How does air pollution threaten mental health? Protocol for a machine-learning enhanced systematic map

Area of Science:

• Environmental health
• Neuroscience
• Public health

Background:

• Air pollution exposure is increasingly linked to diverse mental health conditions.
• Research spans biomedical sciences, epidemiology, neuroscience, and social science, highlighting public health significance.
• Fragmented research landscapes hinder integration of insights and identification of trends.

Purpose of the Study:

• To systematically map the existing literature on air pollution and mental health.
• To identify research trends, gaps, and challenges in establishing causal and moderator effects.
• To provide a comprehensive overview for future research and policy development.

Main Methods:

• Systematic map following established evidence synthesis guidelines.
• Comprehensive literature search across multiple databases and search engines (inception–November 2022).
• Machine learning and literature mining for rapid screening and coding, supplemented by manual review and conflict resolution.

Main Results:

• A publicly available database of the synthesized literature will be generated.
• The map will detail the breadth and diversity of research on air pollution and mental health.
• Identification of key research trends and knowledge gaps.

Conclusions:

• This systematic map will consolidate fragmented knowledge on air pollution's mental health impacts.
• It will facilitate a more integrated understanding of environmental influences on mental well-being.
• The findings will inform future research directions and public health policies.