Speech Disfluencies as a Measure of Skill Automaticity in Psychotherapy

Replication Data for a think-aloud study on speech disfluencies as a measure of skill automaticity in psychotherapy. The dataset was authored by Dan Sacks and last updated on March 28, 2026. It is hosted on the Dataverse platform under the Social Sciences category.

Use Cases

• Analyze the relationship between speech disfluencies and therapist skill automaticity based on the study's core hypothesis.
• Replicate statistical findings from the original think-aloud study using the provided data and code.
• Train models to identify or quantify disfluency patterns in therapeutic speech transcripts.
• Investigate the validity of speech-based measures for assessing clinical training outcomes.

Strengths

• Includes replication code alongside the data, facilitating reproducibility.
• Last updated on March 28, 2026, indicating recent maintenance.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

Dan Sacks Dataverse

Collection Method

Likely collected from a think-aloud study in a psychotherapy context.

Freshness

Last updated 2026-03-28 19:44:53; freshness should be verified.