Annual Review of Psychology Transparency and Reproducibility

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Guides researchers in documenting literature search protocols and establishing reproducible meta-analytic workflows for Annual Review of Psychology submissions.

The arpsych-transparency-and-reproducibility skill assists academic authors in meeting the rigorous transparency, open science, and reproducibility standards required for review papers and embedded quantitative syntheses in the Annual Review of Psychology. It provides structured guidance on documenting search queries, inclusion criteria, and selection logic for narrative reviews, as well as managing PRISMA flow diagrams, effect-size data deposition on platforms like OSF, and heterogeneity diagnostics for meta-analyses. Researchers can use this skill to audit their methodology against replication standards and avoid common anti-patterns like omitted conflict-of-interest declarations or undocumented literature claims.

Key Features

01Provides standardized reporting checklists for systematic literature searches and stopping rules
02Ensures compliance with journal-specific author declarations, funding disclosures, and AI usage policies
03Structures heterogeneity assessments, moderator analyses, and publication bias diagnostics
04Guides the deposition of effect-size datasets, coding sheets, and analysis scripts to open science repositories
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06Establishes reproducibility frameworks for embedded meta-analyses including PRISMA-style flow counts

Use Cases

01Verifying compliance with Annual Review of Psychology conflict-of-interest and AI authorship guidelines prior to submission
02Preparing open data repositories on OSF for meta-analytic effect sizes, coding protocols, and analysis scripts
03Documenting search terms, databases, and selection criteria for a comprehensive narrative psychology review