Abstract:

In order to explore the influencing pathways of negative emotions among occupational noise-exposed workers, 493 male workers with high noise exposure from five typical manufacturing enterprises were recruited as subjects. Data were collected through occupational health surveys, noise measurements, and psychological scales. Key variables, including age, cumulative noise exposure (CNE), marital status, and nine other factors, were screened using the least absolute shrinkage and selection operator (LASSO) regression, based on which a Bayesian network model was constructed. The results showed that the detection rate of negative emotions among male workers was 5.7%, with an average noise exposure level of 91.5 dB(A). The model identified multiple influencing pathways, and their probability distributions varied across age groups: in the <30 years group, the pathway “age → marital status → negative emotions” was predominant (16.4%); in the 30-39 years group, the direct pathway “age → negative emotions” was most prominent (30.6%); while in the ≥40 years group, the pathway “age → CNE → negative emotions” was dominant (21.5%-29.4%). Moreover, the high CNE group generally exhibited a higher probability of negative emotions than the medium exposure group. The study indicates that negative emotions among male workers under high noise exposure are interactively influenced by factors such as age, CNE, smoking, drinking, and marital status. The Bayesian network model effectively reveals these complex pathway relationships.

Key words: Bayesian network, male workers, high noise exposure, negative emotions, path analysis