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Moderation of masked affective priming

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Running head: MODERATION OF MASKED AFFECTIVE PRIMING

Automatic evaluation isn’t that crude! Moderation of masked affective priming by type of valence

Dirk Wentura1 and Juliane Degner2 1 2

Saarland University

University of Amsterdam

----------------- Cognition & Emotion, in press -----------------

Address correspondence to: Dirk Wentura Department of Psychology, Saarland University, D-66115, Saarbruecken, Germany Tel.: +49-681-302-4781 Fax: +49-681-302-4049 E-Mail: [email protected]


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Abstract In two experiments, the automatic processing of evaluative information was investigated using a masked affective priming paradigm, varying valence (positive vs. negative) and relevance (other-relevant traits vs. possessor-relevant traits; Peeters, 1983) of prime and target stimuli. It was found that under specified conditions, valence-congruency effects were only found if prime and target matched with regard to relevance type (i.e., were both either of the other-relevant or possessor-relevant type). These results suggest that automatic processing of affective information conveys not only the positive-negative differentiation, but also the relevance type of valence. Consequences for research on automatic attitudes, especially prejudice are discussed. For current research on masked priming, it is important to highlight that the subliminal effect was found even for non-practiced prime stimuli.


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Automatic evaluation isn’t that crude! Moderation of masked affective priming by type of valence Since the seminal article on affective priming by Fazio, Sanbonmatsu, Powell, and Kardes (1986), a lot of research has been done on the automaticity of evaluation (for reviews see Fazio, 2001; Klauer & Musch, 2003; Wentura & Rothermund, 2003). Typically, affective priming is assessed with an evaluation task: participants have to decide for each target stimulus whether it is positive or negative.1 Shortly before each target, a prime stimulus is presented. In cases of affective congruence (i.e., prime and target share the same valence), response times (and/or number of errors) are expected to be lower than in cases of affective incongruence (i.e., prime and target are of different valence). Although there has been some debate about the underlying mechanisms (see, e.g., De Houwer, Hermans, Rothermund, & Wentura, 2002; Klauer & Musch, 2003; Spruyt et al., 2002), it is rather undisputed that this effect reflects the automatically – in the sense of nonintentionally – activated evaluation of the prime. Given this background, the affective priming procedure was proposed as a measurement tool for automatic attitude activation (Fazio, Jackson, Dunton, & Williams, 1995). The underlying rationale is that automatic evaluation of attitude-related stimuli can be inferred from affective priming effects if these stimuli are presented as primes.


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Meanwhile, it has been shown that affective priming effects can be found with subliminally presented prime stimuli (Abrams, Klinger, & Greenwald, 2002; Draine & Greenwald, 1998; Greenwald, Draine, & Abrams, 1996; Greenwald, Klinger, & Liu, 1989; Greenwald, Klinger, & Schuh, 1995; Klauer, Eder, Greenwald, & Abrams, 2007). Thus, even if prime stimuli are processed outside of awareness, their valence is activated. This feature renders the evaluation task the most unobtrusive measure of automatic evaluations. Given this backdrop, we were able to fruitfully use the affective priming technique in its masked version in several studies, tapping different domains of evaluation (Degner & Wentura, in press; Degner, Wentura, Gniewosz, & Noack, 2007; Frings & Wentura, 2003; Otten & Wentura, 1999; Wentura, Kulfanek, & Greve, 2005). The present studies are concerned with a question that is highly relevant for research on automatic processing of affective connotations in general, and research on indirect assessment of attitudes in specific: Is automatic evaluation a rather undifferentiated process that only conveys general positive or negative affective connotations? Or do we find more subtle differentiations at the level of fast, effortless, and unconscious valence processing? With the following studies we explore a candidate distinction for such a differentiation, that is, the other- vs. possessor-relevance introduced by Peeters (1983; Peeters & Czapinski, 1990). Other vs. Possessor-Relevance


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Peeters (1983; Peeters & Czapinski, 1990) introduced a typology of valenced trait adjectives according to the kind of positivity or negativity they convey. That is, the evaluation of a given trait depends on the perspective of the evaluator – whether they evaluate the trait from the perspective of the trait-holder him/herself or from the perspective of someone who has to interact with the trait-holder. Thus, this typology is termed possessorvs. other-relevance (or self- vs. other-profitability, see Peeters, 1983). To give an example, being brutal is primarily bad for the social environment of the brutal person, but not necessarily for the brutal person him-/herself (he/she might be a sadist). On the contrary, being lonely is primarily bad for the lonely individual but not necessarily for his/her social environment. The same applies to positive adjectives: Being honest is primarily good for those who interact with the honest person but not necessarily for the honest person him-/herself (honesty might be abused), whereas being intelligent is primarily good for intelligent persons themselves but not necessarily for the social environment (she or he might have selfish motives). Adjectives like brutal or honest are called otherrelevant, whereas words like lonely or intelligent are called possessorrelevant. Wentura, Rothermund, and Bak (2000) provided first evidence that this typology is relevant for automatic evaluation processes. They found that other-relevant stimuli increased color-naming times in the “Emotional


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Stroop” task compared to possessor-relevant words. Thus, there is some evidence that our cognitive-affective system is tuned to distinguish between these kinds of positivity and negativity at a very basic level. If automatic evaluation differentiates into other- versus possessor-relevance, it can be hypothesized that affective priming will be susceptible to different types of valence as well. In fact, applying the affective priming paradigm to the indirect assessment of attitudes provided first indications that (a) automatic evaluation of socially relevant stimuli seem to comprise a differentiation of possessor- and other-relevance and that (b) this can potentially be assessed with the affective priming task: Interindividual differences in social attitudes such as self-esteem or intergroup prejudice – as measured by questionnaires – were differentially and meaningfully related to priming effects based on attitude-related primes and either self-relevant or other relevant target words (Wentura et al., 2005; Degner et al., 2007). These results indicate that the potential of the affective priming paradigm for the assessment of different types of automatic evaluation should be systematically explored. Overview In the following two experiments, we test for the moderation of masked affective priming effects by relevance type of valence. We hypothesize that – possibly given some boundary conditions – masked affective priming effects are most pronounced if primes and targets are from the same relevance type.


