ArticleBehavior research methods2026
From review to synthesis: A step-by-step methodological guide to systematic reviews and multilevel meta-analyses.
Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Emotional Dependency and Parasocial Grief Following the Alteration or Loss of Companion Artificial Intelligences: A Systematic Review.Behavioral sciences (Basel, Switzerland) · 2026Review
- Global Prevalence of Internet Gaming Disorder: An Umbrella Review of Meta-Analytic Evidence and Implications for Child and Adolescent Psychiatry.Brain sciences · 2026Review
- Effectiveness of Cognitive and Behavioral Interventions in the Treatment of Schizophrenia: An Umbrella Review of Meta-Analyses.Journal of clinical medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We provide a step-by-step guide on conducting a quantitative systematic review (i.e., meta-analysis) using the open-source programming language R, as well as conducting a multilevel meta-analysis, in contexts where effect sizes are non-independent (e.g., multiple studies from the same lab). Quantitative systematic reviews offer researchers a method for synthesizing large bodies of literature, helping clarify inconsistent findings, identify research gaps, and refine theoretical models. However, existing tutorials often assume prior knowledge and/or experience, often overlooking foundational concepts. To address this gap, a comprehensive walkthrough of the systematic review process is presented, covering pre-registration, literature search and retrieval, screening, risk of bias assessment, and data extraction following the PRISMA framework. We then present detailed guidance on how to conduct both traditional and multilevel meta-analyses in R. Specifically, the tutorial explains how to estimate overall meta-analytic effect sizes when effect sizes are independent (traditional meta-analysis) and when effect sizes are nested within labs (multilevel meta-analysis). Procedures for assessing heterogeneity, testing for publication bias, and conducting moderation analyses are also covered. To accompany this tutorial, we supplement annotated R scripts and R notebooks to support transparency, reproducibility, and accessibility for researchers of all levels of experience.
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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.