6 Study 3: Transfer Effects in Indirect Assessment

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6.1  Introduction

↓107

The main purpose of the following study was to explore whether the unexpected positive correlation between the anxiousness and the angriness IAT in Study 2 was due to the salience of a positive-negative self-dimension. If participants classified the attributes within both IATs according to evaluative rather than semantic features, the transfer effect from the anxiousness IAT onto the angriness IAT can be explained. Therefore, I aimed to replicate the transfer effect of the preceding study with a different sample and to check whether the transfer effect could be blocked or strengthened using interventions that block or strengthen a positive-negative self-dimension, respectively. Additionally, I examined whether the anxiousness and the angriness IAT were correlated with a contingency-based color IAT, that assesses method-specific variance due to task-switching costs (Mierke & Klauer, in press). These research questions are discussed in the following sections.

6.1.1  Research Question 1: Interventions for Blocking and Strengthening
the Transfer Effect

Study 2 provided evidence that a positive-negative self-dimension was more salient in the anxiousness IAT than in the angriness IAT. Therefore, a task-recoding in terms of a positive-negative self-dimension seemed to be more likely to occur in the anxiousness than in the angriness IAT. The task-recoding in the anxiousness IAT was assumed to cause the transfer effect from the anxiousness onto the angriness IAT. Two different interventions were examined in Study 3 in order to block the transfer effect.

One intervention employed anagrams of evaluatively neutral nouns. Participants had to identify the misplaced letters in given nouns thereby come up with the correct noun. The other intervention employed the procedure of the contingency-based IAT from Mierke and Klauer (in press). The contingency-based IAT asks for the categorization of geometrical objects and imposes an artificial contingency between the genuinely unassociated target category (color of stimuli) and the attribute category (size of stimuli) (see Chapter 2.4.2). I used meaningless strings instead of geometrical objects as stimulus material because they were easier to implement in the ERTS routines. This modification of the geometrical objects IAT was called color IAT. The detailed procedure is described in the Methods section. The color IAT was expected to block the transfer effect because its stimuli cannot be categorized in terms of a positive-negative self-dimension.

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In contrast, a positive-negative self-dimension is salient in direct self-esteem and mood measures. The transfer effect was expected to be strengthened if self-esteem and mood scales were presented between the anxiousness and the angriness IAT. Additionally, the blocking of the transfer effect through the color IAT or the anagrams seemed likely to be reversed if the self-esteem and the mood scales were presented before the angriness IAT.

6.1.2 Research Question 2: Method-Specific Variance in the IATs

Recently, Mierke and Klauer (in press) showed that method-specific variance due to task-switching can be assessed with a contingency-based IAT (see Chapter 2.4.2). As noted before, the contingency-based IAT was slightly modified for Study 3 and was used as an intervention to block the positive-negative self-dimension. The modified version, the color IAT, employed the same rationale as the geometrical objects IAT from Mierke and Klauer. It was expected that the results of the geometrical objects IAT were replicated in the color IAT. The color IAT should correlate with the absolute scores of the anxiousness and the angriness IAT when the IAT scores are calculated as conventional measures. In contrast, the color IAT should be uncorrelated with the anxiousness and the angriness IAT when the IAT scores are calculated as D measures (Greenwald et al, 2003). This would indicate that the improved D measures control for the method-specific variance that is produced by task-switching costs. Additionally, this would show that the positive correlation between the anxiousness and the angriness is not mediated by the method-specific variance that is assessed by the color IAT.

6.2 Hypotheses

Study 3 tested the following hypotheses:

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Hypothesis 1 (Higher negative correlations of self-esteem and mood with direct anxiousness than with direct angriness measures).

Self-esteem and positive mood show higher negative correlations with direct anxiousness than with direct angriness measures. Therefore, a positive-negative dimension is more salient within the anxiousness IAT than within the angriness IAT. This accounts for the asymmetry of the transfer effect from the anxiousness IAT onto the angriness IAT but not vice versa.

Hypothesis 2 (Negative correlations of self-esteem and mood with the angriness IAT). When mood and self-esteem are assessed directly before the angriness IAT they show negative correlations indicating the influence of a positive-negative self-dimension on the angriness IAT.

