Exploring physical, subjective and psychological wellbeing profile membership in adolescents: a latent profile analysis.

Background: Understanding wellbeing in adolescents and within education settings is crucial to supporting young people. However, research defining and exploring wellbeing has typically taken a focus on subjective, psychological, social and emotional domains and has failed to incorporate aspects of physical health and wellbeing. This study aimed to explore how both physical and subjective and psychological wellbeing can be combined to generate different profiles of wellbeing in adolescents, and to understand the characteristics associated with this profile membership.

Adolescent loneliness across the world and its relation to school climate, national culture and academic performance.

Background: Loneliness during adolescence has adverse consequences for mental health, education and employment outcomes. Yet, we know little about common correlates of loneliness among adolescents, making intervention work difficult.

Aims: In this study, we (1) explore individual-, school- and country-level correlates of loneliness to help identify potential intervention targets, and (2) examine the influence of loneliness on academic performance.

Dual-Factor Mental Health from Childhood to Early Adolescence and Associated Factors: A Latent Transition Analysis.

The dual-factor model of mental health indicates the importance of simultaneously assessing symptoms and subjective wellbeing, but there is limited understanding of how dual-factor mental health changes during the transition from childhood to early adolescence and factors associated with change. The current study investigated dual-factor mental health over a 2-year period from when children were 8-9 years old to 10-11 years old (N = 2402; 48% female), using latent transition analysis. Further analyses determined whether sex and peer support were associated with initial mental health status or specific transitions during this period.

The Application of Latent Class Analysis for Investigating Population Child Mental Health: A Systematic Review.

Latent class analysis (LCA) can be used to identify subgroups of children with similar patterns of mental health symptoms and/or strengths. The method is becoming more commonly used in child mental health research, but there are reservations about the replicability, reliability, and validity of findings. A systematic literature review was conducted to investigate the extent to which LCA has been used to study population mental health in children, and whether replicable, reliable and valid findings have been demonstrated.