The Stroop Effect: Differences in Response Time Attributed to Gender

Paper Info
Page count 7
Word count 2051
Read time 9 min
Topic Psychology
Type Report
Language 🇺🇸 US

Abstract

This study assessed gender-related differences in the Stroop test performance. The experiment was modeled after the original version created by Stroop in 1935. The participants included 150 individuals, 81 of them being male (gender 1), and 69 being female (gender 2). An average age of those taking part in this research was 44 years old. Prior research on the topic included many generalizations and inconsistencies, which made the findings controversial. The results of this study revealed a correlation between the Stroop test response time and gender, which indicated that females performed better. Gender differences observed may indicate the distinctions in cognitive functioning and selective attention between men and women. Further research is needed to investigate causation links and explore the differences attributed to age and education level.

Background

The Stroop test has been used extensively for both clinical settings and academic research. It is a neurophysiological assessment, which examines one’s ability to restrain cognitive interference. The test makes it possible to evaluate how efficient a person is at processing multiple features of the same stimulus. Over the past decades, there have been numerous alternatives to the Stroop experiment proposed by different researchers. The most common version implies the use of three tables, two of which present a congruous condition, while the third one is incongruent (Scarpina & Tagini, 2017). In the first two tables, participants are required to read words (color names) printed in black ink, and then in colored ink, which is consistent to the word. The last table, however, requires cognitive flexibility and selective attention since the words are printed in the colors, which do not correspond to them, and people have to name the color instead of reading the word. Therefore, the Stroop effect defines the difficulty one might have in overcoming their tendency to complete an automated process (read the word), and not to name the color of ink. Apart from measuring cognitive interference, researchers utilize the Stroop test to examine and assess one’s processing speed, attention span, brain activity, and working memory (Scarpina & Tagini, 2017). Studies usually incorporate the test to make estimates and definitive conclusions regarding multiple cognitive functions at once.

There is an issue pertaining to the inconsistencies one may encounter when analyzing the existing academic literature in relation to the Stroop effect. Most notably, certain scholars accept a common generalization that there are no gender distinctions in the display of cognitive interference, which is attributed to such researchers as Macleod (1991). Houx et al. (1993), Klein et al. (1997), and aforementioned Macleod (1991) reported an overall absence of sex differences in the Stroop test performance. It is evident that the topic is rather controversial as Van Boxtel et al. (2001), Mekarski et al. (1996), Baroun and Alansari (2006), and many other researchers presented findings in opposition with the previous group of scholars. Specifically, Baroun and Alansari (2006) report that their results are “clearly indicative of significant gender difference latencies in color naming in favor of the females” (p. 314). It is apparent that the current state of academic research on the topic is faced with the need to fill the gap between Macleod’s generalizations and the findings from the research listed above.

There are a number of differences in brain physiology and activation patterns attributed to gender, which should be taken into consideration as well. There is a common assumption among scholars that such anatomical distinctions lead to sex differentiability in cognitive functioning. While one gender may be better at completing fine motor tasks and faster at scanning information, another may have poorer verbal skills but increased spatial ability. For instance, Li et al. (2006) demonstrated that men activated the brain more to achieve relatively identical levels of cognitive performance as women. In addition, Christakou et al. (2009) concluded that males had a less mature framework for activating certain brain regions responsible for cognitive flexibility. Thus, these studies are important to refer to, while assessing the possible impact of physiological gender differences on the ability of males and females to interpret the stimuli requires during Stroop testing.

Taking into consideration the inconsistencies present in the current body of academic literature regarding the topic of gender differences during the completion of the Stroop test, this research presents a relevant hypothesis. It states that females perform better in the Stroop test as determined by the response time of the participants. The purpose of this study is to investigate the correlation between sex and cognitive functioning, particularly selective attention.

Method

Participants

The participants included 150 individuals, aged 18 to 75, with an average age of 44. Out of the 150 people, the majority included males (81), and the minority was comprised of females (69). It is important to note that participation was voluntary and everyone involved had to sign a letter of informed consent. The participants had a right to leave the study at any time.

Materials

  1. Web-page with the test, which includes:
  • Congruent card with words (web-site)
  • Incongruent card with words (web-site)
  • Stopwatch
  • Detailed standardized instructions
  1. Letter of informed consent
  2. Researchers’ scripts for an introductory part and a conclusion

Procedures

The experiment was conducted at the University of Maryland Global Campus. The researchers selected the participants randomly although they made alterations to the sample based on the potential participant’s gender and age. After that, 150 individuals involved had to sign an informed consent letter. Before entering the auditorium with computers for testing, participants were introduced to the technicalities of the test and task completion. They entered the room in groups of 30 and were subjected to oversight from the research group. The results were analyzed using digital programs, and then placed in one table for visual representation.