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We used the masked version of affective priming to make strategic influences maximally unlikely. Masking, for example, precludes that participants acquire a clear picture of the trial structure which might be used by participants to successfully manipulate effects (Degner, in press; Klauer & Teige-Mocigemba, 2007). Although it is not our dominant concern to add to the debate on unconscious priming (see, e.g., Dehaene & Naccache, 2001), one might evaluate the experiments also in the light of this research field. Therefore we conducted a direct test of prime awareness. For both experiments, we added a further factor, that is, whether participants were instructed to emphasize speed or accuracy in responding. This was done for the following reason. It is known from the affective priming literature that masked priming effects are a rather robust finding if participants are urged to respond very quickly (see, e.g., Draine & Greenwald, 1998; Greenwald et al., 1996). An obvious explanation for affective priming effects is the assumption that the prime prepares either for the correct or the wrong response needed for the target. Given this explanation, it might be relevant that the targets are not yet fully processed when the response is given: it could then be argued that the weight of the task-relevant target attribute is relatively decreased compared to the corresponding prime attribute when the response is generated (Wentura & Rothermund, 2003). Accuracy instructions might counteract this tendency, because participants will give the target features considerably more weight


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and will thus be more susceptible to differences between prime and target (Wentura & Rothermund, 2003). However, accuracy instructions involve the risk of getting no priming effects at all. Thus, we can consider varying instructions as an “adjustment tool” that helps identifying conditions that make the masked affective priming paradigm sensitive to the relevance type of primes and targets. STUDY 1 We start our exploration with an experiment that should guarantee to establish masked affective priming, using our materials and apparatus. Previous studies found stable masked priming effects especially if primes and targets were drawn from the same set of stimuli, such that over the course of the experiment the primes were presented as targets too (Abrams et al., 2002; Abrams & Greenwald, 2000; Draine & Greenwald, 1998). Method Participants Nineteen students (12 women; 7 men) participated in Study 1a. Ten participants were instructed to emphasize speed; nine participants were instructed to emphasize accuracy. The median age was 22.0 years; all of them were native speakers of German. One participant of the emphasis-onaccuracy sample was replaced because his mean overall response time was more than 2.5 standard deviation units below the mean response time of the emphasis-on-speed sample. Study 1b was done to further clarify a detail in


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the results of the emphasis-on-speed sample of Study 1a (see Results section). Ten students (eight women; two men) participated in this replication. They all received the speed instruction. The median age was 22.0 years; all of them were native speakers of German. Design In detail, the experiment was based on a 2 (target valence: positive vs. negative) x 2 (target relevance: other vs. possessor) x 2 (prime valence: positive vs. negative) x 2 (prime relevance: other vs. possessor) withinparticipants design. However, we can reframe the design as essentially two factors that were varied within participants. First, the congruence vs. incongruence of prime and target valences was manipulated. Second, it was manipulated whether prime and target belonged to the same or different category of relevance. A neutral prime condition was added to get a hint as to whether priming effects (i.e., the difference of RTs to congruent and incongruent conditions) were caused by interference or facilitation processes.2 For Study 1a, instruction (emphasis on speed vs. emphasis on accuracy) was manipulated between participants. In Study 1b, all participants received the speed instruction. Materials The stimulus set comprised 10 positive and 10 negative German adjectives (see Appendix). Within each valence set, five adjectives were other-relevant and five adjectives were possessor-relevant according to


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norm data (Wentura, Rothermund, & Bak, 1998). The adjectives had a length of five to eight letters. Mean length of the four type sets ranged from 5.60 letters to 6.40 letters. Absolute pleasantness (on a scale ranging from 0 to +100 was between 52 and 89; Hager, Mecklenbräuker, Möller, & Westermann, 1985; Möller & Hager, 1991). Mean absolute pleasantness of the four type sets ranged from 56 to 72. A string of six x’s was used as a neutral prime condition. Procedure Participants were tested either alone or in pairs. They were seated in front of standard personal computers separated by partition walls. Instructions were given on the CRT screen. Participants were told that they had to classify words with regard to their valence. Participants in the emphasis-on-speed samples received the following instruction: “Decide as quickly as possible. Of course, you should not make errors permanently (otherwise your data would be worthless); but the emphasis on speed might be somewhat at the cost of accuracy. Your error rate can be within the range of 15 to 20 %.” Participants in the emphasis-on-accuracy sample received the following instruction: “Decide quickly, but be as accurate as possible. Of course, you should decide quickly (otherwise your data would be worthless) but the emphasis on accuracy might be somewhat at the cost of speed. On average, your error rate should be below 3 %.” For participants of


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the emphasis-on-accuracy sample, a feedback (“Error!”) appeared on the screen in the case of a false response. Parameters of masked prime presentation were the same as those used by Otten and Wentura (1999) and Wentura et al. (2005). A randomly generated string of nine consonant letters (e.g., mlsdzkhwd) marked the beginning of the trial and also served as a forward mask. It remained on the screen for 300 ms and was then immediately replaced by the prime. Thus, as the prime word was always shorter than the forward mask, it was embedded into the string of random consonants (e.g., mlhonestwd). The prime remained on the screen for 43 ms (three refresh cycles) and was immediately replaced by a different randomly generated string of nine consonant letters that served as a backward mask and was displayed for 14 ms (one cycle). It was replaced by the target stimulus that remained on the screen until a response was given. The ‘positive’ response was assigned to the right index finger, the ‘negative’ response to the left index finger. The inter-trial interval was 2500 ms. At the beginning of the priming task, participants worked through 20 practice trials (i.e., each target word was presented once) in order to become familiarized with the task. After the practice trials, a summarized performance feedback was given, indicating the number of errors, the percentage of errors, and the mean RT. In the emphasis-on-speed sample, the following messages were added depending on participants' performance:


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(a) if the number of errors was less than two: “You have made very few errors. You should try to be faster and less cautious”; (b) if the number of errors was between 2 and 4: “Your error rate is appropriate. Continue to respond quickly”; (c) if the number of errors was above 4: “As an average value across the experiment, the error rate is somewhat too high”. In the emphasis-on-accuracy sample, the following messages were added for the emphasis-on-accuracy participants: (a) if there were any errors: “Try to be more cautious!” (b) if they had made no errors: “Continue to be accurate!”. The main part of the experiment consisted of three blocks of 100 trials each. Within a block, each target word was presented once in each of the five priming conditions, with the sequence determined by a Latin-square design. Each block was further subdivided into five 20-trial sequences. Each 20-trial sequence comprised each target word once, and was followed by the summarized feedback (see above). In each word-prime trial, the prime was randomly chosen from the list of the five possible stimuli, with the restriction that in each 20-trial sequence a prime word appeared only once. In the condition ‘congruent pairs of same relevance type,’ the program precluded the selection of a prime that was identical to the target. Following the main blocks, a direct test of prime identification was administered. Forty more trials (eight trials per prime) were presented that were identical with the trials of the main phase, except for the following detail. Instead of a target word, a row of nine question marks appeared in the


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center of the screen accompanied by two stimuli, one to the right and one to the left of the question marks. One of these words was a repetition of the prime and one was a distractor, which was drawn from the stimulus list with the constraint that it was always from the same valence and relevance type as the prime. The location of the prime repetition was determined at random. Participants were informed that the sequence of flickers preceding the question marks (i.e., the mask-prime-mask sequence) contained either the left or right word. They were instructed to identify this word (i.e., the prime) by pressing the corresponding key (i.e., the key assigned to the right index finger if they decided for the right word, the key assigned to the left index finger if they decided for the left word).3 Results Unless otherwise noted, all effects referred to as statistically significant are associated with p values less than .05, two-tailed. All priming analyses were performed using both subjects (referred to by t1, F1) and item (t2, F2) means. Manipulation check Mean reaction times were derived from correct responses only. Reaction times that were three interquartile ranges above the third quartile with respect to the individual distribution were discarded (see Tukey, 1977), as were those above 1500 ms, or below 150 ms (0.96 %, 0.70 %, and 0.83 % of all values of the emphasis-on-accuracy sample and the emphasis-on-speed