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Hypothesis 3 (Zero correlations of the D measures with the Color IAT). The improved IAT D measures do not correlate with the color IAT indicating that the correlation between the anxiousness and the angriness IAT is not mediated by the method specific variance that is assessed by the color IAT.

Hypothesis 4 (Replication of the transfer effect). The transfer effect from the anxiousness IAT onto the angriness IAT, that is, positive correlations between both IATs and a trend for the angriness IAT to correlate with direct anxiousness measures, is replicated in Study 3.

Hypothesis 5 (Intervention effects). The positive-negative self-dimension and, thus, the transfer effect is blocked through interventions that require the categorization of evaluatively neutral stimuli during an IAT or the processing of evaluatively neutral nouns.

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Hypothesis 6 (Positive-negative self-dimension produces transfer effect). The transfer effect is strengthened or its blocking is reversed through self-ratings on a mood and a self-esteem scale that comprise a positive-negative self-dimension.

6.3 Methods

6.3.1  Participants and Design

180 participants were randomly assigned to the conditions of a 3 (intervention type: color IAT, anagrams, without intervention) x 2 (mood and self-esteem scale: with, without) between subjects design. Assignment was balanced for gender. Most participants were directly approached on the campus of Humboldt University, Berlin. The rest of the participants were recruited by postings at the university buildings. Participants were nonpsychology university students, native German speakers, and had not participated in the lab’s previous studies. Their mean age was M = 23.13 years and ranged from 19 to 33 years. Participants were offered € 6 (approximately US $ 6 at the time) for taking part in a 45 minute lab experiment on personality traits.

Table 24
Overall Procedure and Design of Study 3

Cover story: Personality traits

Duration
(Min.)

(a)

Direct trait measures

- Trait form of the STAI and STAXI
- Speaking Anxiety Scale
- Bipolar self-ratings of anxiousness, angriness,

conscientiousness, and intellect

- Social desirability scales
- Biographical data

10

(b)

IAT

Anxiousness IAT

10

(c)

Intervention

Color IAT

Anagrams

Without

0/5

(d)

Mood and self-esteem scale

+

-

+

-

+

-

0/2

(e)

IAT

Angriness IAT

10

n

30

30

30

30

30

30

~41

Note. STAI = State Trait Anxiety Inventory, STAXI = State Trait Anger Expression Inventory, IAT = Implicit Association Test, + = with, - = without.

6.3.2 Assessments and Measures

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Trait measures. Trait measures were identical to Study 2 except that some scales were dropped, and the items were answered on the computer in the lab. (For more detailed information about scale formats and item numbers see Methods section of Study 2.) The questionnaire started with the trait forms of the State Trait Anxiety Inventory STAI (Laux et al., 1981; English version: Spielberger et al. 1970) and the State Trait Anger Expression Inventory STAXI (Schwenkmezger et al., 1991; English version: Spielberger, 1988). Items of both questionnaires were randomly mixed and were followed by the second series of the Speaking Anxiety Scale (Spitznagel et al., 2000). Next, participants had to rate their conscientiousness and intellect on 10, and their anxiousness and angriness on 5 bipolar adjective pairs each. Pairs were mixed in a fixed random order and presented with a trait instruction. The questionnaire concluded with the Social Desirability Scales by Lück and Timaeus (1969) (English version: Crowne & Marlowe, 1960) and Stöber (1999; without the Item “Have you ever consumed drugs”). Internal consistencies of all trait measures were satisfactory, α > .75 for all scales. At the end of the questionnaire participants had to report their age, sex, dominant hand, academic subject, length of time spent at university, whether they were still students (all were), and whether they had a permanent partner.

