Effects of Pollution on Child and Adolescent Mental Health: A Protocol for a Systematic Review

doi:10.21203/rs.3.rs-27661/v1

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Effects of Pollution on Child and Adolescent Mental Health: A Protocol for a Systematic Review

https://doi.org/10.21203/rs.3.rs-27661/v1

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Background

Whilst there is little uncertainty about the deleterious impact of pollution on human and planetary health, pollution’s impact on child and adolescent mental health is less well understood. This is particularly true for young people in underdeveloped and developing world contexts, about whom research is generally lacking. Furthermore, although child and adolescent resilience continues to be a research priority, little attention has been paid to child and adolescent pathways of resilience in the face or aftermath of pollution exposure.

Methods

We will conduct a systematic review that adheres to PRISMA guidelines. Its purpose is to document what is known about how pollution affects child and adolescent mental health, along with what protects children and adolescents against these effects and associations across diverse contexts.

Discussion

Systematic insights are likely to support psychologists and other mental health practitioners to better support child and adolescent wellbeing globally regardless of exposure to pollution. Systematic review registration We have registered the review protocol in PROSPERO (registration: CRD42020176664).

Psychology

Pediatrics

Health Economics & Outcomes Research

Narrative synthesis

mental wellbeing

mental disorder

pollution-associated risks

resilience

systematic review protocol

Across the globe, human activity has resulted in widespread emissions that are harmful to the earth and its inhabitants¹. In the past century, there have been dramatic increases in chemical pollutants—including plastics, heavy metals, pesticides, building materials, antibiotics, and synthetic hormones—in our air, water, and soil², as well as increases in the noise to which we are exposed³. The harmful physical health sequalae of these emissions are well-recognised^4–5. In comparison, understanding of the mental health effects of pollution is emergent^6–8, particularly when it comes to impacts on children and adolescents^9–10. The under-attention to pollution’s potential mental health effects is problematic, not least because much of the global burden of disease is attributable to mental illness¹¹.

Similarly concerning is the fact that half of all mental disorders are thought to have commenced by the time children reach early adolescence¹². Onset in childhood or adolescence is associated with 10 times the expense of disorders with later onset¹³. Moreover, poor child and adolescent mental health predicts constrained child and adolescent development along with long-term diminished cognitive, psychological and behavioural capacities^14–15. These concerns beg systematic attention to the mental health of children and adolescents, with specific consideration of those who are exposed to pollution. This attention must be inclusive of children and adolescents in low- and middle-income countries (LMICs), given that 85% of the world’s children and adolescents reside in LMICs¹⁶ and the understanding that they may be disproportionately impacted by exposure to pollution¹. To understand the cellular and molecular mechanisms underlying effects of pollution, it is also important to consider the state of the evidence for both animal and human models, rather than solely focusing on humans¹⁷. Causal pathways of the impacts of different pollutants can be established through animal experimental work. Without such a comprehensive understanding, it would be difficult to pinpoint knowledge gaps or effect implementation science aimed at meaningfully supporting the mental health of children and adolescents exposed to pollution.

Further, consideration of child and adolescent mental health should not omit the factors and processes that enable or sustain mental health¹⁸, including when young people are exposed to adverse life experiences or circumstances¹⁹. Whilst young people’s capacity to maintain positive mental health despite exposure to risk is well-researched²⁰, there is limited understanding of the resilience processes that protect child and adolescent mental health specifically during and/or following exposure to environmental pollution²¹. Because resilience processes are multi-systemic and sensitive to developmental, situational, and cultural determinants²², it will be important to ascertain what facilitates child and adolescent resilience to pollution exposure across diverse contexts and highlight contextually relevant resilience-enablers.

Objectives

Taken together, the abovementioned concerns prompt our interest in what is currently known about the associations between pollution and child and adolescent mental health worldwide. This interest is framed by a social ecological perspective of resilience (i.e., the understanding that positive human adaptation to significant risk, such as pollution, is a dynamic and contextually responsive process)²³. Accordingly, the purpose of the proposed review is to systematically synthesize what is known about how pollution impacts child and adolescent mental health, along with what protects children and adolescents against these effects across diverse contexts. To this end, the following questions guide the proposed systematic review:

What is the global extent and focus of published and indexed empirical research on pollution and child and adolescent mental health, including which pollutants and associated mental health outcomes are most frequently investigated?
What does empirical research on pollution and child and adolescent mental health reveal about factors or processes that enable child and adolescent mental health despite exposure to pollution?

