Understanding tinnitus symptom dynamics and clinical improvement through intensive longitudinal data
Abstract Intensive longitudinal sampling enhances subjective data collection by capturing real-time, dynamic inputs in natural settings, complementing traditional methods. This study evaluates the feasibility of using daily self-reported app data to assess clinical improvement among tinnitus patient...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-024-01425-w |
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| Summary: | Abstract Intensive longitudinal sampling enhances subjective data collection by capturing real-time, dynamic inputs in natural settings, complementing traditional methods. This study evaluates the feasibility of using daily self-reported app data to assess clinical improvement among tinnitus patients undergoing treatment. App data from a multi-center randomized clinical trial were analysed using time-series feature extraction and nested cross-validated ordinal regression with elastic net regulation to predict clinical improvement based on the Clinical Global Impression—Improvement scale (CGI-I). With 50% app compliance (N = 129, 8480 entries), the model demonstrated good fit to the test data (McFadden R2 = 0.82) suggesting its generalizability. Clinical improvement was associated with linear declines in tinnitus-related thoughts, jaw tension, tinnitus loudness, increases in happiness, and variability changes in tinnitus loudness and distress. These findings suggest that daily self-reported data on tinnitus symptoms is sensitive to treatment response and provides insights into specific symptom changes that occur during treatment. |
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| ISSN: | 2398-6352 |