ArticlePrevention science : the official journal of the Society for Prevention Research2022
Next-Generation Meta-analysis for Next-Generation Questions: Introducing the Prevention Science Special Issue on Modern Meta-analytic Methods.
Article in Prevention science : the official journal of the Society for Prevention Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The power of the social: A systematic review and meta-analysis of social interventions in Global Mental Health.PLOS mental health · 2026Article
- Modern Meta-Analytic Methods in Prevention Science: Introduction to the Special Issue.Prevention science : the official journal of the Society for Prevention Research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This commentary accompanies the special issue of Prevention Science on modern meta-analytic methods. The papers that comprise this special issue are considered in terms of the next-generation meta-analytic questions they support: questions about multivariate relationships, drawing on real-life data structures, with improved usability, and answered openly. The contributions to this special issue illustrate a range of methods to address these questions, including meta-analytic structural equation modelling; robust variance estimation and network meta-analysis methods; transportability and causal inference; Bayesian methods; and open science. This special issue collectively represents a step forward in the field's ability to address questions of use to improving human welfare through preventing ill health, supporting uptake of these next-generation methods by applied researchers in prevention science. Future methodological developments in meta-analysis should be synergistic with the questions prevention scientists seek to answer, both creating new possibilities and meeting the challenges of improving human health and wellbeing.
Indexed as
Identifiers
34932172What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.