Analysis of the Impact of Individual Differences on Technical Stress and Prediction by Machine Learning

With the gradual penetration of the Internet into people's lives, it has also caused many people to panic about Internet technology, resulting in technical pressure. In this study, a meta-analysis technique was used to clarify the relationship between demographic characteristics, personality characteristics and employee technical stress. The results showed that there was a significant positive correlation between employee's education level and technical stress in demography; There is a significant negative correlation between employee age and technical pressure, which breaks through people's previous understanding of technical pressure; At the same time, female employees are more likely to feel technical pressure than male employees. Among the five personalities, neuroticism is positively correlated with technical stress. Openness, sense of responsibility and extroversion are all negatively correlated with technical stress. However, there is no significant relationship between human and technological pressure. This study revealed the relationship among demographic variables, personality characteristics and technical stress, providing a more accurate estimate of individual differences for predicting technical stress. In addition, a multi-layer perceptron-based employee stress prediction technology is also proposed.