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Volume 16
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10.3390/bs16060852
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Article

Uncovering Motivational Profiles Among Academically Resilient Students: A Population-Level Latent Profile Analysis

by
Michele Zacchilli
1,
Giulia Raimondi
2,*,
Sara Manganelli
1,
Elisa Cavicchiolo
3,
Tommaso Palombi
4,
James Dawe
5,
Barbara Cazzolli
1,6,
Fabio Lucidi
1 and
Fabio Alivernini
1
1
Department of Social and Developmental Psychology, University of Rome “La Sapienza”, Via dei Marsi 78, 00185 Rome, Italy
2
BeSSA Department, Wellbeing, Health and Environmental Sustainability, University of Rome “La Sapienza”, Via delle Fontanelle, 02100 Rieti, Italy
3
Department of Systems Medicine, Tor Vergata University of Rome, Via Montpellier 1, 00133 Rome, Italy
4
Department of Dynamic and Clinical Psychology and Health Studies, University of Rome “La Sapienza”, Via degli Apuli 1, 00185 Rome, Italy
5
Department of Humanities and Social Sciences, Universitas Mercatorum Telematic University, Piazza Mattei 10, 00186 Rome, Italy
6
Department of Statistics, Computer Science, Applications (DiSIA), University of Florence, Viale Giovanni Battista Morgagni 59, 50134 Firenze, Italy
*
Author to whom correspondence should be addressed.
Behav. Sci. 2026, 16(6), 852; https://doi.org/10.3390/bs16060852
Submission received: 25 March 2026 / Revised: 15 May 2026 / Accepted: 21 May 2026 / Published: 26 May 2026
(This article belongs to the Special Issue Stress and Resilience in Adolescence and Early Adulthood)
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Abstract

Academically resilient students achieve high performance despite socioeconomic disadvantages. Although this population has received increasing attention, little is known about its motivational heterogeneity, a critical gap given the central role of motivation in persistence and success. Guided by Self-Determination Theory (SDT), this study examined motivational profiles among a population of academically resilient 10th-grade students in Italy (N = 15,751). Using a person-centered approach, Latent Profile Analysis (LPA) identified three profiles: a “multifaceted regulation resilient” profile (72%), marked by low amotivation and high levels across regulations; a “moderately amotivated resilient” profile (21%), with higher amotivation and lower levels of regulation; and a “strongly amotivated resilient” profile (7%), characterized by the highest amotivation and the lowest levels of regulation. Auxiliary analyses indicated that the amotivated profiles, particularly the “strongly amotivated resilient” profile, exhibited higher school dropout intentions than the “multifaceted regulation resilient” profile. Overall, although the majority of academically resilient students displayed multiple coexisting forms of regulation, a non-negligible subgroup showed significant motivational vulnerability, with amotivation emerging as a central risk factor. These findings challenge the assumption that academic resilience is sufficient to protect students from motivational disengagement and dropout risk. High academic achievement, in other words, should not be taken to imply the absence of motivational concerns. This highlights the importance of moving beyond a one-size-fits-all approach, recognizing that even within resilient populations, specific subgroups remain motivationally vulnerable and in need of tailored support.
Keywords: resilient students; motivation; school dropout; latent profile analysis; LPA; Self-Determination Theory; SDT; amotivation; high school students resilient students; motivation; school dropout; latent profile analysis; LPA; Self-Determination Theory; SDT; amotivation; high school students

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MDPI and ACS Style

Zacchilli, M.; Raimondi, G.; Manganelli, S.; Cavicchiolo, E.; Palombi, T.; Dawe, J.; Cazzolli, B.; Lucidi, F.; Alivernini, F. Uncovering Motivational Profiles Among Academically Resilient Students: A Population-Level Latent Profile Analysis. Behav. Sci. 2026, 16, 852. https://doi.org/10.3390/bs16060852

AMA Style

Zacchilli M, Raimondi G, Manganelli S, Cavicchiolo E, Palombi T, Dawe J, Cazzolli B, Lucidi F, Alivernini F. Uncovering Motivational Profiles Among Academically Resilient Students: A Population-Level Latent Profile Analysis. Behavioral Sciences. 2026; 16(6):852. https://doi.org/10.3390/bs16060852

Chicago/Turabian Style

Zacchilli, Michele, Giulia Raimondi, Sara Manganelli, Elisa Cavicchiolo, Tommaso Palombi, James Dawe, Barbara Cazzolli, Fabio Lucidi, and Fabio Alivernini. 2026. "Uncovering Motivational Profiles Among Academically Resilient Students: A Population-Level Latent Profile Analysis" Behavioral Sciences 16, no. 6: 852. https://doi.org/10.3390/bs16060852

APA Style

Zacchilli, M., Raimondi, G., Manganelli, S., Cavicchiolo, E., Palombi, T., Dawe, J., Cazzolli, B., Lucidi, F., & Alivernini, F. (2026). Uncovering Motivational Profiles Among Academically Resilient Students: A Population-Level Latent Profile Analysis. Behavioral Sciences, 16(6), 852. https://doi.org/10.3390/bs16060852

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