The key terms in our guiding questions include:

Pollution

Following the European Union’s²⁴ definition, pollution is understood as “the direct or indirect introduction, as a result of human activity, of substances, vibrations, heat or noise into air, water or land which may be harmful to human health or the quality of the environment” (p. 6).

Child and adolescent

The term “child and adolescent” includes young people from conception to 24 years of age²⁵.

Child and adolescent mental health

For children and adolescents, mental health implies no or limited indication of: (i) neurodevelopmental disorders (e.g., intellectual disability, communication disorders, autism spectrum disorder, attention-deficit and/or hyperactivity disorder, or specific learning disorders); (ii) disruptive, impulse-control, and conduct disorders; (iii) depressive disorders; (iv) anxiety disorders; or (v) substance disorders²⁶ (Rey, 2015). Lee et al.¹³also include schizophrenia in typical adolescent-onset disorders. All these disorders are recognized by the 5^th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM–5^TR)²⁷. The DSM–5^TR guides practitioner support of mental health.

If the 2020 PRISMA guidelines²⁸ are not available shortly, then the 2009 PRISMA guidelines²⁹ will inform our systematic review. The development of this protocol was informed by Moher et al.³⁰ and Shamseer et al.³¹ This review protocol has been registered in PROSPERO (CRD42020176664).

Eligibility criteria

Regarding study characteristics, only original studies (human or animal) will be included. The human studies are inclusive of foetuses (i.e., conception to birth), children (i.e., new-born to nine years of age), and adolescents (i.e., 10 to 24 years; see Sawyer et al.²⁵) from any country. The animal studies are inclusive of animals exposed to pollutants at the same developmental stages. In instances where the same data set is reported in multiple articles, the article that provides the clearest evidence of pollution impacts on/associations with child and adolescent mental health will be included. Studies will be excluded if:

reference to pollution or mental health is tangential (e.g., only in the introduction or recommendations);
mental health was not formally measured (e.g., through a clinical interview, scale/checklist, self- or caregiver-report, animal behaviour task, or biomarker [animal studies only]);
intervention is the focus (e.g., interventions designed to reduce pollution); or
solvents or pesticides are reported in relation to using these for suicide or substance-abuse.

Regarding report characteristics, only peer-reviewed, indexed journal articles (published and pre-print, on-line) will be included. To fit the profile of the reviewer team, publications in languages other than Cantonese, English, Mandarin, Portuguese, or Spanish will be excluded.

Information sources

Peer-reviewed articles, published on or before 10 April 2020, will be retrieved using the following databases: Africa-Wide, CINAHL, PsycARTICLES, PsycINFO (all via EBSCOhost platform); Medline (via Web of Science Clarivate Analytics); PubMed; Scopus (which includes contents of Embase); Web of Science Core Collection; SciELO Citation Index; and ERIC. The database search will be supplemented by a manual search of the reference lists of well-cited articles identified in the database search. The reviewer team (of which researchers from the Global South comprise the majority) will be sensitive to the inclusion of indexed Global South studies given their historic under-representation in scholarly literature³².

Search strategy

In order to identify relevant article publications, the search strategy listed in Table 1 will be followed. It was developed by author LS1, a librarian working in South Africa, and tested by LS2, a research assistant working in the United Kingdom. The search will be limited to the title, abstract, and topic fields for the databases that allow this limiting.

Study records

Data management

Articles meeting the search strategy will be populated into EndNote and then exported to Zotero to annotate (i.e., to formulate as citations that include the title and abstract).

