Authors: Anna Josefine Munch Sørensen1, Soffi Skovlund Jensen1, Niels Henrik Pontoppidan1, Lena Havtorn1, Claus Nielsen1, Tiberiu-ioan Szatmari1
1Eriksholm Research Centre
Background: The ultimate outcome of hearing rehabilitation is to improve people’s hearing and communication experiences in their everyday life. Traditional methods for evaluating the outcome of hearing aid (HA) treatment rely on user feedback given in the clinic, which tend to be general and based on the user’s recollection of difficult situations. One popular evaluation tool is called the Client Oriented Scale of Improvement (COSI) which is used to assess difficult listening situations. One of the most common situations reported is communication in noise, which can cover a variety of different situations and acoustic scenarios. Therefore, there is a need to be able to capture these scenarios with higher precision and less recall bias to make a more targeted adjustment of HA fittings and to support more informed discussions with the client in the clinical setting on how to improve on those situations.
Method: To be able to continuously evaluate the situations the HA user finds challenging, we developed an app allowing HA users to assess difficult listening situations in the field using Ecological Momentary Assessment (EMA). We created seven environment and 12 intent labels from comparing COSI situations from 85 HA users in our database to the Common Sound Scenarios (CoSS, Wolters 2016) framework and expanded the CoSS categories to capture all COSI situations. These environment and intent categories are presented to the user in the EMA questionnaire along with four questions assessing the difficulty, importance, and occurrence of the situation and whether the HA user feels their HA helps them in the given situation. Along with this subjective evaluation of the user’s listening experience, the acoustic environment surrounding the user is captured via HA data logging to get an objective assessment of the situation. We hope this detailed mapping of difficult situations can provide more informed input for future interventions and HA processing strategies.
