Dataset for the Deez Alexithymia Scale (DAS-21): Adult Community Sample

This dataset contains anonymized item-level and scored responses for the Deez Alexithymia Scale (DAS-21), a 21-item self-report psychometric instrument developed to assess alexithymia as a multidimensional construct. Alexithymia refers to persistent difficulties in identifying and describing emotions, a tendency toward externally oriented thinking, and reduced emotional engagement. The DAS-21 was designed to extend traditional measurement approaches by incorporating emotional detachment as an explicit and theoretically relevant dimension, making the scale suitable for research, educational, and applied psychological contexts.

The dataset is based on a community adult sample (N = 300) and includes demographic variables alongside full item-level responses to all DAS-21 items. Participants are represented by anonymous identifiers to ensure confidentiality. Demographic variables include age (in years), gender (coded numerically), and education level (coded to reflect highest level of completed education). No personally identifiable information is included, and no clinical diagnoses are implied or recorded in the dataset.

Each DAS-21 item is rated using a 5-point Likert-type response format ranging from 1 (Strongly disagree) to 5 (Strongly agree). Higher scores reflect greater levels of alexithymic traits. In addition to raw item responses, the dataset includes computed subscale scores corresponding to the four theoretical dimensions of the DAS-21: Difficulty Identifying Feelings (DIF), Difficulty Describing Feelings (DDF), Externally Oriented Thinking (EOT), and Emotional Detachment (ED). A total alexithymia score is also provided, calculated as the sum of all 21 items. No reverse-scored items are used, reducing scoring complexity and potential user error.

The dataset is structured to facilitate transparency, reproducibility, and secondary analysis. It may be used for psychometric evaluation, scale comparison studies, methodological demonstrations, educational purposes, and exploratory research on emotional awareness and affective processing. Researchers may also use the dataset to test alternative factor structures, examine measurement invariance, or illustrate scoring procedures in teaching and training contexts. While the dataset reflects realistic response distributions consistent with self-report research, it should be interpreted as non-diagnostic and not as a substitute for clinical assessment.

All data are fully anonymized, and participation was voluntary. The dataset does not contain sensitive personal information, health records, or identifying variables.

Overall, this dataset supports open science practices by providing a clear, well-documented resource for the study of alexithymia. By combining item-level data with scored subscales and transparent documentation, the dataset offers a valuable foundation for future research on emotional processing, neurodiversity, and educational implications associated with alexithymic traits.