@article{SprinzlMageleSchoergetal.2023,
  author    = {Sprinzl, Georg Mathias and Magele, Astrid and Schoerg, Philipp and Hagen, Rudolf and Rak, Kristen and Kurz, Anja and Van de Heyning, Paul and Calvino, Miryam and Lassaletta, Luis and Gavil{\´a}n, Javier},
  title     = {A novel representation of audiological and subjective findings for acoustical, bone conduction and direct drive hearing solutions},
  series = {Journal of Personalized Medicine},
  volume    = {13},
  journal   = {Journal of Personalized Medicine},
  number    = {3},
  issn      = {2075-4426},
  doi       = {10.3390/jpm13030462},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311210},
  year      = {2023},
  abstract  = {Background: The benefit of hearing rehabilitation is often measured using audiological tests or subjective questionnaires/interviews. It is important to consider both aspects in order to evaluate the overall benefits. Currently, there is no standardized method for reporting combined audiological and patient reported subjective outcome measures in clinical practice. Therefore, this study focuses on showing the patient's audiological, as well as subjective outcomes in one graph using data from an existing study. Method: The present paper illustrated a graph presenting data on four quadrants with audiological and subjective findings. These quadrants represented speech comprehension in quiet (unaided vs. aided) as WRS\% at 65 dB SPL, speech recognition in noise (unaided vs. aided) as SRT dB SNR, sound field threshold (unaided vs. aided) as PTA\(_4\) in dB HL, wearing time and patient satisfaction questionnaire results. Results: As an example, the HEARRING graph in this paper represented audiological and subjective datasets on a single patient level or a cohort of patients for an active bone conduction hearing implant solution. The graph offered the option to follow the user's performance in time. Conclusion: The HEARRING graph allowed representation of a combination of audiological measures with patient reported outcomes in one single graph, indicating the overall benefit of the intervention. In addition, the correlation and consistency between some results (e.g., aided threshold and aided WRS) can be better visualized. Those users who lacked performance benefits on one or more parameters and called for further insight could be visually identified.},
  language  = {en}
}
@article{MertensAndriesKurzetal.2022,
  author    = {Mertens, Griet and Andries, Ellen and Kurz, Anja and Tȧvora-Vieira, Dayse and Calvino, Miryam and Amann, Edda and Anderson, Ilona and Lorens, Artur},
  title     = {Towards a consensus on an ICF-based classification system for horizontal sound-source localization},
  series = {Journal of Personalized Medicine},
  volume    = {12},
  journal   = {Journal of Personalized Medicine},
  number    = {12},
  issn      = {2075-4426},
  doi       = {10.3390/jpm12121971},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297319},
  year      = {2022},
  abstract  = {The study aimed to develop a consensus classification system for the reporting of sound localization testing results, especially in the field of cochlear implantation. Against the background of an overview of the wide variations present in localization testing procedures and reporting metrics, a novel classification system was proposed to report localization errors according to the widely accepted International Classification of Functioning, Disability and Health (ICF) framework. The obtained HEARRING_LOC_ICF scale includes the ICF graded scale: 0 (no impairment), 1 (mild impairment), 2 (moderate impairment), 3 (severe impairment), and 4 (complete impairment). Improvement of comparability of localization results across institutes, localization testing setups, and listeners was demonstrated by applying the classification system retrospectively to data obtained from cohorts of normal-hearing and cochlear implant listeners at our institutes. The application of our classification system will help to facilitate multi-center studies, as well as allowing better meta-analyses of data, resulting in improved evidence-based practice in the field.},
  language  = {en}
}