Sarah Bauermeister

Background: Social media use is ubiquitous among young people, yet its relationship with mental health may depend on why it is used. Understanding the motives underlying social media engagement may provide greater insights into its potential risks and benefits than considering overall use alone. Objective: This study aimed to identify latent dimensions of motives for social media use and examine their associations with anxiety, depression, well-being, and resilience in a sample of older adolescents. Methods: Cross-sectional data were drawn from the BrainWaves study (N=6820; mean age 16.72, SD 0.74 years). Social media use motives were assessed using 10 items and exploratory factor analysis identified 2 latent dimensions: avoidant-escapist use (boredom, addiction, distraction, and procrastination) and social-recreational use (socializing, communication, entertainment, and observation). Confirmatory factor analysis was used to estimate factor scores, which were examined using linear regression. Structural equation modeling estimated associations with anxiety, depression, well-being, and resilience, with secondary analyses accounting for gender and deprivation. Results: Linear regression analyses showed that avoidant-escapist motives were associated with higher anxiety and depressive symptoms, whereas social-recreational motives were associated with lower symptoms. No interactions with gender or deprivation were observed. The structural equation model showed acceptable model fit (comparative fit index=0.945; root mean squared error of approximation=0.057; standardized root mean squared residual=0.054). Avoidant-escapist motives were associated with higher anxiety (β=0.543) and depressive symptoms (β=0.629) and lower well-being (β=−0.610) and resilience (β=−0.469). Conversely, social-recreational motives were associated with lower anxiety (β=−0.228) and depressive symptoms (β=−0.342) and higher well-being (β=0.362) and resilience (β=0.242; P <.001 in all cases). These patterns remained consistent after accounting for gender and deprivation. Conclusions: Social media use shows different associations with older adolescent mental health depending on underlying motives. Focusing on why young people engage with social media rather than on overall use alone may provide a more informative framework for understanding potential risks and benefits. Given the cross-sectional design, causal inferences cannot be made.

Aims: Cross‐national research on mental health trajectories requires harmonised measures that are valid and comparable. However, measurement scales often differ between cohorts in item content and cultural context. This study aimed to develop a framework for harmonising mental health measures across international cohorts, focussing on depression and anxiety symptoms. Methods: We applied a structured, theory‐driven approach to align item content across two longitudinal ageing cohorts that used different self‐report instruments with heterogeneous item codings: ELSA‐UK and ELSA‐Brasil. Data were collected before, during, and after the COVID‐19 pandemic, providing a natural experiment for examining temporal changes in mental health. The harmonisation process involved: (1) mapping items to DSM‐5 symptom domains via expert review; (2) transforming response formats into harmonised ordinal indicators; (3) leveraging the Harmony AI tool to identify semantically equivalent items; and (4) testing measurement invariance across waves and cohorts using multi‐group confirmatory factor analysis (MGCFA). Results: Scalar invariance was achieved for depression in both longitudinal and cross‐cohort models, enabling meaningful latent mean comparisons between cohorts. For anxiety, scalar invariance was supported within but not across cohorts, likely due to the limited number of conceptually matching items. Conclusion: The proposed harmonisation framework demonstrates the feasibility of robust cross‐cultural comparisons of mental health constructs. Its success depends on the conceptual alignment and quality of available items. This approach provides a methodological template for future harmonisation efforts in global health and psychiatric epidemiology.

