1University of Oklahoma 2Shaker Consulting Re-examining the Relationship between Need for Cognition and Creativity Logan L. Watts1, Logan M. Steele1, Hairong Song1, Kelsey E. Medeiros1, Paul Partlow1, & P. Carter Gibson2 1University of Oklahoma 2Shaker Consulting ABSTRACT Prior studies have demonstrated inconsistent findings regarding the relationship between need for cognition and creativity. In the present study, measurement issues were explored as a potential source of these inconsistencies. Structural equation modeling techniques were used to examine the factor structure underlying the 18-item need for cognition scale in three independent samples drawn from three prior studies. In addition, the relationships between need for cognition and the quality, originality, and elegance of creative problem solutions across multiple domains of performance were analyzed. Across all three samples, the bi-factor model fit the data better than the two-factor and one-factor need for cognition models. After controlling for method-specific variance, the trait factor of the bi-factor model showed consistently positive relationships with all three facets of creative performance and showed stronger relationships with these facets than the composite score results reported in prior studies. METHOD (cont’d) Dependent Variables Ratings of the quality, originality, and elegance of problem solutions were conducted by trained judges using benchmark-rating scales. The reported interrater agreement coefficients for quality, originality, and elegance were acceptable across all three studies (i.e., > .70). Predictor Variable Need for cognition was assessed at the end of each study, following the completion of the creative problem-solving task. The 18-item scale consists of nine positively worded statements and nine negatively worded statements that are typically reverse-scored. The measure has demonstrated adequate internal reliability in numerous, prior studies (e.g., α > .85), and additional evidence of construct validity has been provided by Cacioppo et al. (1996). Description of Analyses and Competing Models Confirmatory factor analysis (CFA) using maximum likelihood estimation in Mplus version 6.12 was employed for all analyses. Three potential models of need for cognition were tested on each sample. In the first model, a one-factor model, all 18 items of the need for cognition scale were constrained to load on a single factor. In the second model, a two-factor correlated model, the nine positively worded items were constrained to load on one factor while the nine negatively worded items were constrained to load on another factor. In the third model, a bi-factor solution was examined which included a trait factor with all 18 items loading onto it as well as two method factors separately predicting positively worded and negatively worded items. FINAL MODEL x1 x2 x6 x10 Method Positive x11 x13 x14 x15 Quality x18 Need for Cognition INTRODUCTION Creative work is by nature complex and demanding (Mumford, Scott, Gaddis, & Strange, 2002). Need for cognition has been identified as a potentially useful predictor of creative performance (Marcy & Mumford, 2007). Need for cognition refers to an individual’s tendency to engage in and enjoy complex tasks (Cacioppo & Petty, 1982). Prior studies have shown an inconsistent pattern of relationships between need for cognition and creativity, perhaps leading some scholars to ignore the role of need for cognition as a predictor of creative performance. The present study examined two potential sources of these inconsistent results—criterion task variability and uncontrolled method variance in the predictor. RESEARCH QUESTIONS Are the relationships between need for cognition and the quality, originality, and elegance of problem solutions stable across problem solving tasks and domains? Could measurement issues associated with the popular, short form of the need for cognition scale explain the inconsistent relationships observed between need for cognition and creative performance? Originality x3 Elegance x4 x5 x7 Method Negative x8 x9 x12 x16 x17 RESULTS Fit Statistics Effects of Need for Cognition on Creativity Outcomes Sample 1 Sample 2 Sample 3 1-factor 2-factor Bi-factor χ2 316.416 256.182 200.757 196.726 176.096 139.701 322.351 270.601 204.517 df 135 134 117 118 χ2/df 2.344 1.912 1.716 1.457 1.314 1.184 2.388 2.019 1.748 AIC 15997.169 15938.935 15917.510 8462.435 8443.805 8439.410 16391.793 16342.042 16309.959 BIC 16200.659 16146.192 16188.830 8631.449 8615.949 8661.632 16594.773 16548.782 16580.600 RMSEA 90% CI .065 [.056, .074] .053 [.043, .063] .047 [.036, .058] .052 [.035, .067] .043 [.023, .060] .033 [.000, .053] .066 [.057, .075] .057 [.047, .066] .049 [.037, .059] CFI .888 .925 .948 .931 .953 .976 .883 .914 .945 TLI .873 .932 .922 .946 .969 .867 .902 .928 SRMR .046 .038 .050 .044 .048 .040 DISCUSSION Limitations Data were drawn from laboratory studies of undergraduate students in psychology at one institution, tempering the generality of our conclusions. Responses from only one measure of need for cognition—Cacioppo et al.’s (1984) short form—were examined, limiting the generality of the conclusions that can be drawn concerning the relationship between need for cognition as an inferred construct and creative performance. Findings The bi-factor model of need for cognition demonstrated the best fit across all three samples, followed by the two-factor and one-factor models. After controlling for method variance, a consistent pattern of effects emerged, such that need for cognition positively predicted quality, originality, and elegance of solutions in both the educational leadership and marketing problem domains. Inconsistent findings regarding need for cognition in prior studies of creative problem solving may be due to uncontrolled method variance associated with item polarity. In conclusion, need for cognition, and how it is measured, should not be ignored in future creativity research. METHOD Samples Three samples were drawn from prior published and unpublished experimental studies of creative problem solving Participants were undergraduate students attending a large university in the southwestern United States Average age = 19 Quality Originality Elegance Composite NFC Bi-factor NFC Sample 1 - *** Sample 2 * ** Sample 3 Note. *p < .10; **p < .05; ***p < .01; NFC = need for cognition. Sample N Domain Creativity Task 1 Partlow, Medeiros, & Mumford (2015) 320 Educational leadership Develop plan for school 2 Watts (2014) 169 3 Medeiros, Partlow, & Mumford (2014) 317 Marketing Develop advertising campaign