Refine
Has Fulltext
- yes (12)
Is part of the Bibliography
- yes (12) (remove)
Document Type
- Journal article (8)
- Doctoral Thesis (4)
Keywords
- tinnitus (12) (remove)
Institute
Tinnitus is a phantom sound perception in the ears or head and can arise from many different medical disorders. Currently, there is no standard treatment for tinnitus that reliably reduces tinnitus. Individual patients reported that acupressure at various points around the ear can help to reduce tinnitus, which was investigated here. With this longitudinal observational study, we report a systematic evaluation of auricular acupressure on 39 tinnitus sufferers, combined with a self-help smartphone app. The participants were asked to report on tinnitus, stress, mood, neck, and jaw muscle tensions twice a day using an ecological momentary assessment study design for six weeks. On average, 123.6 questionnaires per person were provided and used for statistical analysis. The treatment responses of the participants were heterogeneous. On average, we observed significant negative trends for tinnitus loudness (Cohen's d effect size: −0.861), tinnitus distress (d = −0.478), stress (d = −0.675), and tensions in the neck muscles (d = −0.356). Comparison with a matched control group revealed significant improvements for tinnitus loudness (p = 0.027) and self-reported stress level (p = 0.003). The positive results of the observational study motivate further research including a randomized clinical trial and long-term assessment of the clinical improvement.
Background: Tinnitus is often described as the phantom perception of a sound and is experienced by 5.1% to 42.7% of the population worldwide, at least once during their lifetime. The symptoms often reduce the patient's quality of life. The TrackYourTinnitus (TYT) mobile health (mHealth) crowdsensing platform was developed for two operating systems (OS)-Android and iOS-to help patients demystify the daily moment-to-moment variations of their tinnitus symptoms. In all platforms developed for more than one OS, it is important to investigate whether the crowdsensed data predicts the OS that was used in order to understand the degree to which the OS is a confounder that is necessary to consider.