Student- and School-Level Factors Associated With Mental Health and Well-Being in Early Adolescence.

OBJECTIVE: Adolescence is a key developmental window that may determine long-term mental health. As schools may influence mental health of students, this study aimed to examine the association of school-level characteristics with students' mental health over time. METHOD: Longitudinal data from a cluster randomized controlled trial comprising 8,376 students (55% female; aged 11-14 years at baseline) across 84 schools in the United Kingdom were analyzed. Data collection started in the academic years 2016/2017 (cohort 1) and 2017/2018 (cohort 2), with follow-up at 1, 1.5, and 2 years. Students' mental health (risk for depression [Center for Epidemiologic Studies Depression Scale], social-emotional-behavioral difficulties [Strength and Difficulties Questionnaire]) and well-being (Warwick-Edinburgh Mental Well-Being Scale) and relationships with student- and school-level characteristics were explored using multilevel regression models. RESULTS: Mental health difficulties and poorer well-being increased over time, particularly in girls. Differences among schools represented a small but statistically significant proportion of variation (95% CI) in students' mental health at each time point: depression, 1.7% (0.9%-2.5%) to 2.5% (1.6%-3.4%); social-emotional-behavioral difficulties, 1.9% (1.1%-2.7%) to 2.8% (2.1%-3.5%); and well-being, 1.8% (0.9%-2.7%) to 2.2% (1.4%-3.0%). Better student-rated school climate analyzed as a time-varying factor at the student and school level was associated with lower risk of depression (regression coefficient [95%CI] student level: -4.25 [-4.48, -4.01]; school level: -4.28 [-5.81, -2.75]), fewer social-emotional-behavioral difficulties (student level: -2.46 [-2.57, -2.35]; school level: -2.36 [-3.08, -1.63]), and higher well-being (student level: 3.88 [3.70, 4.05]; school-level: 4.28 [3.17, 5.38]), which was a stable relationship. CONCLUSION: Student-rated school climate predicted mental health in early adolescence. Policy and system interventions that focus on school climate may promote students' mental health.

Efficacy and moderators of efficacy of cognitive behavioural therapies with a trauma focus in children and adolescents: an individual participant data meta-analysis of randomised trials.

BACKGROUND: Existing clinical trials of cognitive behavioural therapies with a trauma focus (CBTs-TF) are underpowered to examine key variables that might moderate treatment effects. We aimed to determine the efficacy of CBTs-TF for young people, relative to passive and active control conditions, and elucidate putative individual-level and treatment-level moderators. METHODS: This was an individual participant data meta-analysis of published and unpublished randomised studies in young people aged 6-18 years exposed to trauma. We included studies identified by the latest UK National Institute of Health and Care Excellence guidelines (completed on Jan 29, 2018) and updated their search. The search strategy included database searches restricted to publications between Jan 1, 2018, and Nov 12, 2019; grey literature search of trial registries ClinicalTrials.gov and ISRCTN; preprint archives PsyArXiv and bioRxiv; and use of social media and emails to key authors to identify any unpublished datasets. The primary outcome was post-traumatic stress symptoms after treatment (<1 month after the final session). Predominantly, one-stage random-effects models were fitted. This study is registered with PROSPERO, CRD42019151954. FINDINGS: We identified 38 studies; 25 studies provided individual participant data, comprising 1686 young people (mean age 13·65 years [SD 3·01]), with 802 receiving CBTs-TF and 884 a control condition. The risk-of-bias assessment indicated five studies as low risk and 20 studies with some concerns. Participants who received CBTs-TF had lower mean post-traumatic stress symptoms after treatment than those who received the control conditions, after adjusting for post-traumatic stress symptoms before treatment (b=-13·17, 95% CI -17·84 to -8·50, p<0·001, τ2=103·72). Moderation analysis indicated that this effect of CBTs-TF on post-traumatic stress symptoms post-treatment increased by 0·15 units (b=-0·15, 95% CI -0·29 to -0·01, p=0·041, τ2=0·03) for each unit increase in pre-treatment post-traumatic stress symptoms. INTERPRETATION: This is the first individual participant data meta-analysis of young people exposed to trauma. Our findings support CBTs-TF as the first-line treatment, irrespective of age, gender, trauma characteristics, or carer involvement in treatment, with particular benefits for those with higher initial distress. FUNDING: Swiss National Science Foundation.

Minimising Young Children's Anxiety through Schools (MY-CATS): statistical analysis plan for a cluster randomised controlled trial to evaluate the effectiveness and cost-effectiveness of an online parent-led intervention compared with usual school practice for young children identified as at risk for anxiety disorders.

BACKGROUND: The Minimising Young Children's Anxiety through Schools (MY-CATS) trial is being conducted to determine whether an online evidence-based parent-guided cognitive behavioural therapy intervention in addition to usual school practice is effective and cost-effective compared with usual school practice in reducing anxiety disorders in children aged 4-7 deemed 'at risk' of anxiety disorders. This update article describes the detailed statistical analysis plan for the MY-CATS trial and reports a review of the underpinning sample size assumptions. METHODS AND DESIGN: The MY-CATS study is a two-arm, definitive superiority pragmatic parallel group cluster randomised controlled trial in which schools will be randomised 1:1 to receive either the intervention (in addition to usual school practice) or the usual school practice only. This update to the (published) protocol provides a detailed description of the study methods, the statistical principles, the trial population and the planned statistical analyses, including additional analyses comprising instrumental variable regression and mediation analysis. TRIAL REGISTRATION: ISRCTN82398107 . Prospectively registered on 14 January 2021.

Bayesian statistics in the design and analysis of cluster randomised controlled trials and their reporting quality: a methodological systematic review.

BACKGROUND: In a cluster randomised controlled trial (CRCT), randomisation units are "clusters" such as schools or GP practices. This has methodological implications for study design and statistical analysis, since clustering often leads to correlation between observations which, if not accounted for, can lead to spurious conclusions of efficacy/effectiveness. Bayesian methodology offers a flexible, intuitive framework to deal with such issues, but its use within CRCT design and analysis appears limited. This review aims to explore and quantify the use of Bayesian methodology in the design and analysis of CRCTs, and appraise the quality of reporting against CONSORT guidelines. METHODS: We sought to identify all reported/published CRCTs that incorporated Bayesian methodology and papers reporting development of new Bayesian methodology in this context, without restriction on publication date or location. We searched Medline and Embase and the Cochrane Central Register of Controlled Trials (CENTRAL). Reporting quality metrics according to the CONSORT extension for CRCTs were collected, as well as demographic data, type and nature of Bayesian methodology used, journal endorsement of CONSORT guidelines, and statistician involvement. RESULTS: Twenty-seven publications were included, six from an additional hand search. Eleven (40.7%) were reports of CRCT results: seven (25.9%) were primary results papers and four (14.8%) reported secondary results. Thirteen papers (48.1%) reported Bayesian methodological developments, the remaining three (11.1%) compared different methods. Four (57.1%) of the primary results papers described the method of sample size calculation; none clearly accounted for clustering. Six (85.7%) clearly accounted for clustering in the analysis. All results papers reported use of Bayesian methods in the analysis but none in the design or sample size calculation. CONCLUSIONS: The popularity of the CRCT design has increased rapidly in the last twenty years but this has not been mirrored by an uptake of Bayesian methodology in this context. Of studies using Bayesian methodology, there were some differences in reporting quality compared to CRCTs in general, but this study provided insufficient data to draw firm conclusions. There is an opportunity to further develop Bayesian methodology for the design and analysis of CRCTs in order to expand the accessibility, availability, and, ultimately, use of this approach.