Mathiasen Rubin (serverphone17)

They answered fewer questions in conversations with multiple partners and were more likely to postpone questionnaires when not in quiet environments. Conclusion Data for social situations will likely be underrepresented in EMA. However, these situations are particularly important for the evaluation of hearing aids, as individuals with hearing impairment often have difficulties communicating in noisy situations. Thus, it is vital to optimize the design of the study to find a balance between avoiding memory bias and enabling subjects to report retrospectively on situations where phone usage may be difficult. The implications for several applications of EMA are discussed. Supplemental Material https//doi.org/10.23641/asha.12746849.Purpose The clinical data stored in electronic health records (EHRs) provide unique opportunities for audiological clinical research. In this article, we share insights from our experience of working with a large clinical database of over 730,000 cases. Method Under a framework outlining the process from patient care to researcher data use, we describe issues that can arise in each step of this process and how we overcame specific issues in our data set. Results Correct interpretation of findings depends on an understanding of the data source and structure, and efforts to establish confidence in the data through the processes are discussed under the framework. Conclusion We conclude that EHRs have considerable utility in audiological research, though researchers must exhibit caution and consideration when working with EHRs.Purpose The aim of the study was to learn (a) how datalogging information is being used in clinical practice by hearing care providers (HCPs) in the United States and (b) HCPs' opinions about how information collected through the hearing aids could be broadened in clinical application. Method A mixed-method approach was undertaken consisting of an online quantitative survey and qualitative structured telephone interviews. Survey data were analyzed using descriptives and chi-square analyses. The interview data were transcribed and analyzed using inductive content analysis. Results In total, 154 HCPs completed the survey, of whom 10 also completed an interview. Survey data showed that most HCPs use datalogging for conventional applications, such as counseling and fine-tuning during a hearing aid trial. Interview data highlighted four additional desirable datalogging features (a) data about the sound environment, (b) details about operational aspects of hearing aid use, (c) data about use and nonuse, and (d) automated diagnosis of a hearing aid malfunction. HCPs also envisaged using datalogging in novel ways, such as for demonstrating hearing aid value and supporting decision making. Conclusions Today, datalogging is primarily used as a tool for counseling clients about hours and patterns of hearing aid use and for troubleshooting and fine-tuning. However, HCPs suggested novel and more ambitious uses of datalogging such as for sending alerts about nonuse, for automated diagnosis of a hearing aid malfunction, and for helping the client in their decision making. It remains to be seen whether in the future these will be implemented into clinical practice.Purpose The purpose of the research described here is to create a theoretically based, interactive online program to motivate adults with untreated hearing loss to seek audiology care. We describe the results of the participatory design (PD) approach used to increase uptake and adherence to the Internet-based program. Method Using information gathered from field experts (n = 7), a program outline was generated by the study team. In keeping with PD principles, multiple focus groups and panels consisting of persons with hearing loss (n = 26), frequent communication partners (n = 6), audiologists (n = 9), and other area experts (n = 16) revised and expanded both content and design of the program in an iterative fashion. Results The proposed