# Stuttering in the real world: Quantifying variability to improve measurement reliability and validity

> **NIH NIH R01** · MICHIGAN STATE UNIVERSITY · 2024 · $412,803

## Abstract

Project Summary (30 lines)
Stuttering is a highly variable condition: People exhibit different amounts of stuttering behavior in different
tasks, when talking to different people, in different settings, and at different times. Although variability is
widely acknowledged, most assessments of stuttering behavior, whether conducted in a clinical setting or
for research, involve brief speech samples collected in a small number of settings that do not reflect
natural communication (e.g., monologuing or reading aloud). Unfortunately, we do not know if these
clinic/laboratory measures are representative of people's speaking experiences in the real world. Ample
evidence suggests that they are not, but the vast majority of clinical work and research on stuttering still
does not account for this variability. This raises questions about the validity of existing research that
relies on measures that may not be reflective of people's true stuttering behavior.
In this project, we seek to overcome these uncertainties about the validity of stuttering measurement.
We will collect the largest-ever samples of the everyday speech of people who stutter through
continuous recording of conversational interactions over a 7-day period. This will allow us to
examine the full range of stuttering behaviors that people exhibit across situations and over time.
For Aim 1, we will use these unprecedentedly large speech samples to test whether current practices of
collecting brief speech samples in clinical or laboratory settings are adequate. Pilot data and prior studies
suggests that a broader range of measures will be needed in order to better reflect people's true stuttering
behaviors. For Aim 2, we will develop a measurement model for stuttering using latent variable modeling
to support new methods for evaluating stuttering that are more reflective of real-world variability. For Aim
3, we will use structural regression modeling to explore the ways in which key personal characteristics,
such as the ways in which a person responds to stuttering, contribute to the experience of variability. For
Aim 4, we will conduct a mixed-methods study to explore how variability affects the adverse impact that
stuttering has on people's lives, with the ultimate goal of improving the assessment of stuttering so
that we can reduce adverse impact and enhance quality of life for people who stutter.
Overall Impact: Our findings will increase our understanding of the factors that contribute to the variability
of stuttering and provide needed guidance for improving assessment of stuttering in clinical and laboratory
settings. We will make our carefully transcribed, annotated speech samples available through
FluencyBank, so that other researchers can use our data to answer many unanswered questions about
stuttering in the real world. Our work has the potential to disrupt current thinking about stuttering
measurement while simultaneously providing a solution about how researchers and clinicians can
...

## Key facts

- **NIH application ID:** 10889063
- **Project number:** 5R01DC018795-05
- **Recipient organization:** MICHIGAN STATE UNIVERSITY
- **Principal Investigator:** J. Scott Yaruss
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $412,803
- **Award type:** 5
- **Project period:** 2020-08-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10889063

## Citation

> US National Institutes of Health, RePORTER application 10889063, Stuttering in the real world: Quantifying variability to improve measurement reliability and validity (5R01DC018795-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10889063. Licensed CC0.

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