insomnia reflects heightened arousal and limbic activation rather than abnormalities in sensory transmission (45, 46). Associations between insomnia risk and PTA thresholds or hearing-aid use may reflect behavioral or perceptual factors—such as amplification-related awareness, sleep-environment variables, or chronic disease burden—rather than electrophysiologic abnormalities.
Emotion-regulation strategies (cognitive reappraisal, expressive suppression) showed no significant associations with tinnitus severity, electrophysiology, or emotional distress. Although emotion regulation has been proposed as a contributor to tinnitus-related distress (47), null findings in this cohort are consistent with literature demonstrating substantial heterogeneity in psychological adaptation among tinnitus patients (48). Additionally, ERQ scores reflect higher-order cognitive styles rather than perceptual or sensory-modulatory processes (49, 50), which may explain their independence from electrophysiologic measures. Reduced variability in ERQ scores in an older sample, possible cultural influences on self-reported regulatory style (51, 52), and potential ceiling/floor effects may also contribute. Importantly, ERQ domains assess broad regulatory tendencies, not tinnitus-specific coping strategies, which may make them less sensitive to tinnitus severity or auditory physiology.
4.3 Clinical implications
Given the cross-sectional design and the weak associations observed, the findings do not support the use of ECochG or ABR as indicators of emotional distress or sleep impairment in tinnitus patients. While electrophysiologic testing remains valuable for auditory assessment, its relevance for psychological or sleep-related evaluation appears limited in this population. Sleep-related associations with PTA or hearing-aid use should be interpreted cautiously, as they likely reflect behavioral, perceptual, or disease-related factors rather than electrophysiologic abnormalities. Similarly, associations with anxiolytic or antidepressant use may reflect underlying psychiatric conditions rather than medication effects.
Tinnitus duration was the only determinant of quality-of-life scores, consistent with prior studies reporting cumulative burden with chronicity (53). Clinical assessment should therefore prioritize psychological evaluation, sleep assessment, and audiologic review rather than relying on electrophysiologic measures to infer emotional or sleep status.
4.4 Limitations and future directions
This study has several limitations. Its cross-sectional design precludes causal inference. Reliance on clinical documentation for psychiatric exclusions introduces a risk of misclassification, as some participants may have had undiagnosed mood or anxiety disorders. Conversely, individuals with stable, well-managed psychiatric diagnoses may have been excluded, potentially limiting generalizability. Effect sizes in both correlation and regression analyses were small, indicating limited explanatory value for most associations. Examination of multiple psychological and sleep variables also raises the risk of Type I error.
Future research using longitudinal designs and neuroimaging, combined with multimodal auditory and psychological assessments, may help clarify how central auditory and limbic networks contribute to tinnitus burden. More granular assessment of emotion regulation—including behavioral tasks or ecological momentary assessment—may also clarify its role. Overall, these results indicate that emotional distress and sleep disturbance are prominent in tinnitus but are not strongly reflected in cochlear electrophysiologic measures.
In conclusion, in this cohort, emotional distress and sleep disturbances were common among tinnitus patients, but cochlear electrophysiologic measures showed only weak and inconsistent associations with psychological or sleep-related outcomes. The results suggest that emotional and sleep-related symptoms in tinnitus are influenced by clinical and psychosocial factors rather than by ECochG or ABR parameters. Further longitudinal and multimodal research is needed to clarify these relationships and guide evidence-based management strategies.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by the Institution’s Ethical Review Board of Ningbo Beilun People’s Hospital (Approval number: 2024LP035). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
YL: Writing – original draft, Conceptualization. LB: Conceptualization, Writing – review & editing. XM: Formal analysis, Writing – review & editing, Data curation. KS: Data curation, Writing – review & editing, Methodology. GX: Writing – review & editing, Methodology, Data curation. SL: Data curation, Investigation, Writing – review & editing. KJ: Data curation, Investigation, Writing – review & editing.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1721036/full#supplementary-material