Neurological complications are among typical clinical manifestations, both during the acute phase of SARS-CoV-2 infection and long-term post-acute COVID-19 sequelae, i.e., Long COVID. A growing body of evidence connects SARS-CoV-2 infection to systemic inflammation, peripheral immune dysregulation, functional alteration of the blood–brain barrier (BBB), neuroinflammatory processes, mitochondrial dysfunction and pathological protein aggregation, all of which are central to the pathogenesis of major neurodegenerative diseases. In this review, we discuss the converging shared underlying molecular mechanisms that link the ‘acute’ SARS-CoV-2 infection that often only lasts for days and ‘chronic’ neurodegenerative diseases that often take decades to develop. We further review human induced pluripotent stem cells (iPSCs)-derived brain organoid and BBB models for Parkinson’s disease (PD) and Alzheimer’s disease (AD) as well as artificial intelligence (AI)-facilitated knowledge graph methods that are used to hypothesize and validate the potential mechanistic links. We propose that besides the established links between viral infections and neurodegenerative or neuroinflammatory conditions, such as Epstein-Barr virus (EBV) in multiple sclerosis or herpes zoster in AD, SARS-CoV-2 infection might be another important factor driving the future burden of the most common neurodegenerative diseases. Graphical Abstract Schematic illustrating the potential link between the progression from SARS-CoV-2 infection and immune dysregulation to the development of Long COVID and eventually the subsequent onset of major neurodegenerative diseases (e.g., Parkinson's disease and Alzheimer's disease).

Introduction: Multimorbidity clusters have been associated with increased dementia risk. While lifestyle factors may modify dementia risk, their role in multimorbidity clusters remains unclear. Method: Data from UK Biobank was used to identify clusters of chronic conditions using latent class analysis, assess their associations with dementia risk using Cox regression, and potential moderating effects of lifestyle factors. Results: We included 465,175 participants (mean age = 56.52 ± 8.01, 53.87 % female). Five clusters were identified and significantly associated with increased dementia risk, with the cardiometabolic (HR = 2.14, p < 0.001) and mental health cluster (HR =1.99, p < 0.001) exhibiting the highest risk. Only moderate physical activity lowered dementia risk in the pain-dominated multimorbidity cluster (HR = 0.77, p = 0.039). Discussion: Lifestyle factors including physical activity may protect against dementia in specific multimorbidity clusters. Future research involving objective and multiple lifestyle measures is needed.

Adolescence is characterised by rapid cognitive change representing a substantial increase in cognitive complexity and processing load. The transition to a digital society has further increased complexity and load, providing an explanation for increased levels of poor mental health in young people. The impact of social media platform use on mental health was investigated in a sample of 15,135 young people aged 16-19 years from 51 schools, across 31 UK Local Education Authorities, as part of the BrainWaves cohort.Social media use (hours per day) was marginally greater for girls (x̄ =4.1) than boys (x̄ =3.8). Of the 15 platforms investigated, 12 were related to duration of use (hours per day) in girls and 10 platforms in boys. The platform most strongly related to duration was TikTok (bgirls=1.34, bboys=0.97). Duration was associated with poor mental health (higher anxiety and depression scores) in both girls (b=0.29, p<0.001) and boys b=0.35, p<0.001). Non-duration-related platform-specific associations were also found.Whilst these data do not support a total social media ban for young people, they strengthen the case for limiting access, requiring platform design to promote emotional, cognitive and physical wellbeing, and educating young people to be better informed about social media use.