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samples [Exp. 1a and 1b], respectively). The emphasis-on-speed sample (Exp. 1a) had a mean RT of M = 527 ms (SD = 40 ms), whereas the emphasis-on-accuracy sample had a mean RT of M = 587 ms (SD = 64 ms); this constitutes a significant difference, t(17) = 2.48. The emphasis-on-speed sample (Exp. 1a) had a mean error rate of M = 9.5 % (SD = 2.7 %), whereas the emphasis-on-accuracy sample had a mean error rate of M = 2.4 % (SD = 1.3 %); this again constitutes a significant difference, t(12.99) = 7.37. The emphasis-on-speed samples of Study 1a and 1b did not significantly differ neither with regard to mean RT (M[Exp. 1b] = 543 ms; SD = 43 ms), t(18) = 0.85, ns, and mean error rate (M[Exp. 1b] = 8.0 %; SD = 4.1 %), t(18) = 0.95, ns. Priming effects (Study 1a) The Block factor did not significantly moderate the priming results. Thus, this factor was discarded. To simplify the presentation of results, priming indices were calculated as the difference of incongruent and congruent mean RTs. Mean reaction times for the conditions of interest are shown in Table 1. A 2 (instruction: emphasis on speed vs. accuracy) x 2 (prime-target relevance: same vs. different) analysis of variance with the priming indices as the dependent variable yielded a significant interaction of instruction and relevance, F1(1,17) = 8.36, MSe = 179; F2(1,19) = 8.14, MSe = 481, all other Fs < 1.


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In the emphasis-on-speed sample, there no moderation of priming by relevance match was found, t1(9) = 1.73, p > .10; t2(19) = 1.46, p > .16. For both relevance types, a significant and marked priming effect emerged for prime-target pairs of the same relevance type, t1(9) = 2.93, d1 = 0.93; t2(19) = 2.19, d2 = 0.49, and for prime-target pairs of different relevance types, t1(9) = 4.57, d1 = 1.45; t2(19) = 5.86, d2 = 1.31, respectively. On the contrary, in the emphasis-on-accuracy sample, the priming effect was significantly moderated by relevance match, t1(8) = 2.34, d = 0.78; t2(19) = 2.37, d = 0.53. There was a marked and significant priming effect for primetarget pairs of the same relevance type, t1(8) = 4.25, d1 = 1.42; t2(19) = 4.11, d2 = 0.92, whereas no priming effect occurred for prime-target pairs of different relevance types, t1(8) = 1.12, ns, d1 = 0.37; t2(19) = 1.49, ns, d2 = 0.33. Mean error rates for the conditions of interest are shown in Table 1. In a 2 (instruction: emphasis on speed vs. accuracy) x 2 (prime-target relevance: same vs. different) analysis of variance with priming indices as the dependent variable, a significant main effect of instruction occured, F1(1,17) = 7.49, MSe = 24.2; F2(1,19) = 12.03, MSe = 31.75, all other Fs < 1. There was a significant priming effect for the emphasis-on-speed sample, M = 4.8 %, t1(9) = 3.38, d1 = 1.07; t2(19) = 4.78, d2 = 1.07, whereas there was no priming effect for the emphasis-on-accuracy sample, M = 0.5 %,


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both |t1|s < 1. Priming was not moderated by relevance match in either sample, all |t|s < 1. Priming effects (Study 1b) In the emphasis-on-speed sample of Study 1a, there was a slight numerical (but non-significant) difference between priming effects for same and different relevance in an unexpected direction (12 ms vs. 22 ms). To test whether this difference is replicable, we conducted Study 1b. Mean reaction times for the conditions of interest are shown in Table 1. In a 2 (prime-target relevance: same vs. different) x 2 (affective priming: congruent vs. incongruent) analysis of variance there was nothing but a significant main effect of affective priming F1(1,9) = 14.40, MSe = 297; F2(1,19) = 29.94, MSe = 350, indicating an affective congruency effect (all other Fs < 1). For both relevance types, a significant and marked priming effect emerged: t1(9) = 3.60, d1 = 1.14; t2(19) = 4.71, d2 = 1.05, for prime-target pairs of the same relevance type, t1(9) = 2.11, d1 = 0.67, p < .05 (one-tailed); t2(19) = 3.90, d2 = 0.78, for prime-target pairs of different relevance types. The results for the error rates are comparable to those for RTs (see Table 1). In a 2 (prime-target relevance: same vs. different) x 2 (affective priming: congruent vs. incongruent) analysis of variance, there was nothing but a significant main effect of Affective Priming F1(1,9) = 8.71, MSe = 22.4; F2(1,19) = 24.58, MSe = 15.9, indicating an affective congruency effect (both Fs < 1 for relevance and both Fs < 2.57, ns for the interaction).


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Direct effects (Study 1a) The signal detection sensitivity for the masked primes was d’ = .32 (SD = .50; range of -0.13 to 0.65 plus one outlier with d’ = 1.56) for the emphasis-on-speed sample and d’ = .17 (SD = .29; range of -0.29 to 0.63) for the emphasis-on-accuracy sample, t(17) = 0.77, ns, for the difference. Although the overall mean d’ of M = 0.25 (SD = .41) was significantly above zero, t(18) = 2.65, there was only one participant with a significant contingency between the position of the prime repetition (i.e., to the left or to the right of the question marks) and response (left or right key), χ2 > 11.31, all other χ2s < 3.28, p > .07. We followed the suggestion by Draine and Greenwald (1998) to regress the priming indices (i.e., the difference variable ‘incongruent minus congruent priming’) on d’. Since both variables have a meaningful neutral point, the intercept can be interpreted as the amount of priming in the absence of awareness (i.e., d’ = 0). We regressed the RT priming indices on d’, separately for the speed and the accuracy sample. Table 1 includes the intercepts (and their standard errors). For the emphasis-on-speed sample, both intercepts were significantly above zero, t(8) = 2.00, p < .05 (onetailed; t(8) = 0.62, ns, for the slope) for prime-target pairs of same relevance type, t(8) = 3.23 (t(8) = 1.03, ns, for the slope) for prime-target pairs of different relevance type. For the emphasis-on-accuracy sample, the intercept for prime-target pairs of same relevance type was significantly above zero,


