School-based mindfulness training in early adolescence: what works, for whom and how in the MYRIAD trial?

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Abstract

Background

Preventing mental health problems in early adolescence is a priority. School-based mindfulness training (SBMT) is an approach with mixed evidence.

Objectives

To explore for whom SBMT does/does not work and what influences outcomes.

Methods

The My Resilience in Adolescence was a parallel-group, cluster randomised controlled trial (K=84 secondary schools; n=8376 students, age: 11–13) recruiting schools that provided standard social–emotional learning. Schools were randomised 1:1 to continue this provision (control/teaching as usual (TAU)), and/or to offer SBMT (‘.b’ (intervention)). Risk of depression, social–emotional–behavioural functioning and well-being were measured at baseline, preintervention, post intervention and 1 year follow-up. Hypothesised moderators, implementation factors and mediators were analysed using mixed effects linear regressions, instrumental variable methods and path analysis.

Findings

SBMT versus TAU resulted in worse scores on risk of depression and well-being in students at risk of mental health problems both at post intervention and 1-year follow-up, but differences were small and not clinically relevant. Higher dose and reach were associated with worse social–emotional–behavioural functioning at postintervention. No implementation factors were associated with outcomes at 1-year follow-up. Pregains−postgains in mindfulness skills and executive function predicted better outcomes at 1-year follow-up, but the SBMT was unsuccessful to teach these skills with clinical relevance.

SBMT as delivered in this trial is not indicated as a universal intervention. Moreover, it may be contraindicated for students with existing/emerging mental health symptoms.

Clinical implications

Universal SBMT is not recommended in this format in early adolescence. Future research should explore social−emotional learning programmes adapted to the unique needs of young people.

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Most cited references 30

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Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods.

David P. MacKinnon, Chondra Lockwood, Jason Henry Williams (2004)

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.

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When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts

Janus Jakobsen, Christian Gluud, Jørn Wetterslev … (2017)

Background Missing data may seriously compromise inferences from randomised clinical trials, especially if missing data are not handled appropriately. The potential bias due to missing data depends on the mechanism causing the data to be missing, and the analytical methods applied to amend the missingness. Therefore, the analysis of trial data with missing values requires careful planning and attention. Methods The authors had several meetings and discussions considering optimal ways of handling missing data to minimise the bias potential. We also searched PubMed (key words: missing data; randomi*; statistical analysis) and reference lists of known studies for papers (theoretical papers; empirical studies; simulation studies; etc.) on how to deal with missing data when analysing randomised clinical trials. Results Handling missing data is an important, yet difficult and complex task when analysing results of randomised clinical trials. We consider how to optimise the handling of missing data during the planning stage of a randomised clinical trial and recommend analytical approaches which may prevent bias caused by unavoidable missing data. We consider the strengths and limitations of using of best-worst and worst-best sensitivity analyses, multiple imputation, and full information maximum likelihood. We also present practical flowcharts on how to deal with missing data and an overview of the steps that always need to be considered during the analysis stage of a trial. Conclusions We present a practical guide and flowcharts describing when and how multiple imputation should be used to handle missing data in randomised clinical. Electronic supplementary material The online version of this article (10.1186/s12874-017-0442-1) contains supplementary material, which is available to authorized users.

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Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies

Marco Solmi, Joaquim Radua, Miriam Olivola … (2021)

