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Table 3 Contrasts run in Experiment 3

From: Can corrections spread misinformation to new audiences? Testing for the elusive familiarity backfire effect

dV/hypothesis

Effect tested

F(1,405)

P

False-claim inference scores

 H1FISl+: NE < FCOl+

Familiarity backfire effect

0.06

.810

 H1FISl-: NE < FCOl-

Familiarity backfire effect

8.45

.004ab

 H7FIS: FCOl- < FCOl+

Load effect on correction

6.65

.010a

False-claim belief ratings

 H1FBRl-: NE < FCOl-

Familiarity backfire effect

6.40

.012ab

 H1FBRl+: NE < FCOl+

Familiarity backfire effect

3.39

.066b

 H7FBR: FCOl- < FCOl+

Load effect on correction

0.45

.501

True-claim inference scores

 H1TISl-: NE < FCOl-

Effect of affirmation vs. baseline

19.21

< .001a

 H1TISl+: NE < FCOl+

Effect of affirmation vs. baseline

15.69

< .001a

 H7TIS: FCOl- > FCOl+

Load effect on affirmation

0.18

.671

True-claim belief ratings

 H1TBRl-: NE < FCOl-

Effect of affirmation vs. baseline

40.61

< .001a

 H1TBRl+: NE < FCOl+

Effect of affirmation vs. baseline

22.32

< .001a

 H7TBR: FCOl- > FCOl+

Load effect on affirmation

2.60

.108

  1. Note. Hypotheses are numbered H1 and H7 (primary hypotheses in bold; see text for details); subscripts FIS, TIS, FBR, and TBR refer to false-claim and true-claim inference scores and belief ratings, respectively; no-load and load conditions are indicated by l- and l+. Conditions are NE no-exposure; FCOl± fact-check-only with no load or with load. aindicates statistical significance (for secondary contrasts: after Holm-Bonferroni correction). bindicates effect in the opposite of hypothesized direction