ArticleScientific reports2020
Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Cluster-based psychological phenotyping and differences in anxiety treatment outcomes.Scientific reports · 2023Trial
- Tinnitus, hyperacusis and somatic complaints in a diverse Norwegian clinical population: implications for assessment and rehabilitation.Annals of medicine · 2026Article
- Tinnitus Phenotypes and Their Response to the Enriched Acoustic Environment (EAE) Treatment.Brain sciences · 2026Article
- Tinnitus and tinnitus disorder: Genetic, neurobiological, and clinical differentiation.iScience · 2026Review
- Uncovering latent trajectories of daily tinnitus symptoms through app-based monitoring during treatment.Internet interventions · 2026Article
- Development and Validation of a Nomogram to Identify and Predict High-Distress Psychosocial Phenotypes in Tinnitus Patients: A Latent Profile Analysis.Psychology research and behavior management · 2026Article
- Tinnitus Subtyping and Personalized Treatment via Audiometric and Psychometric Clustering.Yonsei medical journal · 2025Article
- Review
- Heterogeneity in response to treatment across tinnitus phenotypes.Scientific reports · 2024Article
- Longitudinal dynamic clinical phenotypes of in-hospital COVID-19 patients across three dominant virus variants in New York.International journal of medical informatics · 2024Article
- Emotional self-states and coping responses in patients with chronic tinnitus: a schema mode model approach.Frontiers in psychiatry · 2024Article
- Limited Link of Common Blood Parameters with Tinnitus.Journal of clinical medicine · 2023Article
- Tinnitus and Influencing Comorbidities.Laryngo- rhino- otologie · 2023Review
- Article
- Comparing Clustering Methods Applied to Tinnitus within a Bootstrapped and Diagnostic-Driven Semi-Supervised Framework.Brain sciences · 2023Article
- Systems Medicine Approach for Tinnitus with Comorbid Disorders.Nutrients · 2022Article
- Dimensions of Tinnitus-Related Distress.Brain sciences · 2022Article
- Characterization of Maternal Psychosocial Stress During Pregnancy: The Healthy Start Study.Women's health reports (New Rochelle, N.Y.) · 2022Article
- Too Blind to See the Elephant? Why Neuroscientists Ought to Be Interested in Tinnitus.Journal of the Association for Research in Otolaryngology : JARO · 2021Review
- A Review and a Framework of Variables for Defining and Characterizing Tinnitus Subphenotypes.Brain sciences · 2020Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic tinnitus is a complex, multi-factorial symptom that requires careful assessment and management. Evidence-based therapeutic approaches involve audiological and psychological treatment components. However, not everyone benefits from treatment. The identification and characterisation of patient subgroups (or "phenotypes") may provide clinically relevant information. Due to the large number of assessment tools, data-driven methods appear to be promising. The acceptance of these empirical results can be further strengthened by a comprehensive visualisation. In this study, we used cluster analysis to identify distinct tinnitus phenotypes based on self-report questionnaire data and implemented a visualisation tool to explore phenotype idiosyncrasies. 1228 patients with chronic tinnitus from the Charité Tinnitus Center in Berlin were included. At baseline, each participant completed 14 questionnaires measuring tinnitus distress, -loudness, frequency and location, depressivity, perceived stress, quality of life, physical and mental health, pain perception, somatic symptom expression and coping attitudes. Four distinct patient phenotypes emerged from clustering: avoidant group (56.8%), psychosomatic group (14.1%), somatic group (15.2%), and distress group (13.9%). Radial bar- and line charts allowed for visual inspection and juxtaposition of major phenotype characteristics. The phenotypes differed in terms of clinical information including psychological symptoms, quality of life, coping attitudes, stress, tinnitus-related distress and pain, as well as socio-demographics. Our findings suggest that identifiable patient subgroups and their visualisation may allow for stratified treatment strategies and research designs.
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