Predicting hearing aid use in adults: the Beaver Dam Offspring Study.

Area of Science:

• Audiology
• Gerontology
• Biostatistics

Background:

• Hearing loss is a prevalent condition, particularly among aging populations.
• Hearing aid (HA) adoption is crucial for managing hearing loss but can be challenging.
• Predicting HA use is essential for effective patient management and intervention.

Purpose of the Study:

• To develop and evaluate a predictive model for hearing aid (HA) use.
• To assess if incorporating non-traditional audiological factors enhances model prediction accuracy.

Main Methods:

• Two predictive models were developed: a 'clinical' model using standard audiological data and an 'expanded' model including additional health and lifestyle factors.
• Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 10-fold cross-validation was employed.
• Model performance was assessed using receiver operating characteristic (ROC) curves and concordance statistics (c-statistics).

Main Results:

• Both the clinical and expanded models identified significant predictors for HA use.
• The predictive accuracy, measured by c-statistics, was comparable between the clinical model (0.80) and the expanded model (0.79).
• The difference in predictive ability between the two models was not statistically significant (p=0.41).

Conclusions:

• Standard audiological evaluations provide robust predictive capabilities for hearing aid use.
• The addition of extra clinical, health, and lifestyle factors did not substantially improve the prediction of HA adoption.
• Current audiological assessment practices are effective in identifying individuals likely to benefit from and use hearing aids.