Exploring adult hearing aid user experiences: meaning extraction methods, content patterns, and associations with demographic and outcome variables
Year: 2024
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: Employing automated language analysis, specifically Meaning Extraction Method (MEM) and Principal Component Analysis (PCA), to identify key factors in open-text responses about hearing aid experiences. DESIGN: Exploratory, cross-sectional design, using an online questionnaire. Responses to a single open-ended question were analysed using MEM, PCA, regression, and correlation analyses. STUDY SAMPLE: Participants (n = 538) included adult hearing aid users sampled from the Hearing Tracker website community and Lexie Hearing user databases in the United States. RESULTS: The MEM-derived items revealed six factors related to hearing aid experiences: (1) life change, (2) social situation, (3) quality of life, (4) impact and speech understanding, (5) communication and interaction, and (6) music and environmental sounds. IOI-HA item 3 had the most statistically significant correlations with PCA factors. Quantile regression revealed that factors one and two significantly predicted the IOI-HA total score. Positive correlations were observed between self-reported hearing difficulty and factors one, four, and five, as well as between factor one and general health and factor two and physical activity. CONCLUSION: Natural language analysis of open-ended textual responses can offer valuable insights into hearing aid users' experiences. Future studies should aim to refine this methodology to enhance clinical relevance and generalisability.
Institutions: University of Colorado Anschutz, University of Pretoria, University of Colorado Denver, Stony Brook University, The University of Texas at Austin, The University of Queensland, Sonova (Switzerland), University of Colorado Hospital, Manipal Academy of Higher Education, University of Colorado Health
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4403789955