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Effect Sizes and Statistical Power in Hearing Aid Research
Preeti Pandey1,2,3, Marien Graham4, Anu Sharma3
1Department of Otolaryngology - Head & Neck Surgery, University of Colorado School of Medicine, Aurora.
American Journal of Audiology
|June 9, 2026
Summary
Hearing aid research uses outdated effect size benchmarks. This study proposes new, field-specific benchmarks (0.1, 0.2, 0.5) to improve accuracy and guide sample size planning for better replicability.
Area of Science:
- Audiology
- Biostatistics
- Clinical Research
Background:
- Effect sizes in hearing aid research often rely on generic benchmarks (Cohen's 0.20, 0.50, 0.80).
- These generic benchmarks may not accurately represent typical effect magnitudes in hearing aid studies.
- This can lead to misinterpretation of results and inefficient sample size planning.
Purpose of the Study:
- To determine the actual distribution of effect sizes in adult hearing aid research.
- To establish field-specific benchmarks for interpreting effect sizes.
- To estimate sample sizes needed for adequate statistical power in hearing aid trials.
Main Methods:
- Systematic search of PubMed, CINAHL, and Embase for randomized controlled trials (RCTs) on adult hearing aid use.
- Calculation of absolute Hedges's g effect sizes from eligible studies.
- Use of calculated percentiles (25th, 50th, 75th) as empirical benchmarks.
Main Results:
- Analysis of 33 trials (4,471 participants) identified 63 effect sizes.
- Empirical benchmarks (Hedges's g = 0.10, 0.22, 0.48) were smaller than Cohen's conventional values.
- Few published studies achieved 80% power for a medium effect size using conventional benchmarks.
Conclusions:
- Hearing aid research effect sizes are typically smaller than suggested by generic benchmarks.
- Recommended empirical benchmarks for hearing aid research are 0.1 (small), 0.2 (medium), and 0.5 (large).
- Adopting these benchmarks improves interpretation accuracy, sample size planning, and study replicability.
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