Latent Profile Analysis of Mental Health Among Children and Young Adults With Refugee Backgrounds

Abstract

<h3>Objective</h3><p>Children and young adults comprise a significant proportion of the world’s refugee population and are disproportionately negatively affected by the social determinants of health. This heterogeneous group faces high rates of poor mental health, yet research investigating within-group inequalities in mental health remains limited. We performed a latent profile analysis to explore classes of mental health based on posttraumatic stress symptoms (PTSS), general functioning, and well-being. This study aimed to improve the understanding of mental health differences, thereby providing better guidance for assessment and tailored interventions.</p><h3>Method</h3><p>This study involved 131 children and 127 young adults with refugee backgrounds (mean age 18.21 years, 44.6% female, 23.6% unaccompanied) recruited nationwide in Sweden (2019-2022). To examine classes and their predictors, latent profile analysis was conducted, followed by multinomial logistic regression analysis.</p><h3>Results</h3><p>Latent profile analysis identified four distinct classes: Good Mental Health (58.1%; low PTSS, good functioning and well-being); Severe Mental Distress (13.6%; high PTSS, low functioning and well-being); Moderate Mental Strain (12.4%; low PTSS, moderate functioning, low well-being); and Resilient (15.9%, high PTSS, good functioning, moderate well-being). Social determinants of health, such as being unaccompanied, asylum status, exposure to multiple types of violence, sexual victimization, and child maltreatment, distinguished the classes.</p><h3>Conclusion</h3><p>Children and young adults with refugee backgrounds can be categorized into classes based on clinically relevant mental health indicators. Focusing solely on those individuals at the highest risk for poor mental health may overlook many who are mentally healthy and those who need more targeted support. Future research should aim to replicate findings and to evaluate additional predictive factors at the family and societal levels.</p>