ArticleFrontiers in public health2026
Determining the direction of pro-safety activities using selected methods of statistical analysis.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
2 authors.
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Abstract
Objective: The aim of this study was to determine the strength of the correlation between the studied characteristics describing accident events. Methods: Statistical methods were used for the analysis, particularly Pearson's linear correlation analysis. The study was conducted using PQStat v.1.6.8 statistical software. This study present an analysis of occupational activity and causes of accidents in the studied seniority groups, using Pearson's linear correlation analysis. Determining the strength of correlation, rather than causality, allows for the identification of key characteristics of accidents (e.g., cause of accident, type of activity performed) and the connections between the studied characteristics. Results: The study identified key activities performed by injured workers and causes of accidents in the studied seniority groups, which should form the basis for actions aimed at reducing the number of recorded occupational accidents. To this end, the strongest correlations in the seniority group-activity-cause of accident pattern are presented graphically. Conclusion: Determining the strongest correlations allows for the identification of key areas on which actions aimed at improving occupational safety should be based. These actions may therefore lead to a reduction in the number of recorded accidents in particular age groups in which the strongest connections between the studied characteristics were identified.
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