Objective busyness or subjective scarcity? Scale abbreviation and heterogeneity profiles of college students' perceived time poverty via genetic algorithm

College students in the digital intelligence era face severe challenges of time poverty, yet the length of existing measurement tools limits large–scale screening, and a variable–centered perspective obscures the heterogeneity of the time experience. This study aimed to develop an efficient assessment tool and reveal the latent subtypes of time poverty and their anxiety correlates. Study 1 utilized a genetic algorithm to abbreviate the College Students' Perceived Time Poverty Scale. Based on a global optimization search of the training set ( n 1 = 811), an 8–item short–form scale ( CSPTP–GA ) was developed. In the validation set ( n 2 = 719), the scale demonstrated adequate reliability (Cronbach's α > 0.70), excellent fit indices (χ 2 / df = 2.78, RMSEA = 0.05, CFI = 0.992, IFI = 0.992, TLI = 0.984, SRMR = 0.03), and strong measurement invariance across gender and educational level. Study 2 conducted a latent profile analysis on 507 college students based on the CSPTP–GA , identifying four distinct subgroups: the Low Time Poverty Group (31%), the Academic Conflict Perception Group (20%), the Moderate Time Poverty Group (16%), and the High Time Poverty Group (33%). The Academic Conflict Perception Group identified by the latent profile analysis exhibited characteristics of being objectively not busy but subjectively anxious, forcefully corroborating the theoretical hypothesis that “busyness does not equal poverty”. Furthermore, males and undergraduate students were found to be relatively protected against high time poverty compared to females and postgraduates. This study not only confirms the psychometric efficacy of the genetic algorithm but also emphasizes the importance of distinguishing between objective resource scarcity and subjective cognitive conflict for precision intervention.