Mood Scale. This scale was version A of the Positive-Negative Mood Scale borrowed from the Multidimensional Comfort Questionnaire [Multidimensionaler Befindlichkeitsfragebogen, Steyer, Schwenkmezger, Notz, & Eid, 1997]. On 5-point scales (1 = not at all, 5 = very much) it assesses positive and negative mood with 2 unipolar items each (e.g., “fine”). Items were presented with a state instruction (“At the moment I feel …”) and answers were coded so that higher values indicated more positive mood. Internal consistency of the Mood Scale was satisfactory, α = .88

State Self-Esteem Scale. This scale was a short form of the State Self-Esteem Scale from Heatherton and Polivy (1991) that was translated into German by Riketta and Dauenheimer (2002). The scale deals with self-evaluations (e.g., “I feel satisfied with the way my body looks right now”) that should be answered with regard to how a participant feels at the moment. Answers are given on a 5-point scale (1 = not true at all, 5 = perfectly true), with higher values indicating higher self-esteem. Out of the 20 item original scale I selected 8 items that showed corrected item-total correlations of r > .48 in two student samples (N = 142 and N = 115) of Riketta and Dauenheimer (personal communication, October 17, 2002). Internal consistency of the resulting scale was satisfactory, α = .80.

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Anxiousness and angriness IAT. The procedures were identical to Study 2.

Color IAT. The procedure of the color IAT was identical to the anxiousness and the angriness IAT, but the stimuli closely followed the geometrical objects IAT presented in Mierke and Klauer (in press). While target (color of stimuli) and attribute (size of stimuli) categories were equal to Mierke and Klauer, I used meaningless strings rather than geometrical objects as stimulus material. Task sequence, stimuli, and task description are depicted in Table 25. The geometrical objects IAT was developed to asses interindividual differences in task-switching performance that were shown to reliably contaminate conventional IAT measures (Mierke & Klauer, in press) but not the improved IAT D measures (Greenwald et al., 2003). The geometrical objects IAT imposes an artificial contingency between the genuinely unassociated target category (color) and attribute category (size), so that all blue stimuli are big and all red stimuli are small. I employed the color IAT in order to use a evaluatively neutral IAT procedure for studying its ability to block transfer effects between different IATs. Therefore, my procedure strictly followed the anxiousness and angriness IAT. That was also true for the aspect that (contrary to Mierke & Klauer, in press) within the combined tasks the stimuli alternated between target and attribute. The IAT score was computed as the difference between mean response latencies in the incompatible and the compatible pairing (sequence 3 – sequence 5, see Table 25).

Table 25
Color Implicit Association Test: Task Sequence and Task Description

Response key assignment

Sequence

N of trials

Task

Left key

Right key

1

40

Target discrimination

Red

Blue

2

40

Attribute discrimination

Big

Small

3

80

Initial combined task

Red, big

Blue, small

4

40

Reversed target discrimination

Blue

Red

5

80

Reversed combined task

Blue, big

Red, small

Tasks

Target discrimination: Color of strings

Attribute discrimination: Size of strings

Blue versus red

Big (22, 24) versus small (11, 12) fonts

Nonrelevant size of targets:
Big (22, 24) or small (11, 12) fonts

Nonrelevant colors of attributes:
Yellow, green, or pink

Note. The Color IAT imposed an artificial contingency between target (color) and attribute (size) discrimination so that all blue strings were big and all red strings were small. Strings were xyxyx, yxyxy, yxxxy, xyyyx, and xxyxx.

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Anagrams. Out of a list of 800 nouns that were analyzed by M. Schwibbe, Raeder, G. Schwibbe, Borchardt, and Geiken-Pophanken (1981) I selected 35 nouns the valences of which were rated as neutral, .08 > M > -.08, SD < .60, referring to a 5-point scale ranging from -3 = negative to +3 = positive. The places of two letters were switched within each of these nouns and the nouns were presented on the screen. Participants were instructed to type in the correct noun as quick as possible. If participants did not complete the full 35 nouns within five minutes the presentation of the remaining anagrams was stopped in order to keep time comparable for all participants.

6.4  Results

6.4.1  Correlations of Direct Measures

The correlations between the state self-esteem scale and the direct anxiousness and angriness measures are depicted in the last column of Table 26. As it was expected from Hypothesis 1, self-esteem showed higher negative correlations with direct anxiousness than with direct angriness measures. Although correlations tended to be negative for both, they ranged from intermediate to large for direct anxiousness, and were not even marginally significant for the direct angriness measures. The correlation differences (Steiger, 1980) were nonsignificant when comparing the correlations of the bipolar anxiousness and angriness self-rating, t (87) = 1.17, n.s. (one-tailed), and significant when comparing the correlations of the trait forms of the State Trait Anxiety and Anger Expression Inventories, t (87) = 2.44, p < .01 (one-tailed). Although the self-esteem scale was presented with a state instruction, and anxiousness and angriness were assessed as traits, the correlational pattern with trait self-esteem might be very similar, as state and trait self-esteem are highly correlated (Heatherton & Polivy, 1991).

