Is more time better for divergent thinking? A meta-analysis of the time-on-task effect on divergent thinking

Paek, Sue Hyeon; Alabbasi, Ahmed M. Abdulla; Acar, Selçuk; Runco, Mark A.

doi:10.1016/j.tsc.2021.100894

Cited by 39 publications

(23 citation statements)

References 67 publications

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“…As expected, the overall mean effect size showed high heterogeneity, requiring moderator analysis. Moderator selection was based on possible sources of variability identified by previous meta-analyses in creativity (Abdulla Alabbasi et al, 2021; Abraham, 2016; Acar & Runco, 2012; Acar, Runco, & Park, 2020; Baer & Kaufman, 2008; Paek et al, 2021; Reiter-Palmon et al, 2019; Runco et al, 2010; Said-Metwaly et al, 2020; Kogan, 1974; Thompson et al, 2021). These included year of publication (Baer, 2012; Mar’i & Karayanni, 1983), cross-cultural comparisons (Shao et al, 2019; Storme et al, 2017), age (Cheung & Lau, 2010; Palmiero et al, 2014), DT test (Runco et al, 2016), DT subscale (Karwowski et al, 2016), type of task (Abdulla Alabbasi et al, 2021; Taylor & Barbot, 2021), and ability (Abdulla Alabbasi et al, 2021; Runco, 1993).…”

Section: Discussionmentioning

confidence: 99%

“…One of the advantages of the meta-analysis method is the identification of sources of inconsistencies (Acar, Ogurlu, & Runco, 2020), which can be used as moderators that aim to explain heterogeneity in the mean effect size. This is especially true when the included studies: (a) study different age groups; (b) use different tests to assess the same construct; (c) span over several decades; (d) use different types of tasks (i.e., figural vs. verbal); (e) study different populations of students (e.g., gifted and average students); (f) assess different skills under the same construct; (g) include both published an unpublished works and (h) examine possible cultural differences in DT Abdulla et al, 2020;Acar & Runco, 2012;Acar, Runco, & Park, 2020;Paek et al, 2016;Paek et al, 2021;Said-Metwaly et al, 2020). Moreover, one needs to account for the potentially different outcomes between published and unpublished studies (Cooper, 2016;Lipsey & Wilson, 2001).…”

Section: Gender Difference In Dt: Sources Of Inconsistencies and Rese...mentioning

confidence: 99%

See 1 more Smart Citation

Gender differences in creative potential: A meta-analysis of mean differences and variability.

Alabbasi¹,

Thompson²,

Runco³

et al. 2022

Psychology of Aesthetics, Creativity, and the Arts

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The current study examined gender differences in divergent thinking (DT) using meta-analyses of mean difference and variation. The main objective of the meta-analysis of mean difference was to resolve contradictory findings in the creativity literature regarding the prevalence of creativity among males or females in creative potential. The meta-analysis of variation aimed to test the greater male variability hypothesis (GMVH) in DT. To test gender differences in means (i.e., Hedges' g), results from 213 studies (k = 1,251; N = 115,289) were analyzed using a three-level approach. Females slightly outperformed males in DT, g = À.065, 95% CI [À.095, À.034], p = # .001. Three-level multiple regression analyses showed that the mean effect size significantly varied by (a) country, (b) DT subscale, (c) type of task, and (d) ability (gifted vs. nongifted). In the second meta-analysis, the GMVH in creative potential was tested by synthesizing the results of 1,152 effect sizes from 187 studies (k = 1,152; N = 101,328). The results confirmed the existence of greater male variability (GMV) in DT, (InVR) = 1.216, 95% CI [1.14, 1.29], p # .001, indicating 21.6% GMV in DT. Multiple regression analyses explained 29.82% of variability in the mean effect (InVR) at Level-2 (within-studies variance), and 5% of the variability in the mean effect at Level-3 (between-studies variance). The mean difference findings support the gender similarity hypothesis, while variation results tend to support the gender differences hypothesis. Limitations and recommendations for future studies are discussed.

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Section: Discussionmentioning

confidence: 99%

Section: Gender Difference In Dt: Sources Of Inconsistencies and Rese...mentioning

confidence: 99%

Gender differences in creative potential: A meta-analysis of mean differences and variability.

