Social fit. On six items (Walton & Cohen, 2007), participants reported whether they felt that they belonged or fit in socially at their university (e.g., “I feel like I belong as a student at [university]”), = .86, M = 5.11, SD = 1.25. Comfort in interactions. On items we created, participants reported whether they felt comfortable engaging in a variety of interpersonal behaviors in college (e.g., “I feel comfortable sharing my opinions with other [university] students”), = .82, M = 5.26, SD = 1.01. Value of working with others. On five items we created, participants reported whether they perceived seeking help from others as valuable for being a successful student (e.g., “Getting extra help outside of class is part of being a good student”), = .84, M = 6.09, SD = 0.80. Demographics. We obtained the following demographic information from the university registrar: gender, racial and ethnic background, high school grade point average (GPA), whether they were receiving Pell grants (as a measure of household income), and generation status. Results Difference-education message. Using the coding scheme from Stephens, Hamedani, & Destin (2014), we assessed whether participants in the difference-education condition learned that students’ diverse backgrounds can shape their college experiences. Specifically, we coded whether participants mentioned that people have backgrounds “like mine” and people’s different backgrounds matter. Two coders, unaware of participants’ generation status and condition, coded the data ( = .622–.838, Landis & Koch, 1977); coding disagreements were resolved through consensus. Supporting our hypothesis, participants in the difference-education condition more often mentioned that people have backgrounds like theirs and that people’s different backgrounds matter than did participants in the control condition. See Table 1 for sample
Improved college experiences (Time 2). To assess our intervention’s effects on participants’ college experiences, we measured five constructs associated with psychological toughness: (a) positive vs. negative affect over the previous 30 days, (b) resilience, (c) psychological vulnerability, (d) experience of stress in college, and (d) well-being. Positive versus negative affect. On 16 items, participants reported how much positive (seven items, e.g., “engaged”) and negative affect (nine items, e.g., “anxious”) they experienced over the past 30 days on a scale from 1 (very slightly) to 5 (extremely), = .87, M = 3.41, SD = 0.73 and = .88, M = 2.97, SD = 0.84, respectively. We modeled this measure after the Psychological Distress Scale (Kessler et al., 2002). We subtracted participants’ scores on the negative affect composite from the positive affect composite to create an overall affective balance score, M = 0.45, SD = 1.30. Higher values indicate greater positive affect. Resilience. On six participants reported their overall resilience (e.g., “I am able to adapt to change”) on a scale from 1 (not true at all) to 5 (true nearly all the time), = .72, M = 3.83, SD = 0.59. We used two items from Duckworth and colleagues’ (2007) Grit Scale and four items from the Connor-Davidson Resilience Scale (Connor & Davidson, 2003). Psychological vulnerability. On four items developed by Wickrama and colleagues (2013), participants reported their overall psychological vulnerability (e.g., “How often have you found that you could not cope with all the things that you had to do?”) on a scale from 0 (never) to 4 (very often), = .74, M = 1.10, SD = 0.77. College stress. On nine items from the College Student Stress Scale (Feldt, 2008), participants reported their experiences of stress while at college (e.g., “How often have you questioned your ability to handle difficulties in your life?”) on a scale from 0 (never) to 4 (very often), = .85, M = 2.10, SD = 0.85.
Wickrama, K. A., Ralston, P. A., O’Neal, C. W., Illich, J. Z., Harris, C. M., Coccia, C.,…Lemacks, J. (2013). Linking life dissatisfaction to health behaviors of African Americans through psychological competency and vulnerability. Research on Aging, 35(5), 591-611. doi:10.1177/0164027512449473 Wilson, T. D. (2011). Redirect: The surprising new science of psychological change. New York, NY: Little, Brown. Yeager, D. S., & Walton, G. M. (2011). Social-psychological interventions in education: They’re not magic. Review of Educational Research, 81(2), 267–301. doi:10.3102/0034654311405999 Yeager, D. S., Walton, G. M., Brady, S. T., Akcinar, E. N., Paunesku, D., Keane, L.,…Dweck, C. S. (2016). Teaching a lay theory before college narrows achievement gaps at scale. Proceedings of the National Academy of Sciences, 113(24), E3341-E3348. doi:10.1073/pnas.1524360113 Table 1 Between-condition Comparison of the Percentage of Responses Coded Within Each Coding Category Chi-Square Analysis Sample Response condition Control condition 2 r [95% CI] Coding Category
Table 3 Univariate Analysis of Covariance Results for Point Average (GPA) and Potential Mediators in Study 2 Variable Academic Performance Academic Performance Mediators GPA Social Fit Time 1 Academic Empowerment Time 1 Social Fit Time 2 Academic Empowerment Time 2 F F F F F Covariate High School GPA 18.52*** 1.01 1.01 0.27 0.17 Race and Ethnicity 0.38 0.46 0.13 0.58 0.01 Gender 0.12 0.11 1.28 0.32 1.65 Low-income Status 1.88 3.90+ 0.72 1.91 0.24 Main and Interactive Effect Condition 7.75** 2.24 0.26 0.26 1.06 Generation 0.36 0.23 0.003 0.04 1.49 Condition Generation 5.01* 3.91* 5.85* 2.08 7.12** Note. Degrees of freedom (df) for GPA = 1, 115, df for both Time 1 academic performance mediators = 1, 125, df for both Time 2 academic performance mediators = 1, 95. GPA = grade point average, race and ethnicity (0 = disadvantaged, 1 = advantaged), gender (0 = male, 1 = female), low-income status (0 = low income, 1 = not low income), condition (0 = control, 1 = difference-education) and generation (0 = first-generation, 1 = continuing-generation). + p < .10, * p < .05, ** p < .01, *** p < .001.