Concerning the correlations of the positive mood scale with direct anxiousness and angriness measures, the same pattern was true (see column 8 of Table 26). Whereas the anxiousness measures showed marginal or significant negative correlations with positive mood, the correlations of the angriness measures with positive mood were not even marginally significant. However, the correlation differences were nonsignificant when comparing the correlations of the bipolar anxiousness and angriness self-rating, t (87) = .97, n.s. (one-tailed), and marginally significant when comparing the correlations of the trait forms of the State Trait Anxiety and Anger Expression Inventories, t (87) = 1.50, p < .10 (one-tailed). Together, these findings illustrate that a positive-negative self-dimension was represented to a greater extent in direct anxiousness rather than in direct angriness measures. This confirmed the explanation for the transfer effect, and further demonstrated the asymmetry of the transfer effect from the anxiousness IAT onto the angriness IAT, but not vice versa.

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Table 26
Reliabilities and Correlations of the Trait and State Measures in Study 3

1

2

3

4

5

6

7

8

9

1. Bipolar anxiousness

.83

.06

.30***

.40***

.69***

.12

-.11

-.18+

-.31***

2. Bipolar angriness

.81

.13+

.15*

.19*

.59***

-.23**

-.04

-.15

3. Speaking Anxiety Emotionality

.87

.67***

.28***

.20**

-.12

.04

-.19+

4. Speaking Anxiety Worries

.86

.40***

.28***

-.13

-.04

-.36***

5. State Trait Anxiety Inventorya

.90

.30***

-.23**

-.34***

-.59***

6. State Trait Anger Expression Inventorya

.75

-.34***

-.16

-.15

7. Social desirability

.80

.27**

.37***

8. Mood scale (state instruction)

.87

.48***

9. State self-esteem

.80

 

Note. N = 180, n = 90 for mood and self-esteem scales. Internal consistencies (Cronbach’s α) are printed in italics along the diagonal.
a Trait form. + p < .05 *p < .05 **p < .01 ***p < .001.

Considering the other correlations in Table 26, the findings of Study 2 were clearly replicated. Again, the bipolar anxiousness and angriness self-ratings did not correlate with each other. The bipolar anxiousness self-rating correlated highly with the trait form of the State Trait Anxiety Inventory, and weakly with the trait form of the State Trait Anger Expression Inventory, whereas the opposite was true for the bipolar angriness self-rating. Finally, direct anxiousness and angriness measures tended to correlate with social desirability that was especially the case for direct angriness measures.

6.4.2 Descriptive Statistics for the Anxiousness and the Angriness IAT

Before I explore the correlations of the IATs, I will discuss briefly their descriptive statistics. The mean raw score (in milliseconds) of the anxiousness IAT was M = -173.4, SD = 176.5, and ranged from -748.7 to 310.0. Only 24 (13 female, 11 male) out of 180 participants had positive IAT scores. Thus, most of the participants were quicker to combine Me+self-confident and Others+anxious than the reverse mapping. The mean raw score of the angriness IAT was M = -153.2, SD = 124.7, and ranged from –513.6 to 123.0. Only 15 (3 female, 12 male) out of 180 participants had positive scores. Thus, most of the participants were quicker to combine Me+self-controlled and Others+angry than the reverse mapping. The mean raw score of the color IAT was M = 352.1, SD = 162.3, and ranged from 66.2 to 789.4. Thus, all participants were quicker in the compatible rather than in the incompatible pairing.

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Mean error rates were for the anxiousness IAT M = 5.0%, SD = 3.6%, for the angriness IAT M = 3.7%, SD = 3.1%, and for the color IAT M = 4.1%, SD = 3.5%. One participant had an error rate of 21.9% in the angriness IAT. Because exclusion of this participant would not affect the correlational pattern, his data were not discarded from analysis. Error rates for all other participants were below 20% in any IAT. No participant responded quicker than 300 ms in more than 10% of the trial responses in any IAT. The distributions of the D measures were not even marginally different from a normal distribution in all IATs, Z < 1. For every test, internal consistency was computed across the two test halves, and was acceptable for the anxiousness IAT , α = .77, but only marginal for the angriness IAT, α = .60, and the color IAT, α = .59.