Importance: The impact of COVID-19 containment policies (e.g., physical distancing, school closures) on population anxiety has been debated and difficult to resolve. Objective: To estimate the joint effects of state-level COVID-19 containment policies on anxiety symptoms during the early pandemic. Design: Retrospective analysis of a prospective cohort with cross-sectional outcome assessment. Setting: All of Us Research Program, a U.S. national research cohort. Participants: 40,610 adult participants who completed the All of Us COPE survey in July 2020. Exposures: Seven state-level COVID-19 containment policies (school closures, workplace closures, cancellation of public events, restrictions on gatherings, public transport closures, stay-at-home requirements, and restrictions on internal movement) measured from March 22 to May 23, 2020, via the Oxford COVID-19 Government Response Tracker (OxCGRT). Main outcomes and measures: The primary outcome was anxiety symptoms (GAD-7) in July 2020. Using quantile g-computation, we classified policies as anxiety-increasing or anxiety-decreasing by the sign of their training-set contributions, then re-estimated joint effects in a holdout testing set. Results: Among participants (64% female; mean age: 57.8 years), 13.3% (n=5398) reported moderate-to-severe anxiety (GAD-7 score 10-21) in July 2020. The joint effect of all seven containment policies was not significant (β = 1.88, 95% CI: -0.51 to 4.28, p = 0.12). An anxiety-increasing joint effect from 4 policies (school, workplace, public events, internal movement; β = 2.98, 95% CI: 0.30 to 5.66, p = 0.03) and an anxiety-decreasing joint effect from 3 policies (gatherings, public transport, stay-at-home; β = -1.10, 95% CI: -1.75 to -0.44, p = 0.002) reached significance. Effects were largest in adults 18-44 (anxiety-increasing β = 8.93, 95% CI: 1.50 to 16.37, p = 0.02; anxiety-decreasing β = -2.81, 95% CI: -4.98 to -0.64, p = 0.01), with no significant effects in adults 45 and older. Conclusions and Relevance: Modeling seven containment policies jointly showed no net anxiety effect, a result that masked opposing-direction effects. Partitioning by effect direction revealed significant joint effects exceeding single-policy estimates, with young-adult point estimates above the 4-point GAD-7 minimal clinically important difference (MCID) though lower CI bounds fell below it. These findings may inform the use of containment policies in future pandemics, given their differing association with population anxiety.

Rationale. Childhood adversity can impair mental and physical health later in life, and these deleterious effects may depend on sensitive periods for child abuse during which children are particularly vulnerable. The purpose of this narrative review is to scope previous research on sensitive periods of child adversity that are linked with negative later life outcomes.Methods. Only peer-reviewed original research articles were included in the review. Relevant key information was extracted from the articles and themes were identified as repeated patterns of meaning-making that evolve around a similar interpretation of the research findings.Findings. From the scoped literature on sensitive periods for childhood adversity, three themes were identified: (1) The earlier the childhood adversity in life the worse, (2) There are two sensitive periods that correspond to periods of change in development: early childhood and early adolescence. (3) Sensitive periods for child adversity are domain-specific and depend on the aspect of impaired psychosocial functioning.Conclusions. Despite evidence for sensitive periods for child adversity, it is too early to describe normative, sensitive periods because previous findings were largely study-specific. More research is needed to investigate the impact of child abuse on various domains of psychosocial functioning later in life. More prospective, and longitudinal research is also needed because current findings are subject to retrospective memory bias. Overall, when child abuse occurred during the lifespan may be important information in optimising and personalising treatment options.

Background. Gender differences in neuroticism are well known, with females consistently scoring higher than males across various scales, including the Eysenck Personality Questionnaire-Revised Neuroticism (EPQ-RN) scale. However, it remains unclear whether these differences are genuine or result from gender bias in psychometric instruments. Additionally, the implications of a potential bias for the predictive validity of neuroticism are not well understood. Given the role of neuroticism in predicting cognitive performance, this study aimed to investigate gender-based differential item functioning (DIF) in the EPQ-RN and its effects on the association between neuroticism and cognition.Methods. Using data from 13,573 participants in the UK Biobank study, we conducted logistic regression DIF analyses on the EPQ-RN scale to identify gender-related item bias. Items were grouped into three constructs: bias-free, female-endorsed, and male-endorsed neuroticism. Cross-sectional linear regression and longitudinal structural equation modelling (SEM) were used to evaluate the association between neuroticism constructs and cognition, adjusting for age, gender, education, and depression.Results. Significant DIF was identified in 10 of 12 EPQ-RN items, with six preferentially endorsed by females. However, females also scored higher on bias-free neuroticism, indicating actual gender differences. In cross-sectional analyses, bias-free and female neuroticism were significantly associated with poorer cognitive performance at baseline, whereas the effect of male neuroticism was conditional on the covariates in the model. Longitudinal SEMs did not reveal significant cross-lagged effects, suggesting neuroticism at baseline did not predict cognitive performance at follow-up, irrespective of the type of neuroticism subscale: bias-free, female, or male. Conclusion. Findings reveal substantial gender-based DIF in the EPQ-RN scale, likely overestimating neuroticism scores in females. Yet, even after removing biased items, females still exhibited higher bias-free neuroticism, supporting the notion of genuine gender differences. Importantly, the validity of the neuroticism construct as a predictor of cognition did not depend on DIF, with similar findings for bias-free and gender-specific scales. These findings have implications for interpreting gender differences in cognitive aging, particularly when using widely adopted personality scales such as the EPQ-RN.Keywords: Neuroticism, cognition, longitudinal, gender effects, gender bias, epidemiological research, lifespan development, psychometrics, differential item functioning.

