Open AccessExploring Latent Profiles of Stereotype Threat Susceptibility in U.S. and Colombian Students
Author(s) -
Katherine Picho,
Tatiana Rojas Ospina,
Adriana María Caicedo
Publication year - 2020
Publication title -
revista electrónica de investigación psicoeducativa y psicopedagógica/revista de investigación psicoeducativa
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.256
H-Index - 26
eISSN - 1699-5880
pISSN - 1696-2095
DOI - 10.25115/ejrep.v18i52.2729
Subject(s) - latent class model , stereotype (uml) , psychology , class (philosophy) , demography , social psychology , developmental psychology , sociology , statistics , mathematics , computer science , artificial intelligence
The present study investigated the theoretical Stereotyping Threat-susceptibility groups proposed by Steele (1997) by using a latent class analysis. Method: 413 undergraduate students from the U.S and Colombia, majoring in various Science Technology Engineering and Math (STEM) and non-STEM disciplines completed a stereotype threat susceptibility measure-- the Social Identities and Attitudes Scale, SIAS (Picho & Brown, 2011). Results: For U.S. women in STEM results indicated the presence of three ST susceptibility profiles (i.e., low and high ST susceptibility classes and a disengaged class) and two variations of an un-identified class in the non-STEM sample. High and low susceptibility to ST classes were found for Colombian women in STEM, while the non-STEM sample yielded disengaged and un-identified classes. In both countries, over 70% of the women in STEM were classified as highly susceptible to ST. Discussion: This is the first study investigating latent profiles of susceptibility to ST (SST) so additional replication with samples from different populations is strongly recommended. Extensive investigation into latent profiles of ST susceptibility could provide the insight required to develop differentiated ST reduction strategies for students in STEM and non-STEM fields of study.