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t(7) = 3.20 (t(7) = 0.41, ns, for the slope), whereas the intercept for primetarget pairs of different relevance type failed to be different from zero, t(7) = 0.30, ns (t(7) = 1.30, ns, for the slope). Direct effects (Study 1b) The mean signal detection sensitivity for the masked primes was d’ = .29 (SD = .53; range of –1.07 to 0.65), t(6) = -1.48, ns.4 For prime-target pairs of the same relevance type, the intercept was significantly above zero, t(5) = 2.20, p < .05 (one-tailed; t(5) = -0.77, ns, for the slope). Interestingly, the intercept for prime-target pairs of different relevance type failed to be significantly above zero, t(5) = 0.40, ns (t(5) = -1.22, ns, for the slope). Discussion Study 1 revealed two essential results. Given instructions to emphasize speed, a robust, replicable, and undifferentiated affective priming effect emerged. This result is in line with several other studies published during the last decade (e.g., Draine & Greenwald, 1998). Not unexpectedly, the priming effect was not moderated by a match or mismatch of prime and target relevance. However, given instructions to emphasize accuracy, a moderation by match of relevance type was observed. If prime and target belonged to the same type of relevance with regard to the distinction introduced by Peeters (1983), a significant positive priming effect was observed. If the relevance types of prime and target were different, priming was no longer found. These results at indicate that affective priming effects


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are susceptible to the kind of positivity or negativity of primes and targets. Thus, we can infer that the relevance type of valence is in fact a feature of valent stimuli that is activated under conditions of limited processing and limited awareness. However, one caveat remains with regard to this conclusion. As we have already noted, masked affective priming effects are especially observed if primes are practiced, for example, if primes and targets are drawn from the same set of stimuli (as in Study 1; see Abrams & Greenwald, 2000; Abrams & Grinspan, 2007). Several explanations of the masked affective priming effect focus on this detail. For example, Damian (2001) argued that masked affective priming effects are based on stimulusresponse mappings that become automatized during the course of the experiment. If we attribute our results to this process, we can easily explain the undifferentiated character of the priming effect under speed instructions: This instruction might not only increase the weight of the prime relatively to the target in quickly establishing a response, it might induce a strategy to simply respond on the first evidence available without paying attention to the source of this evidence, that is, whether it stems from the masked prime or the target (Wentura & Rothermund, 2003). Thus, this condition might quickly lead to stimulus-response associations that are blurred with regard to the relevance distinction, because ultimately only a simple positive or negative response has to be given.


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By contrast, accuracy instructions induce a strategy to respond only on the basis of the correct evidence – evidence unambiguously attributable to the target (Wentura & Rothermund, 2003). This can explain that primes that are congruent to the target with regard to valence but not with regard to relevance do not facilitate target responses because the sources of evaluative information can be disentangled on the basis of relevance. Similarly, primes and targets that are incongruent in valence can always be disentangled (irrespective of their relevance). Primes, however, that are congruent to the target with regard to both features facilitate the responding because there is no indication of a wrong source of evidence. This explains why there is affective priming only for pairs matching in relevance but no effect for nonmatching pairs. Essentially, stimulus-response associations evolving throughout the course of the experiment might become more sophisticated than simple positive-negative responses and thus contain connotations of relevance. If this explanation fits, we are faced by somewhat disappointing implications about the automatic processing of the relevance feature. The priming effect that is differentiated according to relevance might be a mere side effect of a deeper processing of the targets, given accuracy instructions: To disentangle sources of evidence, the target is more deeply processed than is needed for a superficial positive versus negative categorization. Eventually, stimulus-response associations are stored including valence and


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relevance and will later be easily retrieved if the same word is presented as a prime. Recently, however, Klauer, Eder, Greenwald, and Abrams (2007) showed masked affective priming with novel stimuli, that is, with stimuli never presented for classification during the course of the experiment. They explicitly argued for a two-component explanation of masked priming: One component is based on response-related stimulus-associations and depends on practice. Another smaller component is based on long-term stored features of the masked prime. Given these considerations, it is important to explore the meaning of the relevance distinction in an experiment that rules out automatized response mappings by using primes that are never openly presented for classification. In addition, this manipulation is important for another reason. Given our goal to corroborate our findings in the area of indirect assessment of attitudes, it is even more important to explore priming effects caused by novel stimuli, since it is a conditio sine qua non in this field of research that the attitude-related primes are never presented for evaluative categorization. STUDY 2 Study 2 is an almost exact copy of Study 1 except that primes and targets were now from different stimulus sets. That is, primes were neither categorized nor even consciously visible throughout the task. Again, we explored affective priming given speed versus accuracy instructions,


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although the reason for doing so was somewhat different than before. Given overall sparse and weak evidence of priming with novel masked primes, which, however, were always found with speed instructions, we used the speed instruction condition simply for establishing a condition that might be needed for obtaining priming at all. Method Participants Study 2 included two independent recruitments of participants. The only difference between Study 2a and 2b was that Study 2b lacked the direct test. A total of fifty-eight students (51 women; 7 men) participated in the experiments (29 participants for Study 2a and 2b, respectively). 30 of them were instructed to emphasize speed, 28 were instructed to emphasize accuracy. The median age was 21.0 years; all of them were native speakers of German. Two participants of the emphasis-on-accuracy sample were replaced because their mean overall response time was more than a standard deviation unit below the mean response time of the emphasis-on-speed sample. Design, Materials, and Procedure Design and Procedure were essentially the same as in Study 1. Now, primes and targets were taken from different stimulus sets. Both, the prime and the target set, comprised 10 positive and 10 negative German adjectives (see Appendix). Within each valence subset, five adjectives were other-


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relevant and five adjectives were possessor-relevant according to norm data (Wentura et al., 1998). Absolute pleasantness (on a scale ranging from 0 to +100; Hager et al., 1985; Möller & Hager, 1991) was between 50 and 87 (prime list) and between 50 and 72 (target list). Mean absolute pleasantness of the four type sets ranged from 60 to 68 (prime list) and from 57 to 66 (target list). To bolster dissimilarity between primes and targets, we selected short adjectives (four to six letters) for the prime list and long adjectives (seven to nine letters) for the target list. Mean length of the four type sets ranged from 4.4 letters to 5.6 letters (prime list) and from 8.0 letters to 8.8 letters (target list). Since it is known that the response-related component of priming might already be triggered by fragments of practiced stimuli (Abrams & Greenwald, 2000), we made sure that there was no confound of matching letters between prime and target for the different conditions (see also Klauer et al., 2007). Therefore, we calculated the overlap of single letters, letter pairs, and letter triplets for each combination of prime and target. Mean overlap for those prime-target combinations matching in valence and relevance was M = 1.97 for single letters (compared to M = 1.94 for the remaining combinations; t[19] = .31, ns), M = 0.23 for letter pairs (compared to M = 0.21; t[19] = .29, ns), and M = 0.04 for triplets (compared to M = 0.02; t[19] = .85, ns). Results


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With the exception of results related to the direct test, we present the data collapsed across Experiments 2a and 2b because experiment (as a factor) did not modify any of the reported results. Manipulation check The emphasis-on-speed sample had a mean RT of M = 531 ms (SD = 67 ms) whereas the emphasis-on-accuracy sample had a mean RT of M = 580 ms (SD = 67 ms); this constitutes a significant difference, t(56) = 2.77. The emphasis-on-speed sample had a mean error rate of M = 11.9 % (SD = 8.7 %), whereas the emphasis-on-accuracy sample had a mean error rate of M = 2.6 % (SD = 2.1 %); this again constitutes a significant difference, t(32.54) = 5.66. Priming effects Mean reaction times were derived from correct responses only. Reaction times that were three interquartile ranges above the third quartile with respect to the individual distribution were discarded (see Tukey, 1977), as were those above 1500 ms, or below 150 ms (0.73 % and 0.98 % of all trials of the emphasis-on-speed sample and the emphasis-on-accuracy sample, respectively). The block factor did not significantly moderate the priming results and was thus discarded. Mean reaction times for the conditions of interest are shown in Table 2. To simplify the presentation of results, priming indices were calculated as the difference of incongruent and congruent mean RTs.


