> Seems that it absolutely skews negative for the kids who had to deal with more lockdowns, i.e. not going to school with their peers. That's incorrect. If yo

> Seems that it absolutely skews negative for the kids who had to deal with more lockdowns, i.e. not going to school with their peers. That's incorrect. If you look at Figure-1 from [the article](https://link.springer.com/article/10.1007/s00787-021-01934-z https://link.springer.com/article/10.1007/s00787-021-01934-z ), it appears that students were happier when they attended either "Not at all" or "Every day". It's the middle-ground options that averaged out to show lower-satisfaction. Or to frame it differently, students who never went to school in-person reported a net-positive average: 33.5% better vs. 32.7% worse (vs. 33.8% the same). That doesn't support the notion that students didn't like staying home. That said, I'd warn against over-interpreting such small differences. --- Separately, if we did want to speculate based on the data: we might guess that it was about consistency. Students appeared to be happiest when they attended not-all-all or every-day, with lower improvements in middle-ground options. Comparing the two extremes, there is a preference for every-day over not-at-all (stressing that we're talking about smaller figures here), but even that might be explainable in terms of consistency: because, before the pandemic, students did attend every-day -- so not-at-all was a major shift in lifestyle for those students, i.e. a major inconsistency. Hypothetically, if students always attended online, but then some had to start attending in-person every-day, we might see the reverse bias, as then it'd be the students who'd have to attend having the major shift in lifestyle. --- All that said, there appear to be more underlying factors. For example, if we look at Table 2, it appears that there was a more considerable gender-gap: * males were happier (2400 vs. 1836); * females weren't (3185 vs. 3861). That's a large enough relative-disparity as to suggest that it may be a mistake to interpret the data in a gender-blind way; the little on-average differences seem overshadowed by the gender-differences.