Risk of bias and low reproducibility of meta-analytic estimates on mental health problems epidemics during the covid-19 pandemic: a meta-research analysis of global evidence on 18,604,876 individuals across 94 countries

First-tracking publications to covid-19-related meta-analytic evidences benefited evidence-based policymaking for safeguarding public mental health in this pandemic. However, such makeshifts had been concerned to cause troubling unreliable estimates for mental health problems epidemics. From 98 meta-analytic studies with 18,604,876 individuals across 94 countries published in the pandemic, we found significant risk of bias (ROBs) in publication, with one meta-analysis for being published per five days at the peak. Despite large-scale samples in these meta-analytic evidences, third-nation populations were substantially underrepresented. Of these meta-analyses, 70.6% (57.1%) showed high ROBs in transparency (methodology), and less than one-fifth of them could be empirically reproducible. Publication in high-impact journals, gaining high citations and fast-tracked publication did not improve transparency/reproducibility. By using individual participant data after minimizing these ROBs, we finally re-estimated these mental health problems epidemics to establish benchmarks. This study indicated that research quality/integrity should be still leading when compromising in emergency conditions.