Selection process

Annotated citations containing the search terms in the title and/or abstract will be independently screened for eligibility by 11 reviewers (LT, YAV, CB, MECL, GPA, MAO, LG, LL, IM, AT, KH). Initially, the first 50 titles and abstracts will be independently screened by all 11 reviewers to determine the clarity of the inclusion/exclusion criteria. Once the criteria have been refined (if/as necessary), the remaining annotated citations will be randomly divided into five sets. Each set will be independently reviewed by groups of 2 reviewers (with one group of 3, due to the odd number). Each of these groups includes at least one reviewer from the Global South. Those articles that meet the inclusion criteria and to which the exclusion criteria do not apply—as well as those where this information is not clear from the title or abstract—will be selected for a full text review. Consensus discussions (see Saldana³³) will be used to resolve any disagreements regarding article selection for full assessment. Should consensus not be reached, LT or KH will evaluate the disputed citation.

Data collection process

The same 11 reviewers will extract relevant data from the identified articles. Reviewers will again work as five groups. Identified articles will be divided between the groups. Within groups, reviewers will independently extract data from the articles assigned to that group. Data extraction will be guided by a data-charting form that will be developed by LT and KH and calibrated by all reviewers (using 10 of the identified articles). The data-charting form will correspond to the items for which data will be sought (see data items). Once a reviewer group has reached consensus on the accuracy of the extracted information, another reviewer group will verify the data extracted from 10% of the completed group’s articles.

Data items

We will extract data for the following categories of information: study descriptors [country context; design/methods (including how mental health was measured); sample (size, age range of human participants or animal subjects, sex of participants/subjects); study limitations]; pollution factors [type, level/intensity, duration of exposure]; and factors/processes that enable/sustain child and adolescent mental health despite exposure to pollution.

Outcomes and prioritization

We will extract data that relate to mental health outcomes in the face or aftermath of exposure to pollution. This includes data relating to symptoms of: (i) neurodevelopmental disorders (e.g., intellectual disability, communication disorders, autism spectrum disorder, attention-deficit and/or hyperactivity disorder, or specific learning disorders); (ii) disruptive, impulse-control, and conduct disorders; (iii) depressive disorders; (iv) anxiety or post-traumatic stress disorders; (v) substance disorders; or schizophrenia. Where possible, the extent of symptoms (e.g., no, limited/mild, severe) will be noted too.

Rigour and risk of bias in individual studies

Three review authors will independently assess the risk of bias in the included quantitative studies by considering the following characteristics³⁴: 1. Completeness of data: were participant exclusions, attrition, and incomplete data adequately addressed in the published report? 2. Selective reporting: is there evidence of selective reporting of analyses (quantitative studies) and might this have affected the published results? 3. Reliability and validity: do the included measures have internal consistency? Have measures used been validated for use in the populations or languages in which they were administered? 4. Participant selection: were the participants sampled in such a way that the results of the study can be generalized to the population? To assess risk of bias in animal studies, SYRCLE’s risk of bias tool for animal studies³⁵ will be applied by three review authors with animal study expertise. SYRCLE’s tool is similar to the Cochrane risk of bias tool specific to randomized control trials.

There is little consensus on which quality appraisal tool is preferred for judging the rigour of qualitative studies and so the decision is generally informed by the objective of the systematic review and reviewer experience with qualitative methodologies³⁶. Given that the author team includes experienced qualitative researchers and that the eligible qualitative studies are likely to include a broad range of qualitative methodologies, the Standards for Reporting Qualitative Research (SRQR³⁷) is preferable³⁶. The SRQR is a 21-item checklist that evaluates all aspects of qualitative studies, including problem formulation, research design, findings and interpretation of findings.

Disagreements between the review authors over the risk of bias and quality limitations in individual studies will be resolved by discussion, with involvement of two additional review authors where necessary. Following Hughes-Morley et al.³⁸, we will not omit any studies that demonstrate bias or limited quality. Instead we will de-emphasise the results of these studies in the conclusions of our synthesis.