References
1. Jarach CM, Lugo A, Scala M, van den Brandt PA, Cederroth CR, Odone A, et al. Global prevalence and incidence of tinnitus: A systematic review and meta-analysis. JAMA Neurol. (2022) 79:888–900. doi: 10.1001/jamaneurol.2022.2189
2. Elarbed A, Fackrell K, Baguley DM, and Hoare DJ. Tinnitus and stress in adults: A scoping review. Int J Audiol. (2021) 60:171–82. doi: 10.1080/14992027.2020.1827306
3. Bhatt JM, Bhattacharyya N, and Lin HW. Relationships between tinnitus and the prevalence of anxiety and depression. Laryngoscope. (2017) 127:466–9. doi: 10.1002/lary.26107
4. Probst T, Pryss R, Langguth B, and Schlee W. Emotional states as mediators between tinnitus loudness and tinnitus distress in daily life: results from the “Trackyourtinnitus” Application. Sci Rep. (2016) 6:20382. doi: 10.1038/srep20382
5. Asnis GM, Majeed K, Henderson MA, Sylvester C, Thomas M, and La Garza RD. An examination of the relationship between insomnia and tinnitus: A review and recommendations. Clin Med Insights Psychiatry. (2018) 9:1179557318781078. doi: 10.1177/1179557318781078
6. Kim D. Cochlear mechanics: implications of electrophysiological and acoustical observations. Hear Res. (1980) 2:297–317. doi: 10.1016/0378-5955(80)90064-7
7. de Azevedo AA, Langguth B, de Oliveira PM, and Figueiredo RR. Tinnitus treatment with piribedil guided by electrocochleography and acoustic otoemissions. Otol Neurotol. (2009) 30:676–80. doi: 10.1097/MAO.0b013e3181ab8fd5
8. Majumdar B, Mason S, and Gibbin K. An electrocochleographic study of the effects of lignocaine on patients with tinnitus. Clin Otolaryngol Allied Sci. (1983) 8:175–80. doi: 10.1111/j.1365-2273.1983.tb01423.x
9. Watanabe K-I, Okawara D, Baba S, and Yagi T. Electrocochleographic analysis of the suppression of tinnitus by electrical promontory stimulation. Audiol. (1997) 36:147–54. doi: 10.3109/00206099709071968
10. Ferraro JA and Durrant JD. Electrocochleography in the evaluation of patients with meniere’s disease/endolymphatic hydrops. J Am Acad Audiol. (2006) 17:045–68. doi: 10.3766/jaaa.17.1.6
11. Ikner CL and Hassen AH. The effect of tinnitus on ABR latencies. Ear Hear. (1990) 11:16–20. doi: 10.1097/00003446-199002000-00005
12. Kehrle HM, Sampaio ALL, Granjeiro RC, de Oliveira TS, and Oliveira CACP. Tinnitus annoyance in normal-hearing individuals: correlation with depression and anxiety. Ann Otology Rhinology Laryngology. (2016) 125:185–94. doi: 10.1177/0003489415606445
13. Patil JD, Alrashid MA, Eltabbakh A, and Fredericks S. The association between stress, emotional states, and tinnitus: A mini-review. Front Aging Neurosci. (2023) 15:1131979. doi: 10.3389/fnagi.2023.1131979
14. Awad M, Abdalla I, Jara SM, Huang TC, Adams ME, and Choi JS. Association of sleep characteristics with tinnitus and hearing loss. OTO Open. (2024) 8:e117. doi: 10.1002/oto2.117
15. Capezuti E, Pain K, Alamag E, Chen X, Philibert V, and Krieger AC. Systematic review: auditory stimulation and sleep. J Clin Sleep Med. (2022) 18:1697–709. doi: 10.5664/jcsm.9860
16. Sanches SGG, Sanchez TG, and Carvallo RMM. Influence of cochlear function on auditory temporal resolution in tinnitus patients. Audiology Neurotology. (2010) 15:273–81. doi: 10.1159/000272939
17. Raghunandhan S, Ravikumar A, Kameswaran M, Mandke K, and Ranjith R. Electrophysiological correlates of behavioral comfort levels in cochlear implantees: A prospective study. Indian J Otolaryngol Head Neck Surg. (2015) 67:210–22. doi: 10.1007/s12070-013-0679-x
18. Lee HY, Shin S-H, and Byun SW. Electrocochleography in chronic tinnitus: correlations with audiological profiles and psychological distress. Am J Otolaryngol. (2024) 45:104477. doi: 10.1016/j.amjoto.2024.104477
19. Jiang C, Ding Z, Zan T, Liao W, Li H, Yang X, et al. Pathophysiological insights and multimodal interventions in chronic tinnitus, anxiety, and sleep disorders. Nat Sci Sleep. (2025) 17:2257–73. doi: 10.2147/NSS.S548093
20. Boecking B, Stoettner E, Brueggemann P, and Mazurek B. Emotional self-states and coping responses in patients with chronic tinnitus: A schema mode model approach. Front Psychiatry. (2024) 15:1257299. doi: 10.3389/fpsyt.2024.1257299
21. Zhou Q, Jiang W, Sheng H, Zhang Q, Jin D, Li H, et al. Does tinnitus and emotional distress influence central auditory processing? A comparison of acute and chronic tinnitus in normal-hearing individuals. PloS One. (2025) 20:e0327777. doi: 10.1371/journal.pone.0327777
