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. 2022 Dec 5;12:20999. doi: 10.1038/s41598-022-24932-w

Table 2.

Models investigating the effects of condition, social rejection sensitivity (models 2/3A) and social support (Models 2/3B) on mood.

Dependent variable Predictor variable(s) b df t p R2m/R2c AIC Chi2 P(chi2)
Model 1
0.01/0.56 7258.5
Mood Condition 7.83 447.43 3.81  < 0.001***
Model 2A
0.09/0.56 7233.1 27.42  < .001***
Mood Condition 7.83 447.55 3.81  < 0.001***
Social rejection sensitivity 2.04 221.38 5.40  < 0.001***
Model 3A
0.09/0.56 7235.0 0.11 .738
Mood Condition 5.81 447.55 0.91 0.363
Social rejection sensitivity 1.89 647.09 3.21 0.001**
Condition × Social rejection sensitivity 0.08 447.55 0.33 0.738
Model 2B
0.08/0.56 7237.6 22.94  < .001***
Mood Condition 7.83 448.59 3.81  < 0.001***
Social support − 3.99 222.57 − 4.91  < 0.001***
Model 3B
0.08/0.56 7239.6 0.00 .959
Mood Condition 7.55 448.59 1.30 0.195
Social support − 3.94 644.85 − 3.13 0.002**
Condition × Social support − 0.02 448.59 − 0.05 0.959

*p < 0.05 **p < 0.01 ***p < 0.001. Mood is operationalised as the sum of anxiety (out of 100), stress (out of 100), and reverse-coded pleasantness (out of 100) measures, with higher scores indicating greater negative mood. Condition is modelled as baseline, post-threat (mood following completion of the learning task threat condition) and post-control (mood following completion of the learning task control condition). Models 2A and 3A included social rejection sensitivity as predictor, and models 2B and 3B included social support as predictor.