Results

The findings are documented in a PDF-file, screenshots of which are presented in Figures 1-4. The average time it took for females to read words in the first task is 73.8 seconds; the time males spent doing the same is 80.14 sec (Figure 5). The average time it took women to name the color in the second task is 77.07 sec, while men spent 83 sec (Figure 5). The findings indicate that females respond to stimuli faster and perform better during the Stroop testing, which is demonstrated by their shorter response time during both tasks.

Results: Part 1.
Figure 1. Results: Part 1.
Results: Part 2.
Figure 2. Results: Part 2.
Results: Part 3.
Figure 3. Results: Part 3.
Results: Part 4.
Figure 4. Results: Part 4.
Task 1 Task 2
Males
(Gender 1)
80.14 sec 83 sec
Females
(Gender 2)
73.8 sec 77.07 sec

Figure 5. Average response time for Gender 1 and Gender 2.

Discussion

The results of the study were achieved by deploying a conflicting stimuli method, which allowed the participants to focus on one list of words at a time. Thus, following the same set of instructions for each word card, they could focus and concentrate specifically on the risk in front of them, with the only challenge being incongruence in the word itself and the color of the ink. The data collected through such an experiment has been satisfactory for further analysis. It demonstrated that females dealt with congruent and incongruent stimuli faster than males. The primary strength of this research was its simplicity, which would let scientists in the future to replicate it easily in an effort to determine validity of current findings.

It is important to note that the results of the study align perfectly with the previous research aimed at assessing sex differences in brain-behavior associations and speed of cognitive processing. The findings are in accord with the conclusions made by Van Boxtel et al. (2001) and Mekarski et al. (1996). Moreover, taking into consideration the research centered specifically on gender and the Stroop effect, the findings of the present study have corresponded perfectly with some of the past studies. One of them includes the article published by Baroun and Alansari (2006) in Social Behavior and Personality: Am International Journey. The scientists assessed the differences in the Stroop test performance among men and women. The results indicated that “women read faster on the color card than did the males, and especially were faster with intercepting three cards of tests (interaction effect)” (Baroun & Alansari, 2006, p. 309). The fact that the study was conducted in Kuwait further highlights the absence of cultural differences in relation to the gender distinctions in cognitive flexibility evaluated through the use of the Stroop test.

In multiple domains of psychology, studies have demonstrated gender distinctions in brain activity despite the same levels of behavioral performance in favor of females. In the study by Li et al. (2006), men “showed greater activation (e.g., bilateral medial frontal and cingulate cortices, thalamus, parahippocampal gryus) than women to achieve similar levels of performance” (as cited in Cuevas et al., 2016, p. 31). The researchers have conducted magnetic resonance imaging to explore the sex distinctions in neural links associated with response inhibition in the process of completing a stop signal task (Li et al., 2006). It is apparent that the phenomenon of gender differences in regards to cognitive and affective processing has been researched for decades.

Another group of scientists to examine sexual differentiation in brain flexibility has been Christakou et al. (2009). Similarly to Li et al. (2006), they used functional neuroimaging to inspect the impact of gender on cognitive functioning as subjects were forced to quickly switch attention due to an interference (Christakou et al., 2009). Thus, using these methods, the scientists uncovered that females possessed a more mature framework for prefrontal and temporal brain activation.

Limitations

In terms of limitations, there are a number of aspects, which have to be acknowledged. A relatively small sample hinders the experiment in terms of proving its validity or generalizing the results. A bigger sample size is needed to produce insights into sex differences in cognitive functioning, which would be representative of a larger population. Another limitation is the fact that the sample was not heterogeneous in terms of race, socio-economic status, or education level. While the participants were completing the test, the research supervisors had been present in the room. This might have affected the sample population by making individuals nervous and uncomfortable. A change in the study’s design would be beneficial in minimizing the amount of pressure they are under.

It is important to acknowledge that the present study has a cross-sectional design, which focuses on the analysis of correlations, disregarding causation. Therefore, it cannot fully assess all the aspects contributing to the gender differences in the Stroop test performance. In addition, the research could shift its vector more towards various functional models, which are the basis of inter-individual differences in cognitive responses to stimuli. The study could benefit from the use of a combination of functional neuroimaging methods to investigate specific mechanisms responsible for distinctions in brain activation and processing.

