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Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis

INTRODUCTION: Disturbed sleep represents a potentially important modifiable risk factor for the development of depression in children and youth. This protocol for a systematic review proposes to investigate whether insomnia and/or sleep disturbances predict child and youth depression in community an...

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Autores principales: Marino, Cecilia, Andrade, Brendan, Aitken, Madison, Bonato, Sarah, Haltigan, John D, Wang, Wei, Szatmari, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462160/
https://www.ncbi.nlm.nih.gov/pubmed/32868348
http://dx.doi.org/10.1136/bmjopen-2019-034606
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author Marino, Cecilia
Andrade, Brendan
Aitken, Madison
Bonato, Sarah
Haltigan, John D
Wang, Wei
Szatmari, Peter
author_facet Marino, Cecilia
Andrade, Brendan
Aitken, Madison
Bonato, Sarah
Haltigan, John D
Wang, Wei
Szatmari, Peter
author_sort Marino, Cecilia
collection PubMed
description INTRODUCTION: Disturbed sleep represents a potentially important modifiable risk factor for the development of depression in children and youth. This protocol for a systematic review proposes to investigate whether insomnia and/or sleep disturbances predict child and youth depression in community and clinical-based samples. METHODS AND ANALYSIS: The protocol adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. English-written, longitudinal studies that quantitatively estimated the prediction of depression by insomnia and/or sleep disturbances in individuals 5–24 years of age will be included. EMBASE, MEDLINE, PsychINFO, Scopus and Web of Science and grey literature will be searched from 1980 to the present. For the selection of studies, two reviewers will be involved. Data extraction will be conducted by one author and checked independently by a second author. Risk of bias will be appraised using the Research Triangle Institute Item Bank tool. Heterogeneity will be measured using the I(2) statistics. Meta-analysis will be carried out if ≥3 results are available and if outcome measures can be pooled. The choice between a random-effect or fixed-effect model will be based both on the I(2) statistics and the participant and study characteristics of the combined studies. Results of the meta-analyses will be summarised by a forest plot. Analyses will be performed in subgroups stratified by key variables defined depending on the amount and type of information retrieved. A narrative synthesis will be conducted in place of the meta-analysis should the pooling of data not be possible. Quality of evidence will be rated using the Grading of Recommendations Assessment, Development and Evaluation guidelines. As this is a protocol for systematic review and meta-analysis of published data, ethics review and approval are not required. The findings will be published in a peer-reviewed journal and disseminated at scientific conferences and in patient advocacy organisations. PROSPERO REGISTRATION NUMBER: CRD42019136729.
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spelling pubmed-74621602020-09-11 Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis Marino, Cecilia Andrade, Brendan Aitken, Madison Bonato, Sarah Haltigan, John D Wang, Wei Szatmari, Peter BMJ Open Mental Health INTRODUCTION: Disturbed sleep represents a potentially important modifiable risk factor for the development of depression in children and youth. This protocol for a systematic review proposes to investigate whether insomnia and/or sleep disturbances predict child and youth depression in community and clinical-based samples. METHODS AND ANALYSIS: The protocol adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. English-written, longitudinal studies that quantitatively estimated the prediction of depression by insomnia and/or sleep disturbances in individuals 5–24 years of age will be included. EMBASE, MEDLINE, PsychINFO, Scopus and Web of Science and grey literature will be searched from 1980 to the present. For the selection of studies, two reviewers will be involved. Data extraction will be conducted by one author and checked independently by a second author. Risk of bias will be appraised using the Research Triangle Institute Item Bank tool. Heterogeneity will be measured using the I(2) statistics. Meta-analysis will be carried out if ≥3 results are available and if outcome measures can be pooled. The choice between a random-effect or fixed-effect model will be based both on the I(2) statistics and the participant and study characteristics of the combined studies. Results of the meta-analyses will be summarised by a forest plot. Analyses will be performed in subgroups stratified by key variables defined depending on the amount and type of information retrieved. A narrative synthesis will be conducted in place of the meta-analysis should the pooling of data not be possible. Quality of evidence will be rated using the Grading of Recommendations Assessment, Development and Evaluation guidelines. As this is a protocol for systematic review and meta-analysis of published data, ethics review and approval are not required. The findings will be published in a peer-reviewed journal and disseminated at scientific conferences and in patient advocacy organisations. PROSPERO REGISTRATION NUMBER: CRD42019136729. BMJ Publishing Group 2020-08-30 /pmc/articles/PMC7462160/ /pubmed/32868348 http://dx.doi.org/10.1136/bmjopen-2019-034606 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Mental Health
Marino, Cecilia
Andrade, Brendan
Aitken, Madison
Bonato, Sarah
Haltigan, John D
Wang, Wei
Szatmari, Peter
Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis
title Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis
title_full Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis
title_fullStr Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis
title_full_unstemmed Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis
title_short Do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? Protocol for a systematic review and meta-analysis
title_sort do insomnia and/or sleep disturbances predict the onset, relapse or worsening of depression in community and clinical samples of children and youth? protocol for a systematic review and meta-analysis
topic Mental Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462160/
https://www.ncbi.nlm.nih.gov/pubmed/32868348
http://dx.doi.org/10.1136/bmjopen-2019-034606
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