Empathy Quotient (EQ) - Trait Profiler Research Dataset

Abstract

This dataset presents anonymized participant responses collected through the Trait Profiler implementation of the Empathy Quotient (EQ). The assessment was administered online between 2026-05-25 and 2026-05-31, resulting in a final sample of 12 completed responses.

Data collection was conducted through the Trait Profiler assessment platform developed by Deen Mohd. Participants voluntarily completed the assessment for educational, self-exploratory, and research purposes. All records were anonymized prior to publication and no personally identifiable information is included in this dataset.

The released dataset contains participant-level response data, assessment scores, and associated measurement information generated according to the scoring procedures of the Empathy Quotient (EQ). Researchers may use these data for psychometric evaluation, reliability analysis, exploratory and confirmatory factor analysis, normative investigations, score distribution analysis, and methodological demonstrations.

Dataset Characteristics

Within the present sample, scores ranged from 51 to 57, producing an observed range of 6 points. The average score was 54.67, while the median score was 57. Variability within the sample was moderate, with a standard deviation of 2.93. The estimated 95% confidence interval for the sample mean ranged from 53.01 to 56.33.

These findings provide an empirical overview of score distributions observed among individuals who voluntarily completed the assessment through the Trait Profiler platform. The data should not be considered representative of any national or clinical population; however, they may provide valuable reference information for comparative studies and future psychometric research.

Contents of the Dataset

The dataset includes anonymized item responses, calculated assessment scores, completion dates, and statistical information derived from participant submissions. The data are distributed in CSV format to facilitate reuse across statistical software environments including R, Python, SPSS, JASP, Jamovi, and Stata.