섹션 링크 공유나이
Age is one of the key confounding factors in the dataset. In other words, it can make it seem like two other variables (such as “number of kids” and “yearly income”) have some kind of stronger relationship, when they are actually both downstream from a common root cause.
One unexpected finding is that while older respondents tend to generate less of their code using AI, they also tend to view the technology more positively.
섹션 링크 공유장애 여부
Gender and age have a big impact on the type of disabilities respondents experience, with hearing impairments and chronic illness becoming more common with age.
And confirming other studies, chronic illness is more present among women; while neurodivergent conditions and mental health issues are over-represented among non-binary respondents.
섹션 링크 공유Health Issues
Poor sleep continues to be the top health issue affecting respondents.
When looking at health issues across countries, the “healthiest” countries (based on the proportion of respondents who reported experiencing no health issues whatsoever) were Italy, Norway, and Switzerland.
But of course, what gets reported as a health issue or not can also be in part cultural, with for example only 8% of Russia-based respondents reporting mental health issues, significantly lower than the 12% figure for all survey respondents.