Promotion of good mental health, prevention, and early intervention before/at the onset of mental disorders improve outcomes. However, the range and peak ages at onset for mental disorders are not fully established. To provide robust, global epidemiological estimates of age at onset for mental disorders, we conducted a PRISMA/MOOSE-compliant systematic review with meta-analysis of birth cohort/cross-sectional/cohort studies, representative of the general population, reporting age at onset for any ICD/DSM-mental disorders, identified in PubMed/Web of Science (up to 16/05/2020) (PROSPERO:CRD42019143015). Co-primary outcomes were the proportion of individuals with onset of mental disorders before age 14, 18, 25, and peak age at onset, for any mental disorder and across International Classification of Diseases 11 diagnostic blocks. Median age at onset of specific disorders was additionally investigated. Across 192 studies (n = 708,561) included, the proportion of individuals with onset of any mental disorders before the ages of 14, 18, 25 were 34.6%, 48.4%, 62.5%, and peak age was 14.5 years (k = 14, median = 18, interquartile range (IQR) = 11–34). For diagnostic blocks, the proportion of individuals with onset of disorder before the age of 14, 18, 25 and peak age were as follows: neurodevelopmental disorders: 61.5%, 83.2%, 95.8%, 5.5 years (k = 21, median=12, IQR = 7–16), anxiety/fear-related disorders: 38.1%, 51.8%, 73.3%, 5.5 years (k = 73, median = 17, IQR = 9–25), obsessive-compulsive/related disorders: 24.6%, 45.1%, 64.0%, 14.5 years (k = 20, median = 19, IQR = 14–29), feeding/eating disorders/problems: 15.8%, 48.1%, 82.4%, 15.5 years (k = 11, median = 18, IQR = 15–23), conditions specifically associated with stress disorders: 16.9%, 27.6%, 43.1%, 15.5 years (k = 16, median = 30, IQR = 17–48), substance use disorders/addictive behaviours: 2.9%, 15.2%, 48.8%, 19.5 years (k = 58, median = 25, IQR = 20–41), schizophrenia-spectrum disorders/primary psychotic states: 3%, 12.3%, 47.8%, 20.5 years (k = 36, median = 25, IQR = 20–34), personality disorders/related traits: 1.9%, 9.6%, 47.7%, 20.5 years (k = 6, median = 25, IQR = 20–33), and mood disorders: 2.5%, 11.5%, 34.5%, 20.5 years (k = 79, median = 31, IQR = 21–46). No significant difference emerged by sex, or definition of age of onset. Median age at onset for specific mental disorders mapped on a time continuum, from phobias/separation anxiety/autism spectrum disorder/attention deficit hyperactivity disorder/social anxiety (8-13 years) to anorexia nervosa/bulimia nervosa/obsessive-compulsive/binge eating/cannabis use disorders (17-22 years), followed by schizophrenia, personality, panic and alcohol use disorders (25-27 years), and finally post-traumatic/depressive/generalized anxiety/bipolar/acute and transient psychotic disorders (30-35 years), with overlap among groups and no significant clustering. These results inform the timing of good mental health promotion/preventive/early intervention, updating the current mental health system structured around a child/adult service schism at age 18.

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Author and article information

Journal

Journal ID (nlm-ta): Evid Based Ment Health

Journal ID (iso-abbrev): Evid Based Ment Health

Journal ID (hwp): ebmental

Journal ID (publisher-id): ebmh

Title: Evidence-Based Mental Health

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Print): 1362-0347

ISSN (Electronic): 1468-960X

Publication date (Print): August 2022

Publication date (Electronic): 7 July 2022

Volume: 25

Issue: 3

Pages: 117-124

Affiliations

[1 ] departmentDepartment of Psychiatry , Warneford Hospital, University of Oxford , Oxford, UK

[2 ] departmentTeaching, Reseach and Innovation Unit , Parc Sanitari Sant Joan de Déu , Sant Boi de Llobregat, Spain

[3 ] departmentNIHR Applied Research Collaboration (PenARC) South West Peninsula , University of Exeter , Exeter, UK

[4 ] departmentDepartment of Psychology , University of Cambridge , Cambridge, UK

[5 ] UCL Institute of Cognitive Neuroscience , London, UK

[6 ] King’s College London, King’s Health Economics, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park , London, UK

[7 ] departmentMedical Research Council Cognition and Brain Sciences Unit , University of Cambridge , Cambridge, UK

[8 ] departmentDepartment of Psychiatry , University of Cambridge , Cambridge, UK

[9 ] departmentDepartment of Human Development and Family Studies , Pennsylvania State University , University Park, Philadelphia, Pennsylvania, USA

Author notes

[Correspondence to ] Professor Willem Kuyken, University of Oxford Department of Psychiatry, Oxford, UK; willem.kuyken@ 123456psych.ox.ac.uk

S-JB, SB, TD, TF, MTG, OCU, JMGW and WK are joint senior authors.

Author information

Jesus Montero-Marin http://orcid.org/0000-0001-5677-1662

Susan Ball http://orcid.org/0000-0002-9937-4832

Willem Kuyken http://orcid.org/0000-0002-8596-5252

Article

Publisher ID: ebmental-2022-300439

DOI: 10.1136/ebmental-2022-300439

PMC ID: 9340034

PubMed ID: 35820993

SO-VID: d04f9511-ab78-4b07-85e8-ed6640b3082b

License:

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

History

Date received : 03 February 2022

Date accepted : 16 May 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome Trust;

Award ID: WT104908/Z/14/Z

Award ID: WT107496/Z/15/Z

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ScienceOpen disciplines: Clinical Psychology & Psychiatry

Keywords: school-based mindfulness training,preventive medicine,mental health,adolescence,process evaluation,moderation,implementation,mediation

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ScienceOpen disciplines: Clinical Psychology & Psychiatry

Keywords: school-based mindfulness training, preventive medicine, mental health, adolescence, process evaluation, moderation, implementation, mediation

School-based mindfulness training in early adolescence: what works, for whom and how in the MYRIAD trial?

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Abstract

Background

Objectives

Methods

Findings

Clinical implications

Related collections

Hogrefe Psychology

Most cited references 30

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods.

When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts

Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies

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