“I Know What I Like” – Indecisiveness Is Unrelated to Behavioral Indicators of Evaluation Difficulties

Indecisiveness, the subjective inability to make satisfying decisions, is an individual difference trait that may impede effective actions. Mechanisms underlying indecisiveness are largely unknown. In four studies, we tested the prediction that indicators of evaluation difficulty were associated with indecisiveness in simple evaluations. Across studies, indecisiveness was measured via self-report while evaluation difficulties were derived behaviorally from three indicators: difficulty distinguishing between similar evaluation objects (i.e., standard deviation of evaluation ratings), evaluation duration (reaction times), and implicit evaluations (evaluative priming effect) using familiar everyday objects. Study 1 (N = 151) was based on attractiveness evaluations of portraits. Studies 2a (N = 201) and 2b (N = 211) used chocolate as evaluation objects and manipulated to what extent the evaluations were equivalent to a decision. In Study 3 (N = 80) evaluations were measured implicitly through evaluative priming using food pictures. Contrary to our predictions, indecisiveness showed no reliable association to any indicator of evaluation difficulty, regardless of type of evaluation object, equivalence of evaluation and decision, and whether evaluation difficulty was based on explicit or implicit evaluations. All null findings were supported by Bayes factors. These counterintuitive results are a first step toward investigating evaluation processes as potential mechanisms underlying indecisiveness, showing that for both explicit and implicit measurements, indecisiveness is not characterized by difficulties when evaluating familiar everyday objects.

Me as good and me as bad: Priming the self triggers positive and negative implicit evaluations

Although theories of personality and human behavior have long assumed that the self is affectively complex, widely used indirect measures of implicit self-evaluations have largely focused on the robustness and cultural universality of the self’s positivity. Such indirect measures assess evaluations on a single continuum, ranging from positive to negative. Thus, they focus on the self’s relative positivity and are inherently incapable of assessing whether the self is associated with good and bad. Using the well-established evaluative priming task, the present work tested the hypothesis that positive implicit self-evaluations coexist with an inkling of negative implicit self-evaluations. Studies 1 and 2 empirically demonstrated that priming the self facilitated the classification of both positive and negative targets (bivalent-priming). In contrast, replicating classic findings, priming a personally significant, liked object facilitated the classification of positive targets and inhibited the classification of negative targets (univalent-priming). Study 3 showed that the bivalent-priming triggered by self-primes cannot be explained by alternative accounts (e.g., arousal, vigilance). Meta-analyses of all studies attests to the robustness and reproducibility of self-primes triggering both positive and negative implicit evaluations. Moreover, tests estimating heterogeneity in the strength of implicit self-evaluations indicated that individual differences in nonclinical, healthy individuals may be limited, possibly reflecting measurement limitations, the nature of implicit self-evaluations, or both. Overall, the present work shines a spotlight on a previously undocumented effect: Despite the self’s robust net positivity, the self reliably triggers negative implicit self-evaluations. Implications for the conceptualization, assessment, and consequences of implicit self-evaluations are discussed.

Facial Stereotype Bias Is Mitigated by Training

People automatically infer others’ personality (e.g., trustworthiness) based on facial appearance, and such facial stereotype biases predict real-world consequences across political, legal, and business domains. The present research tested whether these biases can be mitigated through counterstereotype training aimed at reconfiguring the associations between specific facial appearances and social traits. Across six studies and a replication, a behavioral counterstereotype training consistently reduced or eliminated facial stereotype biases for White male faces in the context of economic trust games, hiring decisions, and even automatic evaluations assessed via evaluative priming. Together, the results demonstrate a fundamental malleability in facial stereotyping related to trustworthiness, with a minimal training able to mitigate the tendency to activate and apply long-held, highly automatized facial stereotypes. These findings suggest that face impressions are more flexible than typically appreciated, and they provide a potential inroad toward combating our ingrained biases based on facial appearance.

The Challenge of Diagnostic Inferences From Implicit Measures: The Case of Non-Evaluative Influences in the Evaluative Priming Paradigm

Implicit measures are diagnostic tools to assess attitudes and evaluations that people cannot or may not want to report. Diagnostic inferences from such tools are subject to asymmetries. We argue that (causal) conditional probabilities p(AM+|A+) of implicitly measured attitudes AM+ given the causal influence of existing attitudes A+ is typically higher than the reverse (diagnostic) conditional probability p(A+|AM+), due to non-evaluative influences on implicit measures. We substantiate this argument with evidence for non-evaluative influences on evaluative priming—specifically, similarity effects reflecting the higher similarity of positive than negative prime-target pairs; integrativity effects based on primes and targets’ potential to form meaningful semantic compounds; and congruity proportion effects that originate in individuals’ decisional strategies. We also cursorily discuss non-evaluative influences in the Implicit Association Test (IAT). These influences not only have implications for the evaluative priming paradigm in particular, but also highlight the intricacies of diagnostic inferences from implicit measures in general.

To Run or Not to Run? Automatic Evaluations and Reflective Attitudes Toward Exercise

Using an evaluative priming procedure, this study tested whether automatic evaluations of running differ among groups based on their amount of exercise and whether they were runners or not. Ninety-five participants (26 ± 5.06 years; 46% female) were divided into five groups: an inactive group, active exercisers, highly active exercisers, active runners, and highly active runners. A priming effect score was calculated based on the concept of response facilitation or inhibition: the reaction is faster when the target and prime are valence congruent and becomes slower if they are incongruent. The highly active runner group differed significantly from the inactive group (p < .01) and from the active exerciser group (p < .05). Furthermore, reflective evaluations were measured via questionnaires. The results show that priming effect scores can detect automatic evaluations of running, and they differ not only because of the amounts of physical exercise but also because of their preferred type of exercise.

Implicit Evaluative Biases Toward Targets Varying in Race and Socioeconomic Status

Generally, White (vs. Black) and high-status (vs. low-status) individuals are rated positively. However, implicit evaluations of simultaneously perceived race and socioeconomic status (SES) remain to be considered. Across four experiments, participants completed an evaluative priming task with face primes orthogonally varying in race (Black vs. White) and SES (low vs. high). Following initial evidence of a positive implicit bias for high-SES (vs. low-SES) primes, subsequent experiments revealed that this bias is sensitive to target race, particularly when race and SES antecedents are presented in an integrated fashion. Specifically, high-SES positive bias was more reliable for White than for Black targets. Additional analyses examining how implicit biases may be sensitive to perceiver characteristics such as race, SES, and beliefs about socioeconomic mobility are also discussed. Taken together, these findings highlight the importance of examining evaluations based on race and SES when antecedents of both categories are simultaneously available.