@article{SchleeNeffSimoesetal.2022,
  author    = {Schlee, Winfried and Neff, Patrick and Simoes, Jorge and Langguth, Berthold and Schoisswohl, Stefan and Steinberger, Heidi and Norman, Marie and Spiliopoulou, Myra and Schobel, Johannes and Hannemann, Ronny and Pryss, R{\"u}diger},
  title     = {Smartphone-guided educational counseling and self-help for chronic tinnitus},
  series = {Journal of Clinical Medicine},
  volume    = {11},
  journal   = {Journal of Clinical Medicine},
  number    = {7},
  issn      = {2077-0383},
  doi       = {10.3390/jcm11071825},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267295},
  year      = {2022},
  abstract  = {Tinnitus is an auditory phantom perception in the ears or head in the absence of a corresponding external stimulus. There is currently no effective treatment available that reliably reduces tinnitus. Educational counseling is a treatment approach that aims to educate patients and inform them about possible coping strategies. For this feasibility study, we implemented educational material and self-help advice in a smartphone app. Participants used the educational smartphone app unsupervised during their daily routine over a period of four months. Comparing the tinnitus outcome measures before and after smartphone-guided treatment, we measured changes in tinnitus-related distress, but not in tinnitus loudness. Improvements on the Tinnitus Severity numeric rating scale reached an effect size of 0.408, while the improvements on the Tinnitus Handicap Inventory (THI) were much smaller with an effect size of 0.168. An analysis of user behavior showed that frequent and intensive use of the app is a crucial factor for treatment success: participants that used the app more often and interacted with the app intensively reported a stronger improvement in the tinnitus. Between study allocation and final assessment, 26 of 52 participants dropped out of the study. Reasons for the dropouts and lessons for future studies are discussed in this paper.},
  language  = {en}
}
@article{UnnikrishnanSchleicherShahetal.2020,
  author    = {Unnikrishnan, Vishnu and Schleicher, Miro and Shah, Yash and Jamaludeen, Noor and Pryss, Ruediger and Schobel, Johannes and Kraft, Robin and Schlee, Winfried and Spiliopoulou, Myra},
  title     = {The effect of non-personalised tips on the continued use of self-monitoring mHealth applications},
  series = {Brain Sciences},
  volume    = {10},
  journal   = {Brain Sciences},
  number    = {12},
  issn      = {2076-3425},
  doi       = {10.3390/brainsci10120924},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-219435},
  year      = {2020},
  abstract  = {Chronic tinnitus, the perception of a phantom sound in the absence of corresponding stimulus, is a condition known to affect patients' quality of life. Recent advances in mHealth have enabled patients to maintain a 'disease journal' of ecologically-valid momentary assessments, improving patients' own awareness of their disease while also providing clinicians valuable data for research. In this study, we investigate the effect of non-personalised tips on patients' perception of tinnitus, and on their continued use of the application. The data collected from the study involved three groups of patients that used the app for 16 weeks. Groups A \& Y were exposed to feedback from the start of the study, while group B only received tips for the second half of the study. Groups A and Y were run by different supervisors and also differed in the number of hospital visits during the study. Users of Group A and B underwent assessment at baseline, mid-study, post-study and follow-up, while users of group Y were only assessed at baseline and post-study. It is seen that the users in group B use the app for longer, and also more often during the day. The answers of the users to the Ecological Momentary Assessments are seen to form clusters where the degree to which the tinnitus distress depends on tinnitus loudness varies. Additionally, cluster-level models were able to predict new unseen data with better accuracy than a single global model. This strengthens the argument that the discovered clusters really do reflect underlying patterns in disease expression.},
  language  = {en}
}