22. Chan SF and La Greca AM. Perceived stress scale (Pss). Encyclopedia Behav Med Springer. (2020) 1646–8.
23. Smarr KL and Keefer AL. Measures of depression and depressive symptoms: beck depression inventory-II (BDI-II), center for epidemiologic studies depression scale (CES-D), geriatric depression scale (GDS), hospital anxiety and depression scale (HADS), and patient health questionnaire-9 (PHQ-9). Arthritis Care Res. (2011) 63:S454–S66. doi: 10.1002/acr.20556
24. Spitzer RL, Kroenke K, Williams JB, and Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Int Med. (2006) 166:1092–7. doi: 10.1001/archinte.166.10.1092
25. Spaapen DL, Waters F, Brummer L, Stopa L, and Bucks RS. The emotion regulation questionnaire: validation of the ERQ-9 in two community samples. Psychol Assess. (2014) 26:46. doi: 10.1037/a0034474
26. Buysse DJ, Hall ML, Strollo PJ, Kamarck TW, Owens J, Lee L, et al. Relationships between the pittsburgh sleep quality index (PSQI), epworth sleepiness scale (ESS), and clinical/polysomnographic measures in a community sample. J Clin Sleep Med. (2008) 4:563–71. doi: 10.5664/jcsm.27351
27. Bastien CH, Vallières A, and Morin CM. Validation of the insomnia severity index as an outcome measure for insomnia research. Sleep Med. (2001) 2:297–307. doi: 10.1016/S1389-9457(00)00065-4
29. Group W. Development of the world health organization whoqol-bref quality of life assessment. Psych Med. (1998) 28:551–8. doi: 10.1017/S0033291798006667
30. Fioretti AB, Fusetti M, and Eibenstein A. Association between sleep disorders, hyperacusis and tinnitus: evaluation with tinnitus questionnaires. Noise Health. (2013) 15:91–5. doi: 10.4103/1463-1741.110287
31. Zeman F, Koller M, Langguth B, Landgrebe M, and Group TRIDS. Which tinnitus-related aspects are relevant for quality of life and depression: results from a large international multicentre sample. Health Qual Life Outcomes. (2014) 12:1–10. doi: 10.1186/1477-7525-12-7
32. Dos Santos RMR, Sanchez TG, Bento RF, and de Lucia MCS. Auditory hallucinations in tinnitus patients: emotional relationships and depression. Int Arch Otorhinolaryngol. (2012) 16:322–7. doi: 10.7162/S1809-97772012000300004
33. Guest H, Munro KJ, Prendergast G, Howe S, and Plack CJ. Tinnitus with a normal audiogram: relation to noise exposure but no evidence for cochlear synaptopathy. Hear Res. (2017) 344:265–74. doi: 10.1016/j.heares.2016.12.002
34. Milloy V, Fournier P, Benoit D, Noreña A, and Koravand A. Auditory brainstem responses in tinnitus: A review of who, how, and what? Front Aging Neurosci. (2017) 9:237. doi: 10.3389/fnagi.2017.00237
35. Auerbach BD, Rodrigues PV, and Salvi RJ. Central gain control in tinnitus and hyperacusis. Front Neurol. (2014) 5:206. doi: 10.3389/fneur.2014.00206
36. Noreña AJ. An integrative model of tinnitus based on a central gain controlling neural sensitivity. Neurosci Biobehav Rev. (2011) 35:1089–109. doi: 10.1016/j.neubiorev.2010.11.003
37. Leaver AM, Renier L, Chevillet MA, Morgan S, Kim HJ, and Rauschecker JP. Dysregulation of limbic and auditory networks in tinnitus. Neuron. (2011) 69:33–43. doi: 10.1016/j.neuron.2010.12.002
38. Rauschecker JP, Leaver AM, and Mühlau M. Tuning out the noise: limbic-auditory interactions in tinnitus. Neuron. (2010) 66:819–26. doi: 10.1016/j.neuron.2010.04.032
39. Searchfield GD, Sanders PJ, and Barde A eds. A scoping review of the role of attention in tinnitus management. In: Seminars in Hearing. Germany: Thieme Medical Publishers, Inc.
