Objective
Determine the extent to which pre-fitting acceptable noise level (ANL), with or without other predictors such as hearing aid experience, can predict real-world hearing aid outcomes at 3 and 12 months post-fitting.
Design
ANLs were measured before hearing aid fitting. Post-fitting outcome was assessed using the International Outcome Inventory for Hearing Aids (IOI-HA) and a hearing aid use questionnaire. Models that predicted outcomes (successful vs. unsuccessful) were built using logistic regression and several machine learning algorithms, and were evaluated using the cross-validation technique.
Study sample
132 adults with hearing impairment.
Results
The prediction accuracy of the models ranged from 61% to 68% (IOI-HA) and from 55% to 61% (hearing aid use questionnaire). The models performed more poorly in predicting 12-month than 3-month outcomes. The ANL cutoff between successful and unsuccessful users was higher for experienced (~18 dB) than first-time hearing aid users (~10 dB), indicating that most experienced users will be predicted as successful users regardless of their ANLs.
Conclusions
Pre-fitting ANL is more useful in predicting short-term (3 months) hearing aid outcomes for first-time users, as measured by the IOI-HA. The prediction accuracy was lower than the accuracy reported by some previous research that used a cross-sectional design.