Decoding cognitive distortions in different age groups: cluster analysis

Introduction. Cognitive biases are persistent thinking errors that influence perception, behavior, and decision-making. Studying them over time is important for understanding the psychological characteristics of perception and the formation of biases.The purpose of the study. To determine age-specific profiles of cognitive biases in a 16–30 year student sample aged using cluster analysis. The primary objective was to apply cluster analysis to questionnaire results to identify persistent thinking patterns and biases in respondents of different ages.Materials and methods. A total of three hundred twenty volunteers (71% women, 29% men) participated in the online survey. The average age of the group was 19.8 ± 4.7 years. The author’s CBB-8 questionnaire included 24 statements reflecting eight key biases; the internal consistency of the entire scale was α = 0.83. After standardization of the indices, the profiles were grouped using the k-means++ method (elbow criterion; optimal k = 3; silhouette = 0.41). Intercluster differences were tested by χ² and one-way ANOVA; two-tailed significance level of 0.05.Results. Three profiles were identified. Cluster 0, “younger”: n = 105; 32.8% (95% CI 27.7–38.3); median age 18 years; low anxiety, high tolerance for uncertainty. Cluster 1, “senior student”: n = 134; 41.9% (95% CI 36.3–47.8); median 23.7 years (IQR 22–25); pronounced pessimism. Cluster 2, “intermediate”: n = 81; 25.3% (95% CI 20.8–30.5); median 21 years.Research limitations. The study did not account for respondents’ socioeconomic status and was cross-sectional, not accounting for age-related changes.Conclusion. Cluster analysis demonstrates the existence of three stable age-related profiles of cognitive biases in the youth sample. The resulting typology can be considered when developing educational programs on critical thinking and prejudice prevention.Compliance with ethical standards. The study was approved by the Ethics Committee of the Research Institute for Healthcare Organization and Medical Management (approval No. 02-01_EC_2025 dated February 11, 2025). All participants provided informed voluntary consent to participate in the study.Funding. The study had no sponsorship.Conflict of interest. The authors declare the absence of obvious and potential conflicts of interest in connection with the publication of this article.Received: March 26, 2025 / Accepted: June 24, 2025 / Published: October 31, 2025

cognitive distortions, cluster analysis, decision making, age groups, psychological health, k-means clustering