CAT: Competitive Attention Test Validation Data Across the Lifespan

The Competitive Attention Test (CAT) dataset provides validation evidence for a psychometric tool assessing distractibility. It includes results from two experiments with a total sample size of 520 participants aged 6 to 89, examining reliability and construct validity. The dataset was authored by Nicola Thibault and last updated on May 21, 2026.

Use Cases

• Validating new attention measures based on indices related to speed, variability, phasic arousal, and accuracy.
• Studying lifespan development of attentional control based on data from participants aged 6 to 89.
• Assessing convergent validity of attention tests by comparing CAT results with established measures like TAP-M and KiTAP.
• Investigating the ecological validity of cognitive neuroscience models of attention using ecologically relevant stimuli.

Strengths

• Validation includes a lifespan sample of participants aged 6 to 89.
• Reliability assessments cover internal consistency (N=520), inter-rater reliability (N=114), and short-term test-retest reliability (N=79).
• Construct validity was evaluated against established attention measures (TAP-M, KiTAP; n=38) and divergent validity with Wechsler intelligence scales.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small (27.1 KB), indicating limited scope.

Provenance

Source

figshare

Collection Method

Data collected from two psychometric validation experiments.

Freshness

Last updated 2026-05-21 05:33:51; freshness should be verified.