6.4.3 Correlations of the Anxiousness and the Angriness IAT with Self-Esteem and Mood

As it was expected from Hypothesis 2, the angriness IAT correlated negatively with the self-esteem and the mood scale that half of the participants (n = 90) completed just before the angriness IAT. Correlations were small but significant for both the self-esteem and the mood scale, r = -.23, p < .05, r = -.21, p < .05. This illustrated once more that categorization of stimuli within the angriness IAT was influenced by a positive-negative self-dimension. The anxiousness IAT, that was completed beforehand, correlated not even marginally with the self-esteem scale and marginally with the mood scale, r = -.10, n.s., r = -.18, p < .10. As one may recall, the opposite was true for direct anxiousness and angriness measures. Only direct anxiousness measures correlated significantly with the mood and self-esteem scale whereas direct angriness measures were not even marginally correlated (see Table 26). Thus, the negative correlation of the angriness IAT was rather an indicator of its susceptibility to a positive-negative self-dimension rather than an indicator for its validity.

6.4.4  Correlations of the Anxiousness and the Angriness IAT with the Color IAT

As it was expected from Hypothesis 3, the D measures of the anxiousness and the angriness IAT were not correlated with the method-specific variance assessed by the color IAT, r = -.10, n.s., r = .07, n.s., n = 60. For these correlations, the absolute magnitude of the D measures was employed, and scores for the color IAT were computed on the basis of untransformed response latencies to maximize the amount of method-specific variance in such scores (Mierke & Klauer, in press). The observed zero correlations indicated that the correlation between the anxiousness and the angriness IAT was not due to their shared reliable contamination by the method-specific variance.

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With regard to conventional measures, the absolute magnitude of the untransformed and the log-transformed scores of the angriness IAT correlated significantly with the color IAT, r = .38, p < .01, r = .27, p < .05. This pattern exactly replicated the findings that Mierke and Klauer (in press) obtained for an extraversion IAT and a flower-insect attitudes IAT. However, it was not true for the anxiousness IAT. For this test, the absolute magnitude of neither the untransformed scores nor the log-transformed scores correlated significantly with the color IAT, r = .09, n.s., r = .06, n.s.. Thus, even so the conventional measures of the angriness IAT showed considerable method-specific variance due to task-switching costs, the anxiousness IAT did not. Consequently, these findings illustrated that the correlation between the anxiousness and the angriness IAT is unlikely to be mediated by the method-specific variance that was assessed by the color IAT.

The different correlations of the anxiousness IAT and the angriness IAT with the color IAT might be attributed to a position effect, since the color IAT was always presented after the anxiousness and before the angriness IAT. Nevertheless, in Mierke and Klauer’s Experiment 3 (in press) an extraversion IAT correlated with method-specific variance that was assessed by a geometrical objects IAT, although the geometrical objects IAT was completed after the extraversion IAT. Therefore, it should be the subject of future studies to explore whether the method-specific variance due to task-switching increases with the number of IATs that are completed.

6.4.5  Correlations of the Anxiousness and the Angriness IAT by Intervention

Contrary to Hypothesis 4, the transfer effect from the anxiousness IAT onto the angriness IAT was not replicated when there were no intervention and no self-ratings on the mood and self-esteem scale before the angriness IAT. As it can be seen for condition (1) in Table 27 the correlation between both IATs tended to be positive but was not even marginally significant.

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Table 27
Correlations of the Anxiousness and the Angriness IAT by Interventions (Study 3)

Intervention

No intervention

Color IAT

Anagrams

 

Mood + SE

without

with

without

with

without

with

 

Condition

(1)

(2)

(3)

(4)

(5)

(6)

 

IAT

 

Anx.

Angr.

Anx.

Angr.

Anx.

Angr.

Anx.

Angr.

Anx.

Angr.

Anx.

Angr.

 

Angr. IAT

.24

-

.38*

-

.46**

-

.53**

-

.38*

-

.53**

-

 

Bip. anx.