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Most importantly, in the emphasis-on-speed sample, a significant priming effect occurred for trials matching according to relevance type, t1(29) = 5.01, d = .91; t2(19) = 3.91, d = .88, but not for mismatching trials, both |t|s < 1, ns. The difference between the two priming effects was significant, t1(29) = 3.07, d = .56; t2(19) = 2.11; d = .47. Not unexpectedly, for the emphasis-on-accuracy sample, there was no priming effect at all, with t1(27) = 1.37, ns; t2(19) = 1.32, ns, for the overall priming effect, and both |t|s < 1, ns, for the difference between relevance-matching and nonmatching priming effects. For the sake of completeness, the interaction effect in a 2 (instruction: emphasis on speed vs. accuracy) x 2 (prime-target relevance: same vs. different) analysis of variance with the priming indices as the dependent variable was significant, F1(1,56) = 5.88, MSe = 239; F2(1,19) = 3.64, p < .05 (one-tailed)5, MSe = 236, thereby allowing to solely focus on the effects in the speed condition. Mean error rates for the conditions of interest are shown in Table 2. In a 2 (instruction: emphasis on speed vs. accuracy) x 2 (prime-target relevance: same vs. different) analysis of variance of priming indices, there were no significant effects, all |F|s < 1. Overall, there was a small positive priming effect of M = 1.2 %, d = .33, t1(57) = 2.52; t2(19) = 3.03. Direct effects The signal detection sensitivity for the masked primes was d’ = .29 (SD = .39; range of -0.49 to 1.05) for the emphasis-on-speed sample and d’ = .24


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(SD = .57; range of -0.51 to 0.90 plus one outlier with d’ = 1.71) for the emphasis-on-accuracy sample, t(27) = 0.31, ns, for the difference. Although the overall mean d’ of M = 0.27 (SD = .48) was significantly above zero, t(28) = 2.99, there were only three participants with a significant contingency between the position of the prime repetition in the task display (i.e., to the left or to the right of the question marks) and response (left or right key), χ2 > 5.16, all other χ2 < 3.47, p > .05. We regressed the RT priming indices for the emphasis-on-speed sample on d’ (see Table 2). 6 For prime-target pairs of same relevance type the intercept was significantly above zero, t(13) = 5.88 (t(13) = -1.65, ns, for the slope), whereas the intercept for prime-target pairs of different relevance type failed to be different from zero, t(13) = 0.79, ns (t(13) = -0.11, ns, for the slope). Discussion Study 2 revealed a masked affective priming effect with unpracticed primes. This is inherently a noteworthy result, because evidence for masked affective priming with non-practiced items has been rather sparse up to now (but see Klauer et al., 2007). This effect, however, only emerged for primetarget pairs belonging to the same type of relevance, given speed instructions. In other words: if we assume that accuracy instructions lead to a lower weight for prime features in creating a response, it seems as if primes without episodic response associations are to weak to affect the response to the target. Given speed instructions, however, only evidence


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unequivocally matching or mismatching the target feature needed for classification influences the response. STUDY 3 Interpretation of the results of Study 1 and 2 remains preliminary regarding one possible objection. It is rather inevitable that the 2x2 variation of valence-congruency and relevance match is somewhat confounded with semantic relatedness. Words within one relevance subtype of valence might be semantically related to each other but not to words of the other relevance subtype. Even if no direct associative links exist, halo effects might be stronger within a relevance subtype of the valence categories than across subtypes. To account for this possible confound, we endorsed the following strategy: We collected semantic association ratings for each word pair that was presented as prime-target pair in Study 1 and Study 2. We used these ratings for individual regression analyses for the samples of interest of Study 1 (i.e., the accuracy sample) and Study 2 (i.e., the speed sample), using trials as the unit of analysis (see Lorch & Myers, 1990; see, e.g., Otten & Wentura, 2001, for an application). In a first step, response times were regressed on three predictors, that is, two variables coding (a) valence congruency and (b) relevance (both coded with +0.5 vs. -0.5), as well as (c) their product term to account for the interaction of valence congruency and relevance. Note that the mean of the individual regression weights for the product term corresponds to the mean difference between priming for pairs


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matching in relevance and those non-matching in relevance. Thus, the test for deviance from zero for the mean regression weight corresponds to the interaction test in the 2 (valence congruency) x 2 (relevance match) design of Study 1 and 2. In a second step, we added the semantic similarity rating of a given prime-target pair as a further predictor in the individual regression analyses. If the interaction effects between valence congruency and relevance match found in Study 1 and Study 2 were due to semantic similarity, this predictor should be associated with a mean regression weight that significantly deviates from zero whereas the mean regression weight for the interaction term of valence congruency and relevance should no longer be significant. Method Participants For Study 3a, eight students (5 women; 3 men; median age 26.0 years) rated the semantic similarity of all possible prime-target combinations of Study 1. For Study 3b, eight students (4 women; 4 men; median 22.0 years) rated the semantic similarity of all possible prime-target combinations of Study 2. All of them were native speakers of German. Materials and Procedure For Study 3a, the rating list consisted of all possible prime-target combinations of Study 1, that is, 190 word pairs. For reasons of comparison and to provide participants with anchors, each of the 20 primes and targets


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was additionally paired with one synonym and one antonym — resulting in 40 additional word pairs. Thus, each participant rated 230 word pairs. For Study 3b, the rating list consisted of all possible prime-target combinations of Study 2, that is, 400 word pairs. Again, each of the 20 primes and 20 targets were additionally paired with one synonym and one antonym. Thus, each participant rated 480 pairs. Participants were tested alone on a standard personal computer. Instructions were given on the CRT screen. Participants were told that they were presented with pairs of adjectives and that they had to rate the semantic similarity of the two words on a scale from -4 (denoting an antonym) over 0 (denoting no relationship) to +4 (denoting a synonym). If both words denote roughly the same (i.e., can be used interchangeably in most cases) – as, for example, intelligent and smart – participants were instructed to use a value of +4. If both words denote roughly the opposite of one another – as, for example, intelligent and stupid – they were instructed to use a value of -4. If both words had nothing in common – as, for example, intelligent and enamored – they were instructed to use a value of 0. The values in between should be used with regard to semantic overlap, for example, slightly different contexts of usage or a more narrow or broader term – for example, intelligent and talented. Participants worked through the individually randomized list of 230 (Study 3a) or 480 (Study 3b) trials. Results


