APA Annual Conference (Division 7), August , Chicago, IL. Submission Type: Individual Poster Proposal

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1 APA Annual Conference (Division 7), August , Chicago, IL Submission Type: Individual Poster Proposal Title: Predictors of Well-being Among College Students: A Multi-level Analysis Authors: Angela Robinson, M.S. (principal author) Angela.robinson@memphis.edu University of Memphis, College of Education Dept of Counseling, Educ Psyc & Research Chia-chen Yang, PhD Cyang2@memphis.edu University of Memphis, College of Education Dept of Counseling, Educ Psyc & Research 303d Ball Hall, Memphis, TN, / Graduate Student Membership Abstract The transition to college can be a stressful time as it often includes dramatic shifts in social, academic, and physical environments (Arnett, 2007). Successful adjustment to this new environment is imperative for the overall well-being of college students. Past studies have shown that students self-efficacy (Yu & Luo, 2018), stress (Denovan & Macaskill, 2017), and social support (Khallad & Jabr, 2016) impact the well-being of college students. While many studies narrowly focus on student-level characteristics, school-level factors such as school type, sector, and size may also impact students well-being (Pascarella & Terenzini, 2005). The purpose of this study is to examine predictors of students well-being to determine the variability explained by between-school versus within-school factors. This cross-sectional study used a sample from the 2016 Emerging Adulthood Measured at Multiple Institutions (EAMMI2) dataset. The study sample included 23 schools and 2,203

2 PREDICTORS OF WELL-BEING 2 participants (72.9% female, 63.2% white, 9.3% Hispanic, 7% African American). Participants completed a self-report survey that included measures of subjective well-being, perceived stress, self-efficacy, and perceived social support. SPSS was used to conduct multi-level linear regressions to analyze between- and within-school variability. The null model revealed that 2.5% of variability in well-being existed between schools ( = 0.04, p = 0.018). This amount of variability was significantly greater than zero, so a second model was conducted to further examine school-level predictors of well-being. The second model included three school-level variables: school type (2-year or 4-year), school sector (public or private), and school size (small, medium, or large). The analysis indicated that between-school variability was only significant for school type ( = 0.03, p < 0.01), suggesting that 4-year institutions are associated with better well-being than 2-year institutions. Additionally, school type explained 25% of the overall variance between-schools (see Table 2). Considering the modest amount of between-school variability, a third model was conducted to analyze within-school variance in well-being. The following student-level predictors explained 42.3% of within-school variability: perceived stress (t = -0.76, p < 0.001), self-efficacy(t = 0.52, p < 0.001), perceived social support from family(t = 0.22, p < 0.001), and perceived social support from friends (t = 0.14, p < 0.001). Lastly, interactions were analyzed for school-level and student-level predictors. No cross-level interactions were significant, indicating that student-level predictors did not change as a function of school-level predictors. Since a greater amount of variability existed within-schools, student-level interactions were analyzed. The analysis revealed significant interactions between self-efficacy and stress (t = 0.24, p < 0.01), and between perceived social support from family and stress (t = 0.05, p = 0.02),

3 PREDICTORS OF WELL-BEING 3 indicating that self-efficacy and social support from family served to buffer the effect of stress on well-being. There was no significant interaction between stress and support from friends. Whereas earlier studies focused on the main effects of student-level factors, this study presents a few student-level interaction effects. Further, as one of the few studies simultaneously testing school- and student- level predictors, this research reveals that both levels play a role in students well-being, particularly the student-level factors.

4 PREDICTORS OF WELL-BEING 4 Table 1 Cronbach s Alpha, Mean, Standard Deviation, Correlations SD Well-being (1-7) Stress (1-5) * 3.Efficacy (1-4) * -0.38* 4.PSS- Family (1-7) * -0.26* 0.17* 5.PSS- Friends (1-7) * -0.20* 0.21* 0.46* Note: *p <.05, PSS = Perceived Social Support, Numbers in parentheses reflect the range of the scale

5 PREDICTORS OF WELL-BEING 5 Table 2 Subjective Well-being Multilevel Models Null Means as Outcomes Random Slopes Intercepts & Slopes as Outcomes Fixed Effect Estimate (SE) Estimate (SE) Estimate (SE) Estimate (SE) Intercept 4.44 (0.05)* 4.08 (0.13)* 4.43 (0.53)* 4.11 (0.12)* School Type 0.42 (0.13)* 0.42 (0.13)* Stress (0.04)* (0.04)* Self-Efficacy 0.52 (0.05)* 0.45 (0.05)* PSS- Family 0.23 (0.02)* 0.21 (0.02)* PSS- Friends 0.14 (0.02)* 0.14 (0.02)* Stress*Self-Efficacy 0.24 (0.07)* Stress* PSS-Family 0.05 (0.02)* Random Part Level 1: Var(r ij) = 1.71* 1.71* 0.99* 0.98* Level 2: Var(u 0j) = 0.04* 0.03* 0.05* 0.03* Slope: Var(u 1j) = Covar (u 0j u 1j) = Log Likelihood df LRT 8.15* * 8.48 LRT df 1 a 6 a 3 b AIC BIC ICC Proportion of Level 1 Variance Explained % 42.8% Proportion of Level 2 Variance Explained 25% 25% Note: *p <.05, School Type (2yr or 4yr); PSS = Perceived Social Support; student level variables are group mean centered; a= compared to null model; b = compared to random slopes model

6 PREDICTORS OF WELL-BEING 6 References Arnett, J. (2007). Emerging adulthood: What is it, and what is it good for?. Child development perspectives, 1(2), Denovan, A. & Macaskill, A. (2017). Stress and subjective well-being among first year UK undergraduate students. Journal of Happiness Studies, 18, Doi: /s y Khallad, Y. & Jabr, F. (2016). Effects of perceived social support and family demands on college students mental well-being: A cross-cultural investigation. International Journal of Psychology, 51(5), Doi: /ijop Pascarella, E. & Terenzini, P. (2005). How college affects students. San Francisco, CA: Jossey Bass Yu, Y. & Lou, J. (2018). Dispositional optimism and well-being in college students: Self efficacy as a mediator. Social Behavior and Personality, 46(5), Doi: /sbp.6746