.54**

-.04

.24

-.03

.54**

.19

.34+

.23

.46*

-.07

.35+

.30

 

Bip. angr.

.10

.42*

-.23

-.06

.20

.04

-.08

-.18

-.25

.27

.04

.06

 

Emotionality

.15

-.06

.08

-.05

.19

.19

.00

.00

.27

.01

.16

.27

 

Worries

.35+

-.13

.25

.09

.34+

.15

-.07

-.01

.33+

.14

.05

.21

 

STAI

.47**

.07

.21

.10

.50**

.24

.33+

.02

.28

-.22

.43*

.78***

STAXI

.15

.52**

-.08

-.02

.14

.10

.11

-.03

.07

.47**

.29

.25

 

SD

-.17

-.26

-.03

.13

.32+

.14

-.11

.04

.35+

-.01

-.04

-.14

 

Note. n =30. Mood + SE = Mood and self-esteem scale (state instruction), Angr. = Angriness, Anx. = Anxiousness, Bip. anx. = Bipolar anxiousness self-rating, Bip. angr. = Bipolar angriness self-rating, Emotionality = Speaking Anxiety Emotionality, Worries = Speaking Anxiety Worries, STAI = Trait form of the State Trait Anxiety Inventory, STAXI = Trait form of the State Trait Anger Expression Inventory, SD = Social desirability.
Correlations that differed significantly due to the presentation of the mood and self-esteem scale are underlined (p < .05, one-tailed). + p < .10 * p < .05 ** p < .01 *** p < .001.

More importantly, the angriness IAT showed sizeable convergent validity with the bipolar angriness self-rating and the trait form of the State Trait Anger Expression Inventory. Inspection of the scatterplots revealed homogenous distributions. Thus, the angriness IAT did not correlate significantly with either the anxiousness IAT or with direct anxiousness measures. Therefore, Hypothesis 4 was not confirmed.

With regard to Hypothesis 5, I explored the groups that completed the color IAT or the anagrams but not the mood and self-esteem scales before the angriness IAT. Contrary to Hypothesis 5, the color IAT that required a categorization of senseless strings according to color and size was not sufficient to block the transfer effect. As it can be seen for condition (3) in Table 27, the anxiousness and angriness IAT correlated considerably in this group. The angriness IAT did not correlate with direct angriness but showed small positive correlations with direct anxiousness measures that nonetheless failed to reach significance. In contrast, in the anagram group, the angriness IAT tended to show weaker correlations with the anxiousness IAT, and instead correlated with direct angriness measures. As it is shown for condition (5) in Table 27, the angriness IAT correlated weakly, but due to the small sample size nonsignificantly, with the bipolar angriness self-rating, and intermediately with the trait form of the State Trait Anger Expression Inventory. However, the angriness IAT still correlated significantly with the anxiousness IAT. Thus, Hypothesis 5 was confirmed, demonstrating that the anagrams increased the convergent validity of the angriness IAT. Nevertheless, the anagrams were incapable of entirely eliminating the correlation between the anxiousness and the angriness IAT. On the other side, the color IAT was generally inappropriate to block the transfer effect

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Concerning the effects of the mood and self-esteem scale that should promote a positive-negative self-dimension, Hypothesis 6 was successfully confirmed. When these scales were presented between the anxiousness and the angriness IAT, the convergent validity of the angriness IAT was diminished, and both IATs tended to correlate more highly with each other. Although this correlation increase was not significant, the pattern was replicated in all three groups (see condition (2), (4), and (6) in Table 27). More importantly, the decrease of convergent validity with direct angriness measures was significant for the no intervention group (see condition (2) in Table 27). In addition, there was a significant increase in the correlation between the angriness IAT and the trait form of the State Trait Anxiety Inventory in the anagram group (see condition (6) in Table 27). It should be noted that the latter correlation showed a homogenous scatterplot and was not driven by outliers. Altogether, the transfer effect was clearly strengthened through the presentation of the mood and self-esteem scales.

6.5  Discussion

This section first summarizes the main findings of Study 3. Then I discuss why the transfer effect might not have been replicated in the no-intervention group and refer to the problem of small sample sizes.

