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. SAMPLE: A total of 518,210 students aged 15 years from 75 countries provided self-reported loneliness data. RESULTS: Using multilevel modelling, we found individual-, school- and country-level correlates of self-reported school-based loneliness, and showed that loneliness negatively influenced academic performance. CONCLUSIONS: Based on the findings, interventions that focus on enhancing social and emotional skills, increasing trust between teachers and students and changing school climate to be more inclusive are likely to be the most effective for adolescents; they should also be culturally sensitive.

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. Following class enumeration procedures, a 5-class model was selected at both timepoints. Classes were: (1) complete mental health, (2) vulnerable, (3) emotional symptoms but content, (4) conduct problems but content, and (5) troubled. Half of the sample changed mental health status during the study period. Sex and peer support were associated with specific mental health statuses and subsequent transitions. The findings have implications for mental health screening practice and identifying those in need of targeted interventions.

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

Background: 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. Objective: 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. Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A search of literature, published between January 1998 and December 2017, was carried out using MEDLINE, EMBASE, PsycInfo, Scopus, ERIC, ASSIA, and Google Scholar. A total of 2,748 studies were initially identified, of which 23 were eligible for review. The review examined the methods which studies had used to choose the number of mental health classes, the classes that they found, and whether there was evidence for the validity and reliability of the classes. Results: Reviewed studies used LCA to investigate both disparate mental health symptoms, and those associated with specific disorders. The corpus of studies using similar indicators was small. Differences in the criteria used to select the final LCA model were found between studies. All studies found meaningful or useful subgroups, but there were differences in the extent to which the validity and reliability of classes were explicitly demonstrated. Conclusions : LCA is a useful tool for studying and classifying child mental health at the population level. Recommendations are made to improve the application and reporting of LCA and to increase confidence in findings in the future, including use of a range of indices and criteria when enumerating classes, clear reporting of methods for replicability, and making efforts to establish the validity and reliability of identified classes.