Study identifies socioemotional wellbeing profiles among Chilean adolescents

A New Map of Adolescent Wellbeing Reveals Four Distinct Psychological Profiles in Chilean Students

Adolescent wellbeing may not exist on a single sliding scale from “healthy” to “struggling.” A study of 1,384 Chilean students has instead identified four distinct patterns of socioemotional wellbeing, suggesting that young people can combine psychological strengths and vulnerabilities in different ways. The findings, reported in Applied Research in Quality of Life, use a statistical technique called latent profile analysis to sort students into naturally occurring groups based on their overall patterns of covitality—the combined effect of several traits associated with mental health, wellbeing and positive adjustment at school. The researchers say the results could help schools move beyond one-size-fits-all mental-health programs and identify students who may need different kinds of support.

The study included students from fifth through ninth grades, spanning the transition from late childhood into early adolescence. Just over half of the participants, 52.4 percent, were female. Rather than calculating a single average wellbeing score for the entire sample, the research team examined how students’ responses clustered across multiple socioemotional indicators. This matters because two students with the same overall score could have very different psychological profiles: one might show broadly strong resources, while another could have pronounced strengths in some areas alongside serious difficulties in others. Covitality is designed to capture this interaction. It is a “meta-construct,” meaning that it describes the combined and potentially synergistic influence of several first-order characteristics rather than a single trait.

To detect these patterns, the researchers conducted a series of latent profile analyses, or LPA. In this person-centered method, the statistical model assumes that an unseen categorical variable—profile membership—helps explain the way observed scores are distributed. The analysis compares solutions with different numbers of groups and evaluates which one best represents the data without creating unnecessary complexity. Each student is assigned a probability of belonging to every profile, with the final classification generally reflecting the group for which that probability is highest. Unlike a simple ranking, LPA is intended to reveal configurations of characteristics: groups of students whose wellbeing indicators rise and fall together in recognizably different ways.

The analysis produced an optimal four-class solution. The profiles formed an ordered range from low-risk to high covitality, indicating that the groups differed in their overall level of socioemotional wellbeing as well as in the pattern of strengths represented by the measures. The researchers describe the four classes as distinct across all of the covitality dimensions assessed in the study. The result does not mean that every young person fits neatly into one permanent category, nor does it establish that psychological wellbeing progresses through four fixed stages. Instead, the profiles offer a snapshot of statistically distinguishable patterns within this particular group of students. Because the study is based on observed associations, the categories should be understood as tools for identifying needs, not as diagnoses.

The profiles also differed according to sex and age. The source material does not report the detailed size or composition of each class in the abstract, but it states that all four profiles showed differences by these demographic characteristics. Such variation is important because adolescence is a period of rapid social, emotional and developmental change. Wellbeing can shift as students encounter new academic expectations, changing peer relationships and increasing pressure to define their identity. A group-level average may conceal those differences, while a profile-based approach can show whether particular combinations of strengths and difficulties are more common at different ages or among different groups of students. The findings do not, however, demonstrate that sex or age causes a particular wellbeing pattern.

Bullying behavior was another factor associated with the four profiles. Students in the different covitality groups differed in their reported bullying experiences or behaviors, linking the psychological-strength patterns to the social environment of school. The study’s design does not establish whether bullying lowers covitality, whether lower covitality increases vulnerability to involvement in bullying, or whether both are shaped by broader conditions such as school climate, peer networks or family circumstances. That distinction is crucial. Bullying is not simply an individual problem that can be solved by strengthening a student’s personal coping skills. Effective prevention may also require changes in supervision, school norms, reporting systems, peer dynamics and adult responses. Still, identifying how bullying involvement aligns with different socioemotional profiles could help schools target prevention more precisely.

Life satisfaction likewise varied across the four classes. In adolescent research, life satisfaction generally refers to a young person’s global evaluation of how well life is going, rather than a temporary mood or a measure of clinical symptoms. It can reflect experiences at home, school and among peers, as well as a student’s expectations and sense of personal competence. By examining life satisfaction alongside covitality, the researchers connected internal psychological resources with a broad indicator of subjective wellbeing. Students with stronger, more integrated socioemotional profiles tended to occupy a different position on this measure than students in lower-covitality groups, according to the study. Yet the cross-sectional findings cannot show whether improving socioemotional skills would directly raise life satisfaction.

The practical promise of the research lies in its potential use as an early-warning and prevention framework. A universal school screening program could theoretically identify students with broadly strong resources, students with intermediate or uneven patterns, and those showing a high-risk configuration. Educators and mental-health professionals could then combine universal support with more specific interventions instead of treating all students as though they faced identical challenges. A student experiencing bullying may need safety planning and a coordinated school response; another with low life satisfaction may benefit from support involving family relationships, school attachment or emotional skills; a student with high strengths might be encouraged to act as a positive peer influence. The study does not test any intervention, so these applications remain implications rather than proven outcomes.

The researchers emphasize that the findings are intended to inform prevention programs and tailored interventions for Chilean students. The work was supported by Chile’s ANID FONDECYT Regular program and the Universidad del Desarrollo, with additional support for Daniel Miranda from the Center of Social Conflict and Cohesion Studies and the Millennium Nucleus on Inequalities and Digital Opportunities. Ethical approval was obtained from the Universidad del Desarrollo, and the procedures were reported to follow the Declaration of Helsinki. The data are available from the authors upon reasonable request. Taken together, the study’s central message is that adolescent wellbeing is multidimensional: understanding how psychological strengths co-occur may reveal needs that disappear when every student is reduced to a single score. The four-profile map is not a final verdict on young people’s mental health, but it offers a more detailed starting point for finding support before difficulties become entrenched.