The pooled VR score effect is robust to study removal and shows no significant publication bias¶
Claim · All claims
Evidence · 1 study · quant-synthesisr3·q3
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
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This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? Sensitivity analyses show the significant VR effect on examination scores is unchanged when any single study is removed, and Begg's test shows no significant publication bias (p = 0.54). → Zhao Jingjie 2020
Evidence¶
Zhao Jingjie 2020¶
Zhao Jingjie, Xu Xinliang, Jiang Hualin, Ding Yi. (2020). The effectiveness of virtual reality-based technology on anatomy teaching: a meta-analysis of randomized controlled studies. BMC Medical Education. https://doi.org/10.1186/s12909-020-1994-z
q3 · i? · quant-synthesis · r3
Sensitivity analysis of the pooled primary outcome, shown in Fig. 5, verifying reliability given heterogeneity above 75%. The funnel plot was symmetrical and Begg's test showed non-significant asymmetry (p = 0.54).
"When any research was removed from the model, the significant results of the VR effect on examination scores were unchanged in the models (SMD = 0.53, 95% CI: 0.01–1.07)"
Discussion¶
Related Claims¶
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- Publication bias could not be ruled out in the pooled teacher-student SEC estimate, though the association persisted across sensitivity analyses — related
- Pooled satisfaction and self-confidence effects are sensitive to individual studies, while knowledge, performance and self-efficacy effects are robust in leave-one-out analysis — related
- The CBL exam-score advantage is robust to subgroup and leave-one-out sensitivity analyses but shows potential publication bias — related
- Pooled PBL-CBL versus LBL estimates for theoretical and practical scores show high heterogeneity and publication bias but remain robust in sensitivity and trim-and-fill analyses — related
- Removing 5 heterogeneous studies leaves the PBL advantage intact (SMD 0.79) with reduced heterogeneity, and the Liu et al study most affects stability — related
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