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Descriptive statistics Interrater reliability was very high (Cronbach’s Alpha = .95, and .91, for Study 3a and 3b, respectively). Mean ratings are listed in Table 3. Two observations should be noted. First, synonyms and antonyms were associated with large (absolute) rating values as expected. In comparison, the mean ratings for the prime-target pairs of Study 1 and 2 were rather low. Second, valence-congruent pairs of the same relevance type were indeed associated with larger similarity ratings compared to valence-congruent pairs of the different relevance type, whereas valence-incongruent pairs of same relevance type were associated with lower ratings compared to their incongruent pairs of the different relevance type.7 Thus, there was indeed a slight confound between the priming variation of interest and semantic similarity. Therefore we adopted the regression approach explained above to test for the alternative explanation that semantic similarity and not match in relevance was the determining factor in the priming task of the accuracy sample. Mean ratings across raters were taken as the indicator of semantic similarity for a given pair. Regression analyses for Data of Study 1 (accuracy condition) First, individual multiple regressions were calculated with trials as the unit of analysis, the response times as the dependent variable, and two variables coding valence congruency, relevance (both coded with +0.5 vs. 0.5), as well as their product term as predictors. The mean individual


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regression weight for the interaction term significantly deviated from zero, M(B) = 15 (SE = 6), t(8) = 2.31. This result is equivalent to the analyses with the aggregated measures: The mean regression weight for the interaction term corresponds to the difference between priming for pairs matching in relevance and those non-matching in relevance (see Table 1).8 Second, the semantic relatedness ratings of prime-target pairs were added as additional predictors. If semantic similarity is the determining factor in the priming task, this predictor should be associated with a mean regression weight that significantly deviates from zero whereas the mean regression weight for the interaction term of valence congruency and relevance should no longer be significant. However, the mean individual regression weight for the rating did not significantly deviate from zero, M(B) = -0.58 (SE = 4.00), t(8) = 0.14, ns. Also, the mean individual regression weight for the interaction term valence congruency by relevance remained significant, M(B) = 18 (SE = 9), t(6) = 2.12, p < .05 (one-tailed).9 Regression analyses for Data of Study 2 (speed condition) We conducted the same kind of analysis for the speed condition of Study 2. In an analysis with two variables coding valence congruency, relevance (both coded with +0.5 vs. -0.5), and their product term, the mean individual regression weight for the interaction term was M(B) = 9 (SE = 3), t(29) = 2.74. Again, the added mean semantic relatedness ratings for each given prime-target pair as additional predictors did not yield a significant


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regression weight, M(B) = -0.51 (SE = 1.51), t(29) = 0.34, ns. The mean individual regression weight for the interaction term of valence congruency and relevance remained significantly deviant from zero, M(B) = 8 (SE = 4), t(29) = 1.98, p < .05 (one-tailed). Discussion With Study 3, we explored whether semantic relatedness might be an alternative explanation for our results. In individual regression analyses, semantic relatedness ratings for the given prime-target pairs served as competing predictors to the interaction term of valence congruency and relevance match. The results were clear: Semantic relatedness did not mediate the priming effects found in Study 1 and Study 2. GENERAL DISCUSSION The experiments reported here were designed to reveal a differentiation of automatic evaluation in the masked affective priming paradigm, as well as its boundary conditions. Taken together, with regard to our main goal the results are clear-cut and demonstrate that affective priming effects – given some specified conditions – were moderated by the relevance distinction introduced by Peeters (1983): affective priming was only found when prime and target stimuli were of the same type of relevance. If there was no match in relevance, affective priming decreased to non-significant levels. This result is important for several reasons. Most of all, it corroborates the claim that the distinction between other-relevant and possessor-relevant valence is


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encoded at a very basic level of representation and is involuntarily activated upon stimulus presentation. Although Wentura and colleagues (2000) had provided first evidence that the distinction of possessor-relevant and otherrelevant valence is a deeply built-in feature of our cognitive-affective system, the present experiments take a step forward. In detail, Wentura and colleagues found increased color-naming latencies in an emotional Stroop paradigm for other-relevant stimuli compared to possessor-relevant stimuli. Thus, it was merely shown that other-relevant stimuli are associated with special processing qualities. Also, the color-naming task was not suited to disentangle positive and negative other-relevant stimuli. The present experiments, however, indicate that the combination of valence and relevance is indeed automatically processed. Moreover, we were able to show that the differentiation is preserved even given masked presentation conditions. With Study 1 and Study 2 we realized two fundamentally different ways of testing for masked priming effects. In Study 1, we used practiced primes by drawing primes and targets from the same set of stimuli (of course by avoiding identity of prime and target in a given trial). It is known that using practiced primes lead to robust priming effects, especially given speed instructions. In fact, in Study 1, the moderation of priming by relevance only occurred when if participants were instructed to sacrifice speed in favor of accuracy. In Study 2, we used primes that were never openly presented


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for evaluative categorization. Recently, Klauer and colleagues (2007) provided evidence for the existence of masked affective priming effects using non-practiced primes. Results of Study 2 corroborate this general claim. Most importantly, we found priming effects being moderated by relevance. This result was bound to speed instructions. No significant priming effects occurred given accuracy instructions, which fits to the results of Klauer and colleagues who found masked affective priming effects with novel primes with a variant of speed instructions. How does this differentiated pattern of results match to existing theories explaining affective priming? It has been shown that affective priming effects in the evaluation task presumably reflect response competition processes (Klauer, Roßnagel, & Musch, 1997; Wentura, 1999; see also Fazio, 2001). The evaluation task, however, only demands a simple positive or negative response. Thus, affective priming effects are easily explainable by assuming that the positive or negative primes are involuntarily processed according to their valence such that the evoked classification helps or hinders the classification of the target. Because this classification is a simple positive versus negative categorization, it seems at first sight rather surprising to find moderation by type of relevance. Note, however, the simple fact that the prime does not entirely determine the response in response priming paradigms (in this case congruent trials would be error free and incongruent trials would result in 100% errors). Thus, the degree of


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fit between the involuntary response-related classification of the prime and the controlled processing of the target plays a major role in determining the response. We assume that the relevance type of positivity and negativity is an inescapable and early part of evaluation – that is, pressing the “negative” key to, for example, the target “lonely” means to categorize “lonely” as possessor-relevant negative. Thus, the prototypical case of matching processing paths (resulting in response facilitation) is only given if prime and targets are valence congruent and of the same type of relevance. On the contrary, in valence-incongruent but relevance-matching trials, the preparatory response triggered by the prime stands in contrast to an upcoming response due to processing of the target. Thus, a clear affective priming effect emerges if prime and targets are from the same relevance type. If there is a mismatch in relevance type, the preparatory classification triggered by the prime neither perfectly matches (in case of valence congruency) nor mismatches (in case of incongruency) first results from processing the target. Thus, affective priming will not be obtained. How does this explanation fit with our results in detail? Note again the difference between using practiced (Study 1) vs. non-practiced primes (Study 2). As we have argued above, this difference in procedure can be linked to the theoretical difference between two components of masked priming (Klauer et al., 2007). One component is response-related, depends on practice, and is therefore observed if primes and targets are from the


