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Tools

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Equal-Life Tools

The Tools page on the Equal-Life Toolbox website is organised into key sections that support various stages of research on the exposome and its impact on children's mental health:

Explore Definition

We develop conceptual models and definitions of the mechanisms of how the three domains of the exposome impact the mental health and cognitive development in children and young adults

The Guidebook

Our guidebook offers concepts and definitions to help you understand the exposome and its components, particularly the factors influencing mental health and cognitive development in children of different ages at different places and circumstances.

The Glossary

Too many words? use the glossary to clarify concepts and look up definitions

Collect, measure, model

We develop conceptual models and definition of the mechanisms of how the physical and social environment impact the mental health and cognitive development in children and young adults aged 0 to 21 years.

Multimodal data collection and enrichment

We develop novel methods for exposome data collection and enrichment, based on new and complementary data sources. It aims to offer new insights into aspects of the built and natural environment that are not covered by conventional datasets.

Internal Exposome Tools

We discover novel internal biomarkers in relation to children’s mental health. What is a biomarker? How biomarkers are used in Equal-Life? Explore our biological protocols

Physical
Exposome Tools

We create a detailed description of the external exposome by developing comprehensive data and open-source models for the built and natural environments, air pollution, and noise

Social exposome Tools

We construct an enriched description of the external exposome by developing detailed data and new, open-source models for the built- and natural- environments, air pollution, and noise.

Algorithms for Data Analysis and Health Impact Assessment

We analyze how integrated exposures affect children's mental health and development by harmonizing cohort and school study data. Using machine learning and statistical methods, we model these relationships, considering moderation and mediation effects, to provide insights and recommendations.

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Statistical Models

We develop and apply machine learning and other statistical methods to model the relationship between exposome and mental health and cognitive development in children, including moderation and mediating effects

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EHEN Cataloge

What is the EHEN catalogue and how to use it. Explore more Exposome project through their metadata

Inform and Involve

We focus on stakeholder involvement and intervention development, including creating a toolkit for stakeholders to facilitate interventions. Additionally, we develop tools for participatory activities, frameworks, and guidance aimed at raising awareness about the exposome.

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Stakeholder involvement and preparation of interventions

We develop novel methods for exposome data collection and enrichment, based on new and complementary data sources. It aims to offer new insights into aspects of the built and natural environment that are not covered by conventional datasets.

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