Evidence map›Paper›PMID 42011189›Full record

ArticleInternet interventions2026

Uncovering latent trajectories of daily tinnitus symptoms through app-based monitoring during treatment.

Milena Engelke, Berthold Langguth, Thomas Probst, Rüdiger Pryss, Stefan Schoisswohl, Jorge Piano Simões, Peter Ten Klooster, Beat Toedtli, Carsten Vogel, Winfried Schlee

Abstract read
In one paragraph

Article in Internet interventions, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Milena EngelkeDepartment of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
Berthold LangguthDepartment of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
Thomas ProbstDivision of Psychotherapy, Department of Psychology, Paris Lodron University Salzburg, Salzburg, Austria.
Rüdiger PryssInstitute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.
Stefan SchoisswohlDepartment of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
Jorge Piano SimõesDepartment of Psychology, Health and Technology, University of Twente, Enschede, the Netherlands.
Peter Ten KloosterDepartment of Psychology, Health and Technology, University of Twente, Enschede, the Netherlands.
Beat ToedtliInstitute for Information and Process Management, Eastern Switzerland University of Applied Sciences, St. Gallen, Switzerland.
Carsten VogelInstitute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.
Winfried SchleeDepartment of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tinnitus heterogeneity is well-documented across phenotypes, etiologies, risk factors, comorbidities and associated burden. However, variability in treatment response remains insufficiently explored and often masked by the group-level comparisons of clinical studies. Moreover, little is known about the temporal trajectories of symptoms during treatment. Longitudinal monitoring via smartphones using Ecological Momentary Assessment provides rich inter- and intraindividual data on fluctuations and trajectories of symptoms. In this study, we investigated whether individual 12-week trajectories of daily self-reported tinnitus symptoms during treatment could be meaningfully sub-grouped. 147 patients provided 9634 observations while undergoing single or combined applications of hearing aids, cognitive-behavioural therapy, structured counseling, and sound therapy. A four-class growth mixture model best fit the data. One class was characterized by an increase in tinnitus symptoms over time (18%), another showed stable symptom trajectories (40%), while the remaining two classes described symptom reductions with different onsets during treatment (early improvement: 20%; late improvement: 21%). The identified classes did not differ in baseline characteristics, indicating that this information could not be used to predict symptom trajectories. Additionally, all four classes were represented in nearly each treatment arm. Notably, retrospective patient-reported outcome measures (PROMs) did not consistently align with latent symptom trajectories. These results underscore the heterogeneity and non-linearity of symptomatic change both within and across treatment modalities. We propose that app-based trajectories reveal details about symptom improvement that cannot be seen in standard PROMs.

Indexed as

Digital phenotypingEcological momentary assessmentExperience samplingGrowth mixture modelingLatent class analysisTinnitusTreatment dynamics

Identifiers

PMID42011189
PMCPMC13091948

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.