The role of meta-analyses and umbrella reviews in assessing the harms of psychotropic medications: beyond qualitative synthesis is a research paper published in Epidemiology and Psychiatric Sciences (2018). On theSindex it has a DataRank of 2.1. It has been cited 46 times, with 28 citing works in its 1-hop citation network.
ὠφελέειν, ἢ μὴ βλάπτειν (Primum non nocere) - Hιppocrates' principle should still guide daily medical prescribing. Therefore, assessing evidence of psychopharmacologic agents' safety and harms is essential. Randomised controlled trials (RCTs) and observational studies may provide complementary information about harms of psychopharmacologic medications from both experimental and real-world settings. It is considered that RCTs provide a better control of confounding variables, while observational studies provide evidence from larger samples, longer follow-ups, in more representative samples, which may be more reflective of real-life clinical scenarios. However, this may not always hold true. Moreover, in observational studies, safety data are poorly or inconsistently reported, precluding reliable quantitative synthesis in meta-analyses. Beyond individual studies, meta-analyses, which represent the highest level of 'evidence', can be misleading, redundant and of low methodological quality. Overlapping meta-analyses sometimes even reach different conclusions on the same topic. Meta-analyses should be assessed systematically. Descriptive reviews of reviews can be poorly informative. Conversely, 'umbrella reviews' can use a quantitative approach to grade evidence. In this editorial, we present the main factors involved in the assessment of psychopharmacologic agents' harms from individual studies, meta-analyses and umbrella reviews. Study design features, sample size, number of the events of interest, summary effect sizes, p-values, heterogeneity, 95% prediction intervals, confounding factor adjustment and tests of bias (e.g., small-study effects and excess significance) can be combined with other assessment tools, such as AMSTAR and GRADE to create a framework for assessing the credibility of evidence.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.578
From this paper's citation signal
Citation Network Contribution
1.5
From 26 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 28% comes from its base citations and 72% from the citation network (26 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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