Data Synthesis

Because we anticipate that studies will not be sufficiently homogenous to accommodate meta-analyses, the results will be tabulated and narratively synthesized. An advantage of narrative syntheses is their juxtaposition of quantitative and qualitative evidence in order to provide a detailed response to the question directing the review³⁹. This juxtaposition will yield a detailed account of what is currently known about how pollution impacts on, or relates to, child and adolescent mental health worldwide, as well as what facilitates child and adolescent mental health resilience in the face or aftermath of pollution exposure. This will be used to signpost limitations and silences in current understandings of child and adolescent mental health during/following exposure to pollution and to advocate for specific research and practice agendas. To ensure replicability of the narrative synthesis, we will make public the completed data-charting forms that informed the synthesis (e.g., as supplemental, on-line files when the review is published). LT and KH will lead the synthesis, with input from the remaining reviewers.

Meta-biases

Meta-bias includes both the selective reporting of outcomes due to their significance, magnitude, or direction and publication bias³¹. To asses meta-biases due to selective outcome reporting, we will: 1) evaluate whether studies have associated protocols, and whether those protocols were published prior to the recruitment of participants; 2) look for discrepancies between the published article and protocol (for those studies with a protocol); and 3) contact authors of the study, where additional information is needed. We do not plan any assessment of meta-biases due to publication bias.

Confidence in cumulative evidence

To assess confidence, we will apply the Grading of Recommendations Assessment, Development and Evaluation (GRADE⁴⁰) and GRADE-CERQual^41–42.

Children and adolescents comprise at least 25% of the world’s population¹⁶. Pollution effects are threatening the wellbeing of this sizeable population¹. To better protect the wellbeing of the world’s current and future children and adolescents, a thorough understanding is needed of how child and adolescent mental health is affected by pollution and what might enable resilience to pollution effects. The review that we propose is a first step in gaining that thorough understanding.

DSM–5^TR: Diagnostic and Statistical Manual of Mental Disorders

GRADE: Grading of Recommendations Assessment, Development and Evaluation

GRADE-CERQual: Confidence in the Evidence from Reviews of Qualitative research

LMIC: low- and middle-income countries

Ethics approval and consent to participate. Not applicable to this protocol.

Consent for publication. All co-authors have consented to publication.

Availability of data and material. Data sharing not applicable—no new data generated for the purposes of formulating this protocol.

Competing interests. None of the authors has any competing interests to declare.

Funding. GCRF Strategic Networking Grant [SBC1001G] funded the meeting where the idea was conceptualised. KH funded LS’s research assistance. The funders are not responsible for the content of the review protocol.

Authors’ contributions. LT led the conceptualisation of the protocol with input from all authors. LT and KH wrote the first and final protocol drafts. All other authors provided valuable editorial input to the drafts.

Acknowledgements. This work was conceived during a meeting of authors LT, KH, LG, YAV, MCL, CB, AT, IM, GA, MAO, as well as [names blinded for review]. CB is a member of the Royal Society Industry Fellows’ College. Queen Mary University is acknowledged for its role in hosting the aforementioned meeting.

