School non-attendance and learned helplessness: latent profiles and ROC curves

Due to the complex school reality, Learned Helplessness (LH) is a student’s response characterized by lack of confident, interpretative bias and negative outlook of success in face of school challenges. These helpless students develop a negative attitude toward school, leading to a withdrawal of sch...

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Main Authors: María Pérez-Marco, Andrea Fuster, Carolina Gonzálvez
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Psychology
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Online Access:https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1557915/full
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author María Pérez-Marco
Andrea Fuster
Carolina Gonzálvez
author_facet María Pérez-Marco
Andrea Fuster
Carolina Gonzálvez
author_sort María Pérez-Marco
collection DOAJ
description Due to the complex school reality, Learned Helplessness (LH) is a student’s response characterized by lack of confident, interpretative bias and negative outlook of success in face of school challenges. These helpless students develop a negative attitude toward school, leading to a withdrawal of school engagement and anxious disorders, reporting links with emotionally based school non-attendance. Taking into account the heterogeneous causes of these problems, in recent years new instruments have been emerged, like Assessing Reasons for School Non-Attendance (ARSNA; Havik et al., 2015), of which there is a clear lack of research. The study aims to: (1) identify latent profiles of school absenteeism based on Assessing Students’ Reported Reasons for School Non-attendance (ARSNA; Havik et al., 2015); (2) analyze differences between school non-attendance profiles and Learned Helplessness (LH); and (3) establish the predictive and discriminative capacity of LH to identify students of the high school non-attendance profile. Consequently, 759 adolescents (M = 14.95, SD = 1.82) fulfilled ARSNA (Havik et al., 2015) and Learned Helplessness Questionnaire (LHQ; Sorrenti et al., 2015). Pearson’s correlation coefficients reported positive and statistically significant correlations between ARSNA dimensions and LH. Latent Profile Analyses revealed 3 school absenteeism profiles. ANOVA indicated statistically significant differences between these profiles and LH. Finally, Logistic Regression and ROC Curves found the predictive and discriminative ability of LH to identify individuals of the high school non-attendance profile. Results contribute to the literature on ARSNA dimensions and LH, highlighting the potential implications for schools and for the intervention against emotionally based school non-attendance.
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spelling doaj-art-2bc68633f6db4598a3a3c0526e98c1b52025-08-20T03:21:53ZengFrontiers Media S.A.Frontiers in Psychology1664-10782025-06-011610.3389/fpsyg.2025.15579151557915School non-attendance and learned helplessness: latent profiles and ROC curvesMaría Pérez-MarcoAndrea FusterCarolina GonzálvezDue to the complex school reality, Learned Helplessness (LH) is a student’s response characterized by lack of confident, interpretative bias and negative outlook of success in face of school challenges. These helpless students develop a negative attitude toward school, leading to a withdrawal of school engagement and anxious disorders, reporting links with emotionally based school non-attendance. Taking into account the heterogeneous causes of these problems, in recent years new instruments have been emerged, like Assessing Reasons for School Non-Attendance (ARSNA; Havik et al., 2015), of which there is a clear lack of research. The study aims to: (1) identify latent profiles of school absenteeism based on Assessing Students’ Reported Reasons for School Non-attendance (ARSNA; Havik et al., 2015); (2) analyze differences between school non-attendance profiles and Learned Helplessness (LH); and (3) establish the predictive and discriminative capacity of LH to identify students of the high school non-attendance profile. Consequently, 759 adolescents (M = 14.95, SD = 1.82) fulfilled ARSNA (Havik et al., 2015) and Learned Helplessness Questionnaire (LHQ; Sorrenti et al., 2015). Pearson’s correlation coefficients reported positive and statistically significant correlations between ARSNA dimensions and LH. Latent Profile Analyses revealed 3 school absenteeism profiles. ANOVA indicated statistically significant differences between these profiles and LH. Finally, Logistic Regression and ROC Curves found the predictive and discriminative ability of LH to identify individuals of the high school non-attendance profile. Results contribute to the literature on ARSNA dimensions and LH, highlighting the potential implications for schools and for the intervention against emotionally based school non-attendance.https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1557915/fulllearned helplessnessschool non-attendanceadolescentslatent profile analysisROC curves
spellingShingle María Pérez-Marco
Andrea Fuster
Carolina Gonzálvez
School non-attendance and learned helplessness: latent profiles and ROC curves
Frontiers in Psychology
learned helplessness
school non-attendance
adolescents
latent profile analysis
ROC curves
title School non-attendance and learned helplessness: latent profiles and ROC curves
title_full School non-attendance and learned helplessness: latent profiles and ROC curves
title_fullStr School non-attendance and learned helplessness: latent profiles and ROC curves
title_full_unstemmed School non-attendance and learned helplessness: latent profiles and ROC curves
title_short School non-attendance and learned helplessness: latent profiles and ROC curves
title_sort school non attendance and learned helplessness latent profiles and roc curves
topic learned helplessness
school non-attendance
adolescents
latent profile analysis
ROC curves
url https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1557915/full
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AT carolinagonzalvez schoolnonattendanceandlearnedhelplessnesslatentprofilesandroccurves