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IntroductionThe prevailing view is that loneliness predominantly affects older adults. However, awareness of high rates of loneliness among younger populations is growing, prompting a call for interventions. The current study aimed to listen to the voices of young people regarding how they cope with loneliness, gaining a better understanding of how to then develop tailored interventions.MethodsThirteen Arts-based focus groups were conducted with 74 participants (8-18 years old), in London, Manchester, and South Yorkshire. Reflexive thematic analysis was utilised.ResultsWe developed six themes as follows: (1) “Determinants of the coping approach for loneliness”, (2) “Considerations to guide decision making”, (3) “Coping strategies to alleviate loneliness”, (4) “Social connection as a coping strategy for loneliness – considerations”, (5) “Being active in your own coping success”, and (6) “Worsening loneliness, coping strategies gone wrong”.ConclusionsParticipants described a partially sequential process in choosing coping strategies for loneliness, including effective and maladaptive choices. Effective strategies were highlighted, reflecting developmental stages with the need for self-motivation. Participants noted challenges in engaging in coping due to skill deficits. These findings are crucial for developing interventions specific to this population.

Abstract Background Elevated loneliness experiences characterise young people. While loneliness at this developmental juncture may emerge from age‐typical upheaval in social relationships, there is little data on the extent to which young people experience high and persistent levels of loneliness, and importantly, who is most vulnerable to these experiences. Using the widespread social restrictions associated with the COVID‐19 pandemic, which precipitated loneliness in many, we aimed to examine adolescents' loneliness profiles across time and the demographic predictors (age, sex, and country) of more severe trajectories. Methods Participants aged 12–18 years, recruited into a multi‐wave study (N = 1039) across three sites (UK, Israel, and India) completed a 3‐item loneliness measure fortnightly across 8 timepoints during the pandemic. Results Latent class growth analysis suggested 5 distinct trajectories: (1) low stable (33%), (2) low increasing (19%), (3) moderate decreasing (17%), (4) moderate stable (23%), and (5) high increasing (8%). Females and older adolescents were more likely to experience persistently high loneliness. Conclusions These findings indicate a need for interventions to reduce loneliness in adolescents as we emerge from the pandemic, particularly for those groups identified as being at highest risk.

Loneliness is common in young people, yet there are few evidence-based interventions to manage youth loneliness. Understanding the ways in which young people cope with social isolation may inform the development of targeted loneliness programmes for young people. During the first year of the COVID-19 pandemic when social restrictions were at a peak, 2500 young people aged 12–25 years were asked to report freely on coping strategies that they would recommend to peers to manage isolation and loneliness. The coding of qualitative responses suggested that young people recommended a range of different coping strategies, which we grouped into categories: contact seeking, approach, distraction, self-care, self-talk, self-compassion, and gratitude. Regression analyses showed that age, sex and socioeconomic background were associated with recommendation of some of the coping strategies. Paradoxically, recommendation of self-compassion was associated with higher levels of loneliness, while recommendation of approach and self-talk was associated with higher levels of wellbeing. This study highlights the importance of exploring how young people manage loneliness, a complex process that involves various strategies and is associated with an individual's demographic characteristics.

Increasing global policy interest in measuring and improving population wellbeing has prompted academic investigations into the dynamics of lifespan life satisfaction. Yet little research has assessed the complete adolescent age range, although it harbours developmental changes that could affect wellbeing far into adulthood. This study investigates how life satisfaction develops throughout the whole of adolescence, and compares this development to that in adulthood, by applying exploratory and confirmatory latent growth curve modelling to UK and German data, respectively (37 076 participants, 10–24 years). We find a near universal decrease in life satisfaction during adolescence. This decrease is steeper than at any other point across adulthood. Further, our findings suggest that adolescent girls' life satisfaction is lower than boys’, but that this difference does not extend into adulthood. The study highlights the importance of studying adolescent subjective wellbeing trajectories to inform research, policy and practice.

Despite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N = 551 (N = 165 imaging), age range: 5–18 years, NKI-Rockland: N = 337 (N = 65 imaging), age range: 6–18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf) abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7–8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence. Keywords: Neurocognitive reorganization, Crystallized intelligence, Fluid intelligence, White matter, Structural equation modelling

Adolescence has been proposed to be a sensitive period of social development, during which the social environment has a heightened effect on brain and behaviour. As such, negative social experiences, such as social exclusion, may have particularly detrimental effects on psychological well-being. However, little is known about how social exclusion affects cognitive performance during this time of life. Here, we compared the effects of exclusion between adolescence and adulthood. We recruited 98 females in three age groups: young adolescents (N = 36, aged 10.1–14.0), mid-adolescents (N = 35, aged 14.3–17.9) and adults (N = 27, aged 18.3–38.1). All age groups showed reductions in mood after exclusion, compared to inclusion, in a virtual ball-tossing game. Young adolescents also showed reduced verbal working memory accuracy following exclusion. There was no effect of exclusion on visuo-spatial working memory in any age group. These results suggest young adolescent girls’ verbal working memory accuracy was affected by a short, virtual social exclusion experience. This highlights the importance of the social environment in adolescence and underlines the need to consider age differences in response to exclusion in the design and timing of social exclusion interventions in schools. Keywords: Cyberball, Sensitive period, Adolescence, n-back, Visuo-spatial working memory, Mood

Existing non-verbal ability tests are typically protected by copyright, preventing them from being freely adapted or computerized. Working towards an open science framework, we provide 80 novel, open-access abstract reasoning items, an online implementation and item-level data from 659 participants aged between 11 and 33 years: the matrix reasoning item bank (MaRs-IB). Each MaRs-IB item consists of an incomplete matrix containing abstract shapes. Participants complete the matrices by identifying relationships between the shapes. Our data demonstrate age differences in non-verbal reasoning accuracy, which increased during adolescence and stabilized in early adulthood. There was a slight linear increase in response times with age, resulting in a peak in efficiency (i.e. a measure combining speed and accuracy) in late adolescence. Overall, the data suggest that the MaRs-IB is sensitive to developmental differences in reasoning accuracy. Further psychometric validation is recommended.

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.