40. Sedley W, Friston KJ, Gander PE, Kumar S, and Griffiths TD. An integrative tinnitus model based on sensory precision. Trends Neurosci. (2016) 39:799–812. doi: 10.1016/j.tins.2016.10.004
41. Camparis CM, Formigoni G, Teixeira M, and De Siqueira J. Clinical evaluation of tinnitus in patients with sleep bruxism: prevalence and characteristics. J Oral Rehabil. (2005) 32:808–14. doi: 10.1111/j.1365-2842.2005.01519.x
42. Gu H, Kong W, Yin H, and Zheng Y. Prevalence of sleep impairment in patients with tinnitus: A systematic review and single-arm meta-analysis. Eur Arch Oto-Rhino-Laryngology. (2022) 279:2211–21. doi: 10.1007/s00405-021-07092-x
43. Koning HM. Sleep disturbances associated with tinnitus: reduce the maximal intensity of tinnitus. Int Tinnitus J. (2019) 23:64–8. doi: 10.5935/0946-5448.20190012
44. Lu T, Li S, Ma Y, Lai D, Zhong J, Li G, et al. Positive correlation between tinnitus severity and poor sleep quality prior to tinnitus onset: A retrospective study. Pscyhiatr Q. (2020) 91:379–88. doi: 10.1007/s11126-019-09708-2
45. Adamchic I, Langguth B, Hauptmann C, and Tass PA. Abnormal cross-frequency coupling in the tinnitus network. Front Neurosci. (2014) 8:284. doi: 10.3389/fnins.2014.00284
46. Crönlein T, Langguth B, Geisler P, and Hajak G. Tinnitus and insomnia. Prog Brain Res. (2007) 166:227–33. doi: 10.1016/S0079-6123(07)66021-X
47. Durai M, O’Keeffe MG, and Searchfield GD. Examining the short term effects of emotion under an adaptation level theory model of tinnitus perception. Hearing Res. (2017) 345:23–9. doi: 10.1016/j.heares.2016.12.013
48. McKenna L, Handscomb L, Hoare DJ, and Hall DA. A scientific cognitive-behavioral model of tinnitus: novel conceptualizations of tinnitus distress. Frontiers in neurology. (2014) 5:196.
49. Andersson G and Edvinsson E. Mixed feelings about living with tinnitus: A qualitative study. Audiological Med. (2008) 6:48–54. doi: 10.1080/16513860801899355
50. Fagelson MA. The association between tinnitus and posttraumatic stress disorder. American Journal of Audiology. (2007) 16:107–117. doi: 10.1044/1059-0889(2007/015)
51. Gross JJ. Emotion regulation: current status and future prospects. psychol Inq. (2015) 26:1–26. doi: 10.1080/1047840X.2014.940781
52. Gross JJ and John OP. Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J Pers Soc Psychol. (2003) 85:348. doi: 10.1037/0022-3514.85.2.348
Keywords: auditory brainstem response, depression, electrocochleography, emotion regulation, sleepdisorders, tinnitus
Citation: Liu Y, Bao L, Mao X, Shao K, Xia G, Liu S and Ji K (2026) Associations between cochlear electrophysiology, emotional health, and sleep quality in adults with tinnitus: a comprehensive analysis. Front. Psychiatry 16:1721036. doi: 10.3389/fpsyt.2025.1721036
Received: 08 October 2025; Accepted: 01 December 2025; Revised: 30 November 2025;
Published: 30 January 2026.
Edited by:
Mario R. Louzã, University of São Paulo, BrazilReviewed by:
Mirta Peček, Sestre milosrdnice University Hospital Center, CroatiaTing-Gang Chang, Taichung Veterans General Hospital, Taiwan
Copyright © 2026 Liu, Bao, Mao, Shao, Xia, Liu and Ji. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Lihao Bao, dmlja3lseTgwQDEyNi5jb20=