Narrative Stimuli Complexity Scores for Aphasia Therapy Research

Twelve narrative stimuli were profiled using a rule-based structural analysis to quantify complexity for aphasia therapy. The dataset includes metrics like sentence count, average sentence length, and complex sentence ratio, normalized into composite scores. Author Hyunsoo Yoo published this exploratory analysis on figshare in April 2026 under a CC-BY-4.0 license.

Use Cases

• Calibrating stimulus difficulty for narrative retelling therapy based on structural complexity scores.
• Sequencing therapy materials based on composite complexity classifications (Low, Medium, High).
• Analyzing the relationship between stimulus structure and produced Information Unit (IU) change.
• Developing transparent, quantifiable methods for profiling discourse-level materials in clinical research.

Strengths

• Dataset is small (23.7 KB), facilitating quick download and inspection.
• Provides a transparent, rule-based profiling method for narrative stimuli.
• Includes derived composite scores for classifying stimuli into three complexity groups.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Row count and column-level documentation are unknown; field semantics must be inferred.
• Scale is limited to 12 stimuli, described as an exploratory single-case analysis.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Stimuli were analyzed using a Python-based pipeline to extract structural metrics.

Time Range

The study timeframe is not specified.

Freshness

Last updated 2026-04-13 14:32:20; freshness should be verified.

Geography

Geographic coverage is not specified.