Supporting the Mental Health Needs of Community College Students.

The United States faces an unprecedented mental health crisis, with youth and young adults at the center. Even before the COVID-19 pandemic, nearly 50 percent of college students reported at least one mental health concern. The COVID-19 pandemic notably exacerbated these issues and underscored the urgent need to identify and implement ways to ameliorate the youth mental health crisis. In 2021, the National Academies of Sciences, Engineering, and Medicine called on the field of higher education to address growing concerns about student mental health by identifying and elevating emerging and promising approaches that offer a more holistic way to support students' mental health. Serving as the main entry point for more than 40 percent of students seeking a postsecondary degree, community colleges represent a tremendous and untapped opportunity to better address mental health in the United States, particularly for students who have been traditionally underserved (e.g., students of color, first-generation students, and low-income students). However, community colleges have limited evidence and guidance to inform the implementation of multilevel, holistic approaches to support students with varying mental health needs. To address this knowledge gap, this article shares a descriptive study of eight community colleges at the forefront of implementing multilevel approaches (a combination of prevention, early intervention, and treatment services) to support student mental health, as well as key facilitators for and barriers to their success.

Comparing Performance of Methods to Deal With Differential Attrition in Randomized Experimental Evaluations.

Background: In randomized controlled trials, attrition rates often differ by treatment status, jeopardizing causal inference. Inverse probability weighting methods and estimation of treatment effect bounds have been used to adjust for this bias. Objectives: We compare the performance of various methods within two samples, both generated through lottery-based randomization: one with considerable differential attrition and an augmented dataset with less problematic attrition. Research Design: We assess the performance of various correction methods within the dataset with problematic attrition. In addition, we conduct simulation analyses. Results: Within the more problematic dataset, we find the correction methods often performed poorly. Simulation analyses indicate that deviations from the underlying assumptions for bounding approaches damage the performance of estimated bounds. Conclusions: We recommend the verification of the underlying assumptions in attrition correction methods whenever possible and, when verification is not possible, using these methods with caution.

Premigration School Quality, Time Spent in the United States, and the Math Achievement of Immigrant High School Students.

Using a nationally representative sample of 1,189 immigrant youth in American high schools, we examine whether the quality of education in their country of origin is related to post-migration math achievement in the 9th grade. To measure the quality of their education in the country of origin, we use country-specific average test scores from two international assessments: the Programme for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS). We find that the average PISA or TIMSS scores for immigrant youth's country of origin are positively associated with their performance on the 9th grade post-migration math assessment. We also find that each year spent in the United States is positively associated with performance on the 9th grade post-migration math assessment, but this effect is strongest for immigrants from countries with low PISA/TIMSS scores.