Alabbasi¹,

Thompson²,

Runco³

et al. 2022

Psychology of Aesthetics, Creativity, and the Arts

Self Cite

View full text Add to dashboard Cite

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“…This method could take advantage of dynamic brain patterns to further unlock sealed functional relations in DT and insight. Moreover, some researchers have raised that task time could potentially affect creative performance (Paek et al, 2021;Wieth and Zacks, 2011). It would be interesting to explore the corresponding neural mechanisms between DT and insight in the future.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Uncovering neural distinctions and commodities between two creativity subsets: A meta‐analysis of fMRI studies in divergent thinking and insight using activation likelihood estimation

Kuang

Chen

Shi

et al. 2022

Human Brain Mapping

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The dual‐process theory that two different systems of thought coexist in creative thinking has attracted considerable attention. In the field of creative thinking, divergent thinking (DT) is the ability to produce multiple solutions to open‐ended problems in a short time. It is mainly considered an associative and fast process. Meanwhile, insight, the new and unexpected comprehension of close‐ended problems, is frequently marked as a deliberate and time‐consuming thinking process requiring concentrated effort. Previous research has been dedicated to revealing their separate neural mechanisms, while few studies have compared their differences and similarities at the brain level. Therefore, the current study applied Activation Likelihood Estimation to decipher common and distinctive neural pathways that potentially underlie DT and insight. We selected 27 DT studies and 30 insight studies for retrospective meta‐analyses. Initially, two single analyses with follow‐up contrast and conjunction analyses were performed. The single analyses showed that DT mainly involved the inferior parietal lobe (IPL), cuneus, and middle frontal gyrus (MFG), while the precentral gyrus, inferior frontal gyrus (IFG), parahippocampal gyrus (PG), amygdala (AMG), and superior parietal lobe were engaged in insight. Compared to insight, DT mainly led to greater activation in the IPL, the crucial part of the default mode network. However, insight caused more significant activation in regions related to executive control functions and emotional responses, such as the IFG, MFG, PG, and AMG. Notably, the conjunction analysis detected no overlapped areas between DT and insight. These neural findings implicate that various neurocognitive circuits may support DT and insight.

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“…Research found that participants generate more ideas with more lenient time conditions (Paek, Abdulla, Acar, & Runco, 2021; Said‐Metwaly, Fernández‐Castilla, Kyndt, & Van den Noortgate, 2020). However, it is important to note that the impact of extended time tends to progressively disappear (Paek et al, 2021) and participants may experience negative emotions (e.g., boredom) if the test time is too long, which may influence their creative performance (Haager, Kuhbandner, & Pekrun, 2018). In addition, testing climate (game‐like or test‐like) is relevant to DT performance.…”

Section: Divergent Thinking (Dt) and Measurementmentioning

confidence: 99%

“…Third, most samples were from Western countries, so future studies may further examine the relationship in Eastern cultures since people from different cultural backgrounds may have different creativity and evaluation patterns (Guo, Lin, Guo, Lu, & Shangguan, 2021; Ivancovsky et al, 2019; Karwowski, 2016). In addition, there are other factors that are relevant to DT performance, such as testing climate (test‐ vs. game‐like) and DT testing time (Paek et al, 2021; Wallach & Kogan, 1965), but this meta‐analysis did not test their effects because many studies did not report the relevant information. Future studies may examine whether those factors affect the relationship between DT and evaluative skill.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Divergent Thinking and Evaluative Skill: A Meta‐Analysis

Guo

Lin

Acar

et al. 2022

Journal of Creative Behavior

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Evaluative skill, the ability to accurately assess ideas in terms of originality or creativity, is a critical component of creativity. It involves discarding bad ideas and discerning ideas that are worthwhile to pursue. In light of the growing research on the association between individuals’ evaluative skill and divergent thinking (DT), a research synthesis is needed to clarify discrepant results. Therefore, we examined the relationship between DT and evaluative skill with a three‐level meta‐analytic approach. Based on 96 effect sizes in 20 studies with a total sample of 3,019 participants, results indicated that DT was positively associated with evaluative skill, r = .13 (95% CI [.07, .20], p < .001). Follow‐up moderator analyses revealed that the type of DT tests, the source of ideas, and the type of evaluation tasks were significant moderators. Compared with Instances, Line Meanings, and Consequences, the relationship was (a) weaker when the Uses task was used as the DT test, (b) stronger when the evaluation task was based on Uses, and (c) stronger when people rated their own ideas than when they rated others. The findings implied that DT and evaluative skill are conceptually distinct but interrelated and suggested ways to enhance evaluative skill.

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Is more time better for divergent thinking? A meta-analysis of the time-on-task effect on divergent thinking

Cited by 39 publications

References 67 publications

Gender differences in creative potential: A meta-analysis of mean differences and variability.

Gender differences in creative potential: A meta-analysis of mean differences and variability.

Uncovering neural distinctions and commodities between two creativity subsets: A meta‐analysis of fMRI studies in divergent thinking and insight using activation likelihood estimation

Divergent Thinking and Evaluative Skill: A Meta‐Analysis

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