6.5.1  Summary of the Main Findings

Study 3 explored whether the unexpected positive correlation between the anxiousness and the angriness IAT that was found in Study 2 was caused by a task-recoding in terms of a positive-negative self-dimension. Therefore, the salience of the positive-negative self-dimension was manipulated, and the effects on the correlations of the angriness IAT were studied. Study 3 tested six hypotheses.

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First, direct anxiousness measures showed a pattern of stronger correlations with negative self-esteem and negative mood than direct angriness measures. Thus, a positive-negative self-dimension was more salient in the stimuli of the anxiousness IAT than of the angriness IAT. This explains the asymmetry of the transfer effect from the anxiousness IAT onto the angriness IAT. Second, the angriness IAT correlated significantly with both, negative self-esteem and negative mood, if they were presented directly before the angriness IAT. This indicated that a positive-negative dimension influenced the angriness IAT. Third, in contrast to the conventional scores, the improved D measure of the angriness IAT did not correlate with the method-specific variance that was assessed by the color IAT. Fourth, unexpectedly, in the no-intervention group, the transfer effect from the anxiousness IAT onto the angriness IAT was not replicated and the IATs were only weakly correlated. This lack of replication is discussed in more detail in Chapter 6.5.2. Fifth, only the anagrams but not the color IAT were capable of reducing the transfer effect and securing the convergent validity of the angriness IAT. However, even the anagrams did not entirely eliminate the correlation between the anxiousness and the angriness IAT. Sixth, when a positive-negative self-dimension was made salient through the presentation of self-esteem and mood scales, the transfer effect was strengthened. This was apparent from a pattern of higher correlations between the anxiousness and the angriness IAT, and from a lack of convergent and discriminant validity of the angriness IAT.

6.5.2  Lack of Replication of the Transfer Effect in the No-Intervention Group

Surprisingly, the transfer effect from the anxiousness IAT onto the angriness IAT failed to be replicated in the no-intervention group of Study 3. The transfer effect was explained by the salience of a positive-negative self-dimension. However, there may be three reasons why a positive-negative self-dimension was weaker in Study 3 than in Study 2.

First, in Study 2 direct anxiousness and angriness measures were completed at home within one week before the lab experiment. In contrast, in Study 3, direct anxiousness and angriness measures were completed during the lab experiment and before the anxiousness and the angriness IAT. Previous studies showed that correlations between IATs and direct measures are affected by the order in which direct measures and the IATs are presented (Bosson et al., 2000), and that correlations between IATs and direct measures are not affected by the presentation order (Nosek et al., 2003). However, a recent meta-analysis (Hofmann, Gawronski, et al., 2003) suggests that first administering the direct measures increases correlations between IATs and direct measures. More importantly, it is theoretically plausible that direct-indirect correlations increase when the direct measures are completed first, because this makes the existing associations more accessible (Fazio, 1995; Strack & Deutsch, in press). It is possible that the angriness IAT in Study 3 was more robust against the transfer effect from the anxiousness IAT because the presentation of the direct angriness measures made the implicit self-concept of angriness more accessible. The presentation of the direct measures before the IATs seemed to have had at least some effect, as direct-indirect correlations tended to be generally higher in Study 3 than in Study 2. For instance, the overall correlation of the anxiousness IAT with the bipolar anxiousness self-ratings tended to be higher in Study 3 (r = .39, p < .001, N = 180) than in Study 2 (r = .25, p < .05, N = 100). Similarly, the correlation of the angriness IAT with the bipolar angriness self-ratings tended to be higher in Study 3 (r = .23, p < .05, n = 90) than in Study 2 (r = .11, n.s., N = 100).

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Second, the cover story in Study 3 was “personality traits”, whereas in Study 2 it was “concentration and personality”, since the cover story in Study 2 had to be discreet in regards to the emotion inductions. Especially during the lab experiment of Study 2, the focus was on concentration tests. Therefore, some participants may have categorized anxious versus self-confident (within the anxiousness IAT) and angry versus self-controlled (within the angriness IAT) in terms of distracted versus concentrated. This might have strengthened the transfer effect. It could also explain why the direct-indirect correlations in Study 2 were, on the whole, lower than in Study 3. Nevertheless, a task-recoding in terms of distracted versus concentrated is unlikely to explain the transfer effect alone because the transfer effect was asymmetrical.

