Abstract
Research demonstrates that when math-based gender stereotypes are activated (e.g., men are better at math than women), women display comparatively poorer math performance than men, a phenomenon referred to as stereotype threat. We evaluated the effectiveness of two forms of self-affirmation in reducing the effects of stereotype threat on women’s math performance. Participants completed a math test under one of four conditions: control (no explicit stereotype activation), stereotype threat (activation of gender performance stereotype), or stereotype threat combined with one of two self-affirmation manipulations. Women in the affirmation conditions either read about women’s greater verbal or relational ability and were asked to write about why the trait is important to their self-concept. No omnibus effect of condition emerged though follow-up analyses revealed several notable findings. While we were unable to replicate stereotype threat effects, contrast analyses revealed that the combined performance of women in the two affirmation conditions was greater than the combined performance of women in the two no-affirmation conditions. Women in the relational affirmation condition performed descriptively greater than the combined performance of women in the other three conditions. These findings demonstrate how self-affirmation, particularly relational affirmation, may facilitate women’s mathematics problem-solving, independent of stereotype threat activation.
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Notes
We analyzed state self-esteem by subscale as well, given that performance and social self-esteem could plausibly have been higher in the relational affirmation condition due to higher performance on the math test and reflecting on having better relational abilities. However, there was no effect of condition on levels of performance self-esteem, F(3,304) = .970, p = .445, η2p = 0.004. Further, there was no effect of condition on social self-esteem, F(3,304) = 1.65, p = .179, η2p = 0.016, or appearance self-esteem, F(3,304) = .187, p = .905, η2p = 0.002. Thus, levels of self-esteem (regardless of type) did not vary by condition.
To account for the large variance in responses on the 10-item math task (M = 5.23, SD = 2.70), we ran an outlier analyses in which target performance scores were Winsorized where scores below 1 were changed to a 1 (n = 5) and scores above 9 were changed to a 9 (n = 26). See Table 1 for descriptive statistics. We then reconducted the above analyses.
First, we conducted a one-way ANCOVA, controlling for differences in baseline math performance, with math performance as the dependent measure and condition (4 levels) as the independent variable. This analysis was again non-significant, F(3, 303) = 1.59, p = .193, η2p = .015. We then conducted two contrasts to determine if specific mean level differences emerged, independent of the non-significant omnibus analysis. In the first contrast, we simultaneously compared math performance in the two affirmation conditions to the two non-affirmation conditions. Again, although not of conventional significance, a trending effect emerged, t(304) = 1.92, p = .066, d = .79. In the second contrast, we conducted a more focused contrast in which I compared the relational affirmation condition simultaneously to the other three conditions. Again, although not of conventional significance, a trending effect emerged, t(304) = 1.92, p = .056, d = 0.39. Thus, reported findings are not due to extreme scores on the math test.
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Appendix. Example probability problem including a prevalence problem (question 1) and predictive value problem (question 2)
Appendix. Example probability problem including a prevalence problem (question 1) and predictive value problem (question 2)
Problem Scenario: Breathalyzers.
Imagine you work in a police department. Your department often uses Breathalyzers to test whether drivers are driving under the influence of alcohol. Based on previous cases in which a person’s sobriety was later verified, you know the following:
Positive Breathalyzer Test (Indicates drunkenness) | Negative Breathalyzer Test (Does not indicate drunkenness) | |
|---|---|---|
Sober Driver | A 150 | B 750 |
Drunk Driver | C 75 | D 25 |
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1.
Based on this table, how likely is it that a driver is drunk?
-
a.
0.15
-
b.
0.50
-
c.
0.10
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d.
0.75
-
a.
-
2.
Based on this table, how likely is it that a driver with a positive Breathalyzer test is actually drunk?
-
a.
0.66
-
b.
0.95
-
c.
0.30
-
d.
0.33
-
a.
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Macchione, A.L., Sacco, D. Comparing the Efficacy of Two Forms of Self-Affirmation to Reduce Stereotype Threat Effects on Women’s Math Performance. Journal for STEM Educ Res 6, 181–198 (2023). https://doi.org/10.1007/s41979-023-00085-x
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DOI: https://doi.org/10.1007/s41979-023-00085-x