Implications for Future Research

The present study provides invaluable resources for the future research on the topic of differences between various groups in terms of cognitive functioning and brain activation. First, the research can be used to investigate the causes of gender differences in the Stroop test performance. The scholars can use the study as the evidence for the existence of such distinctions, and then conduct experiments to determine neural substrates for this phenomenon. Further research is required to examine the entirety of factors contributing to sex differentiability in terms of word-pattern analysis as well as processing of morphological constructs. Although the study shows that women perform better on the Stroop test, demonstrating shorter latencies, it is crucial to determine what it can be attributed to. On the one hand, these results may be caused by a generally higher response speed attributed to females. On the other hand, the gender differences in the Stroop effect may be a result of distinctions in cognitive control and brain activation.

Moreover, it is important to further explore how other factors, apart from gender, such as age and level of education affect Stroop test performance. The findings of this study may be useful in guiding future research to determine the impact of older age and poorer education in cognitive functioning, particularly focusing on selective attention. Scholars should examine the nature of age- and education-related decline in brain activation. Additionally, they can incorporate biological and lifestyle changes into experiments to investigate the correlation between long-term behavioral transformations and cognitive functioning.

References

Baroun, K., & Alansari, B. (2006). Gender differences in performance on the Stroop test. Social Behavior and Personality: An International Journal, 34(3), 309–318. Web.

Christakou, A., Halari, R., Smith, A. B., Ifkovits, E., Brammer, M., & Rubia, K. (2009). Sex-dependent age modulation of frontostriatal and temporo-parietal activation during cognitive control. NeuroImage, 48(1), 223–236. Web.

Cuevas, K., Calkins, S. D., & Bell, M. A. (2016). To Stroop or not to Stroop: Sex-related differences in brain-behavior associations during early childhood. Psychophysiology, 53(1), 30–40. Web.

Houx, P. J., Jolles, J., & Vreeling, F. W. (1993). Stroop interference: Aging effects assessed with the stroop color-word test. Experimental Aging Research, 19(3), 209–224. Web.

Klein, M., Ponds, R. W. H. M., Houx, P. J., & Jolles, J. (1997). Effect of test duration on age-related differences in stroop interference. Journal of Clinical and Experimental Neuropsychology, 19(1), 77–82. Web.

Li, C. R., Huang, C., Constable, R. T., & Sinha, R. (2006). Gender differences in the neural correlates of response inhibition during a stop signal task. NeuroImage, 32(4), 1918–1929. Web.

MacLeod, C. M., & Dunbar, K. (1988). Training and Stroop-like interference: Evidence for a continuum of automaticity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(1), 126–135. Web.

Mekarski, J. E., Cutmore, T. R. H., & Suboski, W. (1996). Gender differences during processing of the Stroop task. Perceptual and Motor Skills, 83(2), 563–568. Web.

Scarpina, F., & Tagini, S. (2017). The Stroop color and word test. Frontiers in Psychology, 8, 1–8. Web.

Van Boxtel, M. P. J., ten Tusscher, M. P. M., Metsemakers, J. F. M., Willems, B., & Jolles, J. (2001). Visual determinants of reduced performance on the Stroop color-word test in normal aging individuals. Journal of Clinical and Experimental Neuropsychology, 23(5), 620–627. Web.

Cite this paper

Reference

NerdyBro. (2022, June 7). The Stroop Effect: Differences in Response Time Attributed to Gender. Retrieved from https://nerdybro.com/the-stroop-effect-differences-in-response-time-attributed-to-gender/

Reference

NerdyBro. (2022, June 7). The Stroop Effect: Differences in Response Time Attributed to Gender. https://nerdybro.com/the-stroop-effect-differences-in-response-time-attributed-to-gender/

Work Cited

"The Stroop Effect: Differences in Response Time Attributed to Gender." NerdyBro, 7 June 2022, nerdybro.com/the-stroop-effect-differences-in-response-time-attributed-to-gender/.

References

NerdyBro. (2022) 'The Stroop Effect: Differences in Response Time Attributed to Gender'. 7 June.

References

NerdyBro. 2022. "The Stroop Effect: Differences in Response Time Attributed to Gender." June 7, 2022. https://nerdybro.com/the-stroop-effect-differences-in-response-time-attributed-to-gender/.

1. NerdyBro. "The Stroop Effect: Differences in Response Time Attributed to Gender." June 7, 2022. https://nerdybro.com/the-stroop-effect-differences-in-response-time-attributed-to-gender/.


Bibliography


NerdyBro. "The Stroop Effect: Differences in Response Time Attributed to Gender." June 7, 2022. https://nerdybro.com/the-stroop-effect-differences-in-response-time-attributed-to-gender/.