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same stimulus set and – we can add, given former studies – if participants are instructed to sacrifice accuracy in favor of speed. Unsurprisingly, in this case the acquired response association is an undifferentiated positive or negative one, given that the evaluation task only asks for a simple positive versus negative categorization. This component of masked affective priming overshadows a second one which is caused by long-term stored features of stimuli and which is prototypically found with non-practiced primes as in our Study 2. As can be seen from Study 2, in this case the differentiation according to type of relevance clearly shows up. Finally, the results of the accuracy condition of Study 1 can be interpreted in two ways. As we have already argued above (see Discussion of Study 1), it might be that automatized stimulus-response associations contain the feature of relevance because accuracy instructions lead to a more differentiated processing of targets. Then, the prime event acts as a cue to this episode. If this was the case, Study 1 (accuracy condition) shows the moderation of priming by relevance as a by-product of target processing. However, given the backdrop of Study 2, we can interpret the same results in line with Study 2: If accuracy instructions undermine the generation of strong stimulus-response associations, the priming effect might reflect the second component of masked affective priming, that is, the retrieval of longterm features. This component shows up in Study 1 (accuracy condition) but


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not in the accuracy condition of Study 2 because practice facilitates access to the long-term representation of the prime. It is beyond the aims of the present article to decide between the two accounts of the accuracy condition of Study 1. At this point of the discussion we should frankly address one caveat. This article is not dominantly about the specific pattern of differentiation in priming found with practiced versus non-practiced primes. To corroborate such a claim a further experiment has to be conducted comprising a replication of the present Experiment 1 and 2, thereby employing the manipulation of practiced versus non-practiced primes as a further factor. It was beyond our present goal to provide this evidence. Our emphasis is on the point that if the relevance distinction is included in the design, we can find – at least given some conditions – affective priming for a match in relevance type of prime and target whereas priming is missing for a nonmatch in relevance. That is what we have shown. It was rather clear from the start on that this differentiation might not turn out given any conditions. On the one hand, the robustness of masked priming effects found with practiced primes and speed instructions reported in the literature (e.g., Draine & Greenwald, 1998) as well as the tiny effects found with nonpracticed primes (e.g., Klauer et al., 2007) even if speed instructions are used were hints to this issue. To summarize: it was not our theoretical point to find exactly the observed pattern of priming effects. It was our aim to find


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evidence for a dependency of affective priming on relevance match at all, of course with the constraint that boundary conditions should fit the pattern of evidence that is generally known about affective priming. The finding of relevance-specific affective priming effects should not be confused with semantic priming effects in the tradition of Meyer and Schvanefeldt (1971; for reviews see Lucas, 2000; McNamara & Holbrook, 2003; McNamara, 2005; Neely, 1991). First, although very similar at surface, semantic priming experiments have a completely different design: in contrast to affective priming, the essential variation (i.e., whether a semantically related or unrelated prime precedes the target) is not confounded with the response needed (i.e., a lexical decision or naming of the target; see, e.g., Klinger, Burton, & Pitts, 2000; Wentura, 2000, Wentura & Degner, in press, for a discussion). Second, in semantic priming research, no robust priming effects of category coordinates (e.g., if rose-tulip is the prime-target pair) were found (Lucas, 2000; Hutchison, 2003). Also, affective priming effects do typically not occur in semantic priming studies (e.g., De Houwer et al., 2002; but see Spruyt et al., 2002, 2004, 2007). Third, we found no evidence for semantic relatedness in Study 3. Fourth, the evidence for masked semantic priming is rather sparse (see, e.g., Wentura & Frings, 2005). Taken together, we assume that automatic affective evaluation processes is not located at the same level of processing as semantic priming effects.


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Finally, our findings have important implication for the application of the affective priming task to the indirect assessment of (social) attitudes. If automatic evaluations are a basis of attitudes that guide approach and avoidance behavior (Han, Olson, & Fazio, 2006), it is of high relevance to dissociate types of automatic evaluations. We want to give only one example of the field of intergroup attitudes. Different outgroups, for example the elderly on the one hand or ethnic outgroups on the other hand, are associated with automatic negativity. However, behaviour towards members of these groups might differ fundamentally based on the type of negativity associated with the groups: Whereas possessor-relevant negativity associated with the elderly might lead to approach and helping behaviour (e.g., paternalistic talk, other-relevant negativity associated with ethnic outgroups might be associated with avoidance or aggressive approach behaviour. There is first evidence, that possessor- and other-relevant associations do indeed play a role in automatic social attitudes (e.g. Degner et al., 2007; Wentura et al., 2005). However, further research is needed to explore their relations to attitude-related behaviours. The current research illustrates that the affective priming task can be an adequate tool for this.


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663. Wentura, D., & Rothermund, K. (2003). The "meddling-in" of affective information: A general model of automatic evaluation effects. In J. Musch & K. C. Klauer (Eds.), The psychology of evaluation: Affective processes in Cognition and Emotion (pp. 51-86). Mahwah, NJ: Lawrence Erlbaum. Wentura, D., Rothermund, K., & Bak, P. (1998). [Ratings for possessorvs. other-relevance of adjectives]. Unpublished data. Wentura, D., Rothermund, K., & Bak, P. (2000). Automatic vigilance: The attention-grabbing power of approach- and avoidance-related social information. Journal of Personality and Social Psychology, 78, 1024-1037. Wilcox, R. R. (1997). Introduction to robust estimation and hypothesis testing. Wilcox, R. R. (1998). How many discoveries have been lost by ignoring modern statistical methods? American Psychologist, 53, 300-314.


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Author Note Dirk Wentura, Department of Psychology, Saarland University, Saarbrücken, Germany. Juliane Degner, Department of Social Psychology, University of Amsterdam, The Netherlands. The research reported in this article was supported by a grant from the Deutsche Forschungsgemeinschaft (DFG) to Dirk Wentura (WE 2284/3). Correspondence concerning this article should be addressed to Dirk Wentura, Department of Psychology, Saarland University, Building A2 4, P.O. Box 15 11 50, 66041 Saarbrücken, Germany, e-mail: [email protected].


