Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116473
Title: Development of a shorten version of the 22-item level of self-criticism scale : using item response theory and factor analysis
Authors: Wong, MYC
Lam, SKK
Wong, JYH
Fung, HW 
Issue Date: 2025
Source: Research on social work practice, First published online May 2, 2025, OnlineFirst, https://doi.org/10.1177/10497315251335256
Abstract: Purpose: Excessive self-criticism, along with negative self-evaluation and perceived unfavorable judgments from others, often leads to emotional distress. The Levels of Self-Criticism (LOSC) scale identifies two distinct forms of self-criticism: comparative self-criticism and internalized self-criticism, yet with varying psychometric stability across different populations.
Method: This study developed a shortened, psychometrically robust version of the LOSC by employing item response theory (IRT) and factor analysis to enhance the practicality and reliability of the scale.
Results: 415 participants completed the baseline survey, and 232 completed the post-test, engaging 83% of females with Mage = 39.73. IRT analysis eliminated 11 items, with the remaining items demonstrating optimal item performance and significant concurrent validity with related measures. This shortened LOSC showed strong test–retest reliability and construct validity.
Discussion: This streamlined scale provides a precise tool for assessing self-criticism, contributing to better psychological practice and research.
Keywords: Factor analysis
Item response theory
Self-criticism
Shorten version
Publisher: SAGE Publications
Journal: Research on social work practice 
ISSN: 1049-7315
EISSN: 1552-7581
DOI: 10.1177/10497315251335256
Rights: This is the accepted version of the publication Claudia Wong, M. Y., Ki Lam, S. K., Wong, J. Y.-H., & Fung, H. W. (2025). Development of a Shorten Version of the 22-Item Level of Self-Criticism Scale: Using Item Response Theory and Factor Analysis. Research on Social Work Practice, 0(0). Copyright © 2025 The Author(s). DOI: 10.1177/10497315251335256.
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