Background: Occupational health and safety (OHS) training is an important way to prevent construction safety risks. However, the effectiveness of OHS training in China is questionable. In this study, the CHAID (chi-squared automatic interaction detection) decision tree, chi-square analysis, and correlation analysis were used to explore the main, secondary, weak, unrelated, and expectation factors affecting the effectiveness of training. It is the first to put forward the “five-factor method” of training effectiveness. It is found that training effectiveness is positively correlated with job responsibilities, OHS training, and job satisfaction. It is also significantly related to job certificate, training time, training method, and working time. However, the effectiveness of training has nothing to do with personal age, marital status, educational level, job type, and whether or not they have experienced industrial accidents. And the workers on site expect the enterprise to provide security and opportunities such as physical safety, training and learning, and future career development. The results show that OHS system training should be strengthened in the construction industry, and classified training should be carried out according to post responsibility, training methods, job satisfaction, and working hours.

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In view of the occupational health and safety (OHS) training on the safety of construction workers, and many complex factors. Through empirical investigation, this study proposes a set of multiple factor comprehensive analysis (CAMF) model to explore the effectiveness of OHS training and its main influencing factors. It has been found that training effectiveness is positively related to whether to receive OHS training or not and also positively related to training methods. It has also been found that the effectiveness of training is positively related to the importance of post responsibility. The results show that the construction industry needs to strengthen the OHS system training of grass-root workers, and the training should be classified and graded according to the workers' educational backgrounds, training methods, job satisfaction, and job responsibilities. In the safety training management of on-site workers, salary is the basic factor, and more attention should be paid to the factors such as workers' physical safety, training and learning, and future career development. The empirical results show that CAMF model has certain practical significance. The research results can provide paths and suggestions for improving the effectiveness of OHS training in China's construction industry, and provide some reference for other developing countries to carry out OHS training.

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To establish a suitable prediction model of construction workers' job satisfaction, this study chooses the widely used models CART (Classification and Regression Tree) and NN (Neural network) in the prediction model to make a comparison and finds out the main influencing factors of construction workers' job satisfaction in occupational health and safety training. Through the investigation and analysis of 280 cases of empirical data, it is found that the CART model based on Kappa value and Accuracy of categorical variables have a better prediction effect, and the main factors affecting job satisfaction are job categories, working days per week and the latest training time. The main innovation of this paper is to add the actual value set of empirical data on the basis of the usual training set, verification set, test set and prediction set, and draw a conclusion by comparing the predicted value with the actual value of kappa.