Clark H, Coll-Seck AM, Banerjee A, Peterson S, Dalglish SL, Ameratunga S, Balabanova D, Bhan MK, Bhutta ZA, Borrazzo J, Claeson M. A future for the world’s children? A WHO–UNICEF–Lancet Commission. The Lancet. 2020 Feb 22;395(10224):605–58.
Landrigan PJ, Fuller R, Acosta NJ, Adeyi O, Arnold R, Baldé AB. & Chiles, T. The Lancet Commission on pollution and health. The Lancet. 2018;391(10119):462–512.
Goines L, Hagler L. Noise pollution: a modem plague. South Med J. 2007 Mar;100(3):287–94.
Watts N, Amann M, Arnell N, Ayeb-Karlsson S, Belesova K, Boykoff M, Byass P, Cai W, Campbell-Lendrum D, Capstick S, Chambers J. The 2019 report of The Lancet Countdown on health and climate change: ensuring that the health of a child born today is not defined by a changing climate. The Lancet. 2019 Nov 16;394(10211):1836–78.
World Health Organisation. More than 90% of the world’s children breathe toxic air every day. [updated 2018 Oct 29; cited 2020 Feb 27]. Available from https://www.who.int/news-room/detail/29–10–2018-more-than–90-of-the-world%E2%80%99s-children-breathe-toxic-air-every-day
Buoli M, Grassi S, Caldiroli A, Carnevali GS, Mucci F, Iodice S, Cantone L, Pergoli L, Bollati V. Is there a link between air pollution and mental disorders?. Environment international. 2018 Sep 1;118:154–68.
Elks S. Can air pollution trigger depression and schizophrenia? Thomson Reuters Foundation News. 2019 Aug 20.
Ren T, Yu X, Yang W. Do cognitive and non-cognitive abilities mediate the relationship between air pollution exposure and mental health?. PloS one. 2019;14(10).
Davis AN, Carlo G, Gulseven Z, Palermo F, Lin CH, Nagel SC, Vu DC, Vo PH, Ho TL, McElroy JA. Exposure to environmental toxicants and young children’s cognitive and social development. Reviews on environmental health. 2019 Mar 26;34(1):35–56.
Rauh VA, Margolis AE. Research review: environmental exposures, neurodevelopment, and child mental health–new paradigms for the study of brain and behavioral effects. Journal of Child Psychology and Psychiatry. 2016 Jul;57(7):775–93.
Patel V, Saxena S, Lund C, Thornicroft G, Baingana F, Bolton P, Chisholm D, Collins PY, Cooper JL, Eaton J, Herrman H. The Lancet Commission on global mental health and sustainable development. The Lancet. 2018 Oct 27;392(10157):1553–98.
World Health Organisation. Adolescent mental health. [updated 2019 Oct 2; cited 2020 Feb 27]. Available from https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health
Lee FS, Heimer H, Giedd JN, Lein ES, Šestan N, Weinberger DR, Casey BJ. Adolescent mental health—opportunity and obligation. Science. 2014 Oct 31;346(6209):547–9.
Patton GC, Sawyer SM, Santelli JS, Ross DA, Afifi R, Allen NB, Arora M, Azzopardi P, Baldwin W, Bonell C, Kakuma R. Our future: a Lancet commission on adolescent health and wellbeing. The Lancet. 2016 Jun 11;387(10036):2423–78.
Raballo A, Poletti M, McGorry P. Architecture of change: rethinking child and adolescent mental health. The Lancet Psychiatry. 2017 Sep 1;4(9):656–8.
Erskine HE, Baxter AJ, Patton G, Moffitt TE, Patel V, Whiteford HA, Scott JG. The global coverage of prevalence data for mental disorders in children and adolescents. Epidemiology and psychiatric sciences. 2017 Aug;26(4):395–402.
Calderón-Garcidueñas L, Torres-Jardón R, Kulesza RJ, Park SB, D’Angiulli A. Air pollution and detrimental effects on children’s brain. The need for a multidisciplinary approach to the issue complexity and challenges. Frontiers in human neuroscience. 2014 Aug 12;8:613.
Williams AL, Merten MJ. Linking community, parenting, and depressive symptom trajectories: Testing resilience models of adolescent agency based on race/ethnicity and gender. Journal of youth and adolescence. 2014 Sep 1;43(9):1563–75.
Davydov DM, Stewart R, Ritchie K, Chaudieu I. Resilience and mental health. Clinical psychology review. 2010 Jul 1;30(5):479–95.
Masten AS. Ordinary magic: Resilience in development. Guilford Publications; 2015 Oct 12.
Cox RS, Irwin P, Scannell L, Ungar M, Bennett TD. Children and youth’s biopsychosocial wellbeing in the context of energy resource activities. Environmental research. 2017 Oct 1;158:499–507.
Ungar M, Theron L. Resilience and mental health: how multisystemic processes contribute to positive outcomes. The Lancet Psychiatry. 2019 Dec 2.
Ungar M. Resilience across cultures. The British Journal of Social Work. 2008 Feb 1;38(2):218–35.
Directive C. Directive 2010/75/EU of the European Parliament and of the Council. Off. J. Eur. Union L. 2010;334:17–19.
Sawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. The Lancet Child & Adolescent Health. 2018 Mar 1;2(3):223–8.
Rey J, editor. IACAPAP textbook of child and adolescent mental health. International Association for Child and Adolescent Psychiatry and Allied Professions; 2015. Available from https://iacapap.org/english/
American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM–5®). American Psychiatric Pub; 2013 May 22.
Page M, McKenzie J, Bossuyt P, et al. Updating the PRISMA reporting guideline for systematic reviews and meta-analyses: study protocol. 2018. https://osf.io/xfg5n.
Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 2009;339:b2535. doi:10.1136/bmj.b2535
Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic reviews. 2015 Dec;4(1):1.
Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. Bmj. 2015 Jan 2;349.
Ainsworth S, Russell JM. Has hosting on science direct improved the visibility of Latin American scholarly journals? A preliminary analysis of data quality. Scientometrics. 2018 Jun 1;115(3):1463–84.
Saldana J. The coding manual for qualitative researchers. London: Sage; 2009.
Viswanathan M, Ansari MT, Berkman ND, Chang S, Hartling L, McPheeters M, Santaguida PL, Shamliyan T, Singh K, Tsertsvadze A, Treadwell JR. Assessing the risk of bias of individual studies in systematic reviews of health care interventions. 2012. Methods Guide for Effectiveness and Comparative Effectiveness Reviews. AHRQ Publication. 2018(10):14.
Hooijmans CR, Rovers MM, De Vries RB, Leenaars M, Ritskes-Hoitinga M, Langendam MW. SYRCLE’s risk of bias tool for animal studies. BMC medical research methodology. 2014 Dec 1;14(1):43.
Majid U, Vanstone M. Appraising qualitative research for evidence syntheses: a compendium of quality appraisal tools. Qualitative health research. 2018 Nov;28(13):2115–31.
O’Brien BC, Harris IB, Beckman TJ, Reed DA, Cook DA. Standards for reporting qualitative research: a synthesis of recommendations. Academic Medicine. 2014 Sep 1;89(9):1245–51.
Hughes-Morley A, Young B, Waheed W, Small N, Bower P. Factors affecting recruitment into depression trials: systematic review, meta-synthesis and conceptual framework. Journal of affective disorders. 2015 Feb 1;172:274–90.
Glover S, Hendron J, Taylor B, Long M. Understanding carer resilience in Duchenne muscular dystrophy: A systematic narrative review. Chronic illness. 2018 Jul 26:1742395318789472.
Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, Schünemann HJ. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. Bmj. 2008 Apr 24;336(7650):924–6.
Lewin S, Booth A, Glenton C, Munthe-Kaas H, Rashidian A, Wainwright M, Bohren MA, Tunçalp Ö, Colvin CJ, Garside R, Carlsen B. Applying GRADE-CERQual to qualitative evidence synthesis findings: introduction to the series. Implementation Science. 2018 Jan 1;13(1):9.
Munthe-Kaas H, Bohren MA, Glenton C, Lewin S, Noyes J, Tunçalp Ö, Booth A, Garside R, Colvin CJ, Wainwright M, Rashidian A. Applying GRADE-CERQual to qualitative evidence synthesis findings—paper 3: how to assess methodological limitations. Implementation Science. 2018 Jan 1;13(1):9.

Table 1: EBSCOhost Search strategy, modified as needed for other electronic databases

pollut* or pesticid* or platicizer* or metal* or DDT or solvent*

AND

mental health or mental illness or mental disorder* or psychiatric illness or psychiatric disorder* or psychiatric condition* or mood disorder* or anxiety-like or depressive-like

AND

foetus* or fetus or child* or adolescen* or youth* or teenager* or juvenil* or neonat* or young or gestation*or prenatal or larva* or embryonic

NOT

Heavy metal music

PRISMAP2015checklist.docx

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Version 1

posted

You are reading this latest preprint version

Effects of Pollution on Child and Adolescent Mental Health: A Protocol for a Systematic Review

Status:

Version 1

Abstract

Background

Objectives

Pollution

Child and adolescent

Child and adolescent mental health

Methods And Analysis

Eligibility criteria

Information sources

Search strategy

Study records

Data management

Selection process

Data collection process

Data items

Outcomes and prioritization

Rigour and risk of bias in individual studies

Data Synthesis

Meta-biases

Confidence in cumulative evidence

Conclusion

Abbreviations

Declarations

References

Tables

Supplementary Files

Status:

Version 1