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oai:data.mendeley.com/j4f94xspg7.1 2026-08-26T13:21:13Z

LIU, JIANPENG High Heterogeneity in AI Anxiety Research: Meta-Analytic and Bibliometric Evidence Consistent with a Pre-paradigmatic Stage Mendeley Data This deposit contains all materials required to reproduce the analyses reported in the manuscript "High Heterogeneity in AI Anxiety Research: Meta-Analytic and Bibliometric Evidence Consistent with a Pre-paradigmatic Stage" (Frontiers in Psychology, Manuscript ID 1924329). Contents of the upload pack: (1) Data.xlsx — the study-level meta-analytic dataset (11 studies, N = 6,156). Effect sizes are standardized deviations of sample means from scale midpoints (Hedges' g), computed with the one-sample sampling-variance formula. Sheets: Study Data, Summary, Subgroup, Leave-One-Out. (2) R Code.R — the complete meta-analysis code (version 10.1), implementing DerSimonian–Laird random-effects pooling with REML and Hartung–Knapp robustness checks, subgroup tests, exploratory meta-regression, PET-PEESE publication-bias assessment, influence diagnostics, and leave-one-out analyses. (3) Bibliometric Analysis Code.py — the bibliometric pipeline (term extraction with a concept dictionary, NetworkX co-occurrence network, Louvain clustering, Kleinberg two-state burst detection). (4) Bibliometric Document List.xlsx — the manually rescreened bibliometric corpus (n = 337 documents) with per-record screening outcomes. Psychology Dataset doi:10.17632/j4f94xspg7.1 oai:data.mendeley.com/j4f94xspg7.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/j4f94xspg7 2026-08-26T13:21:13Z