ArticleBMJ open2024
How does air pollution threaten mental health? Protocol for a machine-learning enhanced systematic map.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Air quality and mental illness: role of bioaerosols, causal mechanisms and research priorities.BJPsych open · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAir pollution exposure has influenced a broad range of mental health conditions. It has attracted research from multiple disciplines such as biomedical sciences, epidemiology, neurological science, and social science due to its importance for public health, with implications for environmental policies. Establishing and identifying the causal and moderator effects is challenging and is particularly concerning considering the different mental health measurements, study designs and data collection strategies (eg, surveys, interviews) in different disciplines. This has created a fragmented research landscape which hinders efforts to integrate key insights from different niches, and makes it difficult to identify current research trends and gaps. METHOD AND ANALYSIS: This systematic map will follow the Collaboration for Environmental Evidence's guidelines and standards and Reporting Standards for Systematic Evidence Syntheses guidelines. Different databases and relevant web-based search engines will be used to collect the relevant literature. The time period of search strategies is conducted from the inception of the database until November 2022. Citation tracing and backward references snowballing will be used to identify additional studies. Data will be extracted by combining of literature mining and manual correction. Data coding for each article will be completed by two independent reviewers and conflicts will be reconciled between them. Machine learning technology will be applied throughout the systematic mapping process. Literature mining will rapidly screen and code the numerous available articles, enabling the breadth and diversity of the expanding literature base to be considered. The systematic map output will be provided as a publicly available database. ETHICS AND DISSEMINATION: Primary data will not be collected and ethical approval is not required in this study. The findings of this study will be disseminated through a peer-reviewed scientific journal and academic conference presentations.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.