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Get Started Free →Use when documenting the literature search and making any embedded meta-analysis reproducible for an Annual Review of Psychology (ARPsych) review. Covers search transparency, meta-analytic rigor, and open materials; it does not run the narrative search (arpsych-literature-synthesis) or design exhibits (arpsych-tables-figures).
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 11% | 0% |
| case-01 | ✗→✓ | ▲ Improved | 105% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 33% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -18% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 47% | 0% |
A pure narrative review has no dataset of its own, so the transparency obligation does not look like a primary-paper replication package. It bites on two things:
arpsych-literature-synthesis, written up so a reader could reproduce the coverage.Post-replication-crisis, ARPsych readers expect both, and a review that asserts "the literature shows…" with no documented basis reads as less authoritative.
Then you have run original analysis and must meet quantitative-synthesis standards:
| Requirement | What to provide | |-------------|-----------------| | PRISMA-style flow | search → screening → included, with counts at each step | | Coding protocol | how effects were extracted/coded; inter-coder reliability | | Effect-size dataset | the extracted effects + moderators, deposited | | Analysis code | scripts reproducing the pooled estimates and plots | | Heterogeneity + bias | I², moderators, funnel/publication-bias diagnostics | | Preregistration (if applicable) | protocol/PROSPERO registration where the synthesis was prospective |
Deposit data and code in a public repository (e.g., OSF) and cite the DOI in the review.
Annual Reviews requires authors to disclose potential sources of bias / conflicts of interest and to state funding; prepare these per the author pages. AI tools are not authors. Re-confirm the exact disclosure format on the live Annual Reviews pages.
text【Review type】narrative | embedded-meta-analysis 【Search transparency】protocol documented reproducibly? Y/N 【If meta-analysis】PRISMA flow + coding + reliability? Y/N 【Open materials】effect data + code deposited (OSF DOI)? Y/N | N/A 【Heterogeneity / bias】I² + funnel/pub-bias reported? Y/N | N/A 【Declarations】COI / bias disclosure + funding prepared; AI not author? Y/N 【Next step】→ arpsych-editor-strategy (align scope/timeline with the Editor)
Other measured skills in the registry, with their headline benchmark lift.