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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, OBJECTIVE, METHODS, METHODS, METHODS, RESULTS. Meshes: Adult, Aged, Bias, Cluster Analysis, Denmark, Female, Hearing Aids, Hearing Loss, Humans, Linear Models, Male, Netherlands, Outcome Assessment (Health Care), Patient Acceptance of Health Care, Self Report, Time Factors.
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Do patterns of hearing aid usage predict hearing aid use amount ( data logged and self-reported ) and overreport? Context: Previous studies found that, on average, users overreport their daily amount of hearing aid use compared to objective measures such as data logging. However, the reasons for this are unclear. This study assessed data-logged and self-reported amount of hearing aid use in a clinical sample of hearing aid users. It identified predictors of data-logged hearing aid use, self-reported hearing aid use, and hearing aid use overreport. This observational study recruited adult hearing aid users from 22 private dispensers in the Netherlands and in Denmark. The sample consisted of 228 hearing aid users. Typical participants were over the age of 65 and retired, were fitted binaurally, and had financially contributed to the cost of their hearing aids. Participants had on average a mild-to-severe sloping bilateral hearing impairment. Participants completed a purposefully designed questionnaire regarding hearing aid usage and the International Outcome Inventory-Hearing Aids. Dispensers collected audiometric results and data logging. Multiple linear regression identified predictors of data-logged hearing aid use, self-reported hearing aid use, and hearing aid use overreport when controlling for covariates. Data logging showed on average 10.5 hr of hearing aid use (n = 184), while participants reported on average 11.8 hr of daily hearing aid use (n = 206). In participants for which both data-logged and self-reported hearing aid use data were available (n = 166), the average absolute overreport of daily hearing aid use was 1.2 (1 hr and 11 min). Relative overreport was expressed as a rate of absolute overreport divided by data-logged hearing aid use. A positive rate denotes hearing aid use overreport: the average overreport rate was .38. Cluster analysis identified two data-logged patterns: "Regular," where hearing aids are typically switched on for between 12 and 20 hr before their user powers them off (57% of the sample), and "On-off," where hearing aids are typically switched on for shorter periods of time before being powered off (43% of the sample). In terms of self-report, 77% of the sample described their hearing aid use to be the same every day, while 23% of the sample described their hearing aid use to be different from day to day. Participants for whom data logging showed an On-off pattern or who reported their hearing aid use to be different from day to day had significantly fewer data-logged and self-reported hours of hearing aid use. Having an On-off data-logging pattern or describing hearing aid use as the same every day was associated with a significantly greater hearing aid use overreport.
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Data-logged and self-reported usage patterns significantly predicted data-logged hearing aid use, self-reported hearing aid use, and overreport when controlling for covariates. The results point to patterns of hearing aid usage as being at least as important a concept as amount of hearing aid use. Dispensers should discuss not only the "how much", but also the "how" of hearing aid usage with their clients. Final Decision: yes