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Footnotes

1

Of course, other tasks (e.g., pronouncing the target, see, e.g., Bargh, Chaiken, Raymond, & Hymes, 1996; Hermans, De Houwer, & Eelen, 1994, Spruyt, Hermans, De Houwer, & Eelen, 2002, 2004, deciding whether it is a legal word, see, e.g., Wentura, 2000, non-affective semantic categorisation, see, e.g., De Houwer et al., 2002, Spruyt, Hermans, De Houwer, & Eelen, 2007, or naming the color in which it is presented, see, e.g., Hermans, van den Broeck, & Eelen, 1998, Rothermund & Wentura, 1998) were employed as well (see, e.g., Klauer & Musch, 2003, for a review). However, the evaluative decision task is the basic task of affective priming research. It is associated with unequivocal results, a process theory that cannot be applied to the other tasks, and is supposedly the only one yielding masked (subliminal) effects which are the focus of the present research.

2

This point should not be overemphasized, though. A simple consideration shows that the comparison of mean RTs for congruent and incongruent trials with the neutral baseline is ambiguous: assume that mean RT for congruent trials is 500 ms and mean RT for incongruent trials amounts to 530 ms. If mean RT for the neutral baseline is M = 530 ms, it seems as if priming was entirely due to facilitation. Now assume that negative primes have an additional main effect (e.g., besides facilitating negative responses for most of the trials they capture attention in some trials, thereby increasing RTs for positive as well as negative targets). This main effect will increase mean RTs for the congruent as well as for the incongruent


51

condition. To extend our example, if this increase amounts to 30 ms, we face a result suggesting that priming is entirely due to interference, which is, however, is not the case. 3

We decided for this version of test because it constitutes what was recently termed a test of “partial awareness” (Abrams & Grinspan, 2007; Kouider & Dupoux, 2004): Any remnant of surface features of the prime (e.g., a letter or a letter pair) helps participants to select the correct answer even if the masked prime was not processed on a semantic level.

4

There were three missing cases for the direct test because their responses were not adequately recorded (probably due to using the wrong keys during the direct test).

5

Because an F-test with one degree of freedom is equivalent to a t-test (with differences as the dependent variables) and given our specific predictions, a one-tailed test is allowed (see Maxwell & Delaney, 1990, p. 144).

6

For the emphasis-on-accuracy sample, both intercepts were not significantly different from zero (see Table 2).

7

We refrained from statistical tests because assumptions of independence are likely violated due to the use of the same words in different pairings.

8

The two kinds of analyses would provide exactly the same result if there would have been no missing trials. That is, any differences are only due to minor differences in error rates and outlier rates for the different conditions. The correlation between the individual difference value between priming for pairs matching in relevance and those non-matching in relevance and the individual regression weight for the interaction term


52

is r = .996. 9

A t-test for trimmed means (see Wilcox, 1997, 1998 ) ωιτη α τριµµινγ οφ γ = .11 was done to adequately account for one outlying regression weight.

Masked priming in the evaluation task

53

Table 1 Mean Response Times (in ms) and Error Rates (in %, in parentheses) as a Function of Prime Condition and Instruction (Study 1) Priming Congruent Incongruent Study 1a Emphasis on Speed Same Relevance Type Different Relevance Type Emphasis on Accuracy Same Relevance Type Different Relevance Type

Study 1b (Emphasis on Speed) Same Relevance Type

520 (7.0) 518 (7.5)

532 (12.0) 541 (12.2)

572 (2.0) 591 (2.4)

594 (2.6) 598 (2.8)

APa

Ib

12 [4]

10

[5]

22 [5]

19

[6]

22 [5]

20

[6]

7 [6]

2

[7]

532 553 21 [6] 20 [9] (5.5) (11.7) Different Relevance Type 535 555 20 [10] 6 [15] (6.7) (9.3) Note: Mean response time for the neutral prime condition was 523 ms, 539 ms, and 580 ms for the emphasis-on-speed samples of Exp. 1a and 1b, and the emphasis-on-accuracy sample, respectively. a Affective Priming: Mean of incongruent minus congruent prime condition; standard errors in brackets. b Intercept of regression of affective priming on d’; standard errors in brackets.


54

Table 2 Mean Response Times (in ms) and Error Rates (in %, in parentheses) as a Function of Prime Condition and Instruction (Study 2) Priming Congruent Incongruent Emphasis on Speed Same Relevance Type

Different Relevance Type

Emphasis on Accuracy Same Relevance Type

APa

Ib

526 (11.9)

539 (12.9)

13 [4]

21

[6]

532 (10.5)

534 (12.4)

2 [4]

4

[6]

582 584 2 [3] 5 [8] (2.1) (2.9) Different Relevance Type 576 581 5 [3] 6 [5] (2.2) (3.1) Note: Mean response time for the neutral prime condition was 526 ms and 578 ms for the emphasis-on-speed samples and the emphasis-on-accuracy sample, respectively. a Affective Priming: Mean of incongruent minus congruent prime condition; standard errors in brackets. b Intercept of regression of affective priming on d’; standard errors in brackets.


55

Table 3 Mean Semantic Similarity Ratings (Standard Deviations across Pairs in Parentheses) as a Function of Valence Congruency and Relevance Match (Study 3) Valence Congruent Incongruent Prime-Target-Pairs of Study 1 Same Relevance Type


Prime-Target-Pairs of Study 2 Same Relevance Type


1.15 (1.02)

Reference Pairs Synonym Antonym

-1.29 (1.00)

0.21 (0.29)

-0.25 (0.31)

0.71 (0.87)

-0.91 (0.78)

3.48 (0.58)

-3.47 (0.60)

3.00 (0.71)

-3.39 (0.62)

0.04 -0.25 (0.46) (0.31) Note: The scale was from -4 (denoting an antonymic relationship) over 0 (denoting no relationship) to +4 (denoting a synonymic relationship).


56 Appendix

The Trait Terms Other-Relevant

Possessor-Relevant

Negative

Positive

Negative

Positive

Primes and Targets

gierig (greedy) grausam (cruel) boshaft (malicious) gemein (mean) geizig (miserly, stingy)

human (humane) zärtlich (affectionate) ehrlich (honest) gütig (kind, generous) gerecht (just)

leblos (lifeless) unfähig (incapable) träge (sluggish) lustlos (listless) einsam (lonely)

heiter (cheerful, serene) begabt (gifted) schön (beautiful) gesund (healthy) aktiv (active)

Primes

gierig (greedy) brutal (brutal) böse (bad) giftig (toxic) geizig (miserly, stingy)

fair (fair) treu (faithful, loyal) lieb (dear) gütig (kind, generous) human (humane)

leblos (lifeless) feige (cowardly) träge (sluggish) lahm (lame) einsam (lonely)

froh (glad) klug (smart) schön (beautiful) gesund (healthy) aktiv (active)

Targets

boshaft (malicious) unsozial (antisocial) kriminell (criminal) aggressiv (aggressive) treulos (unfaithful)

gerecht (just) geduldig (patient) herzlich (cordial) tolerant (tolerant) friedlich (peaceful)

abhängig (dependent) willenlos (aboulic (?)) depressiv (depressed) entmutigt (demoralized) zwanghaft (obsessive)

geschickt (skillful) kreativ (creative) vergnügt (happy) zufrieden (content, satisfied) entspannt (relaxed)

Study 1

Study 2

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