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. 2022 Jul 19;12:12313. doi: 10.1038/s41598-022-16567-8

Table 2.

Effect sizes and publication bias across SITB outcomes.

Binary/categorical n RR [95% CI] p I2 Fail-safe N Begg and Mazumdar rank correlation Egger's test of intercept Duval and Tweedie's Trim and Fill
Classic Orwin's Missing effect sizes Adjusted RR
Overall 362 1.06 [0.99, 1.14] 0.09 7.19% 217 0 τ = − 0.01, p = 0.76 z = 1.87, p = 0.06 0 1.06 [0.99, 1.14]
Suicide ideation 126 1.03 [0.92, 1.14] 0.65 2.70% 0 0 τ = 0.04, p = 0.46 z = 0.79, p = 0.43 0 1.03 [0.92, 1.14]
Suicide attempt 53 1.21 [0.95, 1.55] 0.13 11.77% 0 0 τ = − 0.09, p = 0.35 z = 0.53 p = 0.60 0 1.21 [0.95, 1.55]
Suicide death 6 0.77 [0.47, 1.26] 0.30 0.00% 0 0 τ = 0.60, p = 0.14 z = 1.69, p = 0.09 0 0.77 [0.47, 1.26]
NSSI 28 1.18 [0.89, 1.57] 0.25 0.00% 0 31 τ = − 0.23, p = 0.09 z = − 1.25, p = 0.21 4 1.27 [0.96, 1.68]
Self-harm 30 0.99 [0.80, 1.21] 0.90 23.03% 0 0 τ = − 0.13, p = 0.34 z = 0.32, p = 0.75 0 0.99 [0.80, 1.21]
Hospitalizations 8 1.11 [0.89, 1.39] 0.33 0.00% 0 18 τ = 0.00, p = 1.00 z = − 0.85, p = 0.40 2 1.14 [0.92, 1.42]
Other/combined SITBs 111 1.16 [0.99, 1.36] 0.49 11.46% 66 0 τ = − 0.03, p = 0.60 z = 2.18, p = 0.03 0 1.16 [0.99, 1.36]
Continuous n Hedges’ g [95% CI] p I2 Fail-safe N Begg and Mazumdar rank correlation Egger's test of intercept Duval and Tweedie's Trim and Fill
Classic Orwin's Missing effect sizes Adjusted RR
Overall 50 − 0.04 [− 0.12, 0.05] 0.37 64.60% 5 34 τ = − 0.05, p = 0.58 z = − 1.37, p = 0.17 0 − 0.04 [− 0.12, 0.05]
Suicide ideation 33 − 0.03 [− 0.12, 0.06] 0.53 55.92% 0 0 τ = 0.003, p = 0.99 z = 0.32, p = 0.75 0 − 0.03 [− 0.12, 0.06]
Suicide attempt 3
Suicide death 1
NSSI 1
Self-harm 7 0.12 [− 0.07, 0.32] 0.22 0.00% 0 0 τ = 0.05, p = 1.00 z = 0.24, p = 0.81 0 0.12 [− 0.07, 0.32]
Hospitalizations 1
Other/combined SITBs 4

n number of effect sizes, RR weighted mean risk ratio, CI confidence interval, dashes indicate unavailable information; I2 indicates the percentage of variances due to heterogeneity between studies. Classic Fail-safe N and Orwin’s Fail-safe N represent the number of studies needed to nullify the observed effects statistically and clinically, respectively; Begg and Mazumdar Rank Correlation Test computes the rank order correlation between effect estimates and sampling variance; Egger's Test of the Intercept uses precision (i.e., the inverse of the standard error) to predict the standardized effect (i.e., effect size divided by the standard error); Duval & Tweedie's Trim & Fill estimates effect sizes after accounting for publication bias. Missing cases are the number of cases estimated to be missing below the mean. Boldface indicates significance at p < 0.05.