Background. There is a known association between education and subjective well-being. However, research found that higher levels of education were associated with both higher and lower levels of subjective well-being in various populations. These prima-facie counter-intuitive findings may arise because subjective well-being may be too broad a construct with a plethora of contributing factors. Furthermore, confounding variables may explain the putative association between education and subjective well-being, therefore necessitating a thorough adjustment thereof. Confounding variables comprise, inter alia, cardiometabolic health, socioeconomic factors, psychosocial lifestyle variables, and mental health.Objective. To investigate the effect of education on subjective well-being in the UK Biobank whilst controlling for confounding variables. To investigate differential effects of education on material life satisfaction and relationship satisfaction.Methods. Exploratory factor analysis was conducted to reveal the underlying factor structure of the UK Biobank happiness questionnaire. Serial regression analyses were performed to elucidate the association between education and subjective well-being whilst iteratively adding confounding variables into the model. Results. Education evinced a prima-facie counter-intuitive negative effect on subjective well-being. Exploratory factor analysis indicated that subjective well-being may be decomposed into material life satisfaction and relationship satisfaction. Education differentially affected these constructs; wherein higher levels of education were associated with more material life satisfaction but lower levels of relationship satisfaction, even after thorough adjustment of confounding variables. Conclusion. The effects of education on subjective well-being are complex with evidence for increased material satisfaction but reduced relationship satisfaction. The presupposition that subjective wellbeing can be adequately captured with a single construct has been shattered. Further research should investigate the effect of education on domains of subjective wellbeing rather than amalgamating domains into too broad a construct to be informative.

Background: Social media use is ubiquitous among adolescents, yet its relationship with mental health may depend on why it is used. This study distinguishes between avoidant-escapist and social-recreational motives for social media use and examines their associations with mental health, wellbeing, and resilience in a large cohort of UK schoolchildren.Methods: Cross-sectional data were drawn from the BrainWaves study (N = 6820, Mage = 16.72). Social media motives were assessed using 10 items and derived using exploratory factor analysis (EFA) into two latent factors: avoidant-escapist (boredom, addiction, distraction, procrastination) and social-recreational (socialising, communication, entertainment, observation) use. Confirmatory factor analysis (CFA) was used to estimate factor scores, which were examined in linear regression models. Structural equation modelling (SEM) was then applied to estimate associations with anxiety, depression, wellbeing, and resilience, adjusting for gender and deprivation.Results: In linear regression analyses, avoidant-escapist social media use was associated with higher anxiety and depressive symptoms, whereas social-recreational use was associated with lower levels of both outcomes. No interaction between gender and social media motives was observed. The SEM was a good fit to the data and showed that avoidant-escapist use was associated with higher anxiety and depressive symptoms, and lower wellbeing and resilience. In contrast, social-recreational use was associated with lower anxiety and depressive symptoms, and higher wellbeing and resilience. Conclusions: The associations between social media use and adolescent mental health differ by underlying motives. Avoidant-escapist use is linked to poorer outcomes, whereas social-recreational use is associated with more favourable outcomes. Focusing on why adolescents engage with social media, rather than overall use alone, is necessary for understanding risk and informing interventions. However, given the cross-sectional design, causality cannot be inferred, and associations may be bidirectional.