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Objectives: Psychological distress is a worldwide problem and a serious problem that needs to be addressed in the field of occupational health. This study aimed to use artificial intelligence (AI) to predict psychological distress among workers using sociodemographic, lifestyle and sleep factors, not subjective information such as mood and emotion, and to examine the performance of the AI models through a comparison with psychiatrists., Design: Cross-sectional study., Setting: We conducted a survey on psychological distress and living conditions among workers. An AI model for predicting psychological distress was created and then the results were compared in terms of accuracy with predictions made by psychiatrists., Participants: An AI model of the neural network and six psychiatrists., Primary Outcome: The accuracies of the AI model and psychiatrists for predicting psychological distress., Methods: In total, data from 7251 workers were analysed to predict moderate and severe psychological distress. An AI model of the neural network was created and accuracy, sensitivity and specificity were calculated. Six psychiatrists used the same data as the AI model to predict psychological distress and conduct a comparison with the AI model., Results: The accuracies of the AI model and psychiatrists for predicting moderate psychological distress were 65.2% and 64.4%, respectively, showing no significant difference. The accuracies of the AI model and psychiatrists for predicting severe psychological distress were 89.9% and 85.5%, respectively, indicating that the AI model had significantly higher accuracy., Conclusions: A machine learning model was successfully developed to screen workers with depressed mood. The explanatory variables used for the predictions did not directly ask about mood. Therefore, this newly developed model appears to be able to predict psychological distress among workers easily, regardless of their subjective views., Competing Interests: Competing interests: SS is the Chair of the Occupational Health Technical Committee, Tsukuba Science City Network; SD, YO and DH are members of the Occupational Health Technical Committee and the other authors are members of the Occupational Health Technical Committee Working Group. None of the authors received remuneration., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Early-life adversities are considered to have long-term impact on health. There have been many studies regarding the experience of being bullied and its harmful psychological influence, but such influence on workers remains to be investigated in Japan. We therefore aimed to examine the prevalence of workers with experiences of being bullied or bullying others during childhood and adolescence and to clarify the relation between those experiences and current psychological distress. A cross-sectional study using an anonymous self-report web questionnaire was conducted in November 2017. The study population was 19,481 workers belonging to the Tsukuba Science City Network, and we analyzed the data of 6,015 participants (3,715 men and 2,300 women, aged between 20 years and 59 years). The percentages of participants with experiences of being bullied were 51.5% for men and 56.2% for women; those with experiences of bullying others were 36.5% of men and 29.4% of women. Relations between experiences of bullying and psychological distress were assessed using Chi-squared tests. Logistic regression analyses with psychological distress as an objective variable and experiences of bulling as explanatory variables were performed using those who had no bulling experiences as control. In both men and women, experiences of being bullied were significantly associated with psychological distress after adjustment socioeconomic factors (the odds ratios were 1.26 for men (95% CI = 1.05-1.52) and 1.72 for women (95% CI = 1.39-2.13)). Consideration of past social experiences, such as being bullied, is useful for mental health management among workers reporting psychological distress.