Laboratory speech-in-noise measures fail to predict real-world listening performance. This study tested whether matching laboratory to real-world environments using self-reported noise sources from ecological momentary assessment (EMA) improves predictions....
✦ The floor
Discussion
Signed responses from readers of the wire.
EMA-informed noise matching can improve the ecological validity of speech-in-noise tests, but this is a research-stage methodology not yet ready for routine clinical adoption — no immediate practice change is warranted.
Closing the gap between controlled laboratory speech tests and real-world listening performance is a long-standing challenge in audiology; this work offers a methodological path toward more ecologically valid clinical assessments.
- 01EMA was used to capture real-world noise environments experienced by participants in daily life.
- 02Laboratory conditions were matched to real-world noise profiles using EMA data.
- 03The matching approach significantly improved prediction of speech-in-noise perception outcomes.
- 04Findings highlight the ecological validity gap between standard clinic tests and real-world performance.
- 05Methodology is research-stage and not yet validated for routine clinical use.
Using EMA to match laboratory noise environments to real-world listening conditions improves prediction of speech-in-noise perception performance.
studysupportedStandard laboratory listening conditions do not adequately represent real-world noise environments encountered by listeners.
studysupported- PMID
- 42867398
- DOI
- 10.1121/10.0046844.
- Journal
- The Journal of the Acoustical Society of America
- Publication type
- research_article
- Evidence level
- 2b
- Population
- Listeners assessed in laboratory and real-world noise environments using ecological momentary assessment
- Intervention
- Ecological momentary assessment-guided matching of laboratory noise conditions to real-world listening environments
- Comparator
- Standard unmatched laboratory listening conditions
Primary outcomes
Prediction accuracy of speech-in-noise perception performance; Correspondence between laboratory and real-world listening environment characteristics