Third, in Study 2 participants completed an optimistic risk questionnaire directly before the IATs. In this questionnaire participants rated the probability of positive (e.g., “I married someone wealthy.”) and negative (e.g., “I had a heart attack before age 50.”) events during their lifetime. Items were recoded such that high scores indicated optimism. The optimistic risk questionnaire did not correlate with either the anxiousness IAT, the angriness IAT, or explicit angriness measures. Yet, it showed significant negative correlations with all explicit anxiousness measures (r < -.25). Therefore, the optimistic risk questionnaire might have made a positive-negative dimension in Study 2 more salient, and, thus, strengthened the transfer effect from the anxiousness onto the angriness IAT.

Altogether, it is clear that correlations between the IATs and direct measures are dependent on the context (cf. the special issue of the Journal of Personality and Social Psychology, 71, 2001). Particularly, direct-indirect correlations seem to be affected by the aspects of the personality self-concept that are activated before the IATs. In Study 3, a positive-negative self-dimension was probably weakened by presenting the direct angriness measures beforehand, by focusing on personality traits, and by omitting the optimistic risk questionnaire. Therefore, the transfer effect might have not been replicated in the no intervention group. Nevertheless, it may be assumed that the evaluatively neutral anagrams still contributed to the reduction of the transfer effect in the anagram group for two reasons. First, the transfer effect was replicated in the group that completed the color IAT. Second, the transfer effect was strengthened by the presentation of the self-esteem and the mood scales, that made, in contrast to the evaluatively neutral anagrams, a positive-negative self-dimension more salient.

6.5.3  Small Sample Sizes

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The aim of Study 3 was to test correlational hypotheses about blocking and strengthening of the transfer effect from the anxiousness IAT onto the angriness IAT. The sample sizes for the 6 experimental conditions were quite small (n = .30). It was expected by Hypothesis 5 that the neutral anagrams, as well as the color IAT would block the transfer effect. Results showed that this was true only for the former but not the latter. Therefore, these groups could not be pooled. Additionally, the transfer effect was not replicated in the no-intervention group, and the correlations of the anxiousness and the angriness IAT varied considerably among the groups that completed the self-esteem and the mood scale before the angriness IAT (see Table 27). Consequently, the experimental conditions were discussed individually.

In any correlational study, large sample sizes, at least N ≥ 50, but better N ≥ 100, are called for. Otherwise, results may be driven by a few uncharacteristic participants who are unidentifiable as outliers. I looked for outliers who might have distorted the correlations, and I examined all of direct and indirect measures in every experimental condition individually. However, this search was unsuccessful. Similarly, the inspection of the scatterplots revealed that the correlations showed homogenous distributions. Still, the importance of large sample sizes might be illustrated by the fact that the correlation between the anxiousness IAT and the bipolar anxiousness self-ratings varied considerably between the conditions, from r = .24 to r = .54. This was true although the experimental conditions were identical up to the presentation of the anxiousness IAT. Thus, results of small samples such as in the present study should be considered with caution.

Nevertheless, a pattern of three important results became evident in all experimental conditions. First, in contrast to the bipolar anxiousness and angriness self-ratings, the correlation between the anxiousness IAT and the angriness IAT was positive and different from zero. Second, the correlation between the IATs was higher if a positive-negative self-dimension was made salient through the self-esteem and the mood scales. Third, the convergent and the discriminant validity of the angriness IAT with direct self-report measures was distorted by the presentation of the self-esteem and the mood scales.

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More importantly, a different study with a larger sample size (N = 97) replicated the position effect on the angriness IAT that was found in Study 2 (Teige, Schnabel, Banse, & Asendorpf, in press). In that study, the sequence of the shyness and the angriness IAT was counterbalanced across participants. The correlations between the shyness and the angriness IAT tended to be higher when the shyness IAT was completed as first rather than second test, r = .34 versus r = -.01, z = -1.73, p < .10 (two-tailed). Similar to the anxiousness IAT, the shyness IAT may have made a positive-negative self-dimension more salient, because shyness and anxiousness were highly correlated concerning direct self-reports (r = .69). The study provided further evidence that the transfer effect on the angriness IAT is (a) asymmetrical and (b) most likely caused by the salience of a positive-negative self-dimension.


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