Table 1 Emotion regulation success explained by Pupil Dilation Index and affective distance.

From: Pupil dilation predicts individual self-regulation success across domains

 

Beta estimate

Standard deviation

95% Credible interval

(a)

(Intercept)

1.77

0.14

[1.50; 2.03]

Pupil dilation index

0.34

0.14

[0.06; 0.61]

Affective distance

0.30

0.14

[0.02; 0.58]

Pupil dilation index × Affective distance

0.21

0.19

[− 0.15; 0.58]

Bayes factor

1.83

  

(b)

(Intercept)

1.83

0.20

[1.43; 2.24]

Pupil Dilation Index

0.33

0.16

[0.01; 0.64]

Affective distance

0.28

0.15

[− 0.01; 0.57]

Age

0.07

0.15

[− 0.23; 0.35]

Task order

− 0.13

0.29

[− 0.71; 0.44]

Pupil dilation index × Affective distance

0.20

0.20

[− 0.18; 0.61]

Bayes factor

0.54

  
  1. (a) Results from the Bayesian Linear Regression specified in Eq. (3a). Regulation success (measured on the 9-point SAM scale) was modelled by the mean-centred and standardized coefficients for Pupil Dilation Index (measured as mean difference in the pupil dilation curve for the Regulate > View contrast in the significant regulation time between 3.4 and 5.6 s) and Affective Distance (measured as the absolute value of the distance of the view rating from the neutral valence on the SAM scale). Pupil Dilation Index and Affective Distance were interacted, to test whether it might be easier or harder to reappraise with smaller or greater affective distances.
  2. (b) Augmenting the model (Eq. 3b) by the control regressors for Age and Task Order shows that the explanation of regulation success by PDI is robust to controlling for the age and the order in which participants completed the emotion regulation and dietary health challenge tasks.
  3. Model fits are given as the population level mean of the posterior distribution ± standard deviation (SD) and the 95% credible interval. Bayes